eda-facebook-users-by-country-data-cleaned.ipynb

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     "text": [
      "/kaggle/input/facebook-users-by-country-data-cleaned/data.csv\n"
     ]
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   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
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    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df=pd.read_csv(\"/kaggle/input/facebook-users-by-country-data-cleaned/data.csv\")"
   ]
  },
  {
   "cell_type": "code",
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    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Users</th>\n",
       "      <th>Facebook_Users%</th>\n",
       "      <th>Date_of_Data</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>India</td>\n",
       "      <td>416.6M</td>\n",
       "      <td>29.16%</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>1,428,627,663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>240M</td>\n",
       "      <td>70.59%</td>\n",
       "      <td>2020-12</td>\n",
       "      <td>339,996,563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>176.5M</td>\n",
       "      <td>63.6%</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>277,534,122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>139M</td>\n",
       "      <td>64.23%</td>\n",
       "      <td>2020-12</td>\n",
       "      <td>216,422,446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>91M</td>\n",
       "      <td>77.55%</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>117,337,368</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Name   Users Facebook_Users% Date_of_Data     Population\n",
       "0          India  416.6M          29.16%      2021-06  1,428,627,663\n",
       "1  United States    240M          70.59%      2020-12    339,996,563\n",
       "2      Indonesia  176.5M           63.6%      2021-06    277,534,122\n",
       "3         Brazil    139M          64.23%      2020-12    216,422,446\n",
       "4    Philippines     91M          77.55%      2021-06    117,337,368"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "df.head()"
   ]
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    {
     "data": {
      "text/plain": [
       "(226, 5)"
      ]
     },
     "execution_count": 4,
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   ],
   "source": [
    "df.shape"
   ]
  },
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name               0\n",
       "Users              0\n",
       "Facebook_Users%    0\n",
       "Date_of_Data       0\n",
       "Population         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
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    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
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   "id": "3249978d",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name               object\n",
       "Users              object\n",
       "Facebook_Users%    object\n",
       "Date_of_Data       object\n",
       "Population         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4a745dcf",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "# Population dtype need to be changed\n",
    "df['Population'] = df['Population'].str.replace(',','')\n",
    "df['Population'] = df['Population'].astype('float64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0c8b0ca8",
   "metadata": {
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   "outputs": [],
   "source": [
    "# Changing Users count to numeric\n",
    "def convert_to_numeric(value):\n",
    "    if 'M' in value:\n",
    "        N_value=value.replace(\"M\",\"\")\n",
    "        N_value = pd.to_numeric(N_value)\n",
    "        return float(N_value*1000000)\n",
    "    elif 'K' in value:\n",
    "        N_value=value.replace(\"K\",\"\")\n",
    "        N_value = pd.to_numeric(N_value)\n",
    "        return float(N_value*1000)\n",
    "    else:\n",
    "        return float(value)\n",
    "    \n",
    "df['Users'] = df['Users'].apply(lambda x: convert_to_numeric(x))    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e78e19cd",
   "metadata": {
    "execution": {
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    },
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   },
   "outputs": [],
   "source": [
    "# Changing user percentage to numeric\n",
    "df['Facebook_Users%'] = df['Facebook_Users%'].str.replace('%','')\n",
    "df['Facebook_Users%'] = df['Facebook_Users%'].astype('float').round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "df41da6f",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    416600000.0\n",
       "1    240000000.0\n",
       "2    176500000.0\n",
       "3    139000000.0\n",
       "4     91000000.0\n",
       "Name: Users, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Users\"].head()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 11,
   "id": "b056c966",
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    {
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       "226"
      ]
     },
     "execution_count": 11,
     "metadata": {},
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   ],
   "source": [
    "df[\"Name\"].nunique()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 12,
   "id": "0962630d",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(226,)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
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    }
   ],
   "source": [
    "df[\"Name\"].unique().shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "58d1d950",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-06T10:59:01.257131Z",
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    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Top Country by Facebook_User%\n",
    "top_users_per = df.nlargest(10,'Facebook_Users%')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "45a5b191",
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   "outputs": [
    {
     "data": {
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Users</th>\n",
       "      <th>Facebook_Users%</th>\n",
       "      <th>Date_of_Data</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>Vatican City</td>\n",
       "      <td>799.0</td>\n",
       "      <td>154.25</td>\n",
       "      <td>2020-12</td>\n",
       "      <td>518.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>10300000.0</td>\n",
       "      <td>108.40</td>\n",
       "      <td>2021-03</td>\n",
       "      <td>9516871.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>2900000.0</td>\n",
       "      <td>108.05</td>\n",
       "      <td>2021-03</td>\n",
       "      <td>2716391.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Brunei</td>\n",
       "      <td>461600.0</td>\n",
