analyze_tweet_part2_eda.html

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}
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  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
    </style>
<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>


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<h1 id="Analyze-Tweet-Data">Analyze Tweet Data<a class="anchor-link" href="#Analyze-Tweet-Data">&#182;</a></h1><h2 id="Part-2:-Exploratory-Data-Analysis-(EDA)-and-Data-Visualization">Part 2: Exploratory Data Analysis (EDA) and Data Visualization<a class="anchor-link" href="#Part-2:-Exploratory-Data-Analysis-(EDA)-and-Data-Visualization">&#182;</a></h2><h2 id="Table-of-Contents">Table of Contents<a class="anchor-link" href="#Table-of-Contents">&#182;</a></h2><ul>
<li><a href="#intro">Introduction</a></li>
<li><a href="#analysis">EDA and Visualization</a></li>
<li><a href="#conclusion">Conclusion</a></li>
</ul>
<p><a id='intro'></a></p>
<h2 id="Introduction">Introduction<a class="anchor-link" href="#Introduction">&#182;</a></h2><p>The master dataset created in <strong>Part 1: Data Wrangling</strong> by gathering, assessing, cleaning and merging three datasets was analyzed to generate insights on four key topics listed below.</p>
<ol>
<li>Time of the Day when <em>WeRateDogs (@dogrates)</em> Shows Most Activity</li>
<li>Correlation between Favorite Counts and Retweet Counts</li>
<li>Comparison of Dog Ratings and Sentiment of Tweets</li>
<li>Accuracy and Precision of Predicting Dogs' Breeds from Images</li>
</ol>
<p>The functional roles of the various analytical methods used in this part of the project can be divided into two main categories, <em>Explore</em> and <em>Feature Engineering</em>. Exploring the clean version of the data provided motivations for investigating the four topics listed above. Feature engineering improved the wrangled data and streamlined the application of various analytical methods for generating insights from both statistics which quantitatively summarize the data and plots which visually present patterns in the data.</p>
<p>The next section describes in detail how various analytical methods relevant to each topic were applied to computing meaningful statistics and aims to demonstrate how the overall process of generating meaningful insights rely on efficient organization and arrangement of data, a task which is only feasible after successful wrangling of data. Note that during the investigation and discussion of each topic, the term "Tweet" always refers to original Tweets because all retweets were removed during the data wrangling phase.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">datetime</span> <span class="k">as</span> <span class="nn">dt</span>
<span class="kn">import</span> <span class="nn">copy</span>
<span class="kn">import</span> <span class="nn">statsmodels.api</span> <span class="k">as</span> <span class="nn">sm</span>
<span class="kn">from</span> <span class="nn">textblob</span> <span class="k">import</span> <span class="n">TextBlob</span>
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<span class="o">%</span><span class="k">matplotlib</span> inline
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
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<p><a id='analysis'></a></p>
<h2 id="EDA-and-Visualization">EDA and Visualization<a class="anchor-link" href="#EDA-and-Visualization">&#182;</a></h2><p>The <code>.csv</code> file containing the clean version of the master data from <strong>Part 1: Data Wrangling</strong> was imported to this notebook by using pandas.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># read .csv file containing cleaned master data</span>
<span class="n">df_master</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;data/twitter_archive_master.csv&#39;</span><span class="p">)</span>
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<h3 id="Data-Wrangling">Data Wrangling<a class="anchor-link" href="#Data-Wrangling">&#182;</a></h3><p>Assessment of the dataset imported above revealed that the data types of the two columns <code>tweet_id</code> and <code>timestamp</code> were integer and string (object), respectively. Although the data types of <code>tweet_id</code> and <code>timestamp</code> had been changed to string (object) and datetime, respectively, as documented in the data wrangling efforts from <strong>Part 1</strong>, the data types of these two columns may have been reverted as a result of reading the data from the <code>.csv</code> file. The data types of the <code>tweet_id</code> and <code>timestamp</code> columns were converted back to string (object) and datetime, respectively, as shown in the code block below.</p>

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<span class="n">col_list</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;tweet_id&#39;</span><span class="p">,</span> <span class="s1">&#39;timestamp&#39;</span><span class="p">]</span>

<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">col</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">col_list</span><span class="p">):</span>     
    <span class="c1"># data type of the column that needs to be fixed</span>
    <span class="n">col_dtype</span> <span class="o">=</span> <span class="n">df_master</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">dtype</span>
    
    <span class="k">if</span> <span class="n">i</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="c1"># tweet_id</span>
        <span class="c1"># change data type (of tweet_id) to string</span>
        <span class="n">df_master</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_master</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">dtype</span> <span class="o">=</span> <span class="s1">&#39;str&#39;</span><span class="p">)</span>
    
    <span class="k">else</span><span class="p">:</span> <span class="c1"># timestamp</span>
        <span class="c1"># change data type (of timestamp) to datetime</span>
        <span class="n">df_master</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">arg</span> <span class="o">=</span> <span class="n">df_master</span><span class="p">[</span><span class="n">col</span><span class="p">])</span>

    <span class="c1"># column name: data type before/after</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  - </span><span class="si">{}</span><span class="s1">: from &quot;</span><span class="si">{}</span><span class="s1">&quot; to &quot;</span><span class="si">{}</span><span class="s1">&quot;&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">col</span><span class="p">,</span> <span class="n">col_dtype</span><span class="p">,</span> <span class="n">df_master</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span>
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<pre>  - tweet_id: from &#34;int64&#34; to &#34;object&#34;
  - timestamp: from &#34;object&#34; to &#34;datetime64[ns, UTC]&#34;
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<p>The first three topics of interest will not utilize the data under the columns originally from the image predictions dataset which was gathered, assessed, and cleaned in <strong>Part 1</strong>. Thus, a sequence of steps similar to the one used in <strong>Part 1</strong> for cleaning data, <em>define</em>, <em>code</em>, and <em>test</em>, was used to separate the imported dataset into two sub-datasets, one for investigating the first three topics and another for the remaining topic.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># all columns in the master data</span>
<span class="n">df_master</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 5970 entries, 0 to 5969
Data columns (total 16 columns):
tweet_id              5970 non-null object
timestamp             5970 non-null datetime64[ns, UTC]
source                5970 non-null object
text                  5970 non-null object
rating_numerator      5970 non-null int64
rating_denominator    5970 non-null int64
name                  4107 non-null object
stage                 918 non-null object
retweet_count         5970 non-null int64
favorite_count        5970 non-null int64
jpg_url               5970 non-null object
img_num               5970 non-null int64
prediction            5970 non-null object
breed                 5970 non-null object
confidence            5970 non-null float64
dog_breed             5970 non-null bool
dtypes: bool(1), datetime64[ns, UTC](1), float64(1), int64(5), object(8)
memory usage: 705.5+ KB
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<p><strong>Define</strong></p>
<p>Divide the dataframe object <code>df_master</code> into two dataframe objects.</p>
<ol>
<li><code>df</code>: dataset containing all columns in <code>df_master</code> from <code>tweet_id</code> to <code>favorite_count</code></li>
<li><code>df_image</code>: dataset containing all columns in <code>df_master</code> which were excluded from <code>df</code> except the column <code>tweet_id</code></li>
</ol>
<p><strong>Code</strong></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create two sub-datasets</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df_master</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">6</span><span class="p">]</span>
<span class="n">df_image</span> <span class="o">=</span> <span class="n">df_master</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">np</span><span class="o">.</span><span class="n">r_</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">11</span><span class="p">:</span><span class="mi">16</span><span class="p">]]</span>

<span class="c1"># remove all duplicate rows</span>
<span class="n">df</span><span class="o">.</span><span class="n">drop_duplicates</span><span class="p">(</span><span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>

<span class="c1"># reset index in each sub-dataset</span>
<span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">df_image</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
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<p><strong>Test</strong></p>
<p>Two dataframe objects <code>df</code> and <code>df_image</code> were successfully created from the dataframe object <code>df_master</code> as originally planned.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># first sub-dataset for investigating the first three topics</span>
<span class="n">df</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 1990 entries, 0 to 1989
Data columns (total 10 columns):
tweet_id              1990 non-null object
timestamp             1990 non-null datetime64[ns, UTC]
source                1990 non-null object
text                  1990 non-null object
rating_numerator      1990 non-null int64
rating_denominator    1990 non-null int64
name                  1369 non-null object
stage                 306 non-null object
retweet_count         1990 non-null int64
favorite_count        1990 non-null int64
dtypes: datetime64[ns, UTC](1), int64(4), object(5)
memory usage: 155.5+ KB
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># second sub-dataset for investing the last topic</span>
<span class="n">df_image</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 5970 entries, 0 to 5969
Data columns (total 6 columns):
tweet_id      5970 non-null object
img_num       5970 non-null int64
prediction    5970 non-null object
breed         5970 non-null object
confidence    5970 non-null float64
dog_breed     5970 non-null bool
dtypes: bool(1), float64(1), int64(1), object(3)
memory usage: 239.1+ KB
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<h3 id="1.-Time-of-the-Day-when-WeRateDogs-(@dogrates)-Shows-Most-Activity">1. Time of the Day when <em>WeRateDogs (@dogrates)</em> Shows Most Activity<a class="anchor-link" href="#1.-Time-of-the-Day-when-WeRateDogs-(@dogrates)-Shows-Most-Activity">&#182;</a></h3><h4 id="Explore">Explore<a class="anchor-link" href="#Explore">&#182;</a></h4><p>A subset of the data contained in the dataframe object <code>df</code> was obtained by filtering the data for the timestamps of the Tweets. In this subset, two new columns were created, one for the hour part and another for the day part of the date and time data.</p>
<ul>
<li>The numbers of Tweets posted during each hour on each day of the week suggested that the account regularly posted Tweets during certain hours on each day. On Mondays, for example, the Tweets were posted mainly during the two time periods, four hours starting from around midnight and three hours starting from three in the afternoon.</li>
<li>Also, although the total number of Tweets from each day of the week diminished as the week progressed from Monday, the differences in the counts of Tweets between any two days did not appear to be significant.</li>
</ul>
<p>These two observations motivated the investigation of the time of the day when the Twitter account shows most activity and how the trend from one day compares with the trends from other days of the week.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># sub-dataset for timestamps of tweets</span>
<span class="n">df_1</span> <span class="o">=</span> <span class="n">df</span><span class="p">[[</span><span class="s1">&#39;timestamp&#39;</span><span class="p">]]</span>
<span class="n">df_1</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>

<span class="c1"># hour and day parts of timestamps</span>
<span class="n">df_1</span><span class="p">[</span><span class="s1">&#39;hour&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">timestamp</span><span class="o">.</span><span class="n">dt</span><span class="o">.</span><span class="n">hour</span>
<span class="n">df_1</span><span class="p">[</span><span class="s1">&#39;day&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">timestamp</span><span class="o">.</span><span class="n">dt</span><span class="o">.</span><span class="n">weekday</span>

<span class="c1"># number of tweets in each hour on day 0 (Mondays)</span>
<span class="n">df_1</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;day&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">hour</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
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<pre>hour
1     44
0     42
16    34
3     32
2     30
17    29
15    26
23    21
4     13
19    12
18    11
20    11
21    11
22     8
5      1
13     1
14     1
Name: hour, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># total number of tweets from each day of a week</span>
<span class="n">df_1</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;day&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">hour</span><span class="o">.</span><span class="n">agg</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">)</span>
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<pre>day
0    327
1    295
2    296
3    283
4    281
5    252
6    256
Name: hour, dtype: int64</pre>
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<h4 id="Feature-Engineering">Feature Engineering<a class="anchor-link" href="#Feature-Engineering">&#182;</a></h4><p>To allow for the comparison of Twitter activity during the same hour on each day, the activity was defined as the percentage of Tweets posted during an hour-long period on a given day of the week. This quanitity which was computed by dividing the number of Tweets posted in each hour on a given day by the total number of Tweets from that day was stored in the new column, <code>tweet_percentage</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># percentage of tweets from each hour on a given day of the week</span>
<span class="n">df_1</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;day&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">hour</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span> <span class="o">/</span> <span class="n">df_1</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;day&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">hour</span><span class="o">.</span><span class="n">agg</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span>
<span class="n">df_1</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">df_1</span><span class="p">)</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">columns</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;hour&#39;</span><span class="p">:</span><span class="s1">&#39;tweet_percentage&#39;</span><span class="p">})</span>

<span class="c1"># reset multi-index</span>
<span class="n">df_1</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">level</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;day&#39;</span><span class="p">,</span><span class="s1">&#39;hour&#39;</span><span class="p">],</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>

<span class="n">df_1</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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      <th></th>
      <th>day</th>
      <th>hour</th>
      <th>tweet_percentage</th>
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      <th>0</th>
      <td>0</td>
      <td>1</td>
      <td>13.455657</td>
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      <th>1</th>
      <td>0</td>
      <td>0</td>
      <td>12.844037</td>
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      <th>2</th>
      <td>0</td>
      <td>16</td>
      <td>10.397554</td>
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      <th>3</th>
      <td>0</td>
      <td>3</td>
      <td>9.785933</td>
    </tr>
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      <th>4</th>
      <td>0</td>
      <td>2</td>
      <td>9.174312</td>
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<p>Because no Tweet was posted during several hours of each day, these hours were not recoreded in the dataframe object <code>df_1</code>. To allow for the plotting of the percentages for all 24 hours of each day, these hours without any Twitter activity were added to the dataframe.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># index to which new row can be added</span>
<span class="n">ind</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">+</span> <span class="mi">1</span>

<span class="c1"># daily hours available: 0, 1, ..., 22, 23</span>
<span class="n">hours</span> <span class="o">=</span> <span class="p">[</span><span class="n">hour</span> <span class="k">for</span> <span class="n">hour</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">24</span><span class="p">)]</span>

<span class="c1"># if the hour is not recorded in the dataframe for given day</span>
<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">df_1</span><span class="o">.</span><span class="n">day</span><span class="o">.</span><span class="n">unique</span><span class="p">():</span>
    <span class="k">for</span> <span class="n">hr</span> <span class="ow">in</span> <span class="n">hours</span><span class="p">:</span>
        <span class="k">if</span> <span class="n">hr</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">df_1</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;day == @d&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">hour</span><span class="o">.</span><span class="n">unique</span><span class="p">():</span>
            
            <span class="c1"># add new row with day, hour, and 0 percentage of tweet-posting activity</span>
            <span class="n">df_1</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">ind</span><span class="p">]</span> <span class="o">=</span> <span class="n">d</span><span class="p">,</span> <span class="n">hr</span><span class="p">,</span> <span class="mi">0</span>
            
            <span class="c1"># update index for the next row addition</span>
            <span class="n">ind</span> <span class="o">+=</span> <span class="mi">1</span>

<span class="n">df_1</span><span class="o">.</span><span class="n">tail</span><span class="p">()</span>
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      <td>6</td>
      <td>14</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># sort values by three columns and reset index</span>
<span class="n">df_1</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">by</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;day&#39;</span><span class="p">,</span> <span class="s1">&#39;hour&#39;</span><span class="p">,</span> <span class="s1">&#39;tweet_percentage&#39;</span><span class="p">],</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">df_1</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>

<span class="n">df_1</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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      <th>hour</th>
      <th>tweet_percentage</th>
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      <th>0</th>
      <td>0</td>
      <td>0</td>
      <td>12.844037</td>
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      <th>1</th>
      <td>0</td>
      <td>1</td>
      <td>13.455657</td>
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      <td>0</td>
      <td>2</td>
      <td>9.174312</td>
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      <th>3</th>
      <td>0</td>
      <td>3</td>
      <td>9.785933</td>
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      <th>4</th>
      <td>0</td>
      <td>4</td>
      <td>3.975535</td>
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<p>Before creating a bar plot for each day of the percentages of Tweets in each hour, a dictionary which maps the seven integer values of the <code>day</code> column to their corresponding names of the day was created as shown below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">day_of_week</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Monday&#39;</span><span class="p">,</span> <span class="s1">&#39;Tuesday&#39;</span><span class="p">,</span> <span class="s1">&#39;Wednesday&#39;</span><span class="p">,</span> <span class="s1">&#39;Thursday&#39;</span><span class="p">,</span> <span class="s1">&#39;Friday&#39;</span><span class="p">,</span> <span class="s1">&#39;Saturday&#39;</span><span class="p">,</span> <span class="s1">&#39;Sunday&#39;</span><span class="p">]</span>
<span class="n">dow</span> <span class="o">=</span> <span class="p">[</span><span class="n">day</span> <span class="k">for</span> <span class="n">day</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">7</span><span class="p">)]</span> <span class="c1"># integers representing days of a week</span>

<span class="c1"># dictionary mapping integers to days of a week</span>
<span class="n">dow_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">dow</span><span class="p">:</span>
    <span class="c1"># integer: day of week (ex 0: Monday)</span>
    <span class="n">dow_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">day_of_week</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
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<p>According to the bar plots shown below, the trends in posting Tweets throughout the 24 hourly increments of each day have two modes.</p>
<ul>
<li><em>WeRateDogs</em> showed the most frequent activity or posted tweets most frequently during the first two-hour period from midnight from Monday to Sunday. The hourly percentage of Tweets during this period ranged from 12% to 16%, nearly three to four times the average of 4.17%.</li>
<li>Also, except on Sunday, the account showed the most frequent activity or posted Tweets most frequently during the two-hour period from 16 to 18. The hourly percentage of Tweets during this period ranged from 8% to 11%, nearly two to three times above the average. On Sunday, the second mode was observed on the last hour of the day, showing an hourly percentage of Tweets of 10%.</li>
</ul>
<p>From Monday to Sunday, the account showed the least or no activity during the approximately 10-hour time period from 5 to 15.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create figure with 2-by-4 subplots</span>
<span class="n">rows</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">cols</span> <span class="o">=</span> <span class="mi">4</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span> <span class="o">=</span> <span class="n">rows</span><span class="p">,</span> <span class="n">ncols</span> <span class="o">=</span> <span class="n">cols</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">18</span><span class="p">,</span> <span class="mi">9</span><span class="p">))</span>

<span class="c1"># add figure title and common x, y axes labels for all subplots</span>
<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;Percentage of Hourly Tweets for each Day of the Week&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">18</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="mf">0.06</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Hour of the Day&#39;</span><span class="p">,</span> <span class="n">ha</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">va</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mf">0.09</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Percentage of Tweets Posted (%)&#39;</span><span class="p">,</span> <span class="n">ha</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">va</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">rotation</span> <span class="o">=</span> <span class="s1">&#39;vertical&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>

<span class="c1"># for each subplot, ax[row, col]</span>
<span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">rows</span><span class="p">):</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">cols</span><span class="p">):</span>
        
        <span class="k">if</span> <span class="n">row</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="c1"># in first row, col number = integer for the given day</span>
            <span class="n">df_1_temp</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;day == @col&#39;</span><span class="p">)</span> <span class="c1"># filter data for the given day</span>
            <span class="n">day_name</span> <span class="o">=</span> <span class="n">dow_dict</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="c1"># find name of the day</span>
            
        <span class="k">else</span><span class="p">:</span>
            <span class="c1"># delete last (eighth) subplot because there is only seven days in a week</span>
            <span class="k">if</span> <span class="n">col</span> <span class="o">==</span> <span class="n">cols</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">fig</span><span class="o">.</span><span class="n">delaxes</span><span class="p">(</span><span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">])</span>
                <span class="k">break</span>
            
            <span class="c1"># in second row, col number = integer for the given day - 4</span>
            <span class="n">df_1_temp</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;day == @col + 4&#39;</span><span class="p">)</span>
            <span class="n">day_name</span> <span class="o">=</span> <span class="n">dow_dict</span><span class="p">[</span><span class="n">col</span> <span class="o">+</span> <span class="mi">4</span><span class="p">]</span>

        <span class="c1"># set up xtick locations and labels</span>
        <span class="n">width</span> <span class="o">=</span> <span class="mi">2</span>
        <span class="n">x_loc</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">df_1_temp</span><span class="o">.</span><span class="n">hour</span> <span class="o">*</span> <span class="n">width</span><span class="p">)</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="p">[</span><span class="n">label</span> <span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">24</span><span class="p">)]</span>
        
