COVID_GB.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import libraries \n",
    "import pandas as pd # Import Pandas for data manipulation using dataframes\n",
    "import numpy as np # Import Numpy for data statistical analysis \n",
    "import matplotlib.pyplot as plt # Import matplotlib for data visualisation\n",
    "import random\n",
    "import seaborn as sns\n",
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Date', 'AJK', 'Balochistan', 'KPK', 'GB', 'Sindh', 'Punjab',\n",
       "       'ICT'], dtype=object)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid=pd.read_csv(\"Daily_Cases_By_Province.csv\")\n",
    "covid.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n",
      "C:\\Users\\khana\\Anaconda3\\lib\\site-packages\\pystan\\misc.py:399: FutureWarning:\n",
      "\n",
      "Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "covid_GB=covid[['Date','GB']]\n",
    "covid_GB=covid_GB.rename(columns={'Date':'ds','GB':'y'})\n",
    "covid_GB['y']=covid_GB['y'].diff()\n",
    "covid_GB['y']=covid_GB['y'].fillna(0)\n",
    "model=Prophet()\n",
    "model.fit(covid_GB)\n",
    "month = model.make_future_dataframe(periods=30)\n",
    "forecast_month = model.predict(month)\n",
    "month_figure=model.plot(forecast_month,xlabel='Date',ylabel='Cases Per Day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "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>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11-Mar-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>16-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>17-Mar-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>18-Mar-20</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19-Mar-20</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20-Mar-20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>21-Mar-20</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>22-Mar-20</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>23-Mar-20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>24-Mar-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>25-Mar-20</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>26-Mar-20</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>27-Mar-20</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>28-Mar-20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>29-Mar-20</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>30-Mar-20</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>31-Mar-20</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1-Apr-20</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2-Apr-20</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>3-Apr-20</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>4-Apr-20</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>5-Apr-20</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>6-Apr-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>7-Apr-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>8-Apr-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>9-Apr-20</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>10-Apr-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>11-Apr-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>12-Apr-20</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>13-Apr-20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>14-Apr-20</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>15-Apr-20</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>16-Apr-20</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>17-Apr-20</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>18-Apr-20</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>19-Apr-20</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>20-Apr-20</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>21-Apr-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>22-Apr-20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>23-Apr-20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds     y\n",
       "0   10-Mar-20   0.0\n",
       "1   11-Mar-20   1.0\n",
       "2   12-Mar-20   0.0\n",
       "3   13-Mar-20   0.0\n",
       "4   14-Mar-20   0.0\n",
       "5   15-Mar-20   0.0\n",
       "6   16-Mar-20   0.0\n",
       "7   17-Mar-20   0.0\n",
       "8   18-Mar-20  10.0\n",
       "9   19-Mar-20   8.0\n",
       "10  20-Mar-20   9.0\n",
       "11  21-Mar-20  25.0\n",
       "12  22-Mar-20  16.0\n",
       "13  23-Mar-20   9.0\n",
       "14  24-Mar-20   1.0\n",
       "15  25-Mar-20   3.0\n",
       "16  26-Mar-20   7.0\n",
       "17  27-Mar-20  16.0\n",
       "18  28-Mar-20   9.0\n",
       "19  29-Mar-20  12.0\n",
       "20  30-Mar-20  20.0\n",
       "21  31-Mar-20  36.0\n",
       "22   1-Apr-20   3.0\n",
       "23   2-Apr-20   3.0\n",
       "24   3-Apr-20   3.0\n",
       "25   4-Apr-20  13.0\n",
       "26   5-Apr-20   4.0\n",
       "27   6-Apr-20   1.0\n",
       "28   7-Apr-20   1.0\n",
       "29   8-Apr-20   1.0\n",
       "30   9-Apr-20   2.0\n",
       "31  10-Apr-20   0.0\n",
       "32  11-Apr-20   1.0\n",
       "33  12-Apr-20   8.0\n",
       "34  13-Apr-20   9.0\n",
       "35  14-Apr-20   1.0\n",
       "36  15-Apr-20   3.0\n",
       "37  16-Apr-20   8.0\n",
       "38  17-Apr-20   5.0\n",
       "39  18-Apr-20   7.0\n",
       "40  19-Apr-20   6.0\n",
       "41  20-Apr-20  18.0\n",
       "42  21-Apr-20   0.0\n",
       "43  22-Apr-20   9.0\n",
       "44  23-Apr-20   0.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid_GB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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