       "      <td>102.01</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>452524.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>100.70</td>\n",
       "      <td>2021-03</td>\n",
       "      <td>1485509.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>4200000.0</td>\n",
       "      <td>98.07</td>\n",
       "      <td>2021-03</td>\n",
       "      <td>4310108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Guam</td>\n",
       "      <td>149500.0</td>\n",
       "      <td>86.44</td>\n",
       "      <td>2020-12</td>\n",
       "      <td>172952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>3200000.0</td>\n",
       "      <td>86.42</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>3728282.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Taiwan</td>\n",
       "      <td>20600000.0</td>\n",
       "      <td>86.15</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>23923276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>91000.0</td>\n",
       "      <td>85.63</td>\n",
       "      <td>2020-12</td>\n",
       "      <td>106277.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Name       Users  Facebook_Users% Date_of_Data  \\\n",
       "224          Vatican City       799.0           154.25      2020-12   \n",
       "44   United Arab Emirates  10300000.0           108.40      2021-03   \n",
       "96                  Qatar   2900000.0           108.05      2021-03   \n",
       "146                Brunei    461600.0           102.01      2021-06   \n",
       "116               Bahrain   1500000.0           100.70      2021-03   \n",
       "72                 Kuwait   4200000.0            98.07      2021-03   \n",
       "170                  Guam    149500.0            86.44      2020-12   \n",
       "90                Georgia   3200000.0            86.42      2021-06   \n",
       "30                 Taiwan  20600000.0            86.15      2021-06   \n",
       "181                 Aruba     91000.0            85.63      2020-12   \n",
       "\n",
       "     Population  \n",
       "224       518.0  \n",
       "44    9516871.0  \n",
       "96    2716391.0  \n",
       "146    452524.0  \n",
       "116   1485509.0  \n",
       "72    4310108.0  \n",
       "170    172952.0  \n",
       "90    3728282.0  \n",
       "30   23923276.0  \n",
       "181    106277.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_users_per"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2cc59e57",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-06T10:59:01.317959Z",
     "iopub.status.busy": "2023-04-06T10:59:01.317528Z",
     "iopub.status.idle": "2023-04-06T10:59:02.804986Z",
     "shell.execute_reply": "2023-04-06T10:59:02.803733Z"
    },
    "papermill": {
     "duration": 1.498443,
     "end_time": "2023-04-06T10:59:02.807763",
     "exception": false,
     "start_time": "2023-04-06T10:59:01.309320",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Name'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ploting top 10\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "top_users_per1=top_users_per.set_index(\"Name\")\n",
    "top_users_per1[\"Facebook_Users%\"].plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2ca26588",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-06T10:59:02.824384Z",
     "iopub.status.busy": "2023-04-06T10:59:02.823963Z",
     "iopub.status.idle": "2023-04-06T10:59:03.143245Z",
     "shell.execute_reply": "2023-04-06T10:59:03.142126Z"
    },
    "papermill": {
     "duration": 0.331041,
     "end_time": "2023-04-06T10:59:03.146247",
     "exception": false,
     "start_time": "2023-04-06T10:59:02.815206",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Name'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Population by Users of TOP 10(Facebook_Users%)\n",
    "top_users_per.plot(y=['Population','Users'], x= 'Name', kind = 'bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a5864c38",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-06T10:59:03.164479Z",
     "iopub.status.busy": "2023-04-06T10:59:03.163695Z",
     "iopub.status.idle": "2023-04-06T10:59:03.171655Z",
     "shell.execute_reply": "2023-04-06T10:59:03.170504Z"
    },
    "papermill": {
     "duration": 0.019536,
     "end_time": "2023-04-06T10:59:03.174032",
     "exception": false,
     "start_time": "2023-04-06T10:59:03.154496",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "top_users = df.nlargest(10,'Users')\n",
    "top_users1=top_users.set_index(\"Name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "303a65a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-06T10:59:03.191597Z",
     "iopub.status.busy": "2023-04-06T10:59:03.191184Z",
     "iopub.status.idle": "2023-04-06T10:59:03.390659Z",
     "shell.execute_reply": "2023-04-06T10:59:03.388844Z"
    },
    "papermill": {
     "duration": 0.213929,
     "end_time": "2023-04-06T10:59:03.395786",
     "exception": false,
     "start_time": "2023-04-06T10:59:03.181857",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Users'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Users Partition of TOP 10(Users)\n",
    "top_users1[\"Users\"].plot(kind=\"pie\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "5f9c7ae1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-06T10:59:03.435136Z",
     "iopub.status.busy": "2023-04-06T10:59:03.434749Z",
     "iopub.status.idle": "2023-04-06T10:59:03.763331Z",
     "shell.execute_reply": "2023-04-06T10:59:03.761977Z"
    },
    "papermill": {
     "duration": 0.348627,
     "end_time": "2023-04-06T10:59:03.766213",
     "exception": false,
     "start_time": "2023-04-06T10:59:03.417586",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Name'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Population by Users of TOP 10(Users)\n",
    "top_users.plot(y=['Population','Users'], x= 'Name', kind = 'bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab3057bf",
   "metadata": {
    "papermill": {
     "duration": 0.008939,
     "end_time": "2023-04-06T10:59:03.784557",
     "exception": false,
     "start_time": "2023-04-06T10:59:03.775618",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# UPVOTE IF YOU FIND IT USEFUL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d46000f",
   "metadata": {
    "papermill": {
     "duration": 0.009399,
     "end_time": "2023-04-06T10:59:03.803357",
     "exception": false,
     "start_time": "2023-04-06T10:59:03.793958",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a467d8d7",
   "metadata": {
    "papermill": {
     "duration": 0.009427,
     "end_time": "2023-04-06T10:59:03.822012",
     "exception": false,
     "start_time": "2023-04-06T10:59:03.812585",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 13.669323,
   "end_time": "2023-04-06T10:59:04.553284",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-04-06T10:58:50.883961",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}