Copy of Final Code with Box plot.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"accelerator":"GPU","colab":{"name":"Copy of final_1 w/ final comparison graph.ipynb","provenance":[{"file_id":"1_DCUVoJg2LZ3L1OmIvoJS6bbcXEtvhqg","timestamp":1588486822153},{"file_id":"1AOe20QAf-ufpBw_Ix5JASTdnUyZJKtTJ","timestamp":1588415149717}],"collapsed_sections":[]},"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":"3.7.4"}},"cells":[{"cell_type":"markdown","metadata":{"colab_type":"text","id":"YviLqh8Y8qn-"},"source":["# Stock Price Prediction Supervised Learning\n"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"B0YFSGdxqnal","colab":{"base_uri":"https://localhost:8080/","height":121},"executionInfo":{"status":"ok","timestamp":1596201387610,"user_tz":-330,"elapsed":44565,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"a07e7e0c-d8e0-47e0-d407-5d7e192d56d4"},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n","\n","Enter your authorization code:\n","··········\n","Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"jsZwEpB3qh1y"},"source":["### Importing libraries"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"5R5WdATi8qoF","colab":{},"executionInfo":{"status":"ok","timestamp":1596201462694,"user_tz":-330,"elapsed":909,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}}},"source":["import pandas as pd\n","import numpy as np\n","\n","import math,datetime\n","import time\n","\n","import matplotlib.pyplot as plt\n","from matplotlib import style\n","\n","from sklearn.metrics import accuracy_score\n","from sklearn.linear_model import LinearRegression\n","from sklearn.tree import DecisionTreeRegressor\n","from sklearn.neighbors import KNeighborsRegressor\n","from sklearn import model_selection\n","from sklearn.model_selection import train_test_split\n","\n","\n","#style.use ('ggplot')"],"execution_count":11,"outputs":[]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"2X4bOIWV8qoT"},"source":["### Loading Dataset"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"PrGeA-ux8qoV","colab":{},"executionInfo":{"status":"ok","timestamp":1596201464000,"user_tz":-330,"elapsed":836,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}}},"source":["df = pd.read_csv('/content/drive/My Drive/Colab Notebooks/Stock prediction project/GOOG2.csv',index_col='Date',parse_dates=True)"],"execution_count":12,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"Hfk79UbG8qof","scrolled":true,"colab":{"base_uri":"https://localhost:8080/","height":134},"executionInfo":{"status":"ok","timestamp":1596201464534,"user_tz":-330,"elapsed":932,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"605761fe-bafc-4fb9-c7fb-79f55c3f4756"},"source":["print(df.head())"],"execution_count":13,"outputs":[{"output_type":"stream","text":["                 Open       High        Low      Close  Adj Close    Volume\n","Date                                                                       \n","2004-08-19  49.813286  51.835709  47.800831  49.982655  49.982655  44871300\n","2004-08-20  50.316402  54.336334  50.062355  53.952770  53.952770  22942800\n","2004-08-23  55.168217  56.528118  54.321388  54.495735  54.495735  18342800\n","2004-08-24  55.412300  55.591629  51.591621  52.239193  52.239193  15319700\n","2004-08-25  52.284027  53.798351  51.746044  52.802086  52.802086   9232100\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"BjOhEGI28qoo","colab":{"base_uri":"https://localhost:8080/","height":431},"executionInfo":{"status":"ok","timestamp":1596201464890,"user_tz":-330,"elapsed":896,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"dd9f1e78-1ddc-4851-9bb7-268bfaaeab20"},"source":["df.drop(['Adj Close'], axis=1)"],"execution_count":14,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\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>Open</th>\n","      <th>High</th>\n","      <th>Low</th>\n","      <th>Close</th>\n","      <th>Volume</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2004-08-19</th>\n","      <td>49.813286</td>\n","      <td>51.835709</td>\n","      <td>47.800831</td>\n","      <td>49.982655</td>\n","      <td>44871300</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-20</th>\n","      <td>50.316402</td>\n","      <td>54.336334</td>\n","      <td>50.062355</td>\n","      <td>53.952770</td>\n","      <td>22942800</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-23</th>\n","      <td>55.168217</td>\n","      <td>56.528118</td>\n","      <td>54.321388</td>\n","      <td>54.495735</td>\n","      <td>18342800</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-24</th>\n","      <td>55.412300</td>\n","      <td>55.591629</td>\n","      <td>51.591621</td>\n","      <td>52.239193</td>\n","      <td>15319700</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-25</th>\n","      <td>52.284027</td>\n","      <td>53.798351</td>\n","      <td>51.746044</td>\n","      <td>52.802086</td>\n","      <td>9232100</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-22</th>\n","      <td>1245.540039</td>\n","      <td>1285.613037</td>\n","      <td>1242.000000</td>\n","      <td>1263.209961</td>\n","      <td>2093100</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-23</th>\n","      <td>1271.550049</td>\n","      <td>1293.310059</td>\n","      <td>1265.670044</td>\n","      <td>1276.310059</td>\n","      <td>1566200</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-24</th>\n","      <td>1261.170044</td>\n","      <td>1280.400024</td>\n","      <td>1249.449951</td>\n","      <td>1279.310059</td>\n","      <td>1640400</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-27</th>\n","      <td>1296.000000</td>\n","      <td>1296.150024</td>\n","      <td>1269.000000</td>\n","      <td>1275.880005</td>\n","      <td>1600600</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-28</th>\n","      <td>1287.930054</td>\n","      <td>1288.050049</td>\n","      <td>1232.199951</td>\n","      <td>1233.670044</td>\n","      <td>2898600</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3950 rows × 5 columns</p>\n","</div>"],"text/plain":["                   Open         High          Low        Close    Volume\n","Date                                                                    \n","2004-08-19    49.813286    51.835709    47.800831    49.982655  44871300\n","2004-08-20    50.316402    54.336334    50.062355    53.952770  22942800\n","2004-08-23    55.168217    56.528118    54.321388    54.495735  18342800\n","2004-08-24    55.412300    55.591629    51.591621    52.239193  15319700\n","2004-08-25    52.284027    53.798351    51.746044    52.802086   9232100\n","...                 ...          ...          ...          ...       ...\n","2020-04-22  1245.540039  1285.613037  1242.000000  1263.209961   2093100\n","2020-04-23  1271.550049  1293.310059  1265.670044  1276.310059   1566200\n","2020-04-24  1261.170044  1280.400024  1249.449951  1279.310059   1640400\n","2020-04-27  1296.000000  1296.150024  1269.000000  1275.880005   1600600\n","2020-04-28  1287.930054  1288.050049  1232.199951  1233.670044   2898600\n","\n","[3950 rows x 5 columns]"]},"metadata":{"tags":[]},"execution_count":14}]},{"cell_type":"code","metadata":{"id":"n7iPz_fsasWR","colab_type":"code","colab":{},"executionInfo":{"status":"ok","timestamp":1596201465555,"user_tz":-330,"elapsed":1213,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}}},"source":["#!pip3 install --upgrade pandas"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"iOI8a0So8qov","colab":{"base_uri":"https://localhost:8080/","height":476},"executionInfo":{"status":"ok","timestamp":1596201528274,"user_tz":-330,"elapsed":1890,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"5d34826d-e24b-4405-c677-4675b5eb8c16"},"source":["pd.__version__\n","\n","# plt.style.use('classic')\n","\n","ax = df.plot(kind = 'box', subplots = True, layout = (1,6), sharex = False, sharey = False , title=\"Spread of Various Features\", figsize=(17,7), grid=True, color= \"blue\")\n","#ax = df.plot(kind = 'box', subplots = True, layout = (1,6), sharex = False, sharey = False ,figsize=(15,7), grid=True)\n","\n"],"execution_count":18,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1224x504 with 6 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"sWTFW0aEE0J0","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":511},"executionInfo":{"status":"ok","timestamp":1596194388323,"user_tz":-330,"elapsed":7156,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"d8556413-1ac3-4d39-8009-ce958f04fd43"},"source":["import matplotlib.pyplot as plt\n","df.boxplot(figsize=(15,7))\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1200x560 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"3wHiUk8z0ZmV","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":666},"executionInfo":{"status":"error","timestamp":1596194389047,"user_tz":-330,"elapsed":7713,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"4dc02fee-1c89-4e42-c73c-0d18e2887542"},"source":["import matplotlib.pyplot as plt\n","import numpy as np\n","\n","\n","labels = ['Open', 'High', 'Low', 'Close', 'Volume']\n","\n","fig, axes = plt.subplots(nrows=1, ncols=6, figsize=(9, 4))\n","\n","# rectangular box plot\n","bplot1 = axes[0].boxplot(df,\n","                         vert=True,  # vertical box alignment\n","                         patch_artist=True,  # fill with color\n","                         labels=labels)  # will be used to label x-ticks\n","axes[0].set_title('Rectangular box plot')\n","\n","\n","# fill with colors\n","colors = ['pink', 'lightblue', 'lightgreen']\n","for bplot in (bplot1, bplot2):\n","    for patch, color in zip(bplot['boxes'], colors):\n","        patch.set_facecolor(color)\n","\n","# adding horizontal grid lines\n","for ax in axes:\n","    ax.yaxis.grid(True)\n","    ax.set_xlabel('Three separate samples')\n","    ax.set_ylabel('Observed values')\n"],"execution_count":null,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)","\u001b[0;32m<ipython-input-36-1acd8014604a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     11\u001b[0m                          \u001b[0mvert\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# vertical box alignment\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m                          \u001b[0mpatch_artist\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# fill with color\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m                          labels=labels)  # will be used to label x-ticks\n\u001b[0m\u001b[1;32m     14\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_title\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Rectangular box plot'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/cbook/deprecation.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    294\u001b[0m                 f\"for the old name will be dropped %(removal)s.