Test Dataset Creation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This notebook is for test dataset creation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Dictionary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Field          | Description                                                                           |\n",
    "|----------------|---------------------------------------------------------------------------------------|\n",
    "|Date |Date of incident\t|\n",
    "|Province/State |If there is a breakdown in states\t|\n",
    "|Lat |Latitude\t|\n",
    "|Lon |Longitude\t|\n",
    "|Confirmed |Confirmed cases\t|\n",
    "|Recovered |Recovered cases\t|\n",
    "|Deaths |Death cases\t|\n",
    "|Active |Active cases\t|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.notebook.set_autosave_interval(60000)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autosaving every 60 seconds\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.api as sm\n",
    "import datetime\n",
    "import scipy.stats\n",
    "\n",
    "%matplotlib inline\n",
    "#sets the default autosave frequency in seconds\n",
    "%autosave 60 \n",
    "sns.set_style('dark')\n",
    "sns.set(font_scale=1.2)\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "pd.set_option('display.max_columns',None)\n",
    "#pd.set_option('display.max_rows',None)\n",
    "pd.set_option('display.width', 1000)\n",
    "\n",
    "np.random.seed(0)\n",
    "np.set_printoptions(suppress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"testdataset.csv\",parse_dates=['Date'], index_col=[\"Date\"])"
   ]
  },
  {
   "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>Country</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Active</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>2020-01-22</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>2020-11-24</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-25</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-26</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-27</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-28</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>86424 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Country  Confirmed  Recovered  Deaths  Active\n",
       "Date                                                         \n",
       "2020-01-22  Afghanistan          0          0       0       0\n",
       "2020-01-23  Afghanistan          0          0       0       0\n",
       "2020-01-24  Afghanistan          0          0       0       0\n",
       "2020-01-25  Afghanistan          0          0       0       0\n",
       "2020-01-26  Afghanistan          0          0       0       0\n",
       "...                 ...        ...        ...     ...     ...\n",
       "2020-11-24  Timor-Leste          0         30       0     -30\n",
       "2020-11-25  Timor-Leste          0         30       0     -30\n",
       "2020-11-26  Timor-Leste          0         30       0     -30\n",
       "2020-11-27  Timor-Leste          0         30       0     -30\n",
       "2020-11-28  Timor-Leste          0         30       0     -30\n",
       "\n",
       "[86424 rows x 5 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extract country Malaysia from dataset for analysis and machine learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia = df[df[\"Country\"] == \"Malaysia\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Active</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>2020-01-22</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</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>2020-11-24</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>58847</td>\n",
       "      <td>44153</td>\n",
       "      <td>341</td>\n",
       "      <td>14353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-25</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>59817</td>\n",
       "      <td>46501</td>\n",
       "      <td>345</td>\n",
       "      <td>12971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-26</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>60752</td>\n",
       "      <td>49056</td>\n",
       "      <td>348</td>\n",
       "      <td>11348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-27</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>61861</td>\n",
       "      <td>50204</td>\n",
       "      <td>350</td>\n",
       "      <td>11307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-28</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>63176</td>\n",
       "      <td>51314</td>\n",
       "      <td>354</td>\n",
       "      <td>11508</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>312 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Country  Confirmed  Recovered  Deaths  Active\n",
       "Date                                                      \n",
       "2020-01-22  Malaysia          0          0       0       0\n",
       "2020-01-23  Malaysia          0          0       0       0\n",
       "2020-01-24  Malaysia          0          0       0       0\n",
       "2020-01-25  Malaysia          3          0       0       3\n",
       "2020-01-26  Malaysia          4          0       0       4\n",
       "...              ...        ...        ...     ...     ...\n",
       "2020-11-24  Malaysia      58847      44153     341   14353\n",
       "2020-11-25  Malaysia      59817      46501     345   12971\n",
       "2020-11-26  Malaysia      60752      49056     348   11348\n",
       "2020-11-27  Malaysia      61861      50204     350   11307\n",
       "2020-11-28  Malaysia      63176      51314     354   11508\n",
       "\n",