        <span class="c1"># bar plots for percentage of hourly tweets for each day of week</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">x_loc</span><span class="p">,</span> <span class="n">height</span> <span class="o">=</span> <span class="n">df_1_temp</span><span class="o">.</span><span class="n">tweet_percentage</span><span class="p">,</span> <span class="n">width</span> <span class="o">=</span> <span class="n">width</span><span class="p">,</span> <span class="n">align</span> <span class="o">=</span> <span class="s1">&#39;edge&#39;</span><span class="p">)</span>
        
        <span class="c1"># label suplot with name of the day</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">day_name</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
        
        <span class="c1"># label xticks by increments of two: 0, 2, ..., 22</span>
        <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)):</span>
            <span class="k">if</span> <span class="n">labels</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">%</span> <span class="mi">2</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">labels</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;&#39;</span>
        
        <span class="c1"># add xtick labels to the subplot</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="n">ticks</span> <span class="o">=</span> <span class="n">x_loc</span><span class="p">)</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="p">)</span>
        
        <span class="c1"># statistics for percentages of tweets across hours in a given day</span>
        <span class="n">avg</span> <span class="o">=</span> <span class="n">df_1_temp</span><span class="o">.</span><span class="n">tweet_percentage</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
        <span class="n">sd</span> <span class="o">=</span> <span class="n">df_1_temp</span><span class="o">.</span><span class="n">tweet_percentage</span><span class="o">.</span><span class="n">std</span><span class="p">()</span>
        <span class="n">lower</span> <span class="o">=</span> <span class="n">avg</span> <span class="o">-</span> <span class="n">sd</span><span class="o">/</span><span class="mi">2</span>
        <span class="n">upper</span> <span class="o">=</span> <span class="n">avg</span> <span class="o">+</span> <span class="n">sd</span><span class="o">/</span><span class="mi">2</span>
        
        <span class="c1"># horizontal lines for mean percentage +,- standard deviation/2</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">hlines</span><span class="p">(</span><span class="n">y</span> <span class="o">=</span> <span class="n">lower</span><span class="p">,</span> <span class="n">xmin</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">xmax</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span> <span class="n">colors</span> <span class="o">=</span> <span class="s1">&#39;red&#39;</span><span class="p">,</span> <span class="n">linestyles</span> <span class="o">=</span> <span class="s1">&#39;--&#39;</span><span class="p">)</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">hlines</span><span class="p">(</span><span class="n">y</span> <span class="o">=</span> <span class="n">upper</span><span class="p">,</span> <span class="n">xmin</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">xmax</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span> <span class="n">colors</span> <span class="o">=</span> <span class="s1">&#39;red&#39;</span><span class="p">,</span> <span class="n">linestyles</span> <span class="o">=</span> <span class="s1">&#39;--&#39;</span><span class="p">)</span>
        
        <span class="c1"># legend for statistics</span>
        <span class="n">ax</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mi">30</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">df_1_temp</span><span class="o">.</span><span class="n">tweet_percentage</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;</span><span class="si">{}</span><span class="s1">+/-</span><span class="si">{}</span><span class="s1"> %&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">avg</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="nb">round</span><span class="p">(</span><span class="n">sd</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)),</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
</pre></div>

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<p>Note that for all seven days, the mean percentage of hourly Tweets is approximately 4.17% because of dividing 100% by 24-hour increments. A box plot of the distribution of these percentages of hourly Tweets was created for each day to streamline the comparison of the distribution across days.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># five percentiles for percentages of hourly tweets</span>
<span class="n">percentile_list</span> <span class="o">=</span> <span class="p">[]</span>

<span class="k">for</span> <span class="n">day</span> <span class="ow">in</span> <span class="n">df_1</span><span class="o">.</span><span class="n">day</span><span class="o">.</span><span class="n">unique</span><span class="p">():</span>
    <span class="n">df_1_temp</span> <span class="o">=</span> <span class="n">df_1</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;day == @day&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">tweet_percentage</span>
    
    <span class="c1"># one list of percentiles for each day&#39;s data</span>
    <span class="n">percentile_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">df_1_temp</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">25</span><span class="p">,</span><span class="mi">50</span><span class="p">,</span><span class="mi">75</span><span class="p">,</span><span class="mi">100</span><span class="p">])</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>

<span class="c1"># box plot of distribution for percentages of hourly tweets</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">7</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">boxplot</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">percentile_list</span><span class="p">)</span>

<span class="c1"># change xticks from integers to names of the days</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">day_of_week</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">day_of_week</span><span class="p">)</span>

<span class="c1"># add title and axis labels</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Distribution of Percentage Hourly Tweets for each Day&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Hour of the Day&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Percentage of Tweets Posted (%)&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">);</span>
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<p>As observed in the previous bar plots, the box plots for all seven days showed a minimum percentage of hourly Tweet posts of 0% because on several hourly increments, the account did not post any tweets. The interquartile range of approximately 8% on Monday is the largest, whereas the interquartile range of approximately 6% on Tuesday is the smallest among the seven days of the week. Throughout the seven days, the median of the percentages ranges from 2% to 4%. The maximum percentage of hourly Tweet posts of approximately 16% which was observed on Tuesday, Thursday, and Friday was the largest among the seven days. These three days showed the largest range of percentage values as well, a trend also suggested by the standard deviations of the percentages for Tuesday, Thursday, and Friday which were largest among all seven days.</p>

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<h3 id="2.-Correlation-between-Favorite-Counts-and-Retweet-Counts">2. Correlation between Favorite Counts and Retweet Counts<a class="anchor-link" href="#2.-Correlation-between-Favorite-Counts-and-Retweet-Counts">&#182;</a></h3><h4 id="Explore">Explore<a class="anchor-link" href="#Explore">&#182;</a></h4><p>The distribution of each variable, favorite counts and retweet counts, was explored by applying the <code>describe()</code> method from Pandas to the two columns, <code>favorite_count</code> and <code>retweet_count</code>, in the dataframe object <code>df</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># distribution of favorite counts</span>
<span class="n">df</span><span class="o">.</span><span class="n">favorite_count</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<pre>count      1990.000000
mean       8637.741206
std       12673.683099
min          77.000000
25%        1859.000000
50%        3913.500000
75%       10753.000000
max      162614.000000
Name: favorite_count, dtype: float64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># distribution of retweet counts</span>
<span class="n">df</span><span class="o">.</span><span class="n">retweet_count</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<pre>count     1990.000000
mean      2619.261809
std       4674.985902
min         11.000000
25%        583.250000
50%       1255.500000
75%       2991.750000
max      82729.000000
Name: retweet_count, dtype: float64</pre>
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<p>The quantitative analysis above showed a right-skewed distribution for both variables in which the median lies to the left of the mean. Considering the potential application of the counts of favorite and retweet for understanding the popularity of the corresponding Tweet, the distributions of these two variables must be right-skewed; in other words, large numbers of favorite counts and retweet counts are less likely to be observed than smaller numbers. If the distributions of both the favorite counts and the retweet counts are right-skewed, then what are the direction and the magnitude of the correlation between these two variables?</p>

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<h4 id="Feature-Engineering">Feature Engineering<a class="anchor-link" href="#Feature-Engineering">&#182;</a></h4><p>To streamline the visualization of the correlation between the favorite counts and the retweet counts, a sub-dataset containing only these two variables from the dataframe object <code>df</code> was newly created. In addition to creating a scatter plot for retweet counts vs. favorite counts, the value of the correlation coefficient for these two variables was calculated and displayed in the plot.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># sub-dataset for only the two columns favorite_count and retweet_count</span>
<span class="n">df_2</span> <span class="o">=</span> <span class="n">df</span><span class="p">[[</span><span class="s1">&#39;favorite_count&#39;</span><span class="p">,</span> <span class="s1">&#39;retweet_count&#39;</span><span class="p">]]</span>
<span class="n">df_2</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>

<span class="c1"># configure plot with size, title, and labels for both axes</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">12</span><span class="p">,</span> <span class="mi">7</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Correlation between Retweet and Favorite Counts&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">18</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Favorite Count&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Retweet Count&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>

<span class="c1"># scatter plot of retweet count vs. favorite count</span>
<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">favorite_count</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">retweet_count</span>
            <span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="mi">30</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="n">marker</span> <span class="o">=</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">edgecolors</span> <span class="o">=</span> <span class="s1">&#39;black&#39;</span><span class="p">)</span>

<span class="c1"># compute and display correlation coefficient</span>
<span class="n">corr</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">corrcoef</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">favorite_count</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">retweet_count</span><span class="p">)[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span>
<span class="n">plt</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">favorite_count</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">y</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">retweet_count</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">*</span> <span class="mf">0.9</span>
         <span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Correlation Coefficient: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">corr</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
         <span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">);</span>
</pre></div>

