covid-data-cleaning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "102cb6e4-b315-4952-848d-9bfc7c9f9891",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01e32d8b-22b3-4a30-aa7b-c400383245e6",
   "metadata": {},
   "source": [
    "---\n",
    "### State History"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4a1d2912-3d7e-4145-a96b-03c58d8b2280",
   "metadata": {},
   "outputs": [],
   "source": [
    "states_history = pd.read_csv('./datasets/Covid-19-Data/all-states-history.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "00e3e5c5-f8c2-4b15-83dd-936011d3e6cf",
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>death</th>\n",
       "      <th>deathConfirmed</th>\n",
       "      <th>deathIncrease</th>\n",
       "      <th>deathProbable</th>\n",
       "      <th>hospitalized</th>\n",
       "      <th>hospitalizedCumulative</th>\n",
       "      <th>hospitalizedCurrently</th>\n",
       "      <th>hospitalizedIncrease</th>\n",
       "      <th>inIcuCumulative</th>\n",
       "      <th>...</th>\n",
       "      <th>totalTestResults</th>\n",
       "      <th>totalTestResultsIncrease</th>\n",
       "      <th>totalTestsAntibody</th>\n",
       "      <th>totalTestsAntigen</th>\n",
       "      <th>totalTestsPeopleAntibody</th>\n",
       "      <th>totalTestsPeopleAntigen</th>\n",
       "      <th>totalTestsPeopleViral</th>\n",
       "      <th>totalTestsPeopleViralIncrease</th>\n",
       "      <th>totalTestsViral</th>\n",
       "      <th>totalTestsViralIncrease</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2021-03-07</th>\n",
       "      <td>AK</td>\n",
       "      <td>305.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1293.0</td>\n",
       "      <td>1293.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1731628.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1731628.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-07</th>\n",
       "      <td>AL</td>\n",
       "      <td>10148.0</td>\n",
       "      <td>7963.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>2185.0</td>\n",
       "      <td>45976.0</td>\n",
       "      <td>45976.0</td>\n",
       "      <td>494.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2676.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2323788.0</td>\n",
       "      <td>2347</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>119757.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2323788.0</td>\n",
       "      <td>2347</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-07</th>\n",
       "      <td>AR</td>\n",
       "      <td>5319.0</td>\n",
       "      <td>4308.0</td>\n",
       "      <td>22</td>\n",
       "      <td>1011.0</td>\n",
       "      <td>14926.0</td>\n",
       "      <td>14926.0</td>\n",
       "      <td>335.0</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2736442.0</td>\n",
       "      <td>3380</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>481311.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2736442.0</td>\n",
       "      <td>3380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-07</th>\n",
       "      <td>AS</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2140.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2140.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-07</th>\n",
       "      <td>AZ</td>\n",
       "      <td>16328.0</td>\n",
       "      <td>14403.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>57907.0</td>\n",
       "      <td>57907.0</td>\n",
       "      <td>963.0</td>\n",
       "      <td>44</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
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       "      <td>45110</td>\n",
       "      <td>580569.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>444089.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3842945.0</td>\n",
       "      <td>14856</td>\n",
       "      <td>7908105.0</td>\n",
       "      <td>45110</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           state    death  deathConfirmed  deathIncrease  deathProbable  \\\n",
       "date                                                                      \n",
       "2021-03-07    AK    305.0             NaN              0            NaN   \n",
       "2021-03-07    AL  10148.0          7963.0             -1         2185.0   \n",
       "2021-03-07    AR   5319.0          4308.0             22         1011.0   \n",
       "2021-03-07    AS      0.0             NaN              0            NaN   \n",
       "2021-03-07    AZ  16328.0         14403.0              5         1925.0   \n",
       "\n",
       "            hospitalized  hospitalizedCumulative  hospitalizedCurrently  \\\n",
       "date                                                                      \n",
       "2021-03-07        1293.0                  1293.0                   33.0   \n",
       "2021-03-07       45976.0                 45976.0                  494.0   \n",
       "2021-03-07       14926.0                 14926.0                  335.0   \n",
       "2021-03-07           NaN                     NaN                    NaN   \n",
       "2021-03-07       57907.0                 57907.0                  963.0   \n",