       "[312 rows x 5 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drop unwanted features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Country', 'Confirmed', 'Recovered', 'Deaths', 'Active'], dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia.drop(['Country'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Active</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-22</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-24</th>\n",
       "      <td>58847</td>\n",
       "      <td>44153</td>\n",
       "      <td>341</td>\n",
       "      <td>14353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-25</th>\n",
       "      <td>59817</td>\n",
       "      <td>46501</td>\n",
       "      <td>345</td>\n",
       "      <td>12971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-26</th>\n",
       "      <td>60752</td>\n",
       "      <td>49056</td>\n",
       "      <td>348</td>\n",
       "      <td>11348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-27</th>\n",
       "      <td>61861</td>\n",
       "      <td>50204</td>\n",
       "      <td>350</td>\n",
       "      <td>11307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-28</th>\n",
       "      <td>63176</td>\n",
       "      <td>51314</td>\n",
       "      <td>354</td>\n",
       "      <td>11508</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>312 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Confirmed  Recovered  Deaths  Active\n",
       "Date                                            \n",
       "2020-01-22          0          0       0       0\n",
       "2020-01-23          0          0       0       0\n",
       "2020-01-24          0          0       0       0\n",
       "2020-01-25          3          0       0       3\n",
       "2020-01-26          4          0       0       4\n",
       "...               ...        ...     ...     ...\n",
       "2020-11-24      58847      44153     341   14353\n",
       "2020-11-25      59817      46501     345   12971\n",
       "2020-11-26      60752      49056     348   11348\n",
       "2020-11-27      61861      50204     350   11307\n",
       "2020-11-28      63176      51314     354   11508\n",
       "\n",
       "[312 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Active</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</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>307</th>\n",
       "      <td>2020-11-24</td>\n",
       "      <td>58847</td>\n",
       "      <td>44153</td>\n",
       "      <td>341</td>\n",
       "      <td>14353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>2020-11-25</td>\n",
       "      <td>59817</td>\n",
       "      <td>46501</td>\n",
       "      <td>345</td>\n",
       "      <td>12971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>60752</td>\n",
       "      <td>49056</td>\n",
       "      <td>348</td>\n",
       "      <td>11348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>61861</td>\n",
       "      <td>50204</td>\n",
       "      <td>350</td>\n",
       "      <td>11307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>2020-11-28</td>\n",
       "      <td>63176</td>\n",
       "      <td>51314</td>\n",
       "      <td>354</td>\n",
       "      <td>11508</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>312 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Confirmed  Recovered  Deaths  Active\n",
       "0   2020-01-22          0          0       0       0\n",
       "1   2020-01-23          0          0       0       0\n",
       "2   2020-01-24          0          0       0       0\n",
       "3   2020-01-25          3          0       0       3\n",
       "4   2020-01-26          4          0       0       4\n",
       "..         ...        ...        ...     ...     ...\n",
       "307 2020-11-24      58847      44153     341   14353\n",
       "308 2020-11-25      59817      46501     345   12971\n",
       "309 2020-11-26      60752      49056     348   11348\n",
       "310 2020-11-27      61861      50204     350   11307\n",
       "311 2020-11-28      63176      51314     354   11508\n",
       "\n",
       "[312 rows x 5 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"ConfirmDiff\"] = malaysia[\"Confirmed\"].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"DeathsDiff\"] = malaysia[\"Deaths\"].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"RecoverDiff\"] = malaysia[\"Recovered\"].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"ActiveDiff\"] = malaysia[\"Active\"].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
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       "      <th>3</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Confirmed  Recovered  Deaths  Active  ConfirmDiff  DeathsDiff  RecoverDiff  ActiveDiff\n",
       "0 2020-01-22          0          0       0       0          NaN         NaN          NaN         NaN\n",
       "1 2020-01-23          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "2 2020-01-24          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "3 2020-01-25          3          0       0       3          3.0         0.0          0.0         3.0\n",
       "4 2020-01-26          4          0       0       4          1.0         0.0          0.0         1.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia.reset_index(inplace=True, drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>3</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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      ],
      "text/plain": [
       "        Date  Confirmed  Recovered  Deaths  Active  ConfirmDiff  DeathsDiff  RecoverDiff  ActiveDiff\n",
       "0 2020-01-22          0          0       0       0          NaN         NaN          NaN         NaN\n",