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PDplMnrKCYcBeEr4NFocvQg4Y/65h3OewlhUpp8Kbur2zWL8Ga58YQ9lBDWky4iHIWiifaf4ncfsLlzbvcOl3MqYS3vJr3cLi2itc9/JiyB+HV0Whx6dfv4TLEa8HGHie1KLP8k0N7ugLqbsPTnyJTLS7Di+zS+LvO4vfcNhFc99iDsnb2nw5uC7weGEJYcpZpEOBTm3/owvmbat78/+neKS/lEY+fcFoT79LgeLu80ws6Mm13KUWiiy1iZMMFtYfnRgJLXd3KH66sirM9/IHqV5lPCY3GLDtfXlzeBJnW87d8jvNL4/eQJ0br0V1O2F/latKdcpAPv/VLn3F6EycbzLhyp4nnCH9B9Cb/47yA6KoX3vtE5dwxhovxC9I58CH/QhwP79GVJR4fLrYkudylhcr02cGAXy2ueIbyx69Joj+giwpv0fhKdvzJl2+Rk4CQXjhBzHyv6LWFv6Rzn3JWEJwp7Radd4r3vOPnvq3rg7GjMbxPeyPZdYJL3PrkHLjmWJ104Asz7hEnKHsCMlKPAJG/XT6M/5jOjVrMIh93bhLA+Gu99i3Pu6egy5qRcF4T1o3sTDol2NfAa4cgjB0WXNauX26XT8YTjyJ/hnLszetNwvvf6lDBJ+4ELR8i423v/eSe3fRZh4nY74ed2TcLPX/INxpWdnKc7fyJMwKudc6OBN4Gf0o97XiO9HfctLH+icGyH711H+NyBS5xzmxKe1G8FHEbYy9ybN6kmfUJ48nQ08IT3/lXn3BXRda/mwlFQViUc7WkxYdLdJR+Ou34E8EfAu/DZBu8Q9uQfQXhF5vjojZzJ7ZPX90h0fWtF1/c50aEIo1d1/kpYc/9Hwvt3diI8oexunXtPt31H59wJhGVb9xPWtv8xWnb0NmEP/mTgsX78PSgDmPaUi3TCh4943oJw9I9tCB+y8TvCpPZwwifStaRsfxdhT8pHhD2IpxA+pGKn1CM49GEcycudT/iDdw5hwv0D731XH260gLDe8Z3oPOcTJvH7AdOBjV04PjKEw4DNJvzh7vQYzNHkbmvCXtdfEI6QsjJwhF9+WL/+8Dlhsj+ecBi81YCfeu/bDuOWMpYHCE9OLiMsKTiBlD2E0dEsriRMSi4jepOb9/5NQpcWwprmpORe4HYf5+69/4xw/99IeEJ2BWFN7DmkPNmybpdO0f3+G8IbKK+JTsvrXtGe4N8R3tB8JWH5QGfOJPyMbhNtdxjhiDRbRGPfuYvzdSp6hWgi4VWxHxMON/kBYQLWn86kd+N+kvC74GM6HFs82pM+jrCzYALhfhxL+PnfqeMbQI3OIPxcXkb42YSwN3wSYQI9lfA4eooOh3Xsivd+JuExOZtw319J+KCzfwFjvfeXdzjLcdF1rEE4rvgRhFd5tuywBOYowjHv9yL8/qggLEPsy+2G8HvuTcJ9f3i0V/x70XUfSPhd+uPo3726uhCR3ihobe3svVUiIiIiIpIp2lMuIiIiIpJlmpSLiIiIiGSZJuUiIiIiIlmmSbmIiIiISJYNyEMitrS0tDY36w2uIiIiIpI+iUTRQsLRino0ICflzc2tLFpU3/OG/ayychCLFy/N+PXmI7WyUys7tbJTKxt1slMrO7Wyy/VWw4ZVvm/ddkAeErGxsbk1G5NyERERERk4hg2rfJHwGRA90pryDKqoKMn2EPKGWtmplZ1a2amVjTrZqZWdWtnFqZUm5Rm0ZElfP1hs4FErO7WyUys7tbJRJzu1slMruzi10qQ8g0pLB+QS/j5RKzu1slMrO7WyUSc7tbJTK7s4tdKkPIMaG5uzPYS8oVZ2amWnVnZqZaNOdmplp1Z2cWqlSXkGFRUpt5Va2amVnVrZqZWNOtmplZ1a2cWpVXxuSR4YiEe66Su1slMrO7WyUysbdbJTKzu1sotTK03KMyhGj5u0Uys7tbJTKzu1slEnO7WyUyu7OLXSpDyD4vQSS7qplZ1a2amVnVrZqJOdWtmplV2cWsXnluSBxsambA8hb6iVnVrZqZWdWtmok51a2amVXZxaaVKeQaWliWwPIW+olZ1a2amVnVrZqJOdWtmplV2cWhXEaYG8VWNjc+uiRfXZHoaIiIiIxNiwYZUvAltZttWe8gwaPLg020PIG2plp1Z2amWnVjbqZKdWdmplF6dW2lMuIiIiIrFUWzuf6urp1NTMpapqNJMnT2LEiJEZu37tKc9RlZWDsj2EvKFWdmplp1Z2amWjTnZqZadWdt21qq2dz9ix45g5s5SXXjqJmTNLGTt2HLW18zM4QjtNyjNo8eKl2R5C3lArO7WyUys7tbJRJzu1slMru+5aVVdPp67uAJqapgK70NQ0lfr6A6iunp65AfaCJuUZpGe+dmplp1Z2amWnVjbqZKdWdmpl112rmpq5NDWNb3daY+N4amrmpntYfaJJeQbpma+dWtmplZ1a2amVjTrZqZWdWtl116qqajTFxbPbnZZIzKaqanS6h9UnmpRnUEVFfN4hnG5qZadWdmplp1Y26mSnVnZqZdddq8mTJ1FRcSvFxScCD5FInEh5+a1MnjwpcwPsBR19JYMKCgoYiL37Qq3s1MpOrezUykad7NTKTq3semqVT0df0aQ8g8rKSliyZFnGrzcfqZWdWtmplZ1a2aiTnVrZqZVdrrfSIRFz1LJlTdkeQt5QKzu1slMrO7WyUSc7tbJTK7s4tdKkPIOKi5XbSq3s1MpOrezUykad7NTKTq3s4tQqPrckD7S0DLylQn2lVnZqZadWdmplo052amWnVnZxalWcyStzziWAmcA6QDPwM6AJuBFoBV4Ffum9b3HOnQHsHn3/OO/9v5xzG1i3zeTtEhERERH5OjK9p3w3oNh7/13gbOA84BLgVO/99kABsKdzrgrYEdga2A+YFp2/N9vmnMLCgmwPIW+olZ1a2amVnVrZqJOdWtmplV2cWmV6Uv4mUOycKwSGAI3AlsAT0fdnAeOB7YCHvfet3vsPovMM6+W2OaepqSXbQ8gbamWnVnZqZadWNupkp1Z2amUXp1aZnpR/RVi68gZwLXAFUOC9Ty4IWgysRJiwf5FyvuTpvdm2S4WFBSQSRZSUFFFaWkxxcSFlZQkKCwuoqCgBln9sa8d/KypKKCwsoKwsQXFxIaWlxZSUFJFIFDFoUIKiogLKy8NlDB5c2sVllFJQUEBZWQlFReEyEolwGaWlxRQVFVJWVkJBQUHbQfE7XkbyssvLSygqKmDQoESsblNpaSJ2tyld99OgQYnY3aZ03U9dXUY+36Z03U8lJcWxu03puJ9KSopjd5vSdT+VlZXE7jal635KjiNOtyld91Pq76pcvE29kdHjlDvnLgEavPdTnHPfAB4DVvHeD42+vycwgbBHfZD3/qLo9Jei01/23o+0bOu9X9jVOPThQblPrezUyk6t7NTKRp3s1MpOrexyvVUuH6f8c5bv1f4MSAAvOefGRqftCjwF/AOY6JwrdM6NAgqjSXZvts05yWdU0jO1slMrO7WyUysbdbJTKzu1sotTq4wefQW4FLjeOfcUUAKcArwAXOucKwFeB+703jdH2zxLeOLwy+j8v+7Ftjmnrq4h20PIG2plp1Z2amWnVjbqZKdWdmplF6dWGV2+kiuytXylsnIQixcvzfj15iO1slMrO7WyUysbdbJTKzu1ssv1Vr1ZvqJJuYiIiIhIGuTymvIBLfluXOmZWtmplZ1a2amVjTrZqZWdWtnFqZX2lIuIiIiIpIH2lOeo5HEspWdqZadWdmplp1Y26mSnVnZqZRenVtpTLiIiIiKSBtpTnqPidCzNdFMrO7WyUys7tbJRJzu1slMruzi10qQ8gxoaGrM9hLyhVnZqZadWdmplo052amWnVnZxaqVJeQYlEpn+rKb8pVZ2amWnVnZqZaNOdmplp1Z2cWqlSXkGNTe3ALB48WKmTbucfffdk3HjtmX//X/En/50I01NTRkbS03NC2y33Vbm63z88dl8+ulCAP74xxkcffQRaRvbsmXLuPbaGRx44D6MG7ct++67J1dddSX19XX9dh2zZv2N3XYbx8SJO/LVV1+1+/r22//MXnvt1uNl9LZhdxobG7n33rvM27e2tjJjxjT22GMCO+20HdXVl9Hc3Nzl9m+95Zk06UgmTNieww47gOeee7bd9x944D5+8pMfsvPO23L00Yczd+6rfb4tuSz5Myg9UysbdbJTKzu1sotTK73RM4NKSopYuPAzjjrqMFZZZVUOP/znDB8+gjfffIPLLptKVdVWnH76ORkZS03NCxx77C+YM+efFBd3/yzzf//7L/vs833+8pd7GDnyG9TX19PU1MiQISv1+7gaGxs59tijqK+v52c/O5r11tuADz/8gCuvvISVV16Fyy6b3uN4LXbZZSz77LMfu+/+A9Zaa3i7r1dddVXq65ewyiqr9DjWL7/8gtVWG/q1xzNr1t+45prp3HPPg6bt//KXm/nLX27hjDPOpbi4kNNOO4W99/4JBx106Arbfv755+y//4/Ybrsd+OlPD+W11/7DpZdeRHX1NWy00Wief/6fnHzyr/nd785go41Gc/fdtzNr1gPceed9lJdXfO3blktKSopYtqzrJy+ynFrZqJOdWtmplV2ut+rNGz3js88/DxQUFHDVVVdSXFzMpZdOo7Q0HMZn+PARrLTSyhxzzFHsvfdP2HjjTbI80vY6PnErLy9P23XdeutNfPjhh9xxxz2UlQ0GQp+RIy/lgAP25oknHmPcuO997ev56quv2HzzLVhrreGdfl1a2vOHESQSiX6ZkMOKjXty++1/5ogjjmLMmC0pLS3m6KOPYcaMaZ1Oyh966AHKy8v57W9Po7i4mHXWWZe5c1/lz3++mbPOOp/PPvuMI474eVvXww//ObfddivvvPM2m266eX/cvJxRUFCQ7SHkDbWyUSc7tbJTK7s4tdKkPIOWLFnK7NkP88tfHts2IU8aM2ZLrrjiatZffwMAvvzyS6666kqefvoJGhoa2Hbb7Tn++JMYMmQlampe4JxzTmf77Xfk739/kB//+AD+97//0trayjvvvMXHHy/giitmsMYaa3LZZRfz1FNzKC0dxLbb7sAxxxzX6d7PV199henTr8D71ykoKGCzzcYwZcppDBu2Ovvu+wMA9ttvL0455Qz++9+PeOGFf3HVVX9sO++0aZfz1luelVdehf33P4i99/4xAOeddyYVFYP5/PPP+Mc/nmTo0NU5+ODD2G2373faaNasv7H77j+gsnIITU3LX5IaMWIkV1wxo61PQ0MD119/DY888hBffvkFVVXf5oQTfsOaa64FwMcfL+DSSy/i+eefY8iQlZgwYReOPPIXLFz4SdvtOf74yey66x7MmvW3dl+PGbMl1157Vdte6zfffIMrrriE119/jVVXHcohhxzOHnvsucKrDV1dZyKR4MEH7+f+++/lO9/5P+666zaKiorYeefvccwxx/PyyzWcf/5ZAGy33Vbcccd9vPTSi5x//lk8/fQLKzRauPATPv54AZtvPgYIL91tttkWfPzxAhYs+B9rrLFmu+0/+qiWjTYa3e4Vhg02+Ca33DITgIkTly/VaWhYym233coqq6zKeuut3+l9lM/i9DJnuqmVjTrZqZWdWtnFqZXWlGfQggUfsWRJPRtttHGn36+q2opBg8Ie2lNOOZG33/ZceOElXH75dD744H3OOef0tm0/+eRj6urquP76W9omuA8/PItDD/0ZU6dewbrrrscFF5zFF18sYtq067joosv48MP3Oe+8M1e43vr6Ok466Ti22uo7/OlPt3PJJdV89FEtM2deD8C114bJ29VX38C4cRPanXfevPc49tij2WKLKq6//haOOOIorrrqCh57bHbbNvfeeyff/Kbj+utvZuut/4+pU3/Pl19+scI4GhqWMn/+h3zrW6NJJIpW+P7mm2/B4MFh7/nUqRfwxBOPceqpZzFjxo00Nzdz8skn0NzcTGtrK6ecchKVlUP44x9v5owzzuWZZ57i6qurWX31NfjrXx8C4Oyzf8+vfnXiCl+nWrRoEb/61STWXnsdbrjhFn7+86P5wx9+z7///XK77bq7zqTXX3+NefPeZdq06/jZzyZx11238dxzz7Lppptz7LG/ZrXVhvLXvz7E6quvwbhxE9rG1dHChWFt/9B0teHFAAAgAElEQVShwwBIJIpYddVVgfC46GjVVVflk08WtDvtf//7L198sajdac899yzjx2/PDTdcy7HHnkBFxeBOrz+fdfa4ks6plY062amVnVrZxamV9pRn0GefhUlQcmLZlbfffouXX67h5pvvYJ111gXgjDPO4YAD9uHdd99p2+7AAw9mxIiRbV9vuKFjxx13AqC2dj5PPjmHBx6Y3bb2+9RTz2Kffb7PggX/a3d9S5Ys4aCDDmP//X9KQUEBw4ePYOzYnXn11VcAWHnlVaJ/V15hWcf999/D+utvwFFH/RKAUaPWZt6897j11pvYeefxAKy33gYceOAhAPz855O4667beffdd9hii6p2l7V48WIAKioG09DQ9Zsnv/zyS/7+9we58MJLqaraqq3Pj360O8899ywlJSV89FEtM2bcQFFREWuvvQ4nnHAyJ5wwmaOPPqZtyUllZSWDBw9uuz+SX6d69NGHKS8v54QTTqaoqIhRo9bhyy+/oKWl/fq1F198vtvrBGhubuakk37H4MGDWXvtdbj77tt54425bLPNtgwePJjCwsK2sRUVFXW5hKahYSkAJSUl0ddNJBLh/5ctW7bC9mPHjuPGG6/jrrtuY8899+aNN17ngQfuo7Gx/WGkNthgQ66//maeeuoJzj//LNZaawSbbLJpl/dDPurucSXtqZWNOtmplZ1a2cWplSblGbTGGmHCtXjxl91u9/7771FeXtE2IQcYNWodKiuH8P7777HSSisDsOaaw9udb6211mr7/3nz3qO1tZW9995jhcv/8MMPKCxc/iLJaqsNZbfdvs9tt93CW2+9ybx57/H2228yenTPa9vnzZu3whr4TTfdjLvvvqPt69QnDsm9r50dsST55GHx4sWUlSWoq1txgpkcf0tLS7vrHTJkpbYnBKWlJXz11WJ22WVs2/dbW1tpbGxkwYL/tRtPz7fvPTbc8JsUFS1/Jr733j8Bwptlk95//71urxNgpZVWbjfpLy+v6NORW5KT8WXLllFcXExZWYLPPlsC0PZKS6p1112PU045g0svvYjLL/8Dw4ePZN999+P2229tt91qqw1ltdWGsuGGjldf/Q9//etdsZuUd/e4kvbUykad7NTKTq3s4tRKk/IMWmWVNRgyZCXmzn2Nb31rxSUsp58+hfHjJ7ZNujpqaWmmpWX52qmO25WULF+n3tzcTFlZGTfc0H7iBWHy9frrr7V9/cknH3PkkQex4YaO73xnG37wg7145pmneeWVl1c4b0edjbW5uaXd4fkSicQK23T2xsaSkhLWX39DXn/9tba97KkuvfQi1ltvgy6fLDQ3t9DS0kxzczMjR36Diy66bIVtVl99jW5vT0fW459artPaoSfDhq0OwGeffUp5eTl1dcv49NNPAbp84+nEibsxYcIufPbZZ6y22mrcc8+dbU/qXn31FUpLB7Hhht9s237dddflww8/6PXYcl1cfnFnglrZqJOdWtmplV2cWmlNeQatvHIF48d/j7vvvn2FZQY1NS/w2GOPsPLKK7P22utQX1/HvHnvtX3/vffepa6ujlGj1jZd16hRa7NkyRJaWsJkceTIbwBw5ZWXUFfX/njfTz75OOXlFUydegU//vH+bL75GD76qBYIE8bu3tm8zjrr8tpr7Y9p/dprr5jH2dHEibvx4IP30dLS0O7099+fx3333UNZWRkjR36DoqKidtf7xReLmD//A0aNWodvfGNtPv54AUOGrNR22z/99FOuvrq63ZMai5EjR/H222+1O9/555/Fdddd3W67r3udvXn3+NChw1hjjTXbnjRVVg7ilVdebju9o5qaFzj11N9QWFjI0KFDKSgo4Omnn2xb+nP33Xdw3XVXtTuP92+w9trrrnBZ+a6ysuej6kigVjbqZKdWdmplF6dWmpRn0OLFSznssJ+zbNkyjj/+l9TUvEBt7Xxmzfobp5/+W3bb7ftsttkWjBq1Dt/97vacd94ZvP76a7z++mucd96ZbLbZFmy4oTNd1zrrrMvWW3+Xc845nddee5W33nqTc889g88++4yhQ9vvTR0yZCUWLvyE55//J7W187n55ht54onHWLYsrDkuKysD4O2336S+vv3x3ffaax/effdtZsyYxgcfvM+sWX/j7rvvaDv6Sm/tvfePWXPN4Rx22CE888zT1NbO54knHuPEE49liy2q2HnnCZSVlfHDH+7N5ZdPpabmBd55523OOed0hg1bna233obvfOf/GD58BGeffSpvvfUmr776ChdeeA6FhYUrHPWmJ9/73q4sWVLPFVdcwgcfvM8jjzzE7Nl/Z+utt2m33de9zrKyMr766is++OB9mpqaaGhY2vZhTZ354Q/3YcaMal588XmefPIfzJgxjX333a/t+59//nnbfTVq1Do899yz3H77n/noo1quu+5q5s79T9v2P/rRvvzzn89w11238eGHH3DNNdPx/o12lxcXixcvzfYQ8oZa2aiTnVrZqZVdnFpp+UoGhWdzq3DVVX/k+uuv4dxzz2DRokUMHz6cAw88tN0k6NRTz+TSSy/mV7+aRGFhIdtvvyPHHHNCr67vtNPO5vLLp3LCCb+koKCArbbamuOPP2mF7XbeeQL//vdLnHbaFAC+9a3RHHPMCVxzzXQaGpay0kors9tu3+ess07l6KOPbXfe1Vdfg4svvpzq6sv4y19uZo011mTy5OP4/vd/2PtAQGlpKZdffhW33noDl156MZ9+upBhw4YxYcIuHHTQYW2H9Zs06VhaW1s59dSTaWxsZKutvsPll1/VNgH+/e8v4bLLpnL00YdTWlrKDjvsxDHHHN/r8QwePJiLLrqcyy+fyn333c3qq6/Jb397Optuunm7NeVFRUVf6zqrqr7N2muvw6GH7s/06X/k3Xff7vKQiAAHHHAQixZ9zu9+9xuKi4vYddfvs//+B7V9/2c/O5hdd92DI444iqFDh3LOORdSXX0Z11wzjQ03dFx22fS2ZTWbbLIZZ5/9e6699iqmTbuc9dffgEsuubLXS33yQWXloFj9Ak8ntbJRJzu1slMruzi10id6ioiIiIikQW8+0VPLVzIoTuue0k2t7NTKTq3s1MpGnezUyk6t7OLUSnvKRURERETSQHvKc1RFReeHOpQVqZWdWtmplZ1a2aiTnVrZqZVdnFppUp5BS5Y09ryRAGrVG2plp1Z2amWjTnZqZadWdnFqpUl5BpWW6mA3Vmplp1Z2amWnVjbqZKdWdmplF6dWmpRnUGNjc88bCaBWvaFWdmplp1Y26mSnVnZqZRenVpqUZ1BRkXJbqZWdWtmplZ1a2aiTnVrZqZVdnFrF55bkgYF4pJu+Uis7tbJTKzu1slEnO7WyUyu7OLXSpDyDYvS4STu1slMrO7WyUysbdbJTKzu1sotTK03KMyhOL7Gkm1rZqZWdWtmplY062amVnVrZxalVfG5JHmhsbMr2EPKGWtmplZ1a2amVjTrZqZWdWtnFqZUm5RlUWprI9hDyhlrZqZWdWtmplY062amVnVrZxalVQZwWyFs1Nja3LlpUn+1hiIiIiEiMDRtW+SKwlWVb7SnPoMGDS7M9hLyhVnZqZadWdmplo052amWnVnZxaqU95SIiIiIiaaA95TmqsnJQtoeQN9TKTq3s1MpOrWzUyU6t7NTKLk6ttKdcRERERCQNtKc8R8Xp2Vy6qZWdWtmplZ1a2aiTnVrZqZVdnFppT7mIiIiISBpoT3mOqqiIzzuE002t7NTKTq3s1MpGnezUyk6t7OLUSpPyDKqvX5btIeQNtbJTKzu1slMrG3WyUys7tbKLUytNyjNo0KD4fOpUuqmVnVrZqZWdWtmok51a2amVXZxaaVKeQcuWNWV7CHlDrezUyk6t7NTKRp3s1MpOrezi1EqT8gwqLlZuK7WyUys7tbJTKxt1slMrO7Wyi1Or+NySPNDSMvCOdNNXamWnVnZqZadWNupkp1Z2amUXp1aalIuIiIiIZJkm5RlUWFiQ7SHkDbWyUys7tbJTKxt1slMrO7Wyi1MrTcozqKmpJdtDyBtqZadWdmplp1Y26mSnVnZqZRenVpqUZ1BJSXG2h5A31MpOrezUyk6tbNTJTq3s1MouTq00Kc+gpUsbsz2EvKFWdmplp1Z2amWjTnZqZadWdnFqpUl5BpWXl2R7CHlDrezUyk6t7NTKRp3s1MpOrezi1KqgtTU+h5Kxamxsbl20qD7bwxARERGRGBs2rPJFYCvLttpTnkGVlYOyPYS8oVZ2amWnVnZqZaNOdmplp1Z2cWqlPeUiIiIiImmgPeU5Kk7P5tJNrezUyk6t7NTKRp3s1MpOrezi1Ep7ykVERERE0kB7ynPU4MGl2R5C3lArO7WyUys7tbJRJzu1slMruzi10p5yEREREZE00J7yHBWnY2mmm1rZqZWdWtmplY062amVnVrZxamVJuUZ1NAQn0+dSje1slMrO7WyUysbdbJTKzu1sotTK03KMyiRKM72EPKGWtmplZ1a2amVjTrZqZWdWtnFqZUm5RnU3NyS7SHkDbWyUys7tbJTKxt1slMrO7Wyi1MrTcozqKAg2yPIH2plp1Z2amWnVjbqZKdWdmplF6dWmpRnUEGcHjlpplZ2amWnVnZqZaNOdmplp1Z2cWqlSXkGxekllnRTKzu1slMrO7WyUSc7tbJTK7s4tdKkPIMSiaJsDyFvqJWdWtmplZ1a2aiTnVrZqZVdnFppUp5BDQ1N2R5C3lArO7WyUys7tbJRJzu1slMruzi10qQ8g8rKEtkeQt5QKzu1slMrO7WyUSc7tbJTK7s4tSpobW3N9hgyrrGxuXXRovpsD0NEREREYmzYsMoXga0s22pPeQZVVg7K9hDyhlrZqZWdWtmplY062amVnVrZxamV9pSLiIhIWtXWzqe6ejo1NXOpqhrN5MmTGDFiZLaHJZJ22lOeo+L0bC7d1MpOrezUyk6tbNSpZ7W18xk7dhw33VTKSy+dxMyZpYwdO47a2vnZHlrO0uPKLk6tNCnPoMWLl2Z7CHlDrezUyk6t7NTKRp16Vl09nbq6A2hsnArsQlPTVOrrD6C6enq2h5az9Liyi1MrTcozKE7P5tJNrezUyk6t7NTKRp16VlMzl6am8e1Oa2wcT03N3CyNKPfpcWUXp1aalGdQnJ7NpZta2amVnVrZqZWNOvWsqmo0xcWz252WSMymqmr017rc2tr5TJlyChMn/pApU06J1XIYPa7s4tRKb/TMoIqKEurqlmX8evORWtmplZ1a2amVjTr1LLmmvL7+ABobx5NIzKa8/FbmzHm0z2/2TF5mXd0BNDWNp7h4NhUVX+8yc4keV3a53qo3b/TM+KTcOTcF+AFQAkwHngBuBFqBV4Ffeu9bnHNnALsDTcBx3vt/Oec2sG7b3RiyNSkvLCygpWXgPQnqC7WyUys7tbJTKxt1sunvo69MmXIKM2eW0tQ0te20ROJEDj64gQsuOL8/hpxVelzZ5XqrnD36inNuLPBdYFtgR+AbwCXAqd777YECYE/nXFX0/a2B/YBp0UX0ZtucU1panO0h5A21slMrO7WyUysbdbIZMWIkl112MX//+71ccMH5X3tvdtzXqetxZRenVpleUz4R+A9wD3A/8DdgS8LecoBZwHhgO+Bh732r9/4DoNg5N6yX2+acxsbmbA8hb6iVnVrZqZWdWtmok11/tkrXOvVcoceVXZxaZXpSPpSwC39f4BfALUCh9z75usNiYCVgCPBFyvmSpxf0YtsuFRYWkEgUUVJSRGlpMcXFhZSVJSgsLKCiogRY/m7ejv9WVJRQWFhAWVmC4uJCSkuLKSkpIpEoYtCgBEVFBZSXh8sYPLi0w3lL2/4tKCigrKyEoqJwGYlEuIzS0mKKigopKyuhoKCg7Twdx5G87PLyEoqKChg0KJGV25R62/rzNiWvO063KV33U0lJcexuU7rup/Ly+N2mdN1PRUWFsbtN6bifwnXG6zal634qLS3ut9t03HHHMHjwn0kkTgQeIpE4kYqKPzN58qRYPPbKygbmz1NfblPq76pcvE29kdE15c653wOfeO//EH39b2BD73159PWewATgTWCQ9/6i6PSXotNf9t6PtGzrvV/Y1Tiytaa8pKSIZcvi84wundTKTq3s1MpOrWzUya6/W8X5U0L1uLLL9Va9WVOe6YU4TwO/cs5dAqwFVACPOufGeu/nALsCjwNvAxc556YCIwl70xc6516ybpvh22UyAA9002dqZadWdmplp1Y26mTX361GjBgZizd1dkaPK7s4tcropNx7/zfn3A7AvwhLZ34JvAdc65wrAV4H7vTeNzvnngKeTdkO4Ne92DbnFBUVxmrtUzqplZ1a2amVnVrZqJOdWtmplV2cWuk45RlUVFRAc/PA690XamWnVnZqZadWNupkp1Z2amWX661y9pCIA11paSLbQ8gbamWnVnZqZadWNupkp1Z2amUXp1baUy4iIiIikgbaU56jkofMkZ6plZ1a2amVnVrZqJOdWtmplV2cWmlPuYiIiIhIGmhPeY5KHkxeeqZWdmplp1Z2amWjTnZqZadWdnFqpT3lIiIiIiJpoD3lOSpOz+bSTa3s1MpOrezUykad7NTKTq3s4tRKe8pFRERERNJAe8pzVEVFfN4hnG5qZadWdmplp1Y26mSnVnZqZRenVpqUZ1B9/bJsDyFvqJWdWtmplZ1a2aiTnVrZqZVdnFppUp5BgwbF51On0k2t7NTKTq3s1MpGnezUyk6t7OLUSpPyDFq2rCnbQ8gbamWnVnZqZadWNupkp1Z2amUXp1aalGdQcbFyW6mVnVrZqZWdWtmok51a2amVXZxaxeeW5IGWloF3pJu+Uis7tbJTKzu1slEnO7WyUyu7OLXSpFxEREREJMs0Kc+gwsKCbA8hb6iVnVrZqZWdWtmok51a2amVXZxaaVKeQU1NLdkeQt5QKzu1slMrO7WyUSc7tbJTK7s4tdKkPINKSoqzPYS8oVZ2amWnVnZqZaNOdmplp1Z2cWqlSXkGLV3amO0h5A21slMrO7WyUysbdbJTKzu1sotTK03KM6i8vCTbQ8gbamWnVnZqZadWNupkp1Z2amUXp1YFra3xOZSMVWNjc+uiRfXZHoaIiIiIxNiwYZUvAltZtjXtKXfOne6cG97F99Z2zl3Ri/ENWJWVg7I9hLyhVnZqZadWdmplo052amWnVnZxatXlnnLn3KrJbYCPgYlATSeb7g1c4b0vS8sI00B7ykVEREQk3fprT/ktwCeECTnA36OvO/53NfB4Xwc7kMTp2Vy6qZWdWtmplZ1a2aiTnVrZqZVdnFp1dxyZI4HxhD3l1wPnAu902KYZWAQ8mpbRxczixUuzPYS8oVZ2amWnVnZqZaNOdmplp1Z2cWrV5aTce18LzARwzrUCD3jvF2ZqYHE0eHApX33VkO1h5AW1slMrO7WyUysbdbJTKzu1sotTK/PRV5xzhcDmQAWdLHvx3j/Zv0NLH60pFxEREZF0682actPHIDnntgFuB4YTlrN01AoUWQc4UJWXl1Bfvyzbw8gLamWnVnZqZadWNupkp1Z2amUXp1bWzya9nLB2fBIwH2hJ24hirKEhPp86lW5qZadWdmplp1Y26mSnVnZqZRenVtZJ+abAj7z3s9I5mLhLJIppbo7Pgyed1MpOrezUyk6tbNTJTq3s1MouTq1MHx4EfAAMSedABoLmZr3AYKVWdmplp1Z2amWjTnZqZadWdnFqZZ2UnwGc7ZzbMp2DibuCzlbjS6fUyk6t7NTKTq1s1MlOrezUyi5OrazLV34NrAn8yznXBHQ89kyr936lfh1ZDBXE6ZGTZmplp1Z2amWnVjbqZKdWdmplF6dW1kn539I6igEiTi+xpJta2amVnVrZqZWNOtmplZ1a2cWplWlS7r0/K90DGQgSiSKamuLz4EkntbJTKzu1slMrG3WyUys7tbKLUyvrccoP7mkb7/1NX3848dbQ0JTtIeQNtbJTKzu1slMrG3WyUys7tbKLUyvr8pUbuzi9lbC+/CtAk/IelJUlqKuLxwHu002t7NTKTq3s1MpGnezUyk6t7OLUyjopX6WT0wYDOwDnAz/ttxHFWFweNJmgVnZqZadWdmplo052amWnVnZxamVdU/5FJyd/AfzZOVdO+MTPrfpzYHFUWTmIxYuXZnsYeUGt7NTKTq3s1MpGnezUyk6t7OLUynqc8u68D2zcD5cTe3F50GSCWtmplZ1a2amVjTrZqZWdWtnFqZX1jZ6rdnJyITAc+B3wTn8OKq7i9Gwu3dTKTq3s1MpOrWzUyU6t7NTKLk6trGvKFxLe1NmZBmDf/hlOvMXlQZMJamWnVnZqZadWNupkp1Z2amUXp1bWSfnhrDgpbwW+BB7vYs25dBCnZ3PpplZ2amWnVnZqZaNOdmplp1Z2cWpV0Nra1Q7w+GpsbG5dtKg+28MQERERkRgbNqzyRYwHQ7HuKcc5tzFwJrAjMAT4FHgaON97/+/eD3PgqagoidWhe9JJrezUyk6t7NTKRp3s1MpOrezi1Mq0p9w5tyXwJPAxcA+wAFgT2AtYHdjee/9iGsfZr7K1p7ywsICWloH3ykRfqJWdWtmplZ1a2aiTnVqtqLZ2PtXV06mpmUtV1WgmT57EiBEj1aoXcr1Vb/aUWyflj0b/u4v3vjHl9BJgFtDkvZ/Yh7FmRbYm5WVlCZYsaex5Q1GrXlArO7WyUysbdbJTq/Zqa+czduw46uoOoKlpPMXFs6mouJU5cx5lgw3WVSujXH9c9WZSbj1O+f8Bl6ROyAG898uAS4FtejXCAaqxsTnbQ8gbamWnVnZqZadWNupkp1btVVdPjybkU4FdaGqaSn39AVRXT1erXohTK+uk/DPCOvLODAGa+mc48VZU1B+f1TQwqJWdWtmplZ1a2aiTnVq1V1Mzl6am8e1Oa2wcT03NXLXqhTi1st6Sh4BznXMu9cTo63Oi70sPBuKRbvpKrezUyk6t7NTKRp3s1Kq9qqrRFBfPbndaIjGbqqrRatULcWplPfrKb4FngVedc68R3ui5BrAx8AFwYnqGFy8xetyknVrZqZWdWtmplY062alVe5MnT+LOO8dRVwdNTeNJJGZTXn4rkyc/qla9EKdWpj3l3vtPgTHACcCb0fl89PXm3vuP0jbCGInTSyzpplZ2amWnVnZqZaNOdmrV3ogRI5kz51EOOaSBMWMu5uCDG5gz51FGjBipVr0Qp1b68KAMKioqoLl54PXuC7WyUys7tbJTKxt1slMrO7Wyy/VW/fbhQc65MsLe8He8939JOb0YmAvcQvjwoNw9Fk0OKS1NUF8fjwPcp5ta2amVnVrZqZWNOtmplZ1a2cWpVZf7/J1z5cAjwNnAeh2+vQrwFnAq8IhzblDaRhgjcXnQZIJa2amVnVrZqZWNOtmplZ1a2cWpVXcLcY4DvgVs670/P/Ub3vtPvPe7AxOALYFj0jfE+Bg8uDTbQ8gbamWnVnZqZadWNupkp1Z2amUXp1bdTcoPAC7w3v+zqw2893MIHx70034eVyx99VVDtoeQN9TKTq3s1MpOrWzUyU6t7NTKLk6tupuUrwO8YLiMJ1lxeYt0orJSq3ys1MpOrezUyk6tbNTJTq3s1MouTq26m5R/AaxquIzBQF3/DCfeFi9emu0h5A21slMrO7WyUysbdbJTKzu1sotTq+4m5f8EDjRcxgHAa/0znHiL07O5dFMrO7WyUys7tbJRJzu1slMruzi16u6QiFcAjznnzgHO8d63e3trdFjE04C9gf3SN8T4iNOzuXRTKzu1slMrO7WyUSc7tbJTK7s4ter2w4OccycD5wMfA48B7xP2ro8CdgLWAC723p+c/qH2n2x9eFBFRSl1dfF5Q0I6qZWdWtmplZ1a2aiTnVrZqZVdrrfqzYcH9fiJns65HYETgfFA8rgzXxGOYX6Z9/6pvg81O7I1KS8oKGAgfoJqX6iVnVrZqZWdWtmok51a2amVXa636rdP9ATw3j8BPAHgnBsKNHvvP/9aIxygBg1KsGRJfA5yn05qZadWdmplp1Y21k61tfOprp5OTc1cqqpGM3nyJEaMGJmBEeYOPabs1MouTq163FMeR9naU15UVEhzc0vGrzcfqZWdWtmplZ1a2Vg61dbOZ+zYcdTVHUBT03iKi2dTUXErc+Y8OqAm5npM2amVXa636s2e8u6OviL9rLhYua3Uyk6t7NTKTq1sLJ2qq6dHE/KpwC40NU2lvv4Aqqunp3+AOUSPKTu1sotTq/jckjzQ0jLwXpXoK7WyUys7tbJTKxtLp5qauTQ1jW93WmPjeGpq5qZrWDlJjyk7tbKLUytNykVERNKoqmo0xcWz252WSMymqmp0lkYkIrnINCl3zu3gnBvcxfdWds7t27/DiqfCwoJsDyFvqJWdWtmplZ1a2Vg6TZ48iYqKWykuPhF4iETiRMrLb2Xy5EnpH2AO0WPKTq3s4tTKuqf8ceBbXXxvK+Cm/hlOvDU15e4bEXKNWtmplZ1a2amVjaXTiBEjmTPnUQ45pIExYy7m4IMbBtybPEGPqd5QK7s4tery6CvOuTuBb0ZfbgK8AyzpZNORwALvfVeT9pyTraOvlJWVxOawPemmVnZqZadWdmplo052amWnVna53qq/jlN+KXBk9P+bAB74pMM2zcDDwIxejnFAWrq0MdtDyBtqZadWdmplp1Y26mSnVnZqZRenVl1Oyr33/wD+AeCcAzjHe/9uhsYVS+XlJTn9UbC5RK3s1MpOrezUykad7NTKTq3s4tSqVx8e5JwbBewErAXcCHwD+I/3fmlaRpcm2Vq+IiIiIiIDR79/eJBzrsA5dyVhXfkNwHnA8OjffzvnRvRxrANKZeWgbA8hb6iVnVrZqZWdWtmok51a2amVXZxaWY++ciZwGHAosAaQPP7MiYQlMBf098DiaPHivCY1VJMAACAASURBVHpBIavUyk6t7NTKTq1s1MlOrezUyi5Orbp7o2eqw4Ep3vtbnHNFyRO99684504DLrFeoXNudeBFYALQRFgG0wq8CvzSe9/inDsD2D36/nHe+3855zawbmsdS6ZVVg6K1YMnndTKTq3s1MpOrWzUyU6t7NTKLk6trHvKVyMcfaUznwBDLBfinEsQjtSSPLTiJcCp3vvtCXvf93TOVQE7AlsD+wHT+rBtTorLgyYT1MpOrezUyi7XW9XWzmfKlFOYOPGHTJlyCrW187MyjlzvlEvUyk6t7OLUyjopfwU4pIvv7QX8x3g5U4GrgY+ir7cEnoj+fxYwHtgOeNh73+q9/wAods4N6+W23SosLCCRKKKkpIjS0mKKiwspK0tQWFhARUUJsHyNUsd/KypKKCwsoKwsQXFxIaWlxZSUFJFIFDFoUIKiogLKy8NlDB5c2u68q6xSHl1GKQUFBZSVlVBUFC4jkQiXUVpaTFFRIWVlJRQUFFBRUdrpOJKXXV5eQlFRAYMGJbJym5ZfRv/epsrK0tjdpnTdT0OGDIrdbUrX/ZT8GYzTbUrX/TR4cGnO3qbPPlvA2LHjuOmmUl566SRuuqmUnXYaz//+91HG76fBg0sH7M9Tb2/TkCGDYneb0nU/rbxyWexuU7rup9TfVbl4m3rDdPQV59wE4EHgGeABwhryc4H1CXuo9/TeP9DDZRwKjPTen+ucmwP8AnjMez88+v7OhGUybwCfeu+vik5/Mjr9Seu23vu3uxuLjr4iIpK/pkw5hZkzS2lqmtp2WiJxIgcf3MAFF5yfxZGJiLTX70df8d4/AuwClADnE5aPnAZsDOzV04Q8cjgwIZqQbwHcBKye8v1KYBHwZfT/HU9v6cW2OSn5jEp6plZ2amWnVna53KqmZi5NTePbndbYOJ6amrkZH0sud8o1amWnVnZxamVdvoL3/lHv/TaEie9IYIj3foz3/n7j+Xfw3u/ovR8LvAwcDMxyzo2NNtkVeIrwgUUTnXOF0XHRC733C4GXerFtTmpoiM+nTqWbWtmplZ1a2eVyq6qq0RQXz253WiIxm6qq0RkfSy53yjVqZadWdnFqZT36CgDOue2AccCawAXOuR2Al7z3/+3j9f8auNY5VwK8DtzpvW92zj0FPEt40vDLPmybkxKJYpqb4/PgSSe1slMrO7Wyy+VWkydP4s47x1FXB01N40kkZlNefiuTJz+a8bHkcqdco1Z2amUXp1bWNeVlwG3AHixfMvJt4EJgM2Cs9/71NI6zX2VrTXkiUURjY3PGrzcfqZWdWtmplV2ut6qtnU919XRqauZSVTWayZMnMWLEyIyPI9c75RK1slMru1xv1Zs15dY95RcSDju4PfAcsCw6/aeEI6FcAPywd8MceAoKet5GArWyUys7tbLL9VYjRozMiTd15nqnXKJWdmplF6dW1jXl+wEne+//QfjwHgC89wuAcwiHJpQeFMTpkZNmamWnVnZq1bUVj/tdm+0h5QU9puzUyk6t7OLUyjoprwA+7uJ7S4BB/TOceGtubul5IwHUqjfUyk6tOldbO5+xY8cxc2Y47vfMmaVsu+2OWftAnnyix5SdWtmplV2cWlkn5f8EfuWcS13uktxjfjiQsx9tn0sSiaJsDyFvqJWdWtmpVeeqq6dTV3dAdNzvXWhqmkpd3QFUV0/P9tBynh5Tdmplp1Z2cWplXVP+G8Knab4BPEyYkE9yzm1EWLy+c3qGFy8NDU3ZHkLeUCs7tbJTq86F436f1O60cNzvi7M0ovyhx5SdWtmplV2cWlk/POhF4DvA88BeQDPhjZ0LgW2998+mbYQxUlaWyPYQ8oZa2amVnVp1LpeO+51v9JiyUys7tbKLUyvrIRE38t6/kYHxZES2DokoIpKLkmvKwxKW5cf9njPn0awcZlBEJC56c0hE65ryuc65d51z05xzu0XHLZdeqqzU+2Gt1MpOrezUqnMjRoxkzpxHOeSQBsaMuZiDD27g+eef1oTcQI8pO7WyUyu7OLWy7infCpgAfA/YBmgBngQeBB703r+dzkH2N+0pFxEREZF06/c95d77F7z3F3jvdwJWBfYlvOnzKMA753xfBzuQxOnZXLqplZ1a2amVnVrZqJOdWtmplV2cWlmXrwDgnCsCNgYcsA6wJlAAxGeVfRotXrw020PIG2plp1Z2amWnVjbqZKdWdmplF6dWpkm5c+4M59xsYBHhmOU/BxYAxwKjvPfrpW+I8RGnZ3PpplZ2amWnVnZqZaNOdmplp1Z2cWplXVOe/LikGuBi4D7v/ZJ0DiydtKZcREQk82pr51NdPZ2amrlUVY1m8uRJekOxxFpv1pRbJ+WbA2Oj/7YHKoEXCW/2fBJ42nv/Zd+Gm3nZmpRXVJRQV7cs49ebj9TKTq3s1MpOrWzUye7zzxfwne/s0HbozeLi2VRU6NCbndHjyi7XW/X7pLyjaJK+A7BL9F+z976k1xeUJdmalBcWFtDS0vveA5Fa2amVnVrZqZWNOtlNmXIKM2eW0tQ0te20ROJEDj64gQsuOD+LI8s9elzZ5XqrdBynHADn3CDn3DjC0Vf2Jxwm8Uvgr70d5EBUWlqc7SHkDbWyUys7tbJTKxt1snv55ddpahrf7rTGxvHU1MzN0ohylx5XdnFqZX2j5+nOuTnA58DDwK7A48DOwFDv/b5pG2GMNDY2Z3sIeUOt7NTKTq3s1MpGnezGjBlNcfHsdqclErOpqhqdpRHlLj2u7OLUyvr04ljgEcJxyR/y3n+cviHFV1FRIU1NLT1vKGrVC2plp1Z2amWjTnbHH38Md9yxI3V10NQ0nkRiNuXltzJ58qPZHlrO0ePKLk6trMtXpgG/9t7f1HFC7pxb2zl3Rf8PLX76sn5/oFIrO7WyUys7tbJRJ7sRI0YwZ86jHHJIA2PGXMzBBzfoTZ5d0OPKLk6tunyjp3Nu1eQ2wMfARMIhETvaG7jCe1+WlhGmQbbe6JlIFMXqZZZ0Uis7tbJTK7uOrXQou87pMWWnVnZqZZfrrXrzRs/ulq/cAnwv+v8C4O/dbNvd9yRSVFSY0w+cXKJWdmplp1Z2qa1qa+czduy46FB2J/Gf/8zmzjvHaS8nekz1hlrZqZVdnFp1Nyk/EhhPmJBfD5wHvNNhm2bCp3xqQZhBY2NTtoeQN9TKTq3s1MoutVV19fRoQh4OZdfUtAv19eH0gX4oOz2m7NTKTq3s4tSqy0m5974WmAngnGsFHvDeL8zUwOKotDRBfX3uHuA+l6iVnVrZqZVdaquamrk0NZ3U7vvhUHYXZ2NoOUWPKTu1slMruzi1Mh19xXs/0zlX7Jz7KTAOWJNwRJbtgBe996+kcYyxEZcHTSaolZ1a2Q3UVn1ZD57aqqpqNP/5z2yamnZpO02HsgsG6mOqL9TKTq3s4tTKepzy1YB/AjcAVYS15pXAj4BnnHNbp22EMTJ4cGm2h5A31Or/2zvzMDnKanG/vc1MMpmwL5oEECElIELCRSIKRhNIADGyCUTCJuq9OL8LAaIEvYprwLBK5CqbhCUCDiAIJiGJBmQJQiAYti+AAklALmAIWSfTy++PU53p6emZOT2Zru6qOe/zzDMz3dXVX71TlZw6fb7z6TFXevqjq3w9+MyZ9Tz77BRmzqxn9OgxrFy5otvXFbpqbj6bxsZZJJMXAHNIpS7wW9mdXeHR1z798ZzqLeZKj7nSEyVX2paIVwJbAXsAByB15gDHA08C/buoUMnata3VHkJoMFd6zJWe/uiqYz34eNLpy1i/fiIzZlzb7esKXQ0ZMtRa2XVBfzyneou50mOu9ETJlTYoPxr4nnPuDWBzD0XnXCtwORKoGz3Q1NRQ7SGEBnOlx1zp6Y+upB68/KXNi10NGTKUadN+zty5f2DatJ9bQO7TH8+p3mKu9JgrPVFypQ3KE8DGLp5L0p45N7phzZquFBrFmCs95kpPf3Q1cmTvljbvj656g3nSY670mCs9UXKlDcr/DPzQ87xtCh7LeZ6XAs4BHu7zkUWQKN3NVRpzpcdc6emPrnpbD94fXfUG86THXOkxV3qi5KrLFT0L8Tzv48BjQB3wBDAemA18Atga+Jxz7uUKjrNPqdaKnobR37FVIauDeTcMw6gO5azoqQrKATzP2xGYDIwGtgNWA48CVzjnlvdqpFWiWkF5Y2M969ZFZ0JCJTFXesLiquOqkGNJJufT2Dgr0AmDYXFVC5grHeZJj7nSY6701LqrigTl3eF53nbOufe3eEcBUa2gPBaL0Re++wPmSk9YXE2dehEzZ9ZvXhUSIJW6gFNPbQ1sVciwuKoFasVVrWf5a8VTGDBXesyVnlp3VU5Q3m1Nued5dZ7njfe/BpZ4Pul53vnAK70bav+ioSFV7SGEBnOlJyyuetsFpC8Ji6taoBZc9bbHepDUgqewYK70mCs9UXLVZVDueZ4HLAMe9L+e9zxv94LnjwJeAKYDH1R4nJFg06Z0tYcQGsyVnrC46m0XkL4kLK5qgVpw1dse60FSC57CgrnSY670RMlVd5nyS4FBwLeAiUAGuNzzvJTneTcD9wM7At9FJnwaPZBMapvdGOZKT1hc1cKqkGFxVQvUgqta+HSlJ2rBU1gwV3rMlZ4oueruSA4GLnbO3eCcuxP4BnA4cAswCbgR2MM5N905t6nyQw0/2Wzt1jzVGuZKT1hc1cKqkGFxVQvUgqta+HSlJ2rBU1gwV3rMlZ4ouUp289w2wHMFvz8FDADGAmOdc3+p5MAMw4ge+VUhu6PWJ/YZwdHcfDYtLWNYtw7S6bGkUvP9T1cWVHtohmEYfU53mfIEUNhjJr9k0vkWkPeOeNwWPtVirvREyVWlJ/ZFyVWlqQVXtfDpSk/UgqewYK70mCs9UXLVXaa8K57v81H0E9LpbLWHEBrMlZ4oueo4sQ/S6fGsXy+P90XbxCi5qjS14krz6Uo1qRVPYcBc6TFXeqLkqqfq+FKFOtEp3gmYurre3AP1T8yVnii5qvTEvii5qjTmSod50mOu9JgrPVFy1dORXO55Xr7dYf7zgas8z1tdtF3OOTehb4cWPTZubKv2EEKDudITJVcjR+7N0qXzSafHb36sLyf2RclVpTFXOsyTHnOlx1zpiZKr7jLljyBtEJv8r0HAw0C24LH81+DKDjMaDBxYV+0hhAZzpSdKrirdNjFKriqNudJhnvSYKz3mSk+UXMVqeWnSStHWlsl98MH6ag/DMIwSWPcVwzAMIyrssEPTYuA/NNtaUB4gTU0NrFmzsecNDXNVBuZKj7nSY650mCc95kqPudJT664sKO8By5QbhmEYhmEYlaacoDw6a5OGgKamhmoPITSYKz3mSo+50mOudJgnPeZKj7nSEyVXlik3DMMwDMMwjApgmfIaZdCg+moPITSYKz3mSo+50mOudJgnPeZKj7nSEyVXlik3DMMwDMMwjApgmfIaJUq9NCuNudJjrvSYKz3mSod50mOu9JgrPVFyFZ21SUNAa2t0Vp2qNOZKT1hdVaMfeVhdVQNzpcM86TFXesyVnii5skx5gKRSdg+kxVzpCaOrlStXMHr0GGbOrOfZZ6cwc2Y9o0ePYeXKFRV93zC6qhZ5VytXrmDq1IsYN+4rTJ16UcX/RmHDzik95kqPudITJVcWlAdIJpOt9hBCg7nSE0ZXM2Zcy7p1E0mnLwPGk05fxvr1E5kx49qKvm8YXVWLTCZbtZunMGHnlB5zpcdc6YmSKwvKAyQWq/YIwoO50hNGV8888yLp9NgOj7W1jeWZZ16s6PuG0VW1iMWqd/MUJuyc0mOu9JgrPVFyZUF5gMSidOZUGHOlJ4yuRo7cm2RyfofHUqn5jBy5d0XfN4yuqkUsFqvazVOYsHNKj7nSY670RMmVBeUBEqWPWCqNudITRlfNzWfT2DiLZPICYA6p1AUMHDiL5uazK/q+YXRVLTKZbNVunsKEnVN6zJUec6UnSq4sKA+QVCpR7SGEBnOlJ4yuhgwZysKFCzjttFZGjJjOqae2snDhgop3Xwmjq2qRSiWqdvMUJuyc0mOu9JgrPVFyZYsHBUg8HiOb7X++e4O50mOu9JgrPXlX1WhdGSbsnNJjrvSYKz217qqcxYMsKA+QxsY61q3bFPj7hhFzpcdc6TFXesyVDvOkx1zpMVd6at2VBeU9UK2g3DAMwzAMw+g/lBOUW015gDQ1NVR7CKHBXOkxV3rMlR5zpcM86TFXesyVnii5sky5YRhGyLA6b8MwjHBgmfIaJUp3c5XGXOkxV3qi4CqoVTaj4CoIzJMec6XHXOmJkisLygNkzZqN1R5CaDBXesyVnii4CmqVzSi4CgLzpMdc6TFXeqLkyoLyAInS3VylMVd68q5WrlzB1KkXMW7cV5g69aI+z5xGgSicV0GtshkFV0FgnvSYKz3mSk+UXFlQHiBRupurNOZKz5o1GwMraQg7UTivglplMwqugsA86TFXesyVnii5sqA8QBob66o9hNBgrvQ0NtYFVtIQdqJwXgW1ymYUXAWBedJjrvSYKz1RcmVBeYBs2NBW7SGEBnOlZ8OGtsBKGsJOFM6rIUOGsnDhAk47rZURI6Zz6qmtLFy4oM+7r0TBVRCYJz3mSo+50hMlV8lqD6A/UV+fjNTJU0nMlZ76+iQjR+7N0qXzSafHb368EiUNYScq59WQIUOZNu3nFX2PqLiqNOZJj7nSY670RMmVBeUB0taWqfYQQoO50tPWlqG5+WxaWsawbh2k02NJpeb7JQ0Lqj28msLOKz3mSod50mOu9JgrPVFyZeUrAZJImG4t5kpPIhEPrKQh7Nh5pcdc6TBPesyVHnOlJ0quLFMeIP1x9dTeYq705F0FUdIQduy80mOudJgnPeZKj7nSEyVX0bm9CAEROm8qjrnSY670mCs95kqHedJjrvSYKz1RcmVBeYBE6SOWSmOu9ATlKgqLE9l5pcdc6TBPesyVHnOlJ0quYlFK+2tpa8vkPvhgfeDvm0jEyGT6n+/eYK70BOEqvziR9EIfSzI5n8bGWaGrW7fzSo+50mGe9JgrPeZKT6272mGHpsXAf2i2Daym3PO8FHATsBtQD/wUeBG4GcgBzwPfds5lPc/7IXAUkAbOdc79zfO8PbTbBnVM5VJfn2L9+k3VHkYoCKurlStXMGPGtTzzzIuMHLk3zc1nVzxoDcJVx8WJIJ0ez/r18niY6tjDel5VA3OlwzzpMVd6zJWeKLkKMud/CvC+c+4Q4AhgBnAF8H3/sRgwwfO8kcDngYOAk4Bf+a8vZ9uaJConTRCE0VW1lroPwlVUFicK43lVLcyVDvOkx1zpMVd6ouQqyKD898D/FPyeBg4AHvZ/nw2MBT4HPOScyznn3gSSnuftUOa2NcmgQfXVHkJoCKOrai11H4SrkSP3Jpmc3+GxMC5OFMbzqlqYKx3mSY+50mOu9ETJVWBBuXNurXNujed5TUAL8H0g5pzLFwKtAbYCBgOrC16af7ycbbslHo+RSiWoq0tQX58kmYwzYECKeDxGY2MdAE1NDSW/NzbWEY/HGDAgRTIZp74+SV1dglQqQUNDikQixsCBso/8iZJ/bSwW8/dRTywWY8CAOhIJ2UcqJfuor0+SSMQZMKCOWCxGY2N9yXHk9z1wYB2JRIyGhlRVjql9H317TBs2bArdMXWVTb7vvoc44ohjmDr1It577199fkytremK/52am89m0KDfkUxeAMwhlbqAxsbfcc453w7V3yk/haa/XU+9Oaa1a1sjd0yV+DutW7cpcsdUqb/Tpk3pyB1Tpf5O2WwucsdUqb9T4b9VtXhM5RDoRE/P84YB9wLXOudu8jxvhXNuqP/cBOAwYBnQ4Jz7hf/4s/7jS7TbOufe624c1Zro2dTUwJo1GwN/3zASRldTp17EzJn1m+uuhXOIxRaRy/2oYpMjg3JVjXr5viaM51W1MFc6zJMec6XHXOmpdVflTPQMLCj3PG8nYCHQ7Jxb4D/2R+By59xCz/N+DfwFeBX4BRJ0DwX+6Jzbr5xtexpLtYJyI9oUdyiJx+eSzc4EngOGAZBKXcCpp7aGanKkYRiGYRi9o5ygPMia8ouAbYD/8Txvoed5C5ESlh95nvcEUAe0OOcWA38FngDuBr7tv/78MratSfIfZxg9E0ZXxUvdb7vt/cDV5ANyqMzkyC11VYv9xys1pjCeV31JOV77uyst5kmPudJjrvREyZX1KTeMClGqnKXWMuW12H+8VsYUhXKdQmrFq2EYRn+iVjPl/Z5yC/77M1Fw1dx8No2NszpMjhw4cBbNzWf36ftsiatSHWPWrTuZiRMnVS1zXskuNlpX1WpvWUnK9RqFazAIzJMec6XHXOmJkisLygMkSr00K03YXeWzrEOHfpw991zIPvv8hFNPba1IVnJLXJXqGJNOH8ZLL62tWjBayZ7oWldBtLcMumyoXK9hvwaDwjzpMVd6zJWeKLmyoDxAGhpS1R5CaAizq8Is6wsvfI9XXhnNihX/7HX5Q0/B25a4KtV/HOYii+S2B6OXXHJprwLI3gSeleyJrnXV2xsD7fFWIhPf03uX6zXM12CQmCc95kqPudITJVcWlAfIpk3pag8hNITZVV9mWTXB25a4Ki6xgXOB2/3vQlvbfrS03FN2ANnbwLN4TPH4ZLLZ61i7ds0WZ5O1rnpzY1DO8fZ1Jl7z3uWWU4X5GgwS86THXOkxV3qi5MqC8gBJJk23ljC46ioz2ZflF5rgbUtcFXeM2WuvR0kkvkJhx5hYbAbZ7Fmk0+cA80in/86HHw7jkksu3eKxdzem4457n3h8Ernc42Qyv+Luu7ff4myy1lVv5gOUc7x9XaKjee/iv3VP5VRhuAZrAfOkx1zpMVd6ouQqOkcSAvIrdBk9U+uuustM9mX5hSZ421JXQ4YMZdq0nzN37h+YNetWBg16oEMwGov9g1xuBDAK+SfjPHK5z9HSck+3AfKWBJ5Dhgxl0KBBxOOnkcs9CUzqk7puratyA1go73j7ukRH+96Ff+tp037e7fHU+jVYK5gnPeZKj7nSEyVXFpQbRi/oLjNZqiQkk/kNf/3rk2VP6KtkfXUpSgWjJ5zwJWKxGcBEYDowHricXO7r3QbIWzr2Sk741FBOAAvlHW9fd+YJ+jwxDMMw+h7rUx4g9fVJWlujU/tUScpxVY1+0uPGfYVnn52CBKh55jBixHTmzv0Dixc/xYQJx7Fp0/bA/wFfBY4ruzd0cW/pVGo+Awd2fH2lz6uVK1dwwAGHks3eSlfH29uxd0cl+rxX0lW5x9uX5+2Wui6F/XulwzzpMVd6zJWeWndVTp/yxMUXX1zZ0dQg2Wzu4o0b26ry3v3xJqi3aFzlg5GnnhrBW29NYunSN5k1awrHHXcMgwcPrtjYXnzx7yxd+ibZ7OGbH0ulfs348dsyduwYrrnmVyxZciDZrIdci9cAe5DNHk42+zatrYsYO1bKXaZNu4Tp06/hxRf/zl57eR3GPXjwYI477hg2bVoE3Mf48dty7bUzOgValTyvBg8ezBtvvMaLL74FjCt5vF29TjP2rthrL49Zs6aQybxNNpsllfo1AwfO4tprZ2zR37ZSrso93sGDBzN27BgmTTqJsWPHbNExbanrrrB/r3SYJz3mSo+50lPLrhob698GrtNsa5nyABkwoI4NG6LTT7OSaF1Va9XMnjKT7Zn0K4DzKJVhvummGX2ywmIQ51UlMrHa9+3LT0HsGtRjrnSYJz3mSo+50lPrrsrJlFtQHiCxWKym7+ZqCa2rnspI+oKuAsPuAsb2m4UcMnVj+ub95W8agD65oQjqvIrCsvN2DeoxVzrMkx5zpcdc6al1V+UE5TbRM0AGDqyr9hBCg9ZVpSe4dddlpbuJgPmJfInEGmAmki2fQyw2mYaG22huPrvPJjIGdV7lj/emm2YAcOaZzYGsRNmX2DWox1zpME96zJUec6UnSq4sKA+Qdetaqz2E0KB11dddLIrZ0l7bxx/fRiyWBlqAi4DHAbmjL3VDkUzew8aNqzv0Pu9ppcYgz6tKrEQZJHYN6jFXOsyTHnOlx1zpiZIrC8oDpKmpodpDCA1aV73pJ10OfdFrO5E4E3gTeIZc7kk2bpxUsnViMvlN0ulZvPLK6M0B76GHfoFDDx3dbRAc5HnV1ytRBo1dg3rMlQ7zpMdc6TFXeqLkyoLyAFmzZmO1hxAaynFVbj/pcqhkr+3iG4o993yGZPI//YB3H9LpHGvWbMWaNfX+apqlg+Agz6tq9w7fUuwa1GOudJgnPeZKj7nSEyVXFpQHSJTu5ipNrbja0vKYnoL6whuKhoat/IB3Oe2rZ14NHOv/vhzoHAQH6Srsi9TUynkVBsyVDvOkx1zpMVd6ouQqWe0B9CeidDdXaWrFVT6bfckll7JgwbeBJGPGjOvxdXmam8+mpWUM69bRoZVgc/OCTtuOHLk3S5fOJ52eR/vqmSCdZVLAVcDlnYLgIF2VczzF1EL3li1xVQvjD5JauQZrHfOkx1zpMVd6ouTKWiIGyKBB9axdG50JCZWkllwV9+juzaqcXQVzhc8NHz6MP/1pDmvWbI0E4B3bPMIPSKUO7dQfPGhXvQlOt9RhX9FbV7Uy/iCppWuwljFPesyVHnOlp9ZdWZ/yHqhWUG6Eky1ZoKingLw40Bsw4FZ22mlnXn31i8CVm/cTj09m223vZ8KEI0OZoa3WIk99RdjHbxiGYVSHcoJyK18JkIED61i/vnZXnaolqu2qMJhevvx10umLOzwvdd3TS7+4YB/tQfcUli6dT0vLmM3Z1Y6dTCCdHs/GjXDAAe/x7rt3sm5doqBE5E7mzSudla22Kw0yQXRKh8c0Dvua3rqqlfEHSRjOq1rAPOkxV3rMlZ4oubKJngHS2tpW7SGEhiBcddX/u7gX9/vvTwDOIT/REnSTG3tqH9hVJ5Nly5aX1eYxDOdVrUwQ7a2rWhl/WzyqrwAAIABJREFUkIThvKoFzJMec6XHXOmJkivLlAdIKpUkk4nOyVNJKu2quyx2cQY7lxsPZIjFjieX+5F6cmNP2dX2iZ3tteP5QC/flUVDGM6rLZkg2pf01lWtjD9IwnBe1QLmSY+50mOu9ETJlWXKAySTyVZ7CKGh0q66y2KXymDDEWy33QdlLVDUU3a1r1YjDcN5VelFnrT01lWtjD9IwnBe1QLmSY+50mOu9ETJlU30DJC6ugSbNmUCf98wUmlX48Z9hWefnUJxh5MRI6YzcuTe3U7q03YfKZ7Imc+uFgZzfdFmz84rPeZKj7nSYZ70mCs95kpPrbuyiZ41SiwWq/YQQkOlXZUqHYnH57J8+esMH74LAwbcxYYNnUsVepq8WUg+uypB93Q/6O64XakylXIDdTuv9JgrPeZKh3nSY670mCs9UXJlmfIASSbjpNPR+ZilklTaVXEWG2YDtwJXk0w+x4ABt3HkkeNZtmx5h8C40q3xSrVJjMdvZM8992bUqJElA/S+dhXlRXLsGtRjrnSYJz3mSo+50lPrrixTXqOkUomaPnFqia5c9VXAWJjFvu++c3j//a3J5Z4DhpFOT2LjRhg0qJW5c//Q4XWVbo1Xqk0iZHjhheU4V18yK9+X51U5nwSEEbsG9ZgrHeZJj7nSY670RMmVTfQMkNbWdLWHEBpKuSpuVThzZj2jR4/Z3MqwXPKlI8OGDSWX+xEwbPNzEmi/2Ok1pSZv5steCtsq9pbSk0zHAR92aqmYpy/Pq57aOIYduwb1mCsd5kmPudJjrvREyZUF5QEyYECq2kMIDaVcVSpgLKcHdXHHFDiHbHYm77138eabhMWLnyrZ/7y3Y4EFwL5A6ZuFvjiv8j3bf/e7+0r2Ti91gxJG7BrUY650mCc95kqPudITJVcWlAfIunXhWnGqq8V1gqCUq64W29nSgLFUa8KGhttYu3ZNp2MvbI23/fbnEIstAp4DJpFOX8a6dSczYcJxvc7mdw76JwOzgHOB0jcL5Z5XxX/XxYuf2vwJxPr1nwYe6rB9lBbJCds1WE3MlQ7zpMdc6TFXeqLkyiZ6BkhTUwNr1mwM/H17Q6kJh42NswKrLS7lqpKTLAtr1YcP34U//elPbNgwqdtj76qtogTQL/dqjCtXruCSSy5lwYK/ks3G+PDDd0mnPwbUE4vBoEGv88gjCwE2j/eggz7Ft771TdXfpauJpJnMCWQy1yGrlo4CTgQOL9nGMcyE6RqsNuZKh3nSY670mCs9te6qnImeFpQbJal0l5HeoOn73Rdoj73UdhKQvwJ8AliKlJ3szz77XMeoUft3mqBaeDMwdOh2zJnzEG1tOwOfJB6vI5u9n1jsG+Ry44jFHmLQoFncddcsTjrplF7dMHU95hVAi//7cmAyAwf+jZNPnhCp7iuGYRiGESTWfaVGqfW7uUIq3WWkJ0q50vT97gu0x15q6XW4mba2LPA+kAMeA25k2bIczh1EOj2Fv//9Hm699WB2283j9dedn6U+nWefPQc4DTgCWEA2eyNwMrnclQDkcuPZuDHOeed9p1OHlvXrJXPe0w1TqWOTTP+5Bb8PI5XajZNP/og6ux+WFophugarjbnSYZ70mCs95kpPlFxZUB4gYTppSi2uE2RtcVeuSi2209doj73UTYJz/8Gjjy4GDgHGIJM0HW1t9cA5AGQyXyeTOYNlyw5H6rfv9Pf4dSAf+I8H2pAMdjttbWN54427uqit7/mGqdSxJZPziMffIZu9oNNiST0RthaKYboGq4250mGe9JgrPeZKT5RcWflKgITpbi6oUpGuKNeVJlurzej29thXrlzBiBGjgLOAywueOR+4DbkHPgrYivbgezlwAvA6cDOa+vQ99ljIK6+M7rK8prvj7OrY7rjjNlpa7i07212LZU7dEaZrsNqYKx3mSY+50mOu9NS6K6sp7wGrKddR7bKE3gbRpWqsy5242psgf+3aNdx55zzgRkoH10cD9wIz/OfzkypPAt4AdgGuKHjdZOA6ksn/6hRAF9aUF940ACoXhZNaIddp5VKth64mu44YMb3TwkuGYRiG0d+woLwHqhWUNzbWhbp1T5BB+qpV7/DpTx+qCqI12dq+yOj21KElm/012eyOSPB9dcErzwE2AMcC/wUcgwTf5yNdSadT3PUE5lBXN5MbbvhfHn74sW4niH760/vyn//5LYYMGVrWcfZ0o6K5kQlbpjzs12CQmCsd5kmPudJjrvTUuiub6FmjbNjQVu0h9Jqga4d/8Yur1ZMZNRMzt3Ti6uLFTzFhwnFs2nQ6MIUlS+aSy7UhAfcw0ul9gJuALyB9xWNI9ngucBfwN+By6uvXksv9lmw2Tjr9KPAj/x2GAYuQriff9LuePM6QIUMZP/6oTuMprK2Px2Nks7myj7PjYkydHff0PJSe7KqtR68GYb4Gg8Zc6TBPesyVHnOlJ0qubPGgAKmvD+89UNDLry9Z8lLJyYyLFi3ptK2UYMwpeGQ58D+88cYbmxf+KWfVzmIWL36Ko46awKZNZwBXAuP9jihnAFf5W13l/34j8AyQQAL2FuAXSGb8Bv7whzt58snH/cWH3iMWK1yoJ9/1ZALTpv28y7Ka4gWdCs+rco6zp8WYNIs1FS6mNGLEdE49tbVmJ3lCuK/BoDFXOsyTHnOlx1zpiZKr6BxJCGhry1R7CL2mL1okllP+MmLE3jz3XMcuITCXV155npUrVxS9LgfcAqSATyHB8CT+/e8jmDlTMvoykfGUbjO6pcYHMGHCcWSzQ5CykkIOo70G/ClgR3+bfZEa8sOorz+DROJ77Lrrjlxxxf0ccMCBAEyb9nOam8/2P32Iq7LMHT+tOJ0lS2bw29/ewVe/ejTf/e4UhgwZ2mPmuvAYN25cTSJxD5lM6S4z5XShqcVSlVKE+RoMGnOlwzzpMVd6zJWeKLmyoDxAEok46XS22sPoFVvaIrGn8pfigPjkk0/gllsmAFkk0F0A3EU6fShf/OJhtLbG/UD3Fyxbthyp4V6ClIOcTj5YzpdctLTc222P867GN3784WzatBPwSX8MhTcJs4nFVpPL3eq/91kFYx1FMnkUp5xyfJcBa7l919s/rTgHGEUuN5Fc7kfceedDzJ7d7rKrfRYfYzI5n0zm1yQSkMkc2ymAD1tpioYwX4NBY650mCc95kqPudITJVcWlAdImCfVbmmA1l19cnvGuD0gvvvuk9ltt4+zbNmbSIC9L/C/ZLMns2rVt4DDeemlhzjiiC9z9NFHsHTpc6TTlyOraHbMaOcz+vlMcj74z7/3kCFDS45vzZoMDz10D3AgsC1SKw7Sf3wuqdRMdt11F1599QKkx3g+az4eSBOP30xz8+MlfeRvQhYtWkI2u4F4vL7k84VZ+/ZPK64CJpJvq5jLjWfduhgTJ06ioWGrLj+FKHWMyWSOPfd8mIaG1zrdFAS1WFOQhPkaDBpzpcM86TFXesyVnii5sqA8QMJ83uQDtEsuuZQFC74NJBkzZpz69d2Vv3QMFpeTTs/jgw8Gkcu9RSIxkkwmv/z7QcC36Bj85pg79xay2U3AB8BgZHJle0Y7FpvLSy8txfP2Ze3aVWSzJ5LJdMzWlxpfNjuODz64hVisjVxuFnAy8E+kPGYFN954I1deeT0wACh2MY7ddnuiZLlOx4z195AFhG7j5Zf32Vxq097ysDBrP87/tGIpcF6Hd0unD+Ollx4EftrlJNxSx5hOH0ZDw5Iu2xeGqTRFQ5ivwaAxVzrMkx5zpcdc6YmSK5voGSCJRPh1z5nzEB98cAzvvXc1d9+9HaNHj2HlyhUlJyAW0t0ExPYJhfm2gHHgalavPoFM5nZgfyQg/wed67rHsWlTA9nsWcikyieA65CgdQ4wmVzuOjZuvIhVq46jrS1BJnM/sE+HyaojR+5dNOkSpAxlD2KxPyMB+WDgQ+BLxOMTmDbtMt544w3gLWBeh1fGYnN5/XXHzJn1PPvsFGbOrN/sqnjSrNxknEYm08T69RM577zvlJxUCzkaG2cRi63u9H5yI3IU3U3C3ZLJrlEhCtdgUJgrHeZJj7nSY670RMlV4uKLL672GAInm81dvHFj8C10crlcqO/opk27hKeeGuEHi3uQzR5ONvs2778/n+9//wc89dQI3nprEkuXvsmsWVM47rhjGDx4MAB77eUxa9YUMpm3yWazpFK/ZuDAWVx77QyWL3+dJUteB55EJmpOB/YAjgD+D3gb+DEwG2igY1b6V8BqJCB/H1gFjPW3uw/YGfgEsBFZZfM9JLB+CxhHNptl06bfs/XWjTz//K3+PnLAb5BylYuor3+UdPpC4NvAJGBvcrkLee+9o9iw4b/9fc/0950f03Xkcl8ik/nNZletrct55JGrWbnyfd5553T/GPNkgfvIZr/G+vV30Np6Tofns9ksdXWzuffeO1m1yvHyy7cD7/pjneGP9bfIaqGyPdzHpEknbd5Hd3+D/N8p6oT9GgwSc6XDPOkxV3rMlZ5ad9XYWP82ki3skejcXoSA+vpUtYfQK/JZ8N/97j7S6deRjLbQ1jaWBQse75TZXb36q0ycOGlzFn3GjGsZOvRj7LnnQvbZ52cdWuc1N59NPH4D8CBSr13IEcDWSEa5BQmW27PgcD3wS3/bMUgAfxwSgD/kfz8GqTXPb5Pd/HsyOY9XXnmeu+/eHjgU+CuSuc4Ci0ilnuNjH9u5KMN8FXCK/3080p/8ZOBx/7Vx4CSy2SVIZv9839l4XnppLa+88nynjLVk5fcllZrPrrvu2GVGe8iQoVxzzTU8/fSTnHlmGyNGTGeffR4jkfgK0uu84/aFhK19YSUI6zVYDcyVDvOkx1zpMVd6ouTKVvQ0uqV4VUcJdO9EFroZRip1AVttdS/vvfcrSi0t39S0CoixYcMpnVaFBPzJjs+wYsU/Wb16HR17f4MEtCDBNf5zP0cC3zrg90hpC8AU4BHgs3Rcrn4KEmRf7v/8MLALqdRuxGI3ksmcQCZzHe3lM0ciGffnSaX+xUEH/QePPfYsudzHgf8H/Iz2gLzweK/w/bQfv2y3AMlkfwkYRDK5hnj892SzX/edzgVuJ5n8Co2NDxTVlLdPqu0qgC7+G/W0vWEYhmEYwWAretYogwbVs3Zta7WH0SPFvawLO3bkJ1fCZFKp3Rg4cBaf+czn+OMf59AxSF0AHMXatY8CnyWXa5/EuXr1YE444STeeedfrF8/gUzmFSTzPAKZRJl/n7lIWchzhaNDSkjOBfZDgt1V5ANb+CLyKVEcKWOZjfQw/yUS4P+WVCrD8OEpRo36CIsW7c0LLxxbsP/PA79DuqmcRVvbHB599Bak5eIzwNlAhuLJpPL7vkW/H+VvI91Y8seSTr/APvu8wKhRrSxa9DO/+8qejBpVv7m7STldTzzv45HrklIpwnIN1gLmSod50mOu9JgrPVFyZUF5gIThpCnuZS3B79iircZRX/91dt/9deLxj/HSSw7JEMeQeu98ZngRudyjSAlHPgs9EbiKV1+dgwTLAKeRb+8Ho4FjkVKWLyAZ7iv9fcwGbkUC5KuALInETQwadC+trRna2trIZD4k39NcMtcp5CZiConEJo4//stceOF3NwesU6dehHPzSaf38cc3DOnwks/Mj/f3scQfR9I/1pnIqp35TPd1/rHN8b9mAYs7OINnkU8XrmbUqJHddjUpp+tJGM6rWsFc6TFXOsyTHnOlx1zpiZIrK18JkKamBtas2Rj4+5bD1KkXcfPNrWQyTUjd9WrgYCQgzXMWkk0ehiyqszUyqXIIMunxKCSYH0YsdhBwMLncOuDvSAeT/IqXV/mvm0HnUpD/QrLedwCNSMC/A5Klzvnv8VWk5vxUYDyx2FxyuXxmPV9fPRm5IdiGePwO9tprfz75yT2AHMuWLWf48F24//772LChEalFfxGpWe+qNGUO8ANkIukngHuAgf4Y1xGPr2f33Yfwz38e5JfE5JFx5D9d6GrRpO5WOe2KDz54lwMP/Nzm8pXCEiHLlnckDNdgrWCudJgnPeZKj7nSU+uuyilfsaDc6MAXvjCeF154BclejwHuBW4Dvolke3+PBMr53+cCNyNdTt4H1iO106cDc4jFbiCXyyDlJJ/03yUGvI5kx38GHE17phykzCQf0KaQOvPDkEz5DUhQ/1lgDdBEe1Yb4BxisUXkcj/yx3YXEjgfC5yIZNzzWfqrkWz29UiQfRWSEY8XjadUTfoh/nPF257LrrvO4a23/kVb2xnAOJLJecTjN7HnnnvzyU/uCcRYtuxNhg8fxp/+NKdkvX05wfTUqRcxc2Z9QYkRpFIXcOqprZHqMW4YhmEYYcNqymuUWr+bA8hmW5H67nygOR5oQwLX2UgQ+g3aM+f5jPKNSCvAZ5EOKY8Dq8jlzgd+DWxCupuMQcpLlgGXIcHwTCQDfjgwH2ntlwP2Rmq8C8cSA1b447gXKWcp5Ai2224Oa9eexcaNo5AJqR1XwOxYknIVUobyV6SefTYSwOOPtbAmfTJyA9JKIrE/mcxzwI+K3v8A3njjRiSLvxw4l3j8He6772523vkjBaVBJ7JkyQ/J5U7yPXRc5bScYPq5514mnT6/w2P5hZmMjoThGqwVzJUO86THXOkxV3qi5MpaIgZIGE6aeHwAnRfo+SpQjyxYM5SOpR0gGfOPIkHuFUgWHaRN4JVIgH0mEhSP97+fgayO+TYSsLcAFwGPIlnpnZAAvLhF4nikz/h/A620dzvJM5u1a//N0KHbEYsNQ8pYlpbYzxja2yQehpTgTPL3ewmSDT/F/96GBM6PkUplueWWmzj99Hq23/69EgsO/Qq5abnRP6aXyeW+TkvLvZ0WDcrlturkUoLpFymH/fb7RL9fFEhLGK7BWsFc6TBPesyVHnOlJ0quLCgPkMbG+moPoUvyvcjfeectpLyjkAXA7sDxwG5IWUjx85+kPcgdhwTafwC2QYLsw4pec5j/3H5IZjqHfHCTQ7Ln+X7iC4pel+9ychVwEtKecQrtfctnsnHjMbz66hvkctchpTCD6Ry8L6C9W0r+5yOQLPzPkPKUZ5Ebjf9CJnT+DfgGDz/8GNOm/Zx58x5g8OA7/Ped44/jNYpvavKBdvvKpXn2pXhlzt4E09/5zrk0Ns4imbwAmEMqdQEDB86iufnssvbTH6jla7DWMFc6zJMec6XHXOmJkisrXwmQ9es3VXsIJVm8+CkmTDiOTZt2QiYvXo+UdBxGeyeVKcA04BUkcxxDgs/CHty7+nuc6/98MDIhdBckaC3MCs8GtkMC08NIJh8kmVxBa+swcrmn/G32QoLcfFA/G6kR/xvSsvA84H+QAP0KJPjezn9sK6QW/hFgAPBnOrZJzHdxmUK+U4zsp43OPcjHkO97XlgWkm9dOHHiJF56aTYy+fQY30n76wsD7aVL55NO55+Tto6xWI5c7vDN/cWbm4tvRLpn2213spaISmr1GqxFzJUO86THXOkxV3qi5MomegbIgAF1bNhQWyfPypUr+PSnP0Nb2+lIIPkQUnoxEKm7/gjwPWTi5ulIIP5b4AGklGVfJBj+A+29vK9HAtNVyITRy4DvIOUshyNB+/XAIOAp//nf+u/5ITAcKZd5DSlRGYhkz/+NlNKcgHRAOZiOCw1NBp5AarkvQUpnliGZ7k8B1wCv+vvcDliHfALw38DT/nEn/TFfXbDf9omeyeT5nHbapg413x3bSO6H1KZLR5jChXyATov8NDTcypFHHsmyZW/2uvtKLZ5XtYq50mOudJgnPeZKj7nSU+uurPtKD1QrKE8k4mQy2cDft5jCNnxr1rzHq6+OpmMQeg4yUfMnSHnF9UggfGPBNmf526xBgugnkOB8V2RS5EFI6cj1/raTkQB6KRKsrwQuRYLhG5CJmMfRcWLlRcDngH8gtefbIovw/Av4NFJecgqSyZ7n7+d5/7V/RUphXkUy9W8AH0cC8CXITUACqTlfhQT8MaTsph6pgc9n5/PjeYa6upt58snHOwXOhU6HDx9GvsNKcaDdFy0Qi6mV8yoMmCs95kqHedJjrvSYKz217sqC8h6oVlBeX5+ktTUd+PvmA8FFi5bQ2voh//jHa+Ry3ySXOxwJwK+m+yXjz0VqrVuKtjkHeBcp2bgDCXLP9Pc1z3/sf5EM+6kFj9+ElJfEgLVIf/MlBfs+FwnyNyGZ7m8hGfaHkM4ug5B68gtoD/Q/RLLh1/lj+xrS0aUVyeYfQsfWiRcgk0qH+q9fiUxWPaJov6v9fewIDGaffd7mL38prrmvLtU6r8KIudJjrnSYJz3mSo+50lPrrqwlYo2SzfbdDVB3GdfirO2DD85m3bqJ5HLfQwLWN5Bs87lIlri43nseHZeMH+9vW8hs4B1k8ufv/MdORIL3c4G3/P0chCzmcxxwOxKc/x3JUE9GMukd2/nJ+z3o7/+b5Ou55fEcMrkzv6Lm4UhpyV1ID/X82OqRnumTkJ7oxRNNxyJ15kt9FycjteUf88eWD+Dbb1BSqQsYNeoj1Bp9eV5FHXOlx1zpME96zJUec6UnSq4sKA8hHWuYp7B06XxaWsaUqFuewrPPXohklQv7iueQVn9XIQvrXO8/dgQShM5EAuc8s5E67XP8beYhEyXrkD7i9yHBdsdFfKAZKYGZC7yATLTM+D/n68h3QcpQJhW8di5SqhJDOrkUMs5/7/zCQOcgNwInFez3Bv+1n0Q6u8yjePKlvP5dJBOev3kYhATg5xZtN7igo0l5kzANwzAMwzA0WFAeIPF4rE/207HfdfuiM5dc8gsWL17M6tUZZCLmh0jN9xFFezgCCTbH074gzz3+Y4cimefL/O3mI+UmIDXkLyFZ9OeQOutfIoF2cSb6CCR4/jpSIvIVJCv/O6Qjyr+QIP1d2rPe+YWFbke6wHwKuSEoLq05FgmiD/Lf92SktGUeMjH1z0jW+8/+9ucDo/zXj/GP83akPGYeUrZyvn98HyB9xo8D5hGLXc/ee+/HqFEfqdmOJn11XvUHzJUec6XDPOkxV3rMlZ4oubKgPEDS6b6ZiCD9rqd0eKytbSx33vk1YAOyEM564Eng/5DAs7g8JV9/tRx4HwnE00g7wUOQIPU2//GTkSD8R3RuFXgjEvA+ROeWh3VIBvty2mvQx/g/n4ZkvfOZ+dVIlnpfpEZ9kP/YLf5+8qtr3uSPZzlSZjIbuSm4vuj9V/njvwUJ/i9BFva52d//l5AM/Uf98U/0jy8/sdMRi7Xy1a8ezzXXXEMt01fnVX/AXOkxVzrMkx5zpcdc6YmSK1s8KEDq6vrmHmjkyL07reAo2d80kuW9CemWshzpu30T7QvsTEHKRr7oPz8KKSG5Efiy//vDSDnJ7sjKm9chXVCKSzdmIxnx3yB13ufRHnzfCFxI+4JCc5EOKn9CJn5eiQTRV9FeZ34eEmDfiwTks/39rUYmbj4OXIsE7Acg9ea3+sf4Q6S+/Hz/uOb5+7oamUx6nj+OK5AWi/cADsmIn0T7aqNXA2cSi7UyePByLrzwu53/ADVGX51X/QFzpcdc6TBPesyVHnOlJ0quonMkIWDjxrY+2U9z89m0tIxh3Tr8vtjXIG0Dd0c6hwxDAsw4EmAv9b8/jJSqbEBqyCcjkzOLJ1LeALyIdCfJr055LhKwFy7kMwvpSz4MWXxnMhI874IE8HcgbRLPQW4ENvnPdVzxsr2c5hykrGUbpMzlZCTjnW99mG/bOMkfx03+e17mjy1f776f//wO/muvo32RoZ8iJT0JYALwF0qtNrrddg8wb15tlqsU01fnVX/AXOkxVzrMkx5zpcdc6YmSK8uUB8jAgXV9sp8hQ4Zyxx23sdtuDwH/CXwWKdX4IhKcLve3HON/H4p0INkayXhPQ4LRv9E5QB4H7IwE2lkkUw3tgfdfkVKPO5EykGEFzw9B+pRPQzLl1wMLkcz3j/3nknTOuM8BmpBSmxOBXyM15UuRrPo/6FwXPx4pPbkJ+XQg39bxciTz3obUq/+GWGwy8AKpVIymptWceOLhDB/+cbbZ5q8kEpsKjlFIpeYzYcLhoQjIoe/Oq/6AudJjrnSYJz3mSo+50hMlV5YpD5B161rV23bX8nDx4qf48pePpa1tT6SEo7CzShzJCF+OBL9xJHP8BBIo51sR7o+0RiyeSDkbWQxoMhIMv1qw79lIh5ME7aUrg5DAfjaSYR8OfBf4JzLJMz9Z9MfIDcPLSIYd2iddXo+0MKxHMtqX096aMN+1pbht4wKku8rCosfzY32E7bdfx623/i8tLfcWLD//lw7Bdnsnm+TmVTbD1mWlnPOqv2Ou9JgrHeZJj7nSY670RMmVLR4UIE1NDaxZs7HH7Tq2PBxLLPYQsdh1fPSjQ/jXv1aRTq8DdkJKUUYgXVb2RUpMXkCWoD8EKRmpA45EyjhWIl1QWpCs+b+AFLLgT+GkyyFIwD7Q3+7fSGCcQEpQrkRqwG9F6tAfRtoSjgH2RFokfpn2shiQ0pRHkCD/JKQs5XkkOz4WycL/DFnh82ZgO6RP+VgkWH+Q9kWEFiCB/Xgk2z8eqQnPM4VY7BHOPPPTTJv2c5Xvvl5lM0i055VhrsrBXOkwT3rMlR5zpafWXdmKnj1QraBcy9SpFzFzZv3mlodSjrIf7atizkGy3hmkfOVwpETk90h/77eRYPtgpMTjQSR4vQypuR6FlJ98yf+6BslsH4Nkqi9DarpvoXM7won+z/kl659Ggv8sUo/+TWRCZnGnlvwqmzsCb/rj2g9Z2fMOoAG5yUgiK2g2IZMz30Ay6Z9BAvePIjcgWyPZ+XuQFokn+h7mAb+lqSnFI48sDFVwbRiGYRhGtCgnKLea8gBpampQbbdo0RJ/Auf5SKB5PNIF5SraO5achZRvXAHsg/QlPx2YgQTGbchEzfnA0f6ej0A6mbQgddizkbKSV5DA9lgkIJ+JtFQsXk5+jj+WY5Es9jVIwP+XNgWVAAAVs0lEQVQrJCN/InJK/V8Xr92I9AE/GmnD+B4SXJ8CfAEJ7Ccivc93QhYeWkYi8WXq6p5m+PC92GuvJoYPX0Fd3d0kEkcBq0gmjyKVuoltt21m++3/wIknfrlfBeTa88owV+VgrnSYJz3mSo+50hMlV1ZTHiCaj1duv/0WXnhhMVKK8nHg/yFlHcUdQsYBj/k/X4UEs/kSjnyGugW5OdsKyY4fhWSat0ey0mmkzOULSCD8e//xg5FM9fUF+8t3W5mAZLYX+PvPItnyNuCr/rb5Ti0Jf9xzkKz7USQS88lk0v7+7kImcw4GnuXoow/j1Vcf4Y03WvjoR7dhr73GsGLF+4wcuTvNzY93qgWXkpN8rfgT/SYIL6aWP7arNcyVHnOlwzzpMVd6zJWeKLmy8pUAGTSonrVrO05IWLlyBT/4wQ+ZM2cBbW1tSEnKWbRPkPwdEkznl4DPMxmZvLkIyaafR+dyka8jWfSH/O1vQO7DjkMC6yORoDiLlLzchrQMfBcJ3JciZTCNSIa9wR/H+UhZye1I7fjdSIb8tIIxLkcy6m8hpSdb09T0AEceOZ6WljoymQeRG4kx/vh+w+zZf+SAAw7s0pVRGnOlx1zpMVc6zJMec6XHXOmpdVfllK9YpjxAik+a22+/hcmTL0AmVKb9r3yN9X1IsH2Uv/VtSMCe7+l9MzIB8lwk01y8ouZcJFO9r//7OP81CWAxkulehUzAfBspY1mATBRNIaUlMX/7j/jvPdR//FJkcunHkJU+00im/Lf+a/J9zF9iq60GsdNOKzjkkI/Q3PwXAO6992AymTMozOwnkzFaWu7dHJTX8gVWa5grPeZKj7nSYZ70mCs95kpPlFxZUB4gAwfWsX79JlauXMHhh4/j3XfXInXhX0MmRn6D9gVwfouUdySQbPcxyKTG25Byk12QVS1v8LdJIxMtxyEB+XVIsH+u/+5zkCx3voc5SECeQ4LrHyOLCh2OLLozCwmuHwGWIR1TViO15isYOHAg2ey/qa9PsMMOHyMeryOb3cT7799NIvEAY8YczIUXPlWypGTPPT/JCy907I+eTh/GM8+0d1DJuzJ6xlzpMVd6zJUO86THXOkxV3qi5MqC8gBpbW3jzDMn8cAD82gvUZlLe6eSJFL+sS9wApKFziIL/7wGXIIEz0OQxX9iSAa7EQmWr0dqt1uRYPsYJPN9hf9cDgnEj6C9r3gKaXM4BGml+DTS2eUQpDSmAZncuRUS0H+JZHINJ59cr2o3WIpRo/bHufmk0+2Z/VRqPiNH7t3BlaHDXOkxV3rMlQ7zpMdc6TFXeqLkymrKA2SnnbYilxuAZMSvKnjmTKQu+5tIjfUCpAPKR5ASlVXAn5HOKA8jvb4TwO6AB/wRCc5BgviByKTLfyN14SuQ7Hp+QZwBSLeU+4CDkGD7OH+7Yf57HogsR/8HSrVGHDFiOnPn/qFXHor7sOcX7Fm4sH1Z+4aGVKSWzq0k5kqPudJjrnSYJz3mSo+50lPrrqwlYo1xzDFfYscddyKX2xbJbj9KxzKSD5GWh9NpXwjna0gwDtLP+zIks/0OEoCfARyKBOT5CaJxJCDfBNyPTARdjmTDn0Ey5XciWfL1yCTSOSSTV9HU9CZNTRmSyUOAi4jHsyQSd7DHHjuTTM7vcDzFWe1yGTJkKAsXLuC001oZMWI6p57a2iEgB8hksr3ef3/DXOkxV3rMlQ7zpMdc6TFXeqLkKhLlK57nxYFrkei1FTjLOfdq968KhmOO+RKPPfY07Yv8SKcRGepzSGZ6KVLOUsg4JFu+FHBIoJ1CAvjtkOz1RiQYH4j0DH8auAmZkPku8ucd4u/vLSSIryOV+j0NDQM48sjVLFvWvvw8UNRm8EkAP6tNny5DP2TI0G7LX2KxLdp9v8Jc6TFXesyVDvOkx1zpMVd6ouQqEkE5snZ8g3PuM57njQIuRxpqVx0JyL9Fe6vA8UjGugVpUzgEWIlkrwtLRGYj9dzrgW2QrPluSOnK+0iZCiSTjaTTrUit+X7EYicSj9/FF75wCK+/voK33lrFrrvuyNSpP+Hhhx8rCLhLL65TKlBeuHBBUbC+oOI9wWNRusoqjLnSY670mCsd5kmPudJjrvREyVVUgvLP4S8h6Zxb5HmeqnYnGAYgGfJCxiGdVZ5A6rbbaF+op3ASZgbYFilFGoy0SszS2DiYlpY7NrcPbF9I50VGjvwIzc1Plgyax48/qtNjGnrKaleCKH0cVWnMlR5zpcdc6TBPesyVHnOlJ0quolJTPhjp15cn43lelzcc8XiMVCpBXV2C+vokyWScAQNSxOMxGhvrgPZlW4u/NzbWEY/HGDAgRTIZp74+SV1dglQqQUNDikQixsCBso9Bg+qRNoMPFY1gLqL+o0grw03+dtcBJyPlLRkkG/4BMslzNjCcwYO35tFHH+bzn/8cIK2AdtllGFdeOZ0///mPXH75pey++24VPqZS+6gnFosxYEAdiYTsI5WSfdTXJ0kk4gwYUEcsFqOxsfQ+8vseOLCOurokDQ2pAP9OlT+mRCJWkWOqr09G7pii+HcK2zGlUonIHVMl/k6pVCJyx1Spv1NDQypyxxTFv1PYjqnw36paPKZyiET3Fc/zrgAWOefu8n9f4Zzrsr4iyO4r++67F++8swopYTmc9h7i+WXu803vY0jNeBbJrmfYaaftmT79Ur/s5EW/dOTsfrGcfDweI5sN/7kZBOZKj7nSY650mCc95kqPudJT667644qejwFHA3f5NeVLqzyezcyZM48DDtifbPbXyMTNViQLnkMy5AB1bLXV9uyww3bU12/FqFH7dwi+e1t2EmYGDEixbl00FgOoNOZKj7nSY650mCc95kqPudITJVdRyZTnu698Ckk5n+Gce7mr7YPuU96x5rv/ZLsNwzAMwzD6M+VkyiMRlJdLtRYPampqYM2ajYG/bxgxV3rMlR5zpcdc6TBPesyVHnOlp9ZdWVDeA9UKyg3DMAzDMIz+g63oWaPkZ+MaPWOu9JgrPeZKj7nSYZ70mCs95kpPlFxZptwwDMMwDMMwKoBlymuUKN3NVRpzpcdc6TFXesyVDvOkx1zpMVd6ouTKMuWGYRiGYRiGUQEsU16j5FePMnrGXOkxV3rMlR5zpcM86TFXesyVnii5sqA8QDZsaKv2EEKDudJjrvSYKz3mSod50mOu9JgrPVFyZUF5gNTXR2UB1cpjrvSYKz3mSo+50mGe9JgrPeZKT5RcWVAeIG1tmWoPITSYKz3mSo+50mOudJgnPeZKj7nSEyVXFpQHSCJhurWYKz3mSo+50mOudJgnPeZKj7nSEyVX0TmSENAfO930FnOlx1zpMVd6zJUO86THXOkxV3qi5MqC8gCJ0HlTccyVHnOlx1zpMVc6zJMec6XHXOmJkqt+2acceBd4o9qDMAzDMAzDMCLNrsAOmg37a1BuGIZhGIZhGDWDla8YhmEYhmEYRpWxoNwwDMMwDMMwqowF5YZhGIZhGIZRZSwoNwzDMAzDMIwqY0G5YRiGYRiGYVQZC8oNwzAMwzAMo8okqz2A/oDneXHgWmA/oBU4yzn3anVHFQye56WAm4DdgHrgp8CLwM1ADnge+LZzLut53g+Bo4A0cK5z7m+e5+2h3TbI46oknuftCCwGDkOO72bMVSc8z5sKfBmoQ66vhzFXnfCvwZnINZgBvoGdV53wPO8g4FLn3Ohyjrkvtg3yOPuCIlf7A9cg51YrcKpz7h3P874BfAs5/p865x7wPG97YBYwAHgLOMM5t76cbQM+1C2m0FXBYxOB/+ec+4z/u7mi03m1I3A9sA2QQM6r16LuyjLlwfAVoMG/AC8ELq/yeILkFOB959whwBHADOAK4Pv+YzFggud5I4HPAwcBJwG/8l9fzrahxw+gfgNs8B8yVyXwPG80cDDwWeT4hmGuuuJIIOmcOxj4MfAzzFUHPM/7DnAD0OA/VCk/nbat9LH1NSVcXY0EmKOBe4Dvep63M/DfyPU5DpjmeV498ANgln/8zwLfKmfbgA6xzyjhCv8m5uvI3x9zJZRw9QvgdufcocD3gU/0B1cWlAfD54A5AM65RcB/VHc4gfJ74H8Kfk8DByBZTYDZwFjE0UPOuZxz7k0g6XneDmVuGwUuA36N3MGDueqKccBS4F7gj8ADmKuuWIYcSxwYDLRhrop5DTi24PdK+Sm1bdgodnWSc26J/3MS2Ah8GnjMOdfqnFsNvAp8ioL/C2k//nK2DRsdXHmetx1wCXBuwTbmSig+rz4LDPU8bz7wNWAh/cCVBeXBMBhYXfB7xvO8flE65Jxb65xb43leE9CC3PHGnHP5pWTXAFvR2VH+8XK2DTWe550OvOucm1vwsLkqzfbIze0JwH8CtwNxc1WStUjpysvIx8G/xM6rDjjn7kZuVvJUyk+pbUNFsSvn3NsAnucdDDQDV9L18Rc+3pOrUtuGikJXnuclgBuBycjx5DFXlLwGdwNWOefGAm8C36UfuLKgPBg+BJoKfo8759LVGkzQeJ43DPgLcKtzbhZQWEPZBHxAZ0f5x8vZNuycCRzmed5CYH/gFmDHgufNVTvvA3Odc5uccw7JzhX+42qu2pmMuBqOzGuZidTh5zFXnanUv1Gltg09nuediHzCd5Rz7l26Pv7Cx3tyVWrbMHMAsCfwv8AdwN6e512FueqK94H7/Z//iCRhIu/KgvJgeAyp68TzvFHIx+79As/zdgIeAr7rnLvJf/hZvyYYpM78r4ijcZ7nxT3P2wW5cXmvzG1DjXPuUOfc5/3azCXAqcBsc1WSR4HxnufFPM/7KNAILDBXJVlFe2bo30AKuwZ7olJ+Sm0bajzPOwXJkI92zv3Df/hvwCGe5zV4nrcVsBcysXXz/4W0H38524YW59zfnHP7+P++nwS86Jw7F3PVFY/SfkyHAi/QD1z1ixKKGuBeJAP6ODK544wqjydILkJmT/+P53n52vJzgF96nlcHvAS0OOcynuf9FXgCuVn8tr/t+cD1ym2jSDnH329c+bPoD0X+4c0f1z8xV6W4ErjJP7Y65Jp8GnPVHZW67jptG9gRVQC/JOOXSHnBPZ7nATzsnPuh53m/RAKeOPA959xGz/N+Csz0pCvGe8BE59w67baBH2AAOOf+Za5Kcj5wg+d5/4UkFSY651ZF3VUsl8v1vJVhGIZhGIZhGBXDylcMwzAMwzAMo8pYUG4YhmEYhmEYVcaCcsMwDMMwDMOoMhaUG4ZhGIZhGEaVsaDcMAzD6IDnebFqj6GSRP34DMMIJ9YS0TAMo0L4C0F9voun33HO7RzgcDrhed5uSCvJE5xzLZ7nDQVuAE5B2oVt6f73B84DRgM7AMuB+4BLq9HX3PO8rYFfAVcAi4N+f8MwjO6wTLlhGEZleQz4TImvI7t7UUC8jYzlz/7vY4FxfbFjf1GZJ4FdgKnI8V6NLJzymL+wWNDsj/Qltky5YRg1h2XKDcMwKssHzrlF1R5EKZxzrUCfj82TVWSuB34PTHLO5RfE+IvneXOA54CfA1/v6/c2DMMIKxaUG4ZhVBnP8z4NXAwcDAxESkqucM79xvO8RuAd4GfOuWkFr9kHWTZ6jHPuz34pyi+QcpmBSPb7AufcK/72FwNfQla4OwNZtvpr/nudAAwCfuvv/l3P837knLvY87wk8APgdGBH/z2/65xb0M0hNQMJ4PyCgBwA59xrnud9x38+fyyDgB8CxwM7A0uB7zvnHvKfHw38BTjQOfd0wes+AK7yx3k6cBlwInA5sqz2a8CFzrn7C/YB8JTneTOdc6d3cwyGYRiBYuUrhmEYlSXmeV6y+Cv/pOd5uyDB4lokOJ4ALAN+7Xnep5xz64D7/ecKORH4F7DQrwX/G7AncDYSdH8MeNTzvI8WvGY/4EDgOCRTXciDwE/9n8cjteUgGe/zkdKTrwAvA7M9zzu4m2M+HFjsnHun1JPOuWudc9f4xx8H5vhjvgQ4Flm2/U+e55VbStME3ITUjX8JqYu/0/O8bYFnaF/u/gzgJ2Xu2zAMo6JYUG4YhlFZjgTair88z9vef34f4Anga865ec652cBp/nOH+t9nASM8z/t4wX5PAO50zmWBycAA4DDn3N3OuRbgi/5j5xe8Jgmc65xb4Jx7sHCQzrl3kcwySEC9wvO8TyAZ8nOcc5c75+Y4505Bsu0/pWuGAm/0aEY4Cvisf/y/cc7Nds4dDzxF5xuHnqgDpjjnrnfOzUMy9g3AF5xzHwIv+ts975x7raudGIZhVAMrXzEMw6gsjyJBczEfAPhB+GzP8xo8z9sbyXYf6G9T73+fC7yPBOKXeJ73KeATdAze/1LY0cQ5957neQvo3P3lpTLGPtr//qfC7D7wJ2Ca53l1zrlNJV6XQZ/0ORRY45ybW/T4HcBVnuc1lTFe6Fgjv8L/3ljmPgzDMALHgnLDMIzKsrqwDroYz/MSSA30t5BM72vAI/7TMQDnXJvneS34QTnwVeAfzrm/+dttAywpsft3kEx8nnV+OYyW7fzvK7t4fnvgrRKPv4F0XSmJX06y0Tm3Hhl7qTKX/GPlBuXrC37O+t/tU2HDMGoe+4fKMAyjunwP+CZwKjDYOTcc+O8S2/0OGOlP6DzB/z3Pv4FSLQZ3RjLsvWU1kEMmoB5Y4qurXuPzgAM8z9uhi+d/ArztT/Dsbuz4z+cni27+P8tfAMgy4IZhRAYLyg3DMKrLZ4CnnXO/L8hij/e/F/bTfgQpx/gOMBypM8/zKPCFgjp1/J/HIH3StWSKfn/UH0OTc+7p/BfSz3wykO5iP9ciWerLilfP9DxvL+QG5D7n3Fr/PZpKTOo8Ealt3wh86D9WOGl1FOV/2lt8fIZhGDWDla8YhmFUl6eACz3Pa0ZaAR6ItCDMIa0NAXDO5TzPuwMJhv/unHuxYB9XIhMy53me9xMkkP4+sAm4qoyxfOB/P9bzvIecc0s8z7sbuM1vqfgSUmf+feAX/iTTTjjnXvU87zzgGmCI53k3AP8HHIDcVKwEzvU3fxBZZOg2z/O+h3ReOQM4CDja3+bv/mt+4nleGzAY+DGSyS+H/PEd5XneWufcy2W+3jAMo2JYptwwDKO6XALMRPp0P4CsOPn/kBKQzxRtOwvp711YuoJzbjlwCFLffQtwI1LX/Rnn3Ar0LEAmlV4DXOA/9jWkf/lUpHXhycCFwEXd7cg59ytkddBWZFn7B5HFgm70x/Vvf7sM8snAPcDP/O/DgCPzHWL8bb4KbPSf/yES3L9axrGB9Ga/1T+W6WW+1jAMo6LEcrlcz1sZhmEYhmEYhlExLFNuGIZhGIZhGFXGgnLDMAzDMAzDqDIWlBuGYRiGYRhGlbGg3DAMwzAMwzCqjAXlhmEYhmEYhlFlLCg3DMMwDMMwjCpjQblhGIZhGIZhVBkLyg3DMAzDMAyjyvx/P8o3fCTSXXwAAAAASUVORK5CYII=
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<p>The scatter plot visually demonstrated that the favorite counts and retweet counts of Tweets have a strong, positive correlation. The high value of the correlation coefficient, 0.93, corroborated this demonstration as well. Thus, a <em>popular</em> Tweet with a large number of favorite counts (or retweet counts) is expected to have a relatively large number of retweet counts (or favorite counts). This observation, however, does not necessarily suggest any causal relationship between these two counts.</p>
<p>The strong, positive correlation between the favorite counts and retweet counts motivated the application of linear regression to test and confirm the observations made from the scatter plot above. Like the scatter plot, favorite counts and the retweet counts were used as the predictor variable and the response variable, respectively, in the linear regression.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># add a new column for y-intercept</span>
<span class="n">df_2</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">df_2</span><span class="p">[</span><span class="s1">&#39;intercept&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>