       "\n",
       "            hospitalizedIncrease  inIcuCumulative  ...  totalTestResults  \\\n",
       "date                                               ...                     \n",
       "2021-03-07                     0              NaN  ...         1731628.0   \n",
       "2021-03-07                     0           2676.0  ...         2323788.0   \n",
       "2021-03-07                    11              NaN  ...         2736442.0   \n",
       "2021-03-07                     0              NaN  ...            2140.0   \n",
       "2021-03-07                    44              NaN  ...         7908105.0   \n",
       "\n",
       "            totalTestResultsIncrease  totalTestsAntibody  totalTestsAntigen  \\\n",
       "date                                                                          \n",
       "2021-03-07                         0                 NaN                NaN   \n",
       "2021-03-07                      2347                 NaN                NaN   \n",
       "2021-03-07                      3380                 NaN                NaN   \n",
       "2021-03-07                         0                 NaN                NaN   \n",
       "2021-03-07                     45110            580569.0                NaN   \n",
       "\n",
       "            totalTestsPeopleAntibody  totalTestsPeopleAntigen  \\\n",
       "date                                                            \n",
       "2021-03-07                       NaN                      NaN   \n",
       "2021-03-07                  119757.0                      NaN   \n",
       "2021-03-07                       NaN                 481311.0   \n",
       "2021-03-07                       NaN                      NaN   \n",
       "2021-03-07                  444089.0                      NaN   \n",
       "\n",
       "            totalTestsPeopleViral  totalTestsPeopleViralIncrease  \\\n",
       "date                                                               \n",
       "2021-03-07                    NaN                              0   \n",
       "2021-03-07              2323788.0                           2347   \n",
       "2021-03-07                    NaN                              0   \n",
       "2021-03-07                    NaN                              0   \n",
       "2021-03-07              3842945.0                          14856   \n",
       "\n",
       "            totalTestsViral  totalTestsViralIncrease  \n",
       "date                                                  \n",
       "2021-03-07        1731628.0                        0  \n",
       "2021-03-07              NaN                        0  \n",
       "2021-03-07        2736442.0                     3380  \n",
       "2021-03-07           2140.0                        0  \n",
       "2021-03-07        7908105.0                    45110  \n",
       "\n",
       "[5 rows x 40 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "states_history.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5a4845c1-d55a-43db-b2b5-8098462404d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 20780 entries, 2021-03-07 to 2020-01-13\n",
      "Data columns (total 40 columns):\n",
      " #   Column                            Non-Null Count  Dtype  \n",
      "---  ------                            --------------  -----  \n",
      " 0   state                             20780 non-null  object \n",
      " 1   death                             19930 non-null  float64\n",
      " 2   deathConfirmed                    9469 non-null   float64\n",
      " 3   deathIncrease                     20780 non-null  int64  \n",
      " 4   deathProbable                     7593 non-null   float64\n",
      " 5   hospitalized                      12382 non-null  float64\n",
      " 6   hospitalizedCumulative            12382 non-null  float64\n",
      " 7   hospitalizedCurrently             17339 non-null  float64\n",
      " 8   hospitalizedIncrease              20780 non-null  int64  \n",
      " 9   inIcuCumulative                   3789 non-null   float64\n",
      " 10  inIcuCurrently                    11636 non-null  float64\n",
      " 11  negative                          13290 non-null  float64\n",
      " 12  negativeIncrease                  20780 non-null  int64  \n",
      " 13  negativeTestsAntibody             1458 non-null   float64\n",
      " 14  negativeTestsPeopleAntibody       972 non-null    float64\n",
      " 15  negativeTestsViral                5024 non-null   float64\n",
      " 16  onVentilatorCumulative            1290 non-null   float64\n",
      " 17  onVentilatorCurrently             9126 non-null   float64\n",
      " 18  positive                          20592 non-null  float64\n",
      " 19  positiveCasesViral                14246 non-null  float64\n",
      " 20  positiveIncrease                  20780 non-null  int64  \n",
      " 21  positiveScore                     20780 non-null  int64  \n",
      " 22  positiveTestsAntibody             3346 non-null   float64\n",
      " 23  positiveTestsAntigen              2233 non-null   float64\n",
      " 24  positiveTestsPeopleAntibody       1094 non-null   float64\n",