\")\n\u001b[1;32m    295\u001b[0m             \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnew\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 296\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    297\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    298\u001b[0m     \u001b[0;31m# wrapper() must keep the same documented signature as func(): if we\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1563\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1564\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1565\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1566\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1567\u001b[0m         \u001b[0mbound\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mboxplot\u001b[0;34m(self, x, notch, sym, vert, whis, positions, widths, patch_artist, bootstrap, usermedians, conf_intervals, meanline, showmeans, showcaps, showbox, showfliers, boxprops, labels, flierprops, medianprops, meanprops, capprops, whiskerprops, manage_ticks, autorange, zorder)\u001b[0m\n\u001b[1;32m   3626\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3627\u001b[0m         bxpstats = cbook.boxplot_stats(x, whis=whis, bootstrap=bootstrap,\n\u001b[0;32m-> 3628\u001b[0;31m                                        labels=labels, autorange=autorange)\n\u001b[0m\u001b[1;32m   3629\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mnotch\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3630\u001b[0m             \u001b[0mnotch\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrcParams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'boxplot.notch'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/cbook/__init__.py\u001b[0m in \u001b[0;36mboxplot_stats\u001b[0;34m(X, whis, bootstrap, labels, autorange)\u001b[0m\n\u001b[1;32m   1169\u001b[0m         \u001b[0mlabels\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mitertools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1170\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mncols\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1171\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Dimensions of labels and X must be compatible\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1172\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1173\u001b[0m     \u001b[0minput_whis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwhis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Dimensions of labels and X must be compatible"]},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x320 with 6 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"yIF_ZFxA8qoz","colab":{}},"source":["df.hist(figsize = (10,10))"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"io2mw2k9qQwH","colab_type":"code","colab":{}},"source":["'''#Skewness before and after applying Log transformation\n","print(df['Close'].skew())\n","Cskew = np.log(df['Close'])\n","print(Cskew.skew())\n","\n","print(df['Volume'].skew())\n","vskew = np.log(df['Volume'])\n","print(vskew.skew())\n","'''"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"DPmxI2Nm8qo4","colab":{}},"source":["# Percentage change in Open and Close Price \n","df['OC_Change'] = (df['Close']-df['Open'])/df['Open']*100"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"FD4EaR_y8qo-","colab":{}},"source":["# Percentage change in High and Low Price \n","df['HL_Change'] = (df['High']-df['Low'])/df['Low']*100"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"T2ji-0PZ8qpB","colab":{}},"source":["df = df[['Close','HL_Change','OC_Change','Volume']]"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"kn6KSC0B8qpE","colab":{}},"source":["print(df.tail()) "],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"2jRt4Yn9FX2R","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":840},"executionInfo":{"status":"ok","timestamp":1596178594977,"user_tz":-330,"elapsed":3118,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"bb8b178d-35e0-421a-aed4-d2f05c2b51ba"},"source":["Close1 = df['Close'][-41:-1]\n","print(Close1)\n","len(Close1)\n","Close2 = Close1.to_numpy()\n","print(Close2)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Date\n","2020-03-02    1389.109985\n","2020-03-03    1341.390015\n","2020-03-04    1386.520020\n","2020-03-05    1319.040039\n","2020-03-06    1298.410034\n","2020-03-09    1215.560059\n","2020-03-10    1280.390015\n","2020-03-11    1215.410034\n","2020-03-12    1114.910034\n","2020-03-13    1219.729980\n","2020-03-16    1084.329956\n","2020-03-17    1119.800049\n","2020-03-18    1096.800049\n","2020-03-19    1115.290039\n","2020-03-20    1072.319946\n","2020-03-23    1056.619995\n","2020-03-24    1134.459961\n","2020-03-25    1102.489990\n","2020-03-26    1161.750000\n","2020-03-27    1110.709961\n","2020-03-30    1146.819946\n","2020-03-31    1162.810059\n","2020-04-01    1105.619995\n","2020-04-02    1120.839966\n","2020-04-03    1097.880005\n","2020-04-06    1186.920044\n","2020-04-07    1186.510010\n","2020-04-08    1210.280029\n","2020-04-09    1211.449951\n","2020-04-13    1217.560059\n","2020-04-14    1269.229980\n","2020-04-15    1262.469971\n","2020-04-16    1263.469971\n","2020-04-17    1283.250000\n","2020-04-20    1266.609985\n","2020-04-21    1216.339966\n","2020-04-22    1263.209961\n","2020-04-23    1276.310059\n","2020-04-24    1279.310059\n","2020-04-27    1275.880005\n","Name: Close, dtype: float64\n","[1389.109985 1341.390015 1386.52002  1319.040039 1298.410034 1215.560059\n"," 1280.390015 1215.410034 1114.910034 1219.72998  1084.329956 1119.800049\n"," 1096.800049 1115.290039 1072.319946 1056.619995 1134.459961 1102.48999\n"," 1161.75     1110.709961 1146.819946 1162.810059 1105.619995 1120.839966\n"," 1097.880005 1186.920044 1186.51001  1210.280029 1211.449951 1217.560059\n"," 1269.22998  1262.469971 1263.469971 1283.25     1266.609985 1216.339966\n"," 1263.209961 1276.310059 1279.310059 1275.880005]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"WK7vMISq8qpH"},"source":["### Features & Labels"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"rox_2FQu8qpH","colab":{"base_uri":"https://localhost:8080/","height":336},"executionInfo":{"status":"ok","timestamp":1596178594978,"user_tz":-330,"elapsed":2727,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"5b2f7f71-bc3b-4ecc-f5d3-687e8a29058f"},"source":["forecast_Col = 'Close'\n","forecast_out = int(math.ceil(0.01*len(df)))\n","df['label'] = df[forecast_Col].shift(-forecast_out)\n","print(df['label'])"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Date\n","2004-08-19    71.785927\n","2004-08-20    74.301498\n","2004-08-23    73.693779\n","2004-08-24    69.982689\n","2004-08-25    74.411087\n","                ...    \n","2020-04-22          NaN\n","2020-04-23          NaN\n","2020-04-24          NaN\n","2020-04-27          NaN\n","2020-04-28          NaN\n","Name: label, Length: 3950, dtype: float64\n"],"name":"stdout"},{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  This is separate from the ipykernel package so we can avoid doing imports until\n"],"name":"stderr"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"j5C_Kphe8qpL","colab":{"base_uri":"https://localhost:8080/","height":225},"executionInfo":{"status":"ok","timestamp":1596178594979,"user_tz":-330,"elapsed":2644,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"8cec61e6-7bb7-4c47-e6b4-ee83c01ce121"},"source":["df.tail()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\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>Close</th>\n","      <th>HL_Change</th>\n","      <th>OC_Change</th>\n","      <th>Volume</th>\n","      <th>label</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2020-04-22</th>\n","      <td>1263.209961</td>\n","      <td>3.511517</td>\n","      <td>1.418655</td>\n","      <td>2093100</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-23</th>\n","      <td>1276.310059</td>\n","      <td>2.183825</td>\n","      <td>0.374347</td>\n","      <td>1566200</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-24</th>\n","      <td>1279.310059</td>\n","      <td>2.477096</td>\n","      <td>1.438348</td>\n","      <td>1640400</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-27</th>\n","      <td>1275.880005</td>\n","      <td>2.139482</td>\n","      <td>-1.552469</td>\n","      <td>1600600</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-28</th>\n","      <td>1233.670044</td>\n","      <td>4.532552</td>\n","      <td>-4.212962</td>\n","      <td>2898600</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                  Close  HL_Change  OC_Change   Volume  label\n","Date                                                         \n","2020-04-22  1263.209961   3.511517   1.418655  2093100    NaN\n","2020-04-23  1276.310059   2.183825   0.374347  1566200    NaN\n","2020-04-24  1279.310059   2.477096   1.438348  1640400    NaN\n","2020-04-27  1275.880005   2.139482  -1.552469  1600600    NaN\n","2020-04-28  1233.670044   4.532552  -4.212962  2898600    NaN"]},"metadata":{"tags":[]},"execution_count":18}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"a78KxVpL8qpN","colab":{"base_uri":"https://localhost:8080/","height":309},"executionInfo":{"status":"ok","timestamp":1596178594980,"user_tz":-330,"elapsed":2449,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"87b20891-3093-48dd-8117-75e40d6c98da"},"source":["df.dropna(inplace=True)\n","df.tail()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  \"\"\"Entry point for launching an IPython kernel.\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\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>Close</th>\n","      <th>HL_Change</th>\n","      <th>OC_Change</th>\n","      <th>Volume</th>\n","      <th>label</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2020-02-25</th>\n","      <td>1388.449951</td>\n","      <td>4.032117</td>\n","      <td>-3.108866</td>\n","      <td>2478300</td>\n","      <td>1263.209961</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-26</th>\n","      <td>1393.180054</td>\n","      <td>2.661345</td>\n","      <td>-0.212010</td>\n","      <td>2202400</td>\n","      <td>1276.310059</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-27</th>\n","      <td>1318.089966</td>\n","      <td>4.140235</td>\n","      <td>-3.228205</td>\n","      <td>2978300</td>\n","      <td>1279.310059</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-28</th>\n","      <td>1339.329956</td>\n","      <td>5.518491</td>\n","      <td>4.839918</td>\n","      <td>3790600</td>\n","      <td>1275.880005</td>\n","    </tr>\n","    <tr>\n","      <th>2020-03-02</th>\n","      <td>1389.109985</td>\n","      <td>4.827731</td>\n","      <td>2.774469</td>\n","      <td>2431500</td>\n","      <td>1233.670044</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                  Close  HL_Change  OC_Change   Volume        label\n","Date                                                               \n","2020-02-25  1388.449951   4.032117  -3.108866  2478300  1263.209961\n","2020-02-26  1393.180054   2.661345  -0.212010  2202400  1276.310059\n","2020-02-27  1318.089966   4.140235  -3.228205  2978300  