<span class="c1"># OLS</span>
<span class="n">lm</span> <span class="o">=</span> <span class="n">sm</span><span class="o">.</span><span class="n">OLS</span><span class="p">(</span><span class="n">df_2</span><span class="p">[</span><span class="s1">&#39;retweet_count&#39;</span><span class="p">],</span> <span class="n">df_2</span><span class="p">[[</span><span class="s1">&#39;intercept&#39;</span><span class="p">,</span> <span class="s1">&#39;favorite_count&#39;</span><span class="p">]])</span> <span class="c1"># linear modeling with OLS: y-var, x-var</span>
<span class="n">results</span> <span class="o">=</span> <span class="n">lm</span><span class="o">.</span><span class="n">fit</span><span class="p">()</span> <span class="c1"># apply the best fit</span>
<span class="n">results</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span> <span class="c1"># summary of linear modeling</span>
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<table class="simpletable">
<caption>OLS Regression Results</caption>
<tr>
  <th>Dep. Variable:</th>      <td>retweet_count</td>  <th>  R-squared:         </th> <td>   0.864</td> 
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  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.864</td> 
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  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>1.265e+04</td>
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  <th>Date:</th>             <td>Sun, 14 Apr 2019</td> <th>  Prob (F-statistic):</th>  <td>  0.00</td>  
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  <th>Time:</th>                 <td>17:45:14</td>     <th>  Log-Likelihood:    </th> <td> -17652.</td> 
</tr>
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  <th>No. Observations:</th>      <td>  1990</td>      <th>  AIC:               </th> <td>3.531e+04</td>
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  <th>Df Residuals:</th>          <td>  1988</td>      <th>  BIC:               </th> <td>3.532e+04</td>
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  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>    
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  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>    
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         <td></td>           <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  
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  <th>intercept</th>      <td> -342.7629</td> <td>   46.749</td> <td>   -7.332</td> <td> 0.000</td> <td> -434.444</td> <td> -251.082</td>
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  <th>favorite_count</th> <td>    0.3429</td> <td>    0.003</td> <td>  112.485</td> <td> 0.000</td> <td>    0.337</td> <td>    0.349</td>
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  <th>Omnibus:</th>       <td>1787.091</td> <th>  Durbin-Watson:     </th>  <td>   1.250</td> 
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  <th>Prob(Omnibus):</th>  <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>239632.559</td>
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  <th>Skew:</th>           <td> 3.669</td>  <th>  Prob(JB):          </th>  <td>    0.00</td> 
</tr>
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  <th>Kurtosis:</th>       <td>56.256</td>  <th>  Cond. No.          </th>  <td>1.86e+04</td> 
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</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 1.86e+04. This might indicate that there are<br/>strong multicollinearity or other numerical problems.
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<p>The <strong>R-squared</strong> value of 0.864 obtained from this linear regression also indicated a strong correlation between the predictor and the response variables in that according to this value, changes in favorite counts account for 86.4% of the variability in retweet counts.</p>
<p>The values of the slope and the y-intercept obtained from applying the linear regression were used to build the following linear model.</p>
$$y = 0.34x-342.76$$<p>The linear fit was added to the scatter plot of retweet counts vs. favorite counts as shown below. Although having more pairs of favorite counts and retweet counts above the center of the distribution of each variable would help build a linear model of greater accuracy, precision, and confidence for larger numbers of favorite and retweet counts, the results from the linear regression support the observations from the scatter plot: favorite counts and retweet counts show a strong, positive relationship.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># configure plot with size, title, and labels for both axes</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">12</span><span class="p">,</span> <span class="mi">7</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Correlation between Retweet and Favorite Counts&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">18</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Favorite Count&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Retweet Count&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>