      " 25  positiveTestsPeopleAntigen        633 non-null    float64\n",
      " 26  positiveTestsViral                8958 non-null   float64\n",
      " 27  recovered                         12003 non-null  float64\n",
      " 28  totalTestEncountersViral          5231 non-null   float64\n",
      " 29  totalTestEncountersViralIncrease  20780 non-null  int64  \n",
      " 30  totalTestResults                  20614 non-null  float64\n",
      " 31  totalTestResultsIncrease          20780 non-null  int64  \n",
      " 32  totalTestsAntibody                4789 non-null   float64\n",
      " 33  totalTestsAntigen                 3421 non-null   float64\n",
      " 34  totalTestsPeopleAntibody          2200 non-null   float64\n",
      " 35  totalTestsPeopleAntigen           999 non-null    float64\n",
      " 36  totalTestsPeopleViral             9181 non-null   float64\n",
      " 37  totalTestsPeopleViralIncrease     20780 non-null  int64  \n",
      " 38  totalTestsViral                   14516 non-null  float64\n",
      " 39  totalTestsViralIncrease           20780 non-null  int64  \n",
      "dtypes: float64(30), int64(9), object(1)\n",
      "memory usage: 6.5+ MB\n"
     ]
    }
   ],
   "source": [
    "states_history.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bb56869b-312e-444d-ae8e-96538cb59a1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state                                   0\n",
       "death                                 850\n",
       "deathConfirmed                      11311\n",
       "deathIncrease                           0\n",
       "deathProbable                       13187\n",
       "hospitalized                         8398\n",
       "hospitalizedCumulative               8398\n",
       "hospitalizedCurrently                3441\n",
       "hospitalizedIncrease                    0\n",
       "inIcuCumulative                     16991\n",
       "inIcuCurrently                       9144\n",
       "negative                             7490\n",
       "negativeIncrease                        0\n",
       "negativeTestsAntibody               19322\n",
       "negativeTestsPeopleAntibody         19808\n",
       "negativeTestsViral                  15756\n",
       "onVentilatorCumulative              19490\n",
       "onVentilatorCurrently               11654\n",
       "positive                              188\n",
       "positiveCasesViral                   6534\n",
       "positiveIncrease                        0\n",
       "positiveScore                           0\n",
       "positiveTestsAntibody               17434\n",
       "positiveTestsAntigen                18547\n",
       "positiveTestsPeopleAntibody         19686\n",
       "positiveTestsPeopleAntigen          20147\n",
       "positiveTestsViral                  11822\n",
       "recovered                            8777\n",
       "totalTestEncountersViral            15549\n",
       "totalTestEncountersViralIncrease        0\n",
       "totalTestResults                      166\n",
       "totalTestResultsIncrease                0\n",
       "totalTestsAntibody                  15991\n",
       "totalTestsAntigen                   17359\n",
       "totalTestsPeopleAntibody            18580\n",
       "totalTestsPeopleAntigen             19781\n",
       "totalTestsPeopleViral               11599\n",
       "totalTestsPeopleViralIncrease           0\n",
       "totalTestsViral                      6264\n",
       "totalTestsViralIncrease                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "states_history.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c0b58a6-5bb3-416e-a13a-66aa7233548d",
   "metadata": {},
   "source": [
    "---\n",
    "### LA data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cb82615f-64aa-4126-8161-351192bc403c",
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>county</th>\n",
       "      <th>fips</th>\n",
       "      <th>confirmed_cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>new_confirmed_cases</th>\n",
       "      <th>new_deaths</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>Alameda</td>\n",
       "      <td>1</td>\n",
       "      <td>87940</td>\n",
       "      <td>1657</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>Alpine</td>\n",
       "      <td>3</td>\n",
       "      <td>88</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>Amador</td>\n",
       "      <td>5</td>\n",
       "      <td>3623</td>\n",
       "      <td>47</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>Butte</td>\n",
       "      <td>7</td>\n",
       "      <td>11843</td>\n",
       "      <td>182</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>Calaveras</td>\n",
       "      <td>9</td>\n",
       "      <td>2130</td>\n",
       "      <td>54</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>24851</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>Solano</td>\n",
       "      <td>95</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24852</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>Sonoma</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24853</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>Stanislaus</td>\n",