       "1 2020-01-23          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "2 2020-01-24          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "3 2020-01-25          3          0       0       3          3.0         0.0          0.0         3.0\n",
       "4 2020-01-26          4          0       0       4          1.0         0.0          0.0         1.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 312 entries, 0 to 311\n",
      "Data columns (total 9 columns):\n",
      " #   Column       Non-Null Count  Dtype         \n",
      "---  ------       --------------  -----         \n",
      " 0   Date         312 non-null    datetime64[ns]\n",
      " 1   Confirmed    312 non-null    int64         \n",
      " 2   Recovered    312 non-null    int64         \n",
      " 3   Deaths       312 non-null    int64         \n",
      " 4   Active       312 non-null    int64         \n",
      " 5   ConfirmDiff  311 non-null    float64       \n",
      " 6   DeathsDiff   311 non-null    float64       \n",
      " 7   RecoverDiff  311 non-null    float64       \n",
      " 8   ActiveDiff   311 non-null    float64       \n",
      "dtypes: datetime64[ns](1), float64(4), int64(4)\n",
      "memory usage: 22.1 KB\n"
     ]
    }
   ],
   "source": [
    "malaysia.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia.replace(to_replace=np.nan, value=0.0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Confirmed  Recovered  Deaths  Active  ConfirmDiff  DeathsDiff  RecoverDiff  ActiveDiff\n",
       "0 2020-01-22          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "1 2020-01-23          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "2 2020-01-24          0          0       0       0          0.0         0.0          0.0         0.0\n",
       "3 2020-01-25          3          0       0       3          3.0         0.0          0.0         3.0\n",
       "4 2020-01-26          4          0       0       4          1.0         0.0          0.0         1.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Treat Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date           0\n",
       "Confirmed      0\n",
       "Recovered      0\n",
       "Deaths         0\n",
       "Active         0\n",
       "ConfirmDiff    0\n",
       "DeathsDiff     0\n",
       "RecoverDiff    0\n",
       "ActiveDiff     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"Month\"] = malaysia[\"Date\"].dt.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"Day\"] = malaysia[\"Date\"].dt.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Confirmed  Recovered  Deaths  Active  ConfirmDiff  DeathsDiff  RecoverDiff  ActiveDiff  Month  Day\n",
       "0 2020-01-22          0          0       0       0          0.0         0.0          0.0         0.0      1   22\n",
       "1 2020-01-23          0          0       0       0          0.0         0.0          0.0         0.0      1   23\n",
       "2 2020-01-24          0          0       0       0          0.0         0.0          0.0         0.0      1   24\n",
       "3 2020-01-25          3          0       0       3          3.0         0.0          0.0         3.0      1   25\n",
       "4 2020-01-26          4          0       0       4          1.0         0.0          0.0         1.0      1   26"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Confirmed', 'Recovered', 'Deaths', 'Active', 'ConfirmDiff', 'DeathsDiff', 'RecoverDiff', 'ActiveDiff', 'Month', 'Day'], dtype='object')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia.drop(['Date','Confirmed', 'Recovered', 'Deaths', 'Active', 'ActiveDiff'],axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ConfirmDiff</th>\n",
       "      <th>DeathsDiff</th>\n",
       "      <th>RecoverDiff</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
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       "      <th>0</th>\n",
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      ],
      "text/plain": [
       "   ConfirmDiff  DeathsDiff  RecoverDiff  Month  Day\n",
       "0          0.0         0.0          0.0      1   22\n",
       "1          0.0         0.0          0.0      1   23\n",
       "2          0.0         0.0          0.0      1   24\n",
       "3          3.0         0.0          0.0      1   25\n",
       "4          1.0         0.0          0.0      1   26"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia = malaysia[['Month', 'Day','ConfirmDiff','RecoverDiff', 'DeathsDiff']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   Month  Day  ConfirmDiff  RecoverDiff  DeathsDiff\n",
       "0      1   22          0.0          0.0         0.0\n",
       "1      1   23          0.0          0.0         0.0\n",
       "2      1   24          0.0          0.0         0.0\n",
       "3      1   25          3.0          0.0         0.0\n",
       "4      1   26          1.0          0.0         0.0"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaysia.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"Month\"] = malaysia[\"Month\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "malaysia[\"Day\"] = malaysia[\"Day\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 312 entries, 0 to 311\n",
      "Data columns (total 5 columns):\n",
      " #   Column       Non-Null Count  Dtype   \n",
      "---  ------       --------------  -----   \n",
      " 0   Month        312 non-null    category\n",
      " 1   Day          312 non-null    category\n",
      " 2   ConfirmDiff  312 non-null    float64 \n",
      " 3   RecoverDiff  312 non-null    float64 \n",
      " 4   DeathsDiff   312 non-null    float64 \n",
      "dtypes: category(2), float64(3)\n",
      "memory usage: 9.9 KB\n"
     ]
    }
   ],
   "source": [