<span class="c1"># scatter plot of retweet count vs. favorite count</span>
<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">favorite_count</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">df_2</span><span class="o">.</span><span class="n">retweet_count</span>
            <span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="mi">30</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="n">marker</span> <span class="o">=</span> <span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">edgecolors</span> <span class="o">=</span> <span class="s1">&#39;black&#39;</span><span class="p">)</span>

<span class="c1"># configure and plot linear fit</span>
<span class="n">slope</span> <span class="o">=</span> <span class="mf">0.3429</span>
<span class="n">intercept</span> <span class="o">=</span> <span class="o">-</span><span class="mf">342.7629</span>
<span class="n">x_</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">df_2</span><span class="o">.</span><span class="n">favorite_count</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">df_2</span><span class="o">.</span><span class="n">favorite_count</span><span class="o">.</span><span class="n">max</span><span class="p">(),</span> <span class="mi">10</span><span class="p">)</span>

<span class="c1"># plot and add legend for the linear fit</span>
<span class="n">linear_fit</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x_</span><span class="p">,</span> <span class="n">x_</span><span class="o">*</span><span class="n">slope</span> <span class="o">+</span> <span class="n">intercept</span><span class="p">,</span> <span class="n">linewidth</span> <span class="o">=</span> <span class="mf">1.5</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles</span> <span class="o">=</span> <span class="n">linear_fit</span>
           <span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Linear Fit</span><span class="se">\n</span><span class="s1">- Slope: </span><span class="si">{}</span><span class="se">\n</span><span class="s1">- y-Intercept: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">slope</span><span class="p">,</span><span class="mi">2</span><span class="p">),</span> <span class="nb">round</span><span class="p">(</span><span class="n">intercept</span><span class="p">,</span><span class="mi">2</span><span class="p">))]</span>
           <span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">12</span><span class="p">);</span>
</pre></div>