1279.310059\n","2020-02-28  1339.329956   5.518491   4.839918  3790600  1275.880005\n","2020-03-02  1389.109985   4.827731   2.774469  2431500  1233.670044"]},"metadata":{"tags":[]},"execution_count":19}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"eLF8ItFA8qpQ"},"source":["### Data Splitting"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"SmCsLzdC8qpQ","colab":{}},"source":["X  =  np.array(df.drop(['label'], axis = 1))\n","Y  =  np.array(df['label'])"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"pxt6oBJu8qpS","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178594981,"user_tz":-330,"elapsed":1940,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"9545d383-a3b5-409d-f9d3-e1b52c608174"},"source":["print(len(X),len(Y))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["3910 3910\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"C9p1SOZB8qpU","colab":{}},"source":["X_train, X_test, Y_train, Y_test = model_selection.train_test_split(X,Y,test_size = 0.2)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"5EOaW4QYwcmh","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178594982,"user_tz":-330,"elapsed":1645,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"17cb2611-1a27-4ce0-8381-5dbab5b96df8"},"source":["a = np.shape(X_train)\n","b = np.shape(Y_train)\n","c = np.shape(X_test)\n","d = np.shape(Y_test)\n","print(a,b,c,d)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["(3128, 4) (3128,) (782, 4) (782,)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"UQWLp9yi8qpX"},"source":["\n","# Linear Regression"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"PhQsj3dX8qpZ","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178596205,"user_tz":-330,"elapsed":2452,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"41abd291-a0d6-41de-e4f7-8b0a467e9a96"},"source":["startlr = time.time()\n","\n","lr = LinearRegression()\n","lr.fit(X_train,Y_train)\n","\n","endlr = time.time()\n","\n","time_lr = endlr-startlr\n","\n","print('Training Time :- {}'.format(time_lr))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Training Time :- 0.032236576080322266\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"U_5WvByZ8qpb","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178596205,"user_tz":-330,"elapsed":2328,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"787c9d1d-b82e-4758-a575-e42d96bb4809"},"source":["accuracy = lr.score(X_test,Y_test)\n","print(accuracy)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["0.9741743358814743\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"L4A_fdIweQa1","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178596206,"user_tz":-330,"elapsed":2142,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"62b21ed5-faef-4819-856c-e1745ff61527"},"source":["len(Y_test)"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["782"]},"metadata":{"tags":[]},"execution_count":26}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"_12P_t1d8qpd","colab":{"base_uri":"https://localhost:8080/","height":151},"executionInfo":{"status":"ok","timestamp":1596178596207,"user_tz":-330,"elapsed":1934,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"eb32287e-75d4-4302-a817-2a34643872df"},"source":["X = X[:-forecast_out]\n","X_old = X[-forecast_out:]\n","\n","Forecast_set = lr.predict(X_old)\n","print(Forecast_set)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[1300.16649404 1299.65275272 1314.15126858 1318.65710631 1307.41766426\n"," 1306.49373768 1306.00123288 1317.94958332 1340.72764887 1327.88288919\n"," 1323.10848484 1309.9936782  1308.62273045 1302.87808689 1314.16569402\n"," 1321.30987832 1321.04496607 1313.57929358 1296.85179004 1302.05873571\n"," 1326.75267178 1335.48689171 1347.76397534 1349.85437897 1351.76482952\n"," 1352.94540536 1357.05469564 1355.04143515 1367.99955904 1361.91784396\n"," 1359.88540972 1363.10546616 1355.54490126 1356.37510667 1351.89939084\n"," 1367.10044154 1359.25084781 1343.44932567 1344.57458368 1372.43087793]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"8HFEVR8wfD93","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":890},"executionInfo":{"status":"ok","timestamp":1596178596208,"user_tz":-330,"elapsed":1793,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"571bbf41-b87c-422e-dbdd-1f33a097a318"},"source":["date= ['2020-03-03','2020-03-04','2020-03-05','2020-03-06','2020-03-09','2020-03-10','2020-03-11','2020-03-12','2020-03-13','2020-03-16',\n","       '2020-03-17','2020-03-18','2020-03-19','2020-03-20','2020-03-23','2020-03-24','2020-03-25','2020-03-26','2020-03-27','2020-03-30',\n","       '2020-03-31','2020-04-01','2020-04-02','2020-04-03','2020-04-06','2020-04-07','2020-04-08','2020-04-09','2020-04-13','2020-04-14',\n","       '2020-04-15','2020-04-16','2020-04-17','2020-04-20','2020-04-21','2020-04-22','2020-04-23','2020-04-24','2020-04-27','2020-04-28',]\n","cl = np.array(Close2)\n","pr = np.array(Forecast_set)\n","dataset11 = pd.DataFrame({'Date': date, 'Close': cl, 'Prediction': pr}, columns=['Date', 'Close', 'Prediction'])\n","print(dataset11)\n","print(dataset11.tail(10))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["          Date        Close   Prediction\n","0   2020-03-03  1389.109985  1300.166494\n","1   2020-03-04  1341.390015  1299.652753\n","2   2020-03-05  1386.520020  1314.151269\n","3   2020-03-06  1319.040039  1318.657106\n","4   2020-03-09  1298.410034  1307.417664\n","5   2020-03-10  1215.560059  1306.493738\n","6   2020-03-11  1280.390015  1306.001233\n","7   2020-03-12  1215.410034  1317.949583\n","8   2020-03-13  1114.910034  1340.727649\n","9   2020-03-16  1219.729980  1327.882889\n","10  2020-03-17  1084.329956  1323.108485\n","11  2020-03-18  1119.800049  1309.993678\n","12  2020-03-19  1096.800049  1308.622730\n","13  2020-03-20  1115.290039  1302.878087\n","14  2020-03-23  1072.319946  1314.165694\n","15  2020-03-24  1056.619995  1321.309878\n","16  2020-03-25  1134.459961  1321.044966\n","17  2020-03-26  1102.489990  1313.579294\n","18  2020-03-27  1161.750000  1296.851790\n","19  2020-03-30  1110.709961  1302.058736\n","20  2020-03-31  1146.819946  1326.752672\n","21  2020-04-01  1162.810059  1335.486892\n","22  2020-04-02  1105.619995  1347.763975\n","23  2020-04-03  1120.839966  1349.854379\n","24  2020-04-06  1097.880005  1351.764830\n","25  2020-04-07  1186.920044  1352.945405\n","26  2020-04-08  1186.510010  1357.054696\n","27  2020-04-09  1210.280029  1355.041435\n","28  2020-04-13  1211.449951  1367.999559\n","29  2020-04-14  1217.560059  1361.917844\n","30  2020-04-15  1269.229980  1359.885410\n","31  2020-04-16  1262.469971  1363.105466\n","32  2020-04-17  1263.469971  1355.544901\n","33  2020-04-20  1283.250000  1356.375107\n","34  2020-04-21  1266.609985  1351.899391\n","35  2020-04-22  1216.339966  1367.100442\n","36  2020-04-23  1263.209961  1359.250848\n","37  2020-04-24  1276.310059  1343.449326\n","38  2020-04-27  1279.310059  1344.574584\n","39  2020-04-28  1275.880005  1372.430878\n","          Date        Close   Prediction\n","30  2020-04-15  1269.229980  1359.885410\n","31  2020-04-16  1262.469971  1363.105466\n","32  2020-04-17  1263.469971  1355.544901\n","33  2020-04-20  1283.250000  1356.375107\n","34  2020-04-21  1266.609985  1351.899391\n","35  2020-04-22  1216.339966  1367.100442\n","36  2020-04-23  1263.209961  1359.250848\n","37  2020-04-24  1276.310059  1343.449326\n","38  2020-04-27  1279.310059  1344.574584\n","39  2020-04-28  1275.880005  1372.430878\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"RPaE0mim8qpf","colab":{"base_uri":"https://localhost:8080/","height":755},"executionInfo":{"status":"ok","timestamp":1596178596209,"user_tz":-330,"elapsed":1635,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"dfcc3e31-9ae4-4450-d4af-4e632dc8d1c2"},"source":["df['Forecast'] = np.nan\n","last_date = df.iloc[-1].name\n","last_unix = last_date.timestamp()\n","one_day = 86400\n","next_unix = last_unix + one_day\n","\n","for i in Forecast_set:\n","    next_date = datetime.datetime.fromtimestamp(next_unix)\n","    next_unix += one_day\n","    df.loc[next_date] = [np.nan for _ in range(len(df.columns) - 1)] + [i]\n","\n","df['Close'].plot(figsize = (15,10))\n","df['Forecast'].plot(figsize = (15,10))\n","plt.legend(loc=4)\n","plt.xlabel('Date')\n","plt.ylabel('Price')\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  \"\"\"Entry point for launching an IPython kernel.\n","/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py:671: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  self._setitem_with_indexer(indexer, value)\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x720 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"bH_KORKs8qph"},"source":["# Decision Tree"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"wwthjsd58qph","colab":{"base_uri":"https://localhost:8080/","height":50},"executionInfo":{"status":"ok","timestamp":1596178597131,"user_tz":-330,"elapsed":2275,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"2c7334e0-3f93-4422-ebad-129acc36d495"},"source":["startdt = time.time()\n","\n","tree = DecisionTreeRegressor( max_depth=5)\n","tree.fit(X_train, Y_train)\n","\n","enddt = time.time()\n","\n","time_dt = enddt-startdt\n","\n","print('Training Time :- {}'.format(time_dt))\n","\n","print('Accuracy:- {}'.format(tree.score(X_test, Y_test)))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Training Time :- 0.010231494903564453\n","Accuracy:- 0.9847205195196789\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"d_vVZmL38qpj","colab":{"base_uri":"https://localhost:8080/","height":151},"executionInfo":{"status":"ok","timestamp":1596178597133,"user_tz":-330,"elapsed":2049,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"06eb3915-7288-4d36-be23-3d099a0b9dad"},"source":["X = X[:-forecast_out]\n","X_old = X[-forecast_out:]\n","\n","Forecast_set = tree.predict(X_old)\n","print(Forecast_set)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[1170.35262617 1170.35262617 1170.35262617 1170.35262617 1170.35262617\n"," 1170.35262617 1170.35262617 1170.35262617 1114.83241711 1170.35262617\n"," 1170.35262617 1170.35262617 1170.35262617 1170.35262617 1170.35262617\n"," 1170.35262617 1170.35262617 1170.35262617 1170.35262617 1170.35262617\n"," 1170.35262617 1170.35262617 1170.35262617 1170.35262617 1170.35262617\n"," 1170.35262617 1170.35262617 1170.35262617 1170.35262617 1170.35262617\n"," 1170.35262617 1242.8599977  1242.8599977  1242.8599977  1412.92729551\n"," 1242.8599977  1242.8599977  1242.8599977  1242.8599977  1412.92729551]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"vMR6cG03SPyX","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":890},"executionInfo":{"status":"ok","timestamp":1596178597134,"user_tz":-330,"elapsed":1909,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"276e105a-2452-483a-9c2e-85af1bbdf01b"},"source":["date= ['2020-03-03','2020-03-04','2020-03-05','2020-03-06','2020-03-09','2020-03-10','2020-03-11','2020-03-12','2020-03-13','2020-03-16',\n","       '2020-03-17','2020-03-18','2020-03-19','2020-03-20','2020-03-23','2020-03-24','2020-03-25','2020-03-26','2020-03-27','2020-03-30',\n","       '2020-03-31','2020-04-01','2020-04-02','2020-04-03','2020-04-06','2020-04-07','2020-04-08','2020-04-09','2020-04-13','2020-04-14',\n","       '2020-04-15','2020-04-16','2020-04-17','2020-04-20','2020-04-21','2020-04-22','2020-04-23','2020-04-24','2020-04-27','2020-04-28',]\n","cl = np.array(Close2)\n","pr = np.array(Forecast_set)\n","dataset11 = pd.DataFrame({'Date': date, 'Close': cl, 'Prediction': pr}, columns=['Date', 'Close', 'Prediction'])\n","print(dataset11)\n","print(dataset11.tail(10))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["          Date        Close   Prediction\n","0   2020-03-03  1389.109985  1170.352626\n","1   2020-03-04  1341.390015  1170.352626\n","2   2020-03-05  1386.520020  1170.352626\n","3   2020-03-06  1319.040039  1170.352626\n","4   2020-03-09  1298.410034  1170.352626\n","5   2020-03-10  1215.560059  1170.352626\n","6   2020-03-11  1280.390015  1170.352626\n","7   2020-03-12  1215.410034  1170.352626\n","8   2020-03-13  1114.910034  1114.832417\n","9   2020-03-16  1219.729980  1170.352626\n","10  2020-03-17  1084.329956  1170.352626\n","11  2020-03-18  1119.800049  1170.352626\n","12  2020-03-19  1096.800049  1170.352626\n","13  2020-03-20  1115.290039  1170.352626\n","14  2020-03-23  1072.319946  1170.352626\n","15  2020-03-24  1056.619995  1170.352626\n","16  2020-03-25  1134.459961  1170.352626\n","17  2020-03-26  1102.489990  1170.352626\n","18  2020-03-27  1161.750000  1170.352626\n","19  2020-03-30  1110.709961  1170.352626\n","20  2020-03-31  1146.819946  1170.352626\n","21  2020-04-01  1162.810059  1170.352626\n","22  2020-04-02  1105.619995  1170.352626\n","23  2020-04-03  1120.839966  1170.352626\n","24  2020-04-06  1097.880005  1170.352626\n","25  2020-04-07  1186.920044  1170.352626\n","26  2020-04-08  1186.510010  1170.352626\n","27  2020-04-09  1210.280029  1170.352626\n","28  2020-04-13  1211.449951  1170.352626\n","29  2020-04-14  1217.560059  1170.352626\n","30  2020-04-15  1269.229980  1170.352626\n","31  2020-04-16  1262.469971  1242.859998\n","32  2020-04-17  1263.469971  1242.859998\n","33  2020-04-20  1283.250000  1242.859998\n","34  2020-04-21  1266.609985  1412.927296\n","35  2020-04-22  1216.339966  1242.859998\n","36  2020-04-23  1263.209961  1242.859998\n","37  2020-04-24  1276.310059  1242.859998\n","38  2020-04-27  1279.310059  1242.859998\n","39  2020-04-28  1275.880005  1412.927296\n","          Date        Close   Prediction\n","30  2020-04-15  1269.229980  1170.352626\n","31  2020-04-16  1262.469971  1242.859998\n","32  2020-04-17  1263.469971  1242.859998\n","33  2020-04-20  1283.250000  1242.859998\n","34  2020-04-21  1266.609985  1412.927296\n","35  2020-04-22  1216.339966  1242.859998\n","36  2020-04-23  1263.209961  1242.859998\n","37  2020-04-24  1276.310059  1242.859998\n","38  2020-04-27  1279.310059  1242.859998\n","39  2020-04-28  1275.880005  1412.927296\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"By0GkkA88qpl"},"source":["# K-NN"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"dpAkekxt8qpl","colab":{"base_uri":"https://localhost:8080/","height":50},"executionInfo":{"status":"ok","timestamp":1596178597793,"user_tz":-330,"elapsed":2214,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"9ed96ec1-68c3-4498-cd22-9ef55988f7e5"},"source":["startknn = time.time()\n","\n","knn = KNeighborsRegressor(13)\n","knn.fit(X_train, Y_train)\n","\n","endknn = time.time()\n","\n","time_knn = endknn - startknn\n","\n","print('Training Time:- {}'.format(time_knn))\n","print('Accuracy:- {}'.format(knn.score(X_test, Y_test)))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Training Time:- 0.0061588287353515625\n","Accuracy:- 0.7018631905850572\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"GL5hDfha8qpn","colab":{"base_uri":"https://localhost:8080/","height":151},"executionInfo":{"status":"ok","timestamp":1596178597794,"user_tz":-330,"elapsed":2024,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"747b78ea-0a99-4d5f-df38-fb7cf6e97fe3"},"source":["X = X[:-forecast_out]\n","X_old = X[-forecast_out:]\n","\n","Forecast_set = knn.predict(X_old)\n","print(Forecast_set)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[1072.79926708 1000.47821062 1007.06922792  930.85312369  791.22398023\n","  843.29076215 1172.95845854  872.55922285  796.89306646  371.96081638\n","  675.07637146  849.51882708  881.56656123  819.33066969  791.22398023\n","  676.22585354  750.38516008  916.88627738  963.78598731  983.62302354\n"," 1102.27907623  954.60477862  874.46823362  854.78322662  961.53520323\n","  947.06512931 1022.64542092  985.56055146 1042.40000562  691.71768185\n","  907.99750223 1076.24537538 1036.82567877 1090.50455892  932.29642646\n","  860.47555769 1001.76301931  983.52000077 1051.06307746  886.16368223]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"Ef06dGOESYGb","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":890},"executionInfo":{"status":"ok","timestamp":1596178597795,"user_tz":-330,"elapsed":1894,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"d61ab1c6-d22e-454d-b935-da48c6448da9"},"source":["date= ['2020-03-03','2020-03-04','2020-03-05','2020-03-06','2020-03-09','2020-03-10','2020-03-11','2020-03-12','2020-03-13','2020-03-16',\n","       '2020-03-17','2020-03-18','2020-03-19','2020-03-20','2020-03-23','2020-03-24','2020-03-25','2020-03-26','2020-03-27','2020-03-30',\n","       '2020-03-31','2020-04-01','2020-04-02','2020-04-03','2020-04-06','2020-04-07','2020-04-08','2020-04-09','2020-04-13','2020-04-14',\n","       '2020-04-15','2020-04-16','2020-04-17','2020-04-20','2020-04-21','2020-04-22','2020-04-23','2020-04-24','2020-04-27','2020-04-28']\n","\n","cl = np.array(Close2)\n","pr = np.array(Forecast_set)\n","dataset11 = pd.DataFrame({'Date': date, 'Close': cl, 'Prediction': pr}, columns=['Date', 'Close', 'Prediction'])\n","print(dataset11)\n","print(dataset11.tail(10))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["          Date        Close   Prediction\n","0   2020-03-03  1389.109985  1072.799267\n","1   2020-03-04  1341.390015  1000.478211\n","2   2020-03-05  1386.520020  1007.069228\n","3   2020-03-06  1319.040039   930.853124\n","4   2020-03-09  1298.410034   791.223980\n","5   2020-03-10  1215.560059   843.290762\n","6   2020-03-11  1280.390015  1172.958459\n","7   2020-03-12  1215.410034   872.559223\n","8   2020-03-13  1114.910034   796.893066\n","9   2020-03-16  1219.729980   371.960816\n","10  2020-03-17  1084.329956   675.076371\n","11  2020-03-18  1119.800049   849.518827\n","12  2020-03-19  1096.800049   881.566561\n","13  2020-03-20  1115.290039   819.330670\n","14  2020-03-23  1072.319946   791.223980\n","15  2020-03-24  1056.619995   676.225854\n","16  2020-03-25  1134.459961   750.385160\n","17  2020-03-26  1102.489990   916.886277\n","18  2020-03-27  1161.750000   963.785987\n","19  2020-03-30  1110.709961   983.623024\n","20  2020-03-31  1146.819946  1102.279076\n","21  2020-04-01  1162.810059   954.604779\n","22  2020-04-02  1105.619995   874.468234\n","23  2020-04-03  1120.839966   854.783227\n","24  2020-04-06  1097.880005   961.535203\n","25  2020-04-07  1186.920044   947.065129\n","26  2020-04-08  1186.510010  1022.645421\n","27  2020-04-09  1210.280029   985.560551\n","28  2020-04-13  1211.449951  1042.400006\n","29  2020-04-14  1217.560059   691.717682\n","30  2020-04-15  1269.229980   907.997502\n","31  2020-04-16  1262.469971  1076.245375\n","32  2020-04-17  1263.469971  1036.825679\n","33  2020-04-20  1283.250000  1090.504559\n","34  2020-04-21  1266.609985   932.296426\n","35  2020-04-22  1216.339966   860.475558\n","36  2020-04-23  1263.209961  1001.763019\n","37  2020-04-24  1276.310059   983.520001\n","38  2020-04-27  1279.310059  1051.063077\n","39  2020-04-28  1275.880005   886.163682\n","          Date        Close   Prediction\n","30  2020-04-15  1269.229980   907.997502\n","31  2020-04-16  1262.469971  1076.245375\n","32  2020-04-17  1263.469971  1036.825679\n","33  2020-04-20  1283.250000  1090.504559\n","34  2020-04-21  1266.609985   932.296426\n","35  2020-04-22  1216.339966   860.475558\n","36  2020-04-23  1263.209961  1001.763019\n","37  2020-04-24  1276.310059   983.520001\n","38  2020-04-27  1279.310059  1051.063077\n","39  2020-04-28  1275.880005   886.163682\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"j2VwyuWLrVeQ"},"source":["# Neural Network Implementation"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"5hxy9vIzrRbq","colab":{}},"source":["import math\n","import numpy as np\n","import pandas as pd\n","from sklearn.preprocessing import MinMaxScaler\n","from tensorflow.keras.models import Sequential\n","from tensorflow.keras.layers import Dense, LSTM, Dropout\n","import matplotlib.pyplot as plt\n","plt.style.use('fivethirtyeight')"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"-gx8NJKprdfu"},"source":["### Loading Dataset for LSTM"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"XfZYaadIrkac","colab":{"base_uri":"https://localhost:8080/","height":431},"executionInfo":{"status":"ok","timestamp":1596178600484,"user_tz":-330,"elapsed":3928,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"2808df2a-2b4a-4240-95da-63908bc61944"},"source":["dfl = pd.read_csv('/content/drive/My Drive/Colab Notebooks/Stock prediction project/GOOG2.csv',index_col=\"Date\",parse_dates=True)\n","#Show the data\n","dfl"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\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>Open</th>\n","      <th>High</th>\n","      <th>Low</th>\n","      <th>Close</th>\n","      <th>Adj Close</th>\n","      <th>Volume</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2004-08-19</th>\n","      <td>49.813286</td>\n","      <td>51.835709</td>\n","      <td>47.800831</td>\n","      <td>49.982655</td>\n","      <td>49.982655</td>\n","      <td>44871300</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-20</th>\n","      <td>50.316402</td>\n","      <td>54.336334</td>\n","      <td>50.062355</td>\n","      <td>53.952770</td>\n","      <td>53.952770</td>\n","      <td>22942800</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-23</th>\n","      <td>55.168217</td>\n","      <td>56.528118</td>\n","      <td>54.321388</td>\n","      <td>54.495735</td>\n","      <td>54.495735</td>\n","      <td>18342800</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-24</th>\n","      <td>55.412300</td>\n","      <td>55.591629</td>\n","      <td>51.591621</td>\n","      <td>52.239193</td>\n","      <td>52.239193</td>\n","      <td>15319700</td>\n","    </tr>\n","    <tr>\n","      <th>2004-08-25</th>\n","      <td>52.284027</td>\n","      <td>53.798351</td>\n","      <td>51.746044</td>\n","      <td>52.802086</td>\n","      <td>52.802086</td>\n","      <td>9232100</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-22</th>\n","      <td>1245.540039</td>\n","      <td>1285.613037</td>\n","      <td>1242.000000</td>\n","      <td>1263.209961</td>\n","      <td>1263.209961</td>\n","      <td>2093100</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-23</th>\n","      <td>1271.550049</td>\n","      <td>1293.310059</td>\n","      <td>1265.670044</td>\n","      <td>1276.310059</td>\n","      <td>1276.310059</td>\n","      <td>1566200</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-24</th>\n","      <td>1261.170044</td>\n","      <td>1280.400024</td>\n","      <td>1249.449951</td>\n","      <td>1279.310059</td>\n","      <td>1279.310059</td>\n","      <td>1640400</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-27</th>\n","      <td>1296.000000</td>\n","      <td>1296.150024</td>\n","      <td>1269.000000</td>\n","      <td>1275.880005</td>\n","      <td>1275.880005</td>\n","      <td>1600600</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-28</th>\n","      <td>1287.930054</td>\n","      <td>1288.050049</td>\n","      <td>1232.199951</td>\n","      <td>1233.670044</td>\n","      <td>1233.670044</td>\n","      <td>2898600</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3950 rows × 6 columns</p>\n","</div>"],"text/plain":["                   Open         High  ...    