       "      <td>99</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24854</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>Ventura</td>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24855</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>Yolo</td>\n",
       "      <td>113</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24856 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             date      county  fips  confirmed_cases  deaths  \\\n",
       "0      2021-05-13     Alameda     1            87940    1657   \n",
       "1      2021-05-13      Alpine     3               88       0   \n",
       "2      2021-05-13      Amador     5             3623      47   \n",
       "3      2021-05-13       Butte     7            11843     182   \n",
       "4      2021-05-13   Calaveras     9             2130      54   \n",
       "...           ...         ...   ...              ...     ...   \n",
       "24851  2020-01-26      Solano    95                0       0   \n",
       "24852  2020-01-26      Sonoma    97                0       0   \n",
       "24853  2020-01-26  Stanislaus    99                0       0   \n",
       "24854  2020-01-26     Ventura   111                0       0   \n",
       "24855  2020-01-26        Yolo   113                0       0   \n",
       "\n",
       "       new_confirmed_cases  new_deaths  \n",
       "0                     27.0         0.0  \n",
       "1                      0.0         0.0  \n",
       "2                      0.0         0.0  \n",
       "3                     26.0         0.0  \n",
       "4                      1.0         0.0  \n",
       "...                    ...         ...  \n",
       "24851                  NaN         NaN  \n",
       "24852                  NaN         NaN  \n",
       "24853                  NaN         NaN  \n",
       "24854                  NaN         NaN  \n",
       "24855                  NaN         NaN  \n",
       "\n",
       "[24856 rows x 7 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cali_counties = pd.read_csv('./datasets/Covid-19-Data/latimes-county-totals.csv')\n",
    "cali_counties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "83e540e1-d4d1-4c98-b5ed-3d957c3116f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 24856 entries, 0 to 24855\n",
      "Data columns (total 7 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   date                 24856 non-null  object \n",
      " 1   county               24856 non-null  object \n",
      " 2   fips                 24856 non-null  int64  \n",
      " 3   confirmed_cases      24856 non-null  int64  \n",
      " 4   deaths               24856 non-null  int64  \n",
      " 5   new_confirmed_cases  24798 non-null  float64\n",
      " 6   new_deaths           24798 non-null  float64\n",
      "dtypes: float64(2), int64(3), object(2)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "cali_counties.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1ea2dbd8-60cf-4740-9a3f-05c2a73c11e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date                    0\n",
       "county                  0\n",
       "fips                    0\n",
       "confirmed_cases         0\n",
       "deaths                  0\n",
       "new_confirmed_cases    58\n",
       "new_deaths             58\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cali_counties.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "36af9c81-9794-41b6-8bca-df1cf8b719a6",
   "metadata": {},
   "outputs": [
    {
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       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>24831</th>\n",
       "      <td>2020-01-27</td>\n",
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       "    <tr>\n",
       "      <th>24838</th>\n",
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       "      <td>Los Angeles</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      ],
      "text/plain": [
       "             date       county  fips  confirmed_cases  deaths  \\\n",
       "18     2021-05-13  Los Angeles    37          1236469   24057   \n",
       "76     2021-05-12  Los Angeles    37          1236256   24041   \n",
       "134    2021-05-11  Los Angeles    37          1235999   24021   \n",
       "192    2021-05-10  Los Angeles    37          1235828   24003   \n",
       "250    2021-05-09  Los Angeles    37          1235651   23999   \n",
       "...           ...          ...   ...              ...     ...   \n",
       "24822  2020-01-30  Los Angeles    37                1       0   \n",
       "24825  2020-01-29  Los Angeles    37                1       0   \n",
       "24828  2020-01-28  Los Angeles    37                1       0   \n",
       "24831  2020-01-27  Los Angeles    37                1       0   \n",
       "24838  2020-01-26  Los Angeles    37                1       0   \n",
       "\n",
       "       new_confirmed_cases  new_deaths  \n",
       "18                   213.0        16.0  \n",
       "76                   257.0        20.0  \n",
       "134                  171.0        18.0  \n",
       "192                  177.0         4.0  \n",
       "250                  229.0         4.0  \n",
       "...                    ...         ...  \n",