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<h3 id="3.-Comparison-of-Dog-Ratings-and-Sentiment-of-Tweets">3. Comparison of Dog Ratings and Sentiment of Tweets<a class="anchor-link" href="#3.-Comparison-of-Dog-Ratings-and-Sentiment-of-Tweets">&#182;</a></h3><h4 id="Explore">Explore<a class="anchor-link" href="#Explore">&#182;</a></h4><p>Tweets posted by <em>WeRateDogs (@dogrates)</em> not only provide comments on the images of dogs but include ratings of dogs out of 10. As observed during the data wrangling phase, these ratings are unique in that the scores may be greater than 1; that is, the numerator may be larger than 10. One would expect that the images of dogs with higher ratings would be associated with noteworthy qualities. This expectation motivated the investigation of whether the qualities which rendered the assigned ratings are reflected in the sentiment of the Tweets.</p>
<p>The <code>textblob</code> package was used for analyzing the sentiment of the Tweets posted by <em>WeRateDogs (@dogrates)</em>. The <code>sentiment</code> property of a <code>TextBlob</code>, both of which are explained in the following discussions, returns a <em>polarity</em> score for the Tweet used to create the <code>TextBlob</code>. This score ranges from -1.0 for most negative sentiment to 1.0 for most positive sentiment. To ensure that the dog ratings are comparable with this scoring scheme, both the distribution of the values for the <code>rating_numerator</code> and the number of occurrences of each unique value were obtained as shown below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># distribution of ratings</span>
<span class="n">df</span><span class="o">.</span><span class="n">rating_numerator</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<pre>count    1990.000000
mean       11.621608
std        40.718213
min         0.000000
25%        10.000000
50%        11.000000
75%        12.000000
max      1776.000000
Name: rating_numerator, dtype: float64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># number of occurrences of each rating</span>
<span class="n">df</span><span class="o">.</span><span class="n">rating_numerator</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span>
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<pre>12      449
10      419
11      396
13      261
9       151
8        95
7        51
14       36
5        33
6        32
3        19
4        15
0        15
2         9
1         4
75        1
420       1
26        1
27        1
1776      1
Name: rating_numerator, dtype: int64</pre>
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<h4 id="Feature-Engineering">Feature Engineering<a class="anchor-link" href="#Feature-Engineering">&#182;</a></h4><p>Based on the analysis of the values for <code>rating_numerator</code>, values below 11, those below 13, and the remaining values were assigned a <code>rating</code> of <em>low</em>, <em>medium</em>, and <em>high</em>, respectively. This operation was performed on the sub-dataset including the data for only the two columns <code>text</code> and <code>rating_numerator</code>, which was first created from the dataframe object <code>df</code> for the purpose of the sentiment analysis.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># original tweets&#39; text and rating_numerator</span>
<span class="n">df_3</span> <span class="o">=</span> <span class="n">df</span><span class="p">[[</span><span class="s1">&#39;text&#39;</span><span class="p">,</span> <span class="s1">&#39;rating_numerator&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>

<span class="c1"># assign a rating of low, medium, or high based on rating_numerator</span>
<span class="k">def</span> <span class="nf">rate</span><span class="p">(</span><span class="n">df</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">df</span><span class="o">.</span><span class="n">rating_numerator</span> <span class="o">&lt;</span> <span class="mi">11</span><span class="p">:</span>
        <span class="k">return</span> <span class="s2">&quot;low&quot;</span>
    <span class="k">elif</span> <span class="n">df</span><span class="o">.</span><span class="n">rating_numerator</span> <span class="o">&lt;</span> <span class="mi">13</span><span class="p">:</span>
        <span class="k">return</span> <span class="s2">&quot;medium&quot;</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">return</span> <span class="s2">&quot;high&quot;</span>

<span class="n">df_3</span> <span class="o">=</span> <span class="n">df_3</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">df_3</span><span class="p">[</span><span class="s1">&#39;rating&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_3</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">rate</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span>
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<p>As briefly introduced in the previous section, the text data of each Tweet was used to create a <code>TextBlob</code> and obtain the polarity score, the first element of the <code>sentiment</code> property. The polarity score of each Tweet was first stored in a list, assigned to a dictionary key, and then joined with the dataframe object created for this sentiment analysis. Finally, histogram plots of the polarity scores for each dog ratings, <em>low</em>, <em>medium</em>, and <em>high</em>, were created and are presented below along with the median of the polarity scores for each dog ratings.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># empty dictionary for storing a list of polarity score of each tweet</span>
<span class="n">sentiment_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">sentiment_dict</span><span class="p">[</span><span class="s1">&#39;sentiment&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">TextBlob</span><span class="p">(</span><span class="n">tweet</span><span class="p">)</span><span class="o">.</span><span class="n">sentiment</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">tweet</span> <span class="ow">in</span> <span class="n">df_3</span><span class="o">.</span><span class="n">text</span><span class="p">]</span>

<span class="c1"># join the polarity score of each tweet to the text, rating_numerator, and rating data</span>
<span class="n">df_3</span> <span class="o">=</span> <span class="n">df_3</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">other</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span> <span class="o">=</span> <span class="n">sentiment_dict</span><span class="p">))</span>

<span class="n">df_3</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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        vertical-align: middle;
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        vertical-align: top;
    }

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      <th></th>
      <th>text</th>
      <th>rating_numerator</th>
      <th>rating</th>
      <th>sentiment</th>
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      <th>0</th>
      <td>This is Phineas. He's a mystical boy. Only eve...</td>
      <td>13</td>
      <td>high</td>
      <td>0.000000</td>
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      <th>1</th>
      <td>This is Tilly. She's just checking pup on you....</td>
      <td>13</td>
      <td>high</td>
      <td>0.366667</td>
    </tr>
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      <th>2</th>
      <td>This is Archie. He is a rare Norwegian Pouncin...</td>
      <td>12</td>
      <td>medium</td>
      <td>0.150000</td>
    </tr>
    <tr>
      <th>3</th>
      <td>This is Darla. She commenced a snooze mid meal...</td>
      <td>13</td>
      <td>high</td>
      <td>0.500000</td>
    </tr>
    <tr>
      <th>4</th>
      <td>This is Franklin. He would like you to stop ca...</td>
      <td>12</td>
      <td>medium</td>
      <td>0.233333</td>
    </tr>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create a figure with subplots arranged in 1-by-3</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">ncols</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">7</span><span class="p">))</span>

<span class="c1"># add figure title and axis labels for all subplots</span>
<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;Distribution of Polarity Scores for each Dog Rating Group&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">18</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="mf">0.06</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Polarity Score&#39;</span><span class="p">,</span> <span class="n">ha</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">va</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mf">0.09</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Count&#39;</span><span class="p">,</span> <span class="n">ha</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">va</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">rotation</span> <span class="o">=</span> <span class="s1">&#39;vertical&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>

<span class="c1"># dictionary of ratings and integers for indexing subplots</span>
<span class="n">rating_dict</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;low&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;medium&#39;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;high&#39;</span><span class="p">:</span> <span class="mi">2</span><span class="p">}</span>

<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">rating_dict</span><span class="p">:</span>
    <span class="c1"># set rating as subplot title </span>
    <span class="n">ax</span><span class="p">[</span><span class="n">rating_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">key</span><span class="o">.</span><span class="n">title</span><span class="p">(),</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
    
    <span class="c1"># plot histogram of the polarity scores for the given rating</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">rating_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">df_3</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;rating == @key&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">sentiment</span><span class="p">)</span>
    
    <span class="c1"># compute and display the median of the polarity scores for the given rating</span>
    <span class="n">median</span> <span class="o">=</span> <span class="n">df_3</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;rating == @key&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">sentiment</span><span class="o">.</span><span class="n">median</span><span class="p">()</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">rating_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]]</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">ax</span><span class="p">[</span><span class="n">rating_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]]</span><span class="o">.</span><span class="n">get_ylim</span><span class="p">()[</span><span class="mi">1</span><span class="p">]</span> <span class="o">*</span> <span class="mf">0.97</span>
                              <span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Median: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">median</span><span class="p">,</span> <span class="mi">3</span><span class="p">)),</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">12</span><span class="p">);</span>
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<p>Comparison of the histograms showed that the center of the distribution of polarity scores increased with the dog rating from 0 for <em>low</em> to 0.062 for <em>medium</em> and 0.233 for <em>high</em>. However, this increase across each group of dog rating appears to be insignificant relative to the range of polarity scores from -1.0 to 1.0 as defined in the <code>textblob</code> package. The gap between the dog ratings and the sentiment of the Tweets can be attributed to two factors.</p>
<ul>
<li>First, unlike polarity scores which can take any numeric values from -1.0 to 1.0, the interquartile range of the values of <code>rating_numerator</code> is limited to only three integers 10, 11, and 12. This outcome of the human-generated rating schema suggests its inherent limitations in quantifying a wide variety of qualities associated with the images of dogs.</li>
<li>Second, the numeric ratings included in the Tweets are not necessarily correlated with the tone of the comments of the dogs' images. Thus, the polarity score assigned to a <code>TextBlob</code> of a Tweet may estimate the sentiment of the comment but still not align with the rating assigned to the dog's image.</li>
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<p>The expectation that the center of the distribution of polarity scores for <em>low</em>, <em>medium</em>, and <em>high</em> ratings of dog would be closer to -1.0, 0.0, and 1.0, respectively, deserves further investigation given a wider and evenly spread distribution of dogs' ratings and comments with tone commensurate with the ratings.</p>

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<h3 id="4.-Accuracy-and-Precision-of-Predicting-Dogs'-Breeds-from-Images">4. Accuracy and Precision of Predicting Dogs' Breeds from Images<a class="anchor-link" href="#4.-Accuracy-and-Precision-of-Predicting-Dogs'-Breeds-from-Images">&#182;</a></h3><h4 id="Explore">Explore<a class="anchor-link" href="#Explore">&#182;</a></h4><p>As mentioned in <strong>Part 1: Data Wrangling</strong>, the images of dogs included in the Tweets from the enhanced Twitter archive were run through a <a href="https://www.youtube.com/watch?v=2-Ol7ZB0MmU">neural network</a>, which made top three predictions of each dog's breed. Various applications for such image recognition technology which utilizes deep learning, machine learning, and artificial intelligence renders the investigation of the accuracy and precision of its outputs necessary. In case of the neural network which made predictions of each dog's breed, two main parameters are worth further investigation for evaluating its performance: <code>confidence</code> and <code>dog_breed</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># top three predictions of dog&#39;s breed for two tweets</span>
<span class="n">df_image</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">66</span><span class="p">:</span><span class="mi">72</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">r_</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">:</span><span class="mi">6</span><span class="p">]]</span>
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      <th></th>
      <th>tweet_id</th>
      <th>prediction</th>
      <th>confidence</th>
      <th>dog_breed</th>
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    <tr>
      <th>66</th>
      <td>887473957103951883</td>
      <td>p1</td>
      <td>0.809197</td>
      <td>True</td>
    </tr>
    <tr>
      <th>67</th>
      <td>887473957103951883</td>
      <td>p2</td>
      <td>0.054950</td>
      <td>True</td>
    </tr>
    <tr>
      <th>68</th>
      <td>887473957103951883</td>
      <td>p3</td>
      <td>0.038915</td>
      <td>True</td>
    </tr>
    <tr>
      <th>69</th>
      <td>887343217045368832</td>
      <td>p1</td>
      <td>0.330741</td>
      <td>True</td>
    </tr>
    <tr>
      <th>70</th>
      <td>887343217045368832</td>
      <td>p2</td>
      <td>0.275645</td>
      <td>False</td>
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      <th>71</th>
      <td>887343217045368832</td>
      <td>p3</td>
      <td>0.134203</td>
      <td>True</td>
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<p>In case of <code>confidence</code>, which quantifies the level of confidence of the neural network in each of its predictions, the confidence level appears to decrease by each prediction for a given tweet. Potential users of such technology would expect this pattern to hold true because the purpose of the neural network is to make <em>top three</em> predictions of each dog's breed. In case of <code>dog_breed</code>, which indicates whether the prediction is infact a dog's breed, the level of prediction or even confidence does not appear to ensure that the output is a breed of a dog. Potential users of this technology would expect to see a dog's breed or at least see more outputs of dogs' breeds for a higher level of prediction.</p>

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<h4 id="Feature-Engineering">Feature Engineering<a class="anchor-link" href="#Feature-Engineering">&#182;</a></h4><p>To evaluate and discuss the accuracy and precision of the neural network in recognizing images of dogs and making top three predictions of each dog's breed, both the rate of success in yielding a dog's breed and the distribution of the confidence levels for each level of prediction were analyzed.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># calculate the rate of success in predicting a dog breed for each level of prediction</span>
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">df_image</span><span class="o">.</span><span class="n">prediction</span><span class="o">.</span><span class="n">unique</span><span class="p">():</span>
    <span class="n">proportion</span> <span class="o">=</span> <span class="n">df_image</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;prediction == @p&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">dog_breed</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">{}</span><span class="s1">: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="nb">round</span><span class="p">(</span><span class="n">proportion</span><span class="p">,</span> <span class="mi">3</span><span class="p">)))</span>
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<pre>p1: 0.74
p2: 0.749
p3: 0.725
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<p>According to the statistics computed and shown above, the mean proportion of predictions which were in fact a breed of dogs did not significantly vary by the first, second, and third predictions. At any level of predictions, the output of the neural network is expected to be a dog's breed approximately 74% of the time.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create a figure with suplots arranged in 1-by-3</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">ncols</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span><span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">7</span><span class="p">))</span>

<span class="c1"># add figure title and axis labels for all subplots</span>
<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;Distribution of Confidence Levels of Each Prediction&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">18</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="mf">0.06</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Confidence Level&#39;</span><span class="p">,</span> <span class="n">ha</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">va</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="mf">0.09</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Count&#39;</span><span class="p">,</span> <span class="n">ha</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">va</span> <span class="o">=</span> <span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">rotation</span> <span class="o">=</span> <span class="s1">&#39;vertical&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>

<span class="c1"># for each subplot indexed by the level of prediction, p1, p2, and p3</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">p</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">df_image</span><span class="o">.</span><span class="n">prediction</span><span class="o">.</span><span class="n">unique</span><span class="p">()):</span>
    
    <span class="c1"># set the level of prediction as the title of the suplot</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">label</span> <span class="o">=</span> <span class="n">p</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
    
    <span class="c1"># plot a stacked histogram for confidence levels of predictions</span>
        <span class="c1"># top: non-dog breed outputs</span>
        <span class="c1"># bottom: dog breed outputs</span>
    <span class="n">stack_hist</span> <span class="o">=</span> <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="n">df_image</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;prediction == @p &amp; dog_breed == True&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">confidence</span>
                           <span class="p">,</span> <span class="n">df_image</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;prediction == @p &amp; dog_breed == False&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">confidence</span><span class="p">]</span>
                      <span class="p">,</span> <span class="n">histtype</span> <span class="o">=</span> <span class="s1">&#39;barstacked&#39;</span>
                      <span class="p">,</span> <span class="n">color</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;green&#39;</span><span class="p">,</span> <span class="s1">&#39;orange&#39;</span><span class="p">]</span>
                      <span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Dog Breed&#39;</span><span class="p">,</span> <span class="s1">&#39;Other&#39;</span><span class="p">])</span>
    <span class="c1"># add legend for colors    </span>
    <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
    
    <span class="c1"># set the range for both x and y axes for all suplots</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">(</span><span class="n">xmin</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span> <span class="n">xmax</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">)</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">(</span><span class="n">ymin</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span> <span class="n">ymax</span> <span class="o">=</span> <span class="mi">700</span><span class="p">)</span>
    
    <span class="c1"># calculate the median of the confidence levels</span>
    <span class="n">median</span> <span class="o">=</span> <span class="n">df_image</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s1">&#39;prediction == @p&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">confidence</span><span class="o">.</span><span class="n">median</span><span class="p">()</span>
    
    <span class="c1"># plot vertical line through the median</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="n">median</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="s1">&#39;r&#39;</span><span class="p">,</span> <span class="n">linestyle</span> <span class="o">=</span> <span class="s1">&#39;--&#39;</span><span class="p">)</span>
    
    <span class="c1"># annotate the vertical line with the median value</span>
    <span class="n">ax</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;Median: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">median</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
                   <span class="p">,</span> <span class="n">xy</span> <span class="o">=</span> <span class="p">(</span><span class="n">median</span><span class="p">,</span> <span class="mi">500</span><span class="p">),</span> <span class="n">xycoords</span> <span class="o">=</span> <span class="s1">&#39;data&#39;</span>
                   <span class="p">,</span> <span class="n">xytext</span> <span class="o">=</span> <span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">textcoords</span> <span class="o">=</span> <span class="s1">&#39;offset points&#39;</span>
                   <span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">12</span><span class="p">,</span> <span class="n">arrowprops</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">arrowstyle</span> <span class="o">=</span> <span class="s2">&quot;-&quot;</span>
                                                      <span class="p">,</span> <span class="n">connectionstyle</span> <span class="o">=</span> <span class="s2">&quot;arc3, rad=0.3&quot;</span>
                                                      <span class="p">,</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;red&#39;</span><span class="p">));</span>
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<p>The three histograms illustrate that the confidence level of a prediction is expected to decrease with each prediction. The median values of the confidence levels for the first, second, and third predictions were 0.587, 0.118, and 0.05, respectively. In addition to this leftward shift of the center of the distribution, the difference in the shape of the distributions for the first and second predictions, left-skewed and right-skewed, supports the higher confidence level expected for the higher level of prediction. In fact, from the second to the third prediction, the distribution of the confidence levels become more right-skewed.</p>
<p>In addition, the plots not only confirm the proximity of the mean proportion of predictions with dog breeds across the three levels of predictions but illustrate that this proximity holds for each binwidth of confidence levels across all three levels of predictions. For the majority of the bars in all three plots, the proportion of green area is larger than twice the proportion of orange area.</p>

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<p><a id='conclusion'></a></p>
<h2 id="Conclusion">Conclusion<a class="anchor-link" href="#Conclusion">&#182;</a></h2><p>Before exploring the data to decide on topics or questions to investigate, review of the data imported from the cleaned dataset in the <code>.csv</code> file revealed that the data types of two columns were reverted back to those observed in the gathered datasets. Also, two sub-datasets were created from the cleaned dataset because only the last of the four topics required the data on the predictions of dogs' breeds from their images. As such, steps from data wrangling may need to be repeated depending on the data or the goals of the project.</p>
<p>For the first topic, exploring the data involved extracting the <em>hour</em> and <em>day</em> parts of datetime data by using methods from the <code>datetime</code> package. These methods required the timestamp to have a data type of datetime, a requirement met by the wrangling efforts from <strong>Part 1</strong>. Engineering the data for calculating the percentage of Tweets from each hour in a day relied on grouping and counting values of the <code>day</code> and <code>hour</code> columns which were newly created while exploring the data.</p>
<p>Investigation of the second topic did not necessarily benefit from the wrangling efforts. However, the analysis and visualization of the correlation between the favorite counts and the retweet counts would not have been possible if the data type of these variables was not numeric.</p>
<p>For the third topic, exploring and engineering the data relied heavily on the numerator values of the dog ratings out of 10. The <code>rating_denominator</code> column was omitted from the analysis because during the wrangling phase, all ratings with denominator values other than 10 were removed. Also, fractions included in the Tweets which were mistakenly identified as ratings were removed during data wrangling.</p>
<p>Visualizing data for the first three topics did rely on wrangling to a certain degree. However, creating plots for the last topic benefited most from the results of the wrangling phase. If the non-variable column headers in the original image predictions data were not tidied, then plotting a histogram of the confidence levels for each level of prediction would have been cumbersome in that three different columns of confidence levels instead of the single <code>confidence</code> column need to be provided as the values for the x-axis. Also, the mean proportion of predictions with dog breeds could not have been computed by iterating through the single <code>dog_breed</code> column without the tidy data.</p>
<p>As mentioned in <strong>Part 1: Data Wrangling</strong>, the gathering, assessing, and cleaning the data defines a bulk of the overall data analysis process. However, unlike the previous part, which supported this statement by demonstrating the exhaustive nature of data wrangling, exploring and engineering the data during exploratory data analysis and data visualization demonstrated the importance of data wrangling by building on the cleaned datasets to organize and arrange data in ways which streamline the discovery of insights from data and presentation of meaningful patterns/trends. Finding insights by performing these tasks on raw data would have been significantly inefficient and futile if at all possible.</p>

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