    "malaysia.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.get_dummies(data=malaysia, drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   ConfirmDiff  RecoverDiff  DeathsDiff  Month_2  Month_3  Month_4  Month_5  Month_6  Month_7  Month_8  Month_9  Month_10  Month_11  Day_2  Day_3  Day_4  Day_5  Day_6  Day_7  Day_8  Day_9  Day_10  Day_11  Day_12  Day_13  Day_14  Day_15  Day_16  Day_17  Day_18  Day_19  Day_20  Day_21  Day_22  Day_23  Day_24  Day_25  Day_26  Day_27  Day_28  Day_29  Day_30  Day_31\n",
       "0          0.0          0.0         0.0        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0       0\n",
       "1          0.0          0.0         0.0        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0\n",
       "2          0.0          0.0         0.0        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0\n",
       "3          3.0          0.0         0.0        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0\n",
       "4          1.0          0.0         0.0        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df2[['Month_2', 'Month_3', 'Month_4', 'Month_5', 'Month_6', 'Month_7', 'Month_8', 'Month_9', \n",
    "           'Month_10', 'Month_11', 'Day_2', 'Day_3', 'Day_4', 'Day_5', 'Day_6', 'Day_7', 'Day_8', 'Day_9', \n",
    "           'Day_10', 'Day_11', 'Day_12', 'Day_13', 'Day_14', 'Day_15', 'Day_16', 'Day_17', 'Day_18', \n",
    "           'Day_19', 'Day_20', 'Day_21', 'Day_22', 'Day_23', 'Day_24', 'Day_25', 'Day_26', 'Day_27', \n",
    "           'Day_28', 'Day_29', 'Day_30', 'Day_31', 'ConfirmDiff', 'RecoverDiff', 'DeathsDiff']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "   Month_2  Month_3  Month_4  Month_5  Month_6  Month_7  Month_8  Month_9  Month_10  Month_11  Day_2  Day_3  Day_4  Day_5  Day_6  Day_7  Day_8  Day_9  Day_10  Day_11  Day_12  Day_13  Day_14  Day_15  Day_16  Day_17  Day_18  Day_19  Day_20  Day_21  Day_22  Day_23  Day_24  Day_25  Day_26  Day_27  Day_28  Day_29  Day_30  Day_31  ConfirmDiff  RecoverDiff  DeathsDiff\n",
       "0        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0       0          0.0          0.0         0.0\n",
       "1        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0          0.0          0.0         0.0\n",
       "2        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0          0.0          0.0         0.0\n",
       "3        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0          3.0          0.0         0.0\n",
       "4        0        0        0        0        0        0        0        0         0         0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0          1.0          0.0         0.0"
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     },
     "execution_count": 37,
     "metadata": {},
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    }
   ],
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  {
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   "execution_count": 38,
   "metadata": {},
   "outputs": [
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       "      <td>4.0</td>\n",
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       "    <tr>\n",
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       "      <td>970.0</td>\n",
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       "      <td>0</td>\n",
       "      <td>935.0</td>\n",
       "      <td>2555.0</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1109.0</td>\n",
       "      <td>1148.0</td>\n",
       "      <td>2.0</td>\n",
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       "    <tr>\n",
       "      <th>311</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1315.0</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Month_2  Month_3  Month_4  Month_5  Month_6  Month_7  Month_8  Month_9  Month_10  Month_11  Day_2  Day_3  Day_4  Day_5  Day_6  Day_7  Day_8  Day_9  Day_10  Day_11  Day_12  Day_13  Day_14  Day_15  Day_16  Day_17  Day_18  Day_19  Day_20  Day_21  Day_22  Day_23  Day_24  Day_25  Day_26  Day_27  Day_28  Day_29  Day_30  Day_31  ConfirmDiff  RecoverDiff  DeathsDiff\n",
       "307        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       2188.0       1673.0         4.0\n",
       "308        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0        970.0       2348.0         4.0\n",
       "309        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0        935.0       2555.0         3.0\n",
       "310        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       1109.0       1148.0         2.0\n",
       "311        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       1315.0       1110.0         4.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = df2.loc[309:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2555.0</td>\n",
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      "text/plain": [
       "     Month_2  Month_3  Month_4  Month_5  Month_6  Month_7  Month_8  Month_9  Month_10  Month_11  Day_2  Day_3  Day_4  Day_5  Day_6  Day_7  Day_8  Day_9  Day_10  Day_11  Day_12  Day_13  Day_14  Day_15  Day_16  Day_17  Day_18  Day_19  Day_20  Day_21  Day_22  Day_23  Day_24  Day_25  Day_26  Day_27  Day_28  Day_29  Day_30  Day_31  ConfirmDiff  RecoverDiff  DeathsDiff\n",
       "309        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0        935.0       2555.0         3.0\n",
       "310        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       1109.0       1148.0         2.0\n",
       "311        0        0        0        0        0        0        0        0         0         1      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       1315.0       1110.0         4.0"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#test.to_csv(\"testcovid.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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