       "24822                  0.0         0.0  \n",
       "24825                  0.0         0.0  \n",
       "24828                  0.0         0.0  \n",
       "24831                  0.0         0.0  \n",
       "24838                  NaN         NaN  \n",
       "\n",
       "[474 rows x 7 columns]"
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     },
     "execution_count": 9,
     "metadata": {},
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    }
   ],
   "source": [
    "# get LA county\n",
    "la_county = cali_counties.loc[cali_counties.county == 'Los Angeles']\n",
    "la_county"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "387205fc-6109-4030-a8b9-807af3abb928",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-13-c8030aea036c>: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",
      "  la_county['date'] = pd.to_datetime(la_county['date'])\n",
      "/Users/yuli/miniforge3/envs/tf/lib/python3.8/site-packages/pandas/core/frame.py:5582: 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",
      "  return super().sort_index(\n"
     ]
    }
   ],
   "source": [
    "la_county['date'] = pd.to_datetime(la_county['date'])\n",
    "la_county.set_index('date', inplace = True)\n",
    "la_county.sort_index(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8e5f687d-fdb5-41ed-8ffd-0e2da26f4c62",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "                 county  fips  confirmed_cases  deaths  new_confirmed_cases  \\\n",
       "date                                                                          \n",
       "2020-01-26  Los Angeles    37                1       0                  NaN   \n",
       "2020-01-27  Los Angeles    37                1       0                  0.0   \n",
       "\n",
       "            new_deaths  \n",
       "date                    \n",
       "2020-01-26         NaN  \n",
       "2020-01-27         0.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
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   ],
   "source": [
    "la_county.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a654da7d-dbc0-415f-a02a-e58da14cf3c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 474 entries, 2020-01-26 to 2021-05-13\n",
      "Data columns (total 6 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   county               474 non-null    object \n",
      " 1   fips                 474 non-null    int64  \n",
      " 2   confirmed_cases      474 non-null    int64  \n",
      " 3   deaths               474 non-null    int64  \n",
      " 4   new_confirmed_cases  473 non-null    float64\n",
      " 5   new_deaths           473 non-null    float64\n",
      "dtypes: float64(2), int64(3), object(1)\n",
      "memory usage: 25.9+ KB\n"
     ]
    }
   ],
   "source": [
    "la_county.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b61c7b13-dc1a-40a4-8ef0-19224348ea17",
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       "  </tbody>\n",
       "</table>\n",
       "<p>341 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 county  fips  confirmed_cases  deaths  new_confirmed_cases  \\\n",
       "date                                                                          \n",
       "2020-01-26  Los Angeles    37                1       0                  NaN   \n",
       "2020-01-27  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-28  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-29  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-30  Los Angeles    37                1       0                  0.0   \n",
       "...                 ...   ...              ...     ...                  ...   \n",
       "2020-12-27  Los Angeles    37           719960    9485              12497.0   \n",
       "2020-12-28  Los Angeles    37           734860    9564              14900.0   \n",
       "2020-12-29  Los Angeles    37           746666    9806              11806.0   \n",
       "2020-12-30  Los Angeles    37           756840   10068              10174.0   \n",
       "2020-12-31  Los Angeles    37           771519   10359              14679.0   \n",
       "\n",
       "            new_deaths  \n",
       "date                    \n",
       "2020-01-26         NaN  \n",
       "2020-01-27         0.0  \n",
       "2020-01-28         0.0  \n",
       "2020-01-29         0.0  \n",
       "2020-01-30         0.0  \n",
       "...                ...  \n",
       "2020-12-27        44.0  \n",
       "2020-12-28        79.0  \n",
       "2020-12-29       242.0  \n",
       "2020-12-30       262.0  \n",
       "2020-12-31       291.0  \n",
       "\n",
       "[341 rows x 6 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# locate only 2020 rows\n",
    "la_county_2020 = la_county.loc['2020']\n",
    "la_county_2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "60513e1d-173c-4e7f-aace-316bef85c402",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yuli/miniforge3/envs/tf/lib/python3.8/site-packages/pandas/core/frame.py:4524: 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",
      "  return super().replace(\n"
     ]
    }
   ],
   "source": [
    "# replace NaN with zeroes since on January 26 2020 there was only one covid-19\n",