Adj Close    Volume\n","Date                                  ...                       \n","2004-08-19    49.813286    51.835709  ...    49.982655  44871300\n","2004-08-20    50.316402    54.336334  ...    53.952770  22942800\n","2004-08-23    55.168217    56.528118  ...    54.495735  18342800\n","2004-08-24    55.412300    55.591629  ...    52.239193  15319700\n","2004-08-25    52.284027    53.798351  ...    52.802086   9232100\n","...                 ...          ...  ...          ...       ...\n","2020-04-22  1245.540039  1285.613037  ...  1263.209961   2093100\n","2020-04-23  1271.550049  1293.310059  ...  1276.310059   1566200\n","2020-04-24  1261.170044  1280.400024  ...  1279.310059   1640400\n","2020-04-27  1296.000000  1296.150024  ...  1275.880005   1600600\n","2020-04-28  1287.930054  1288.050049  ...  1233.670044   2898600\n","\n","[3950 rows x 6 columns]"]},"metadata":{"tags":[]},"execution_count":37}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"LnBLmJperpsO"},"source":["### Preprocessing & Feature Extraction"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"Xe6H3n5Vrr6R","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178600488,"user_tz":-330,"elapsed":3590,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"96bd2362-2c48-4357-ddfc-810983455dea"},"source":["#Get the number of rows and columns in the data set\n","dfl.shape"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(3950, 6)"]},"metadata":{"tags":[]},"execution_count":38}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"PqKbRcZsrsAS","colab":{"base_uri":"https://localhost:8080/","height":558},"executionInfo":{"status":"ok","timestamp":1596178600491,"user_tz":-330,"elapsed":3455,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"8e8f4c67-87f2-4ab6-8a49-c4608dcc2c07"},"source":["#Visualize the closing price history\n","plt.figure(figsize=(16,8))\n","plt.title('Close Price History')\n","plt.plot(dfl['Close'])\n","plt.xlabel('Date', fontsize=18)\n","plt.ylabel('Close Price ', fontsize=18)\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1152x576 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"mXzD4-WdsEKy","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178600493,"user_tz":-330,"elapsed":3274,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"16918a20-06ff-4db7-c60d-74a3ec23f1f6"},"source":["\n","#Create a new dataframe with only the 'Close column\n","data = dfl.filter(['Close'])\n","#Convert the dataframe to a numpy array\n","dataset = data.values\n","#Get the number of rows to train the model on\n","training_data_len = math.ceil( len(dataset) * .8 )\n","\n","training_data_len"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["3160"]},"metadata":{"tags":[]},"execution_count":40}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"NrLkcYEssXxp","colab":{"base_uri":"https://localhost:8080/","height":134},"executionInfo":{"status":"ok","timestamp":1596178600494,"user_tz":-330,"elapsed":3096,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"47f031a2-1231-41f6-af57-1467026e86bc"},"source":["#Scale the data\n","scaler = MinMaxScaler(feature_range=(0,1))\n","scaled_data = scaler.fit_transform(dataset)\n","\n","scaled_data"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[1.11307572e-04],\n","       [2.79949983e-03],\n","       [3.16714518e-03],\n","       ...,\n","       [8.32497375e-01],\n","       [8.30174862e-01],\n","       [8.01594206e-01]])"]},"metadata":{"tags":[]},"execution_count":41}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"SLf3Tt8csb-j","colab":{"base_uri":"https://localhost:8080/","height":823},"executionInfo":{"status":"ok","timestamp":1596178600496,"user_tz":-330,"elapsed":2969,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"19f676db-3ae9-41ae-ee6c-8e901f763602"},"source":["#Create the scaled training data set\n","train_data = scaled_data[0:training_data_len , :]\n","#Split the data into x_train and y_train data sets\n","x_trainl = []\n","y_trainl = []\n","\n","for i in range(60, len(train_data)):\n","    x_trainl.append(train_data[i-60:i, 0])\n","    y_trainl.append(train_data[i, 0])\n","    if i<= 61:\n","        print(x_trainl)\n","        print(y_trainl)\n","        print()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[array([1.11307572e-04, 2.79949983e-03, 3.16714518e-03, 1.63922502e-03,\n","       2.02036376e-03, 2.66458425e-03, 2.07095583e-03, 6.74577906e-04,\n","       7.96002809e-04, 8.09494841e-05, 5.05934276e-04, 0.00000000e+00,\n","       5.29544993e-04, 7.72392091e-04, 7.75765438e-04, 1.79437797e-03,\n","       2.52629803e-03, 3.87208117e-03, 4.04409815e-03, 4.70855872e-03,\n","       5.89581557e-03, 6.52654809e-03, 6.01386712e-03, 6.19600414e-03,\n","       7.01898898e-03, 6.68507168e-03, 6.15552940e-03, 9.05621676e-03,\n","       1.04795767e-02, 9.98038914e-03, 1.09855110e-02, 1.18219858e-02,\n","       1.29384126e-02, 1.25033138e-02, 1.31003129e-02, 1.27225495e-02,\n","       1.18894426e-02, 1.26112453e-02, 1.37917548e-02, 1.41627762e-02,\n","       1.48744535e-02, 1.65777640e-02, 1.61662732e-02, 1.36534686e-02,\n","       1.66519674e-02, 2.44264845e-02, 2.94757025e-02, 2.75868836e-02,\n","       2.89933816e-02, 3.14657108e-02, 3.05685205e-02, 3.23865099e-02,\n","       3.19952538e-02, 3.09159285e-02, 2.85650235e-02, 2.33876346e-02,\n","       2.44669592e-02, 2.31683982e-02, 2.28850736e-02, 2.79983798e-02])]\n","[0.027654345158531587]\n","\n","[array([1.11307572e-04, 2.79949983e-03, 3.16714518e-03, 1.63922502e-03,\n","       2.02036376e-03, 2.66458425e-03, 2.07095583e-03, 6.74577906e-04,\n","       7.96002809e-04, 8.09494841e-05, 5.05934276e-04, 0.00000000e+00,\n","       5.29544993e-04, 7.72392091e-04, 7.75765438e-04, 1.79437797e-03,\n","       2.52629803e-03, 3.87208117e-03, 4.04409815e-03, 4.70855872e-03,\n","       5.89581557e-03, 6.52654809e-03, 6.01386712e-03, 6.19600414e-03,\n","       7.01898898e-03, 6.68507168e-03, 6.15552940e-03, 9.05621676e-03,\n","       1.04795767e-02, 9.98038914e-03, 1.09855110e-02, 1.18219858e-02,\n","       1.29384126e-02, 1.25033138e-02, 1.31003129e-02, 1.27225495e-02,\n","       1.18894426e-02, 1.26112453e-02, 1.37917548e-02, 1.41627762e-02,\n","       1.48744535e-02, 1.65777640e-02, 1.61662732e-02, 1.36534686e-02,\n","       1.66519674e-02, 2.44264845e-02, 2.94757025e-02, 2.75868836e-02,\n","       2.89933816e-02, 3.14657108e-02, 3.05685205e-02, 3.23865099e-02,\n","       3.19952538e-02, 3.09159285e-02, 2.85650235e-02, 2.33876346e-02,\n","       2.44669592e-02, 2.31683982e-02, 2.28850736e-02, 2.79983798e-02]), array([2.79949983e-03, 3.16714518e-03, 1.63922502e-03, 2.02036376e-03,\n","       2.66458425e-03, 2.07095583e-03, 6.74577906e-04, 7.96002809e-04,\n","       8.09494841e-05, 5.05934276e-04, 0.00000000e+00, 5.29544993e-04,\n","       7.72392091e-04, 7.75765438e-04, 1.79437797e-03, 2.52629803e-03,\n","       3.87208117e-03, 4.04409815e-03, 4.70855872e-03, 5.89581557e-03,\n","       6.52654809e-03, 6.01386712e-03, 6.19600414e-03, 7.01898898e-03,\n","       6.68507168e-03, 6.15552940e-03, 9.05621676e-03, 1.04795767e-02,\n","       9.98038914e-03, 1.09855110e-02, 1.18219858e-02, 1.29384126e-02,\n","       1.25033138e-02, 1.31003129e-02, 1.27225495e-02, 1.18894426e-02,\n","       1.26112453e-02, 1.37917548e-02, 1.41627762e-02, 1.48744535e-02,\n","       1.65777640e-02, 1.61662732e-02, 1.36534686e-02, 1.66519674e-02,\n","       2.44264845e-02, 2.94757025e-02, 2.75868836e-02, 2.89933816e-02,\n","       3.14657108e-02, 3.05685205e-02, 3.23865099e-02, 3.19952538e-02,\n","       3.09159285e-02, 2.85650235e-02, 2.33876346e-02, 2.44669592e-02,\n","       2.31683982e-02, 2.28850736e-02, 2.79983798e-02, 2.76543452e-02])]\n","[0.027654345158531587, 0.02862236494395813]\n","\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"6uJuKyCes1TB","colab":{}},"source":["#Convert the x_train and y_train to numpy arrays \n","x_trainl, y_trainl = np.array(x_trainl), np.array(y_trainl)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"UEm0Ufhgs6rF","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596178600497,"user_tz":-330,"elapsed":2634,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"78cf60fa-6352-40dd-8ecb-ff5d4623d7e9"},"source":["#Reshape the data\n","x_trainl = np.reshape(x_trainl, (x_trainl.shape[0], x_trainl.shape[1], 1))\n","x_trainl.shape"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(3100, 60, 1)"]},"metadata":{"tags":[]},"execution_count":44}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"2oa5SVqEtE6u"},"source":["## Build the LSTM model"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"3T8pVmqPtJXG","colab":{"base_uri":"https://localhost:8080/","height":302},"executionInfo":{"status":"ok","timestamp":1596178608046,"user_tz":-330,"elapsed":9840,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"1cf6aea2-c4f7-49bb-e11f-603cfbaaf1c2"},"source":["model = Sequential()\n","\n","model.add(LSTM(50, return_sequences=True, input_shape= (x_trainl.shape[1], 1)))\n","model.add(LSTM(50, return_sequences= False))\n","model.add(Dense(25))\n","model.add(Dense(1))\n","\n","print(model.summary())"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Model: \"sequential\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","lstm (LSTM)                  (None, 60, 50)            10400     \n","_________________________________________________________________\n","lstm_1 (LSTM)                (None, 50)                20200     \n","_________________________________________________________________\n","dense (Dense)                (None, 25)                1275      \n","_________________________________________________________________\n","dense_1 (Dense)              (None, 1)                 26        \n","=================================================================\n","Total params: 31,901\n","Trainable params: 31,901\n","Non-trainable params: 0\n","_________________________________________________________________\n","None\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"Wm3Lih_6tch1","colab":{}},"source":["#Compile the model\n","model.compile(optimizer='adam',loss='mean_squared_error')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"VYpxWZmst2b3","scrolled":true,"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1596179132965,"user_tz":-330,"elapsed":534222,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"3c922747-9d01-4e1b-88c0-5a80c0b5c5ff"},"source":["#Train the model\n","lstm_start = time.time()\n","\n","history = model.fit(x_trainl, y_trainl, epochs=200, batch_size=32)\n","lstm_end = time.time()\n","\n","total_lstm = lstm_end - lstm_start"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Epoch 1/200\n","97/97 [==============================] - 3s 26ms/step - loss: 0.0035\n","Epoch 2/200\n","97/97 [==============================] - 3s 26ms/step - loss: 1.0713e-04\n","Epoch 3/200\n","97/97 [==============================] - 3s 27ms/step - loss: 1.0034e-04\n","Epoch 4/200\n","97/97 [==============================] - 3s 26ms/step - loss: 9.5232e-05\n","Epoch 5/200\n","97/97 [==============================] - 3s 27ms/step - loss: 9.3390e-05\n","Epoch 6/200\n","97/97 [==============================] - 3s 27ms/step - loss: 9.1281e-05\n","Epoch 7/200\n","97/97 [==============================] - 3s 26ms/step - loss: 8.9978e-05\n","Epoch 8/200\n","97/97 [==============================] - 3s 26ms/step - loss: 7.7677e-05\n","Epoch 9/200\n","97/97 [==============================] - 2s 26ms/step - loss: 7.9988e-05\n","Epoch 10/200\n","97/97 [==============================] - 3s 26ms/step - loss: 7.8808e-05\n","Epoch 11/200\n","97/97 [==============================] - 3s 26ms/step - loss: 8.0651e-05\n","Epoch 12/200\n","97/97 [==============================] - 2s 26ms/step - loss: 8.1875e-05\n","Epoch 13/200\n","97/97 [==============================] - 2s 26ms/step - loss: 7.3560e-05\n","Epoch 14/200\n","97/97 [==============================] - 2s 25ms/step - loss: 7.1358e-05\n","Epoch 15/200\n","97/97 [==============================] - 2s 25ms/step - loss: 7.4945e-05\n","Epoch 16/200\n","97/97 [==============================] - 3s 26ms/step - loss: 6.4060e-05\n","Epoch 17/200\n","97/97 [==============================] - 3s 26ms/step - loss: 6.2810e-05\n","Epoch 18/200\n","97/97 [==============================] - 2s 26ms/step - loss: 7.2724e-05\n","Epoch 19/200\n","97/97 [==============================] - 3s 26ms/step - loss: 6.2447e-05\n","Epoch 20/200\n","97/97 [==============================] - 3s 26ms/step - loss: 5.8148e-05\n","Epoch 21/200\n","97/97 [==============================] - 3s 26ms/step - loss: 5.8987e-05\n","Epoch 22/200\n","97/97 [==============================] - 2s 25ms/step - loss: 5.5773e-05\n","Epoch 23/200\n","97/97 [==============================] - 3s 26ms/step - loss: 4.9885e-05\n","Epoch 24/200\n","97/97 [==============================] - 3s 26ms/step - loss: 4.9353e-05\n","Epoch 25/200\n","97/97 [==============================] - 2s 26ms/step - loss: 6.1830e-05\n","Epoch 26/200\n","97/97 [==============================] - 3s 26ms/step - loss: 5.8316e-05\n","Epoch 27/200\n","97/97 [==============================] - 3s 26ms/step - loss: 4.5959e-05\n","Epoch 28/200\n","97/97 [==============================] - 2s 26ms/step - loss: 4.6482e-05\n","Epoch 29/200\n","97/97 [==============================] - 3s 26ms/step - loss: 4.7481e-05\n","Epoch 30/200\n","97/97 [==============================] - 2s 26ms/step - loss: 4.4732e-05\n","Epoch 31/200\n","97/97 [==============================] - 2s 26ms/step - loss: 3.8383e-05\n","Epoch 32/200\n","97/97 [==============================] - 3s 26ms/step - loss: 4.2889e-05\n","Epoch 33/200\n","97/97 [==============================] - 2s 26ms/step - loss: 3.8615e-05\n","Epoch 34/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.7777e-05\n","Epoch 35/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.8684e-05\n","Epoch 36/200\n","97/97 [==============================] - 2s 26ms/step - loss: 3.5571e-05\n","Epoch 37/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.4446e-05\n","Epoch 38/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.9629e-05\n","Epoch 39/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.7080e-05\n","Epoch 40/200\n","97/97 [==============================] - 2s 26ms/step - loss: 4.2306e-05\n","Epoch 41/200\n","97/97 [==============================] - 3s 26ms/step - loss: 4.4244e-05\n","Epoch 42/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.5525e-05\n","Epoch 43/200\n","97/97 [==============================] - 2s 26ms/step - loss: 3.5112e-05\n","Epoch 44/200\n","97/97 [==============================] - 2s 25ms/step - loss: 3.6196e-05\n","Epoch 45/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.3048e-05\n","Epoch 46/200\n","97/97 [==============================] - 2s 26ms/step - loss: 3.0727e-05\n","Epoch 47/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.8355e-05\n","Epoch 48/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.0366e-05\n","Epoch 49/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.9081e-05\n","Epoch 50/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.1012e-05\n","Epoch 51/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.1835e-05\n","Epoch 52/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.0338e-05\n","Epoch 53/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.6194e-05\n","Epoch 54/200\n","97/97 [==============================] - 2s 26ms/step - loss: 3.1010e-05\n","Epoch 55/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.4603e-05\n","Epoch 56/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5959e-05\n","Epoch 57/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.9474e-05\n","Epoch 58/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4460e-05\n","Epoch 59/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.6672e-05\n","Epoch 60/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.6483e-05\n","Epoch 61/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.7278e-05\n","Epoch 62/200\n","97/97 [==============================] - 3s 27ms/step - loss: 3.0065e-05\n","Epoch 63/200\n","97/97 [==============================] - 3s 27ms/step - loss: 3.1792e-05\n","Epoch 64/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3434e-05\n","Epoch 65/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.2726e-05\n","Epoch 66/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4907e-05\n","Epoch 67/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2550e-05\n","Epoch 68/200\n","97/97 [==============================] - 3s 26ms/step - loss: 3.3583e-05\n","Epoch 69/200\n","97/97 [==============================] - 2s 25ms/step - loss: 2.2396e-05\n","Epoch 70/200\n","97/97 [==============================] - 2s 25ms/step - loss: 2.3873e-05\n","Epoch 71/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.4217e-05\n","Epoch 72/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4419e-05\n","Epoch 73/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.7980e-05\n","Epoch 74/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3924e-05\n","Epoch 75/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.8855e-05\n","Epoch 76/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.4422e-05\n","Epoch 77/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.1506e-05\n","Epoch 78/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.1179e-05\n","Epoch 79/200\n","97/97 [==============================] - 3s 28ms/step - loss: 2.1431e-05\n","Epoch 80/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5074e-05\n","Epoch 81/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.2007e-05\n","Epoch 82/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3274e-05\n","Epoch 83/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.7105e-05\n","Epoch 84/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5782e-05\n","Epoch 85/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3676e-05\n","Epoch 86/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.1042e-05\n","Epoch 87/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.1765e-05\n","Epoch 88/200\n","97/97 [==============================] - 3s 27ms/step - loss: 3.3077e-05\n","Epoch 89/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3263e-05\n","Epoch 90/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3155e-05\n","Epoch 91/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.4266e-05\n","Epoch 92/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.2596e-05\n","Epoch 93/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3854e-05\n","Epoch 94/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5497e-05\n","Epoch 95/200\n","97/97 [==============================] - 3s 28ms/step - loss: 2.3333e-05\n","Epoch 96/200\n","97/97 [==============================] - 3s 28ms/step - loss: 2.1808e-05\n","Epoch 97/200\n","97/97 [==============================] - 3s 28ms/step - loss: 3.0233e-05\n","Epoch 98/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.2956e-05\n","Epoch 99/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3338e-05\n","Epoch 100/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.6301e-05\n","Epoch 101/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.2482e-05\n","Epoch 102/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3299e-05\n","Epoch 103/200\n","97/97 [==============================] - 3s 28ms/step - loss: 2.3566e-05\n","Epoch 104/200\n","97/97 [==============================] - 3s 29ms/step - loss: 2.1930e-05\n","Epoch 105/200\n","97/97 [==============================] - 3s 28ms/step - loss: 2.7618e-05\n","Epoch 106/200\n","97/97 [==============================] - 3s 29ms/step - loss: 2.0374e-05\n","Epoch 107/200\n","97/97 [==============================] - 3s 28ms/step - loss: 2.3885e-05\n","Epoch 108/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.6512e-05\n","Epoch 109/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5348e-05\n","Epoch 110/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5467e-05\n","Epoch 111/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.7106e-05\n","Epoch 112/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0545e-05\n","Epoch 113/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.9263e-05\n","Epoch 114/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.5996e-05\n","Epoch 115/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.5495e-05\n","Epoch 116/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.1236e-05\n","Epoch 117/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.3500e-05\n","Epoch 118/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.5217e-05\n","Epoch 119/200\n","97/97 [==============================] - 2s 25ms/step - loss: 2.2388e-05\n","Epoch 120/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2465e-05\n","Epoch 