    "# case in LA on this date (first case), no death and no new cases\n",
    "la_county_2020.replace({np.nan: 0}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2810acf3-fb50-41e1-89fb-7806629311f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 341 entries, 2020-01-26 to 2020-12-31\n",
      "Data columns (total 6 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   county               341 non-null    object \n",
      " 1   fips                 341 non-null    int64  \n",
      " 2   confirmed_cases      341 non-null    int64  \n",
      " 3   deaths               341 non-null    int64  \n",
      " 4   new_confirmed_cases  341 non-null    float64\n",
      " 5   new_deaths           341 non-null    float64\n",
      "dtypes: float64(2), int64(3), object(1)\n",
      "memory usage: 18.6+ KB\n"
     ]
    }
   ],
   "source": [
    "la_county_2020.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4210d0a7-cd1d-4012-8d07-e5f4a690f012",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>county</th>\n",
       "      <th>fips</th>\n",
       "      <th>confirmed_cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>new_confirmed_cases</th>\n",
       "      <th>new_deaths</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",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-27</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-28</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-29</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-30</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 county  fips  confirmed_cases  deaths  new_confirmed_cases  \\\n",
       "date                                                                          \n",
       "2020-01-26  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-27  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-28  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-29  Los Angeles    37                1       0                  0.0   \n",
       "2020-01-30  Los Angeles    37                1       0                  0.0   \n",
       "\n",
       "            new_deaths  \n",
       "date                    \n",
       "2020-01-26         0.0  \n",
       "2020-01-27         0.0  \n",
       "2020-01-28         0.0  \n",
       "2020-01-29         0.0  \n",
       "2020-01-30         0.0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "la_county_2020.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b37d43f9-7d65-44a0-baa1-b023c0474233",
   "metadata": {},
   "outputs": [],
   "source": [
    "# save df\n",
    "la_county_2020.to_csv('./datasets/Covid-19-Data/LA_county_covid_2020.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d88a0b45-83b8-455f-a6ca-555e44fb79e4",
   "metadata": {},
   "source": [
    "---\n",
    "### NYC data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b741c806-d275-4263-9a73-88ca8eb3d59f",
   "metadata": {},
   "outputs": [
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>03/03/2020</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03/04/2020</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>05/09/2021</td>\n",
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       "      <td>47</td>\n",
       "      <td>23</td>\n",
       "      <td>5</td>\n",
       "      <td>658</td>\n",
       "      <td>874</td>\n",
       "      <td>64</td>\n",
       "      <td>26</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>57</td>\n",
       "      <td>74</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>11000</td>\n",
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       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>05/10/2021</td>\n",
       "      <td>635</td>\n",
       "      <td>188</td>\n",
       "      <td>52</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>621</td>\n",
       "      <td>821</td>\n",
       "      <td>60</td>\n",
       "      <td>26</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>70</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>595</td>\n",
       "      <td>168</td>\n",
       "      <td>48</td>\n",
       "      <td>13</td>\n",
       "      <td>6</td>\n",
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       "      <td>55</td>\n",
       "      <td>24</td>\n",
       "      <td>...</td>\n",
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       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11000</td>\n",
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       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>05/12/2021</td>\n",
       "      <td>533</td>\n",
       "      <td>138</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>553</td>\n",
       "      <td>729</td>\n",
       "      <td>48</td>\n",
       "      <td>22</td>\n",
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       "      <td>12</td>\n",
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       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>66</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11000</td>\n",
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       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>05/13/2021</td>\n",
       "      <td>411</td>\n",
       "      <td>114</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
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       "      <td>663</td>\n",
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       "      <td>8</td>\n",
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       "      <td>0</td>\n",
       "      <td>50</td>\n",
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       "      <td>2</td>\n",
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       "      <td>11000</td>\n",
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       "<p>440 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    DATE_OF_INTEREST  CASE_COUNT  probable_case_count  HOSPITALIZED_COUNT  \\\n",
       "0         02/29/2020           1                    0                   1   \n",
       "1         03/01/2020           0                    0                   1   \n",
       "2         03/02/2020           0                    0                   2   \n",
       "3         03/03/2020           1                    0                   7   \n",
       "4         03/04/2020           5                    0                   2   \n",
       "..               ...         ...                  ...                 ...   \n",
       "435       05/09/2021         311                  142                  47   \n",
       "436       05/10/2021         635                  188                  52   \n",
       "437       05/11/2021         595                  168                  48   \n",
       "438       05/12/2021         533                  138                  14   \n",
       "439       05/13/2021         411                  114                   5   \n",
       "\n",
       "     DEATH_COUNT  DEATH_COUNT_PROBABLE  CASE_COUNT_7DAY_AVG  \\\n",
       "0              0                     0                    0   \n",
       "1              0                     0                    0   \n",
       "2              0                     0                    0   \n",
       "3              0                     0                    0   \n",
       "4              0                     0                    0   \n",
       "..           ...                   ...                  ...   \n",
       "435           23                     5                  658   \n",
       "436           23                     4                  621   \n",
       "437           13                     6                  586   \n",
       "438           13                     7                  553   \n",
       "439            9                    11                  506   \n",
       "\n",
       "     all_case_count_7day_avg  HOSP_COUNT_7DAY_AVG  DEATH_COUNT_7DAY_AVG  ...  \\\n",
       "0                          0                    0                     0  ...   \n",
       "1                          0                    0                     0  ...   \n",
       "2                          0                    0                     0  ...   \n",
       "3                          0                    0                     0  ...   \n",
       "4                          0                    0                     0  ...   \n",
       "..                       ...                  ...                   ...  ...   \n",
       "435                      874                   64                    26  ...   \n",
       "436                      821                   60                    26  ...   \n",
       "437                      775                   55                    24  ...   \n",
       "438                      729                   48                    22  ...   \n",
       "439                      663                   39                    20  ...   \n",
       "\n",
       "     si_probable_case_count  SI_HOSPITALIZED_COUNT  SI_DEATH_COUNT  \\\n",
       "0                         0                      0               0   \n",
       "1                         0                      0               0   \n",
       "2                         0                      0               0   \n",
       "3                         0                      0               0   \n",
       "4                         0                      0               0   \n",
       "..                      ...                    ...             ...   \n",
       "435                       9                      1               1   \n",
       "436                      10                      1               1   \n",
       "437                      19                      3               1   \n",
       "438                      12                      0               2   \n",
       "439                       8                      0               0   \n",
       "\n",
       "     si_probable_death_count  SI_CASE_COUNT_7DAY_AVG  \\\n",
       "0                          0                       0   \n",
       "1                          0                       0   \n",
       "2                          0                       0   \n",
       "3                          0                       0   \n",
       "4                          0                       0   \n",
       "..                       ...                     ...   \n",
       "435                        0                      57   \n",