121/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1212e-05\n","Epoch 122/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2619e-05\n","Epoch 123/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3080e-05\n","Epoch 124/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1114e-05\n","Epoch 125/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1838e-05\n","Epoch 126/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2829e-05\n","Epoch 127/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1490e-05\n","Epoch 128/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2701e-05\n","Epoch 129/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.3806e-05\n","Epoch 130/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2776e-05\n","Epoch 131/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1725e-05\n","Epoch 132/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3800e-05\n","Epoch 133/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.5274e-05\n","Epoch 134/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3531e-05\n","Epoch 135/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.5421e-05\n","Epoch 136/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3291e-05\n","Epoch 137/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1486e-05\n","Epoch 138/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2108e-05\n","Epoch 139/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2836e-05\n","Epoch 140/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1406e-05\n","Epoch 141/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0598e-05\n","Epoch 142/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2008e-05\n","Epoch 143/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3590e-05\n","Epoch 144/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3152e-05\n","Epoch 145/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4432e-05\n","Epoch 146/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0642e-05\n","Epoch 147/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1782e-05\n","Epoch 148/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.5902e-05\n","Epoch 149/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1569e-05\n","Epoch 150/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2857e-05\n","Epoch 151/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2014e-05\n","Epoch 152/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2441e-05\n","Epoch 153/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3146e-05\n","Epoch 154/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.3053e-05\n","Epoch 155/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1954e-05\n","Epoch 156/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1349e-05\n","Epoch 157/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4783e-05\n","Epoch 158/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0444e-05\n","Epoch 159/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1358e-05\n","Epoch 160/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4047e-05\n","Epoch 161/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0599e-05\n","Epoch 162/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0291e-05\n","Epoch 163/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1856e-05\n","Epoch 164/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3825e-05\n","Epoch 165/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4982e-05\n","Epoch 166/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3413e-05\n","Epoch 167/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1162e-05\n","Epoch 168/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4159e-05\n","Epoch 169/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.6406e-05\n","Epoch 170/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1589e-05\n","Epoch 171/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4934e-05\n","Epoch 172/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4389e-05\n","Epoch 173/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0617e-05\n","Epoch 174/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2928e-05\n","Epoch 175/200\n","97/97 [==============================] - 3s 27ms/step - loss: 2.4184e-05\n","Epoch 176/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2840e-05\n","Epoch 177/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2925e-05\n","Epoch 178/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2235e-05\n","Epoch 179/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2629e-05\n","Epoch 180/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4977e-05\n","Epoch 181/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1704e-05\n","Epoch 182/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2427e-05\n","Epoch 183/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0193e-05\n","Epoch 184/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2232e-05\n","Epoch 185/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2273e-05\n","Epoch 186/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.4847e-05\n","Epoch 187/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2189e-05\n","Epoch 188/200\n","97/97 [==============================] - 3s 26ms/step - loss: 1.9558e-05\n","Epoch 189/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0965e-05\n","Epoch 190/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0971e-05\n","Epoch 191/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.4571e-05\n","Epoch 192/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.3195e-05\n","Epoch 193/200\n","97/97 [==============================] - 2s 26ms/step - loss: 2.0652e-05\n","Epoch 194/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2153e-05\n","Epoch 195/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.1356e-05\n","Epoch 196/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0058e-05\n","Epoch 197/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2205e-05\n","Epoch 198/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.2715e-05\n","Epoch 199/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.0573e-05\n","Epoch 200/200\n","97/97 [==============================] - 3s 26ms/step - loss: 2.6666e-05\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"e43AhmV9saPL","colab_type":"code","colab":{}},"source":["model.save(\"test_123.h5\")"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"B8NRnYa0skuc","colab_type":"code","colab":{}},"source":["import keras\n","from keras.models import load_model\n","from tensorflow.keras.models import load_model\n","new_model = load_model('test_123.h5')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"5B3sPUHRtab7","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":286},"executionInfo":{"status":"ok","timestamp":1596179481758,"user_tz":-330,"elapsed":834,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"c75f7fe4-e022-4ed7-a069-2e537dfa1299"},"source":["new_model.summary()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Model: \"sequential\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","lstm (LSTM)                  (None, 60, 50)            10400     \n","_________________________________________________________________\n","lstm_1 (LSTM)                (None, 50)                20200     \n","_________________________________________________________________\n","dense (Dense)                (None, 25)                1275      \n","_________________________________________________________________\n","dense_1 (Dense)              (None, 1)                 26        \n","=================================================================\n","Total params: 31,901\n","Trainable params: 31,901\n","Non-trainable params: 0\n","_________________________________________________________________\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"LSqImm1WuGt-","colab":{}},"source":["#Create the testing data set\n","#Create a new array containing scaled values from index 1543 to 2002 \n","test_data = scaled_data[training_data_len - 60: , :]\n","#Create the data sets x_test and y_test\n","x_testl = []\n","y_testl = dataset[training_data_len:, :]\n","for i in range(60, len(test_data)):\n","    x_testl.append(test_data[i-60:i, 0])"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"92RVLyrmu2rQ","colab":{}},"source":["#Convert the data to a numpy array\n","x_testl = np.array(x_testl)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"SOx5n8gPu3ry","colab":{}},"source":["#Reshape the data\n","x_testl = np.reshape(x_testl, (x_testl.shape[0], x_testl.shape[1], 1 ))"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"lcTfbepku6Pc","colab":{}},"source":["#Get the models predicted price values \n","predictionsl = model.predict(x_testl)\n","predictionsl = scaler.inverse_transform(predictionsl)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"J1nNhI4IvTn3","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596179133582,"user_tz":-330,"elapsed":534111,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"e4ab4d14-2bec-44d2-ea86-d7309e010a27"},"source":["#Get the root mean squared error (RMSE)\n","rmse=np.sqrt(np.mean(((predictionsl - y_testl)**2)))\n","rmse"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["30.2736708781226"]},"metadata":{"tags":[]},"execution_count":52}]},{"cell_type":"code","metadata":{"id":"j-q-_HVAVzL1","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":34},"executionInfo":{"status":"ok","timestamp":1596179133583,"user_tz":-330,"elapsed":533946,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"0e24c5c1-1375-4213-96fd-596bb0b0258b"},"source":["from sklearn.metrics import mean_squared_error\n","rr = mean_squared_error(y_testl, predictionsl)\n","#mse = sklearn.metrics.mean_squared_error(y_testl, predictionsl)\n","\n","rmse1 = math.sqrt(rr)\n","\n","print(rmse1)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["30.2736708781226\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"VjG5bvQFvz8G"},"source":["### Visualizing Results of LSTM Model"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"oZe4xM6Tv4XR","colab":{"base_uri":"https://localhost:8080/","height":659},"executionInfo":{"status":"ok","timestamp":1596179135981,"user_tz":-330,"elapsed":535953,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"db918448-b787-452e-ade0-c70475855217"},"source":["#Plot the data\n","train = data[:training_data_len]\n","valid = data[training_data_len:]\n","valid['Predictions'] = predictionsl\n","#Visualize the data\n","plt.figure(figsize=(16,8))\n","plt.title('Model')\n","plt.xlabel('Date', fontsize=18)\n","plt.ylabel('Close Price ', fontsize=18)\n","plt.plot(train['Close'])\n","plt.plot(valid[['Close', 'Predictions']])\n","plt.legend(['Train', 'Val', 'Predictions'], loc='lower right')\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  after removing the cwd from sys.path.\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1152x576 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"vWcfDGibwWR4","colab":{"base_uri":"https://localhost:8080/","height":431},"executionInfo":{"status":"ok","timestamp":1596179135984,"user_tz":-330,"elapsed":535763,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"b88ecb21-6214-46d8-e6eb-75a0ad4a313f"},"source":["#Show the valid and predicted prices\n","valid"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\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>Close</th>\n","      <th>Predictions</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2017-03-09</th>\n","      <td>838.679993</td>\n","      <td>826.841736</td>\n","    </tr>\n","    <tr>\n","      <th>2017-03-10</th>\n","      <td>843.250000</td>\n","      <td>829.778442</td>\n","    </tr>\n","    <tr>\n","      <th>2017-03-13</th>\n","      <td>845.539978</td>\n","      <td>834.269104</td>\n","    </tr>\n","    <tr>\n","      <th>2017-03-14</th>\n","      <td>845.619995</td>\n","      <td>836.282654</td>\n","    </tr>\n","    <tr>\n","      <th>2017-03-15</th>\n","      <td>847.200012</td>\n","      <td>835.988037</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-22</th>\n","      <td>1263.209961</td>\n","      <td>1181.140015</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-23</th>\n","      <td>1276.310059</td>\n","      <td>1236.606567</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-24</th>\n","      <td>1279.310059</td>\n","      <td>1252.529907</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-27</th>\n","      <td>1275.880005</td>\n","      <td>1247.851318</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-28</th>\n","      <td>1233.670044</td>\n","      <td>1243.703003</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>790 rows × 2 columns</p>\n","</div>"],"text/plain":["                  Close  Predictions\n","Date                                \n","2017-03-09   838.679993   826.841736\n","2017-03-10   843.250000   829.778442\n","2017-03-13   845.539978   834.269104\n","2017-03-14   845.619995   836.282654\n","2017-03-15   847.200012   835.988037\n","...                 ...          ...\n","2020-04-22  1263.209961  1181.140015\n","2020-04-23  1276.310059  1236.606567\n","2020-04-24  1279.310059  1252.529907\n","2020-04-27  1275.880005  1247.851318\n","2020-04-28  1233.670044  1243.703003\n","\n","[790 rows x 2 columns]"]},"metadata":{"tags":[]},"execution_count":55}]},{"cell_type":"code","metadata":{"id":"UaARuCsodBoO","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":373},"executionInfo":{"status":"ok","timestamp":1596179135986,"user_tz":-330,"elapsed":535632,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"2a74e31d-b55d-4443-c04e-2f3dc841c819"},"source":["valid.tail(10)"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\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>Close</th>\n","      <th>Predictions</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2020-04-15</th>\n","      <td>1262.469971</td>\n","      <td>1244.119629</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-16</th>\n","      <td>1263.469971</td>\n","      <td>1233.091919</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-17</th>\n","      <td>1283.250000</td>\n","      <td>1229.339844</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-20</th>\n","      <td>1266.609985</td>\n","      <td>1252.655518</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-21</th>\n","      <td>1216.339966</td>\n","      <td>1234.573730</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-22</th>\n","      <td>1263.209961</td>\n","      <td>1181.140015</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-23</th>\n","      <td>1276.310059</td>\n","      <td>1236.606567</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-24</th>\n","      <td>1279.310059</td>\n","      <td>1252.529907</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-27</th>\n","      <td>1275.880005</td>\n","      <td>1247.851318</td>\n","    </tr>\n","    <tr>\n","      <th>2020-04-28</th>\n","      <td>1233.670044</td>\n","      <td>1243.703003</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                  Close  Predictions\n","Date                                \n","2020-04-15  1262.469971  1244.119629\n","2020-04-16  1263.469971  1233.091919\n","2020-04-17  1283.250000  1229.339844\n","2020-04-20  1266.609985  1252.655518\n","2020-04-21  1216.339966  1234.573730\n","2020-04-22  1263.209961  1181.140015\n","2020-04-23  1276.310059  1236.606567\n","2020-04-24  1279.310059  1252.529907\n","2020-04-27  1275.880005  1247.851318\n","2020-04-28  1233.670044  1243.703003"]},"metadata":{"tags":[]},"execution_count":56}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"fTFhrlJiwcpz","colab":{}},"source":["lstm_temp_pred = valid[['Predictions']].tail(40)\n","lstm_temp_ori = valid[['Close']].tail(40)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"DES2-Epowcp4","colab":{}},"source":["lstm_temp_pred.reset_index(drop=True, inplace=True)\n","lstm_temp_ori.reset_index(drop=True, inplace=True)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"XRcj_xUCwcp8","colab":{}},"source":["lstm_temp_pred = lstm_temp_pred.values.tolist()\n","lstm_temp_ori = lstm_temp_ori.values.tolist()"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"aYb5W1TjwcqB","colab":{}},"source":["lstm = []\n","original = []\n","for i in range(40):\n","    lstm.append(lstm_temp_pred[i][-1])\n","    original.append(lstm_temp_ori[i][-1])\n","\n","# lstm = []\n","# original = []\n","# for i in range(30):\n","#     lstm.append(lstm_temp_pred[i][-1])\n","#     original.append(lstm_temp_ori[i][-1])"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"VO5a5U5mS7Y9","colab_type":"code","colab":{}},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"U16LBL9c8qpp"},"source":["### Visualizing Result of Supervised Learning algorithms"]},{"cell_type":"code","metadata":{"colab_type":"code","id":"ANED0Uiq8qpq","colab":{}},"source":["days = [int(i) for i in range(30)]\n","\n","predictions = {'Original':original[:30],\n","               'Linear Regression':lr.predict(X_old)[:30],\n","              'KNN':knn.predict(X_old)[:30],\n","              'Decision Tree':tree.predict(X_old)[:30],\n","              'LSTM':lstm[:30]}\n","\n","predictions = pd.DataFrame(predictions)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"IpH2_JB98qps","scrolled":true,"colab":{"base_uri":"https://localhost:8080/","height":483},"executionInfo":{"status":"ok","timestamp":1596179137410,"user_tz":-330,"elapsed":534902,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"8ff574f6-b6eb-42c9-a8a9-e7c46ff882ec"},"source":["predictions['Original'].plot(figsize = (30,10), fontsize = 20)\n","predictions['Linear Regression'].plot(figsize = (30,10), fontsize = 20)\n","predictions['KNN'].plot(figsize = (30,10), fontsize = 20)\n","predictions['Decision Tree'].plot(figsize = (30,10), fontsize = 20)\n","predictions['LSTM'].plot(figsize = (30,10), fontsize = 20)\n","plt.legend(['Original','Linear Regression', 'KNN', 'Decision Tree', 'LSTM'], fontsize=20)\n","plt.xlabel('Days', fontsize = 30)\n","plt.ylabel('Price', fontsize = 30)\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 2160x720 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab_type":"code","id":"5nE6SX418qpt","colab":{"base_uri":"https://localhost:8080/","height":303},"executionInfo":{"status":"ok","timestamp":1596179137412,"user_tz":-330,"elapsed":534740,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"add22d94-f8d9-4d2e-926b-d3b8e0bddd25"},"source":["objects = ('LR', 'DT', 'KNN', 'LSTM')\n","y_pos = np.arange(len(objects))\n","performance = [time_lr, time_dt, time_knn, total_lstm]\n","\n","plt.bar(y_pos, performance, align='center', color='c', alpha = 0.75)\n","plt.xticks(y_pos, objects)\n","plt.ylabel('Training Time (s)')\n","plt.title('Training Time in Different Models')\n","\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"_LVlw3O4Vc_N","colab_type":"code","colab":{}},"source":["date= ['2020-03-17','2020-03-18','2020-03-19','2020-03-20','2020-03-23','2020-03-24','2020-03-25','2020-03-26','2020-03-27','2020-03-30',\n","       '2020-03-31','2020-04-01','2020-04-02','2020-04-03','2020-04-06','2020-04-07','2020-04-08','2020-04-09','2020-04-13','2020-04-14',\n","        '2020-04-15','2020-04-16','2020-04-17','2020-04-20','2020-04-21','2020-04-22','2020-04-23','2020-04-24','2020-04-27','2020-04-28',]"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab_type":"code","id":"_FLKxoM4wcqy","colab":{"base_uri":"https://localhost:8080/","height":70},"executionInfo":{"status":"ok","timestamp":1596179137418,"user_tz":-330,"elapsed":534394,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"b15d25a2-a634-4f10-c996-9f3eb373fdab"},"source":["days = [str(i) for i in date]\n","\n","predictions = {'Original':original[10:41],\n","               'Linear Regression':lr.predict(X_old)[10:41],\n","              'KNN':knn.predict(X_old)[10:41],\n","              'Decision Tree':tree.predict(X_old)[10:41],\n","              'LSTM':lstm[10:41]}\n","\n","predictions = pd.DataFrame(predictions)\n","print(days)\n","len(days)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["['2020-03-17', '2020-03-18', '2020-03-19', '2020-03-20', '2020-03-23', '2020-03-24', '2020-03-25', '2020-03-26', '2020-03-27', '2020-03-30', '2020-03-31', '2020-04-01', '2020-04-02', '2020-04-03', '2020-04-06', '2020-04-07', '2020-04-08', '2020-04-09', '2020-04-13', '2020-04-14', '2020-04-15', '2020-04-16', '2020-04-17', '2020-04-20', '2020-04-21', '2020-04-22', '2020-04-23', '2020-04-24', '2020-04-27', '2020-04-28']\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["30"]},"metadata":{"tags":[]},"execution_count":65}]},{"cell_type":"code","metadata":{"id":"1QT0J5UA856C","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":552},"executionInfo":{"status":"ok","timestamp":1596179137420,"user_tz":-330,"elapsed":534180,"user":{"displayName":"Shubham Sood","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi0ldgwk3p_Q0rON7ydNzarF2aCo0j89DXbT0ZVKiM=s64","userId":"08327893235702426167"}},"outputId":"8ae1cd74-344b-41e2-d910-0676554883aa"},"source":["predictions['Original'].plot(figsize = (30,10), fontsize = 20)\n","predictions['Linear Regression'].plot(figsize = (30,10), fontsize = 20)\n","predictions['KNN'].plot(figsize = (30,10), fontsize = 20)\n","predictions['Decision Tree'].plot(figsize = (30,10), fontsize = 20)\n","predictions['LSTM'].plot(figsize = (30,10), fontsize = 20)\n","plt.legend(['Actual Closed Price','Linear Regression', 'KNN', 'Decision Tree', 'LSTM'], fontsize=20)\n","\n","bars = days\n","y_pos = np.arange(len(bars))\n"," \n","# Create names\n","plt.xticks(y_pos, bars)\n","plt.xticks(rotation=90)\n","\n","\n","plt.xlabel('Dates', fontsize = 30)\n","plt.ylabel('Price', fontsize = 30)\n","\n","\n","fig = plt.gcf()\n","fig.set_size_inches(16,6)\n","\n","\n","plt.show()\n","\n","plt.savefig(\"High resoltion.png\",dpi=300)"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1152x432 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"VYil-BUX8_uC","colab_type":"code","colab":{}},"source":[""],"execution_count":null,"outputs":[]}]}