       "436                        1                      54   \n",
       "437                        0                      52   \n",
       "438                        0                      52   \n",
       "439                        0                      50   \n",
       "\n",
       "     si_all_case_count_7day_avg  SI_HOSPITALIZED_COUNT_7DAY_AVG  \\\n",
       "0                             0                               0   \n",
       "1                             0                               0   \n",
       "2                             0                               0   \n",
       "3                             0                               0   \n",
       "4                             0                               0   \n",
       "..                          ...                             ...   \n",
       "435                          74                               3   \n",
       "436                          70                               2   \n",
       "437                          67                               2   \n",
       "438                          66                               2   \n",
       "439                          64                               1   \n",
       "\n",
       "     SI_DEATH_COUNT_7DAY_AVG  si_all_death_count_7day_avg  INCOMPLETE  \n",
       "0                          0                            0           0  \n",
       "1                          0                            0           0  \n",
       "2                          0                            0           0  \n",
       "3                          0                            0           0  \n",
       "4                          0                            0           0  \n",
       "..                       ...                          ...         ...  \n",
       "435                        3                            3       11000  \n",
       "436                        2                            3       11000  \n",
       "437                        2                            2       11000  \n",
       "438                        2                            2       11000  \n",
       "439                        2                            2       11000  \n",
       "\n",
       "[440 rows x 62 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc = pd.read_csv('./datasets/Covid-19-Data/NYC_COVID-19_Daily_Counts_of_Cases_Hospitalizations_and_Deaths.csv')\n",
    "nyc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6bee13d3-fead-4153-8108-3a98cc2ce978",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yuli/miniforge3/envs/tf/lib/python3.8/site-packages/pandas/core/indexing.py:1637: 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_single_block(indexer, value, name)\n"
     ]
    }
   ],
   "source": [
    "# make date in correct ISO8601 format\n",
    "for i in range(0, nyc.shape[0]):\n",
    "    nyc['DATE_OF_INTEREST'].iloc[i] = '-'.join([nyc['DATE_OF_INTEREST'][i].split('/')[2], nyc['DATE_OF_INTEREST'][i].split('/')[0], nyc['DATE_OF_INTEREST'][i].split('/')[1]])\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f844d716-7ed4-419c-abc8-4b14af69c9cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE_OF_INTEREST</th>\n",
       "      <th>CASE_COUNT</th>\n",
       "      <th>probable_case_count</th>\n",
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       "      <th>DEATH_COUNT</th>\n",
       "      <th>DEATH_COUNT_PROBABLE</th>\n",
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       "      <th>HOSP_COUNT_7DAY_AVG</th>\n",
       "      <th>DEATH_COUNT_7DAY_AVG</th>\n",
       "      <th>...</th>\n",
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       "      <th>si_probable_death_count</th>\n",
       "      <th>SI_CASE_COUNT_7DAY_AVG</th>\n",
       "      <th>si_all_case_count_7day_avg</th>\n",
       "      <th>SI_HOSPITALIZED_COUNT_7DAY_AVG</th>\n",
       "      <th>SI_DEATH_COUNT_7DAY_AVG</th>\n",
       "      <th>si_all_death_count_7day_avg</th>\n",
       "      <th>INCOMPLETE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-29</td>\n",
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       "    <tr>\n",
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       "      <td>2020-03-02</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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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>5</td>\n",
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       "      <th>435</th>\n",
       "      <td>2021-05-09</td>\n",
       "      <td>311</td>\n",
       "      <td>142</td>\n",
       "      <td>47</td>\n",
       "      <td>23</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2021-05-10</td>\n",
       "      <td>635</td>\n",
       "      <td>188</td>\n",
       "      <td>52</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>621</td>\n",
       "      <td>821</td>\n",
       "      <td>60</td>\n",
       "      <td>26</td>\n",
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       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>70</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2021-05-11</td>\n",
       "      <td>595</td>\n",
       "      <td>168</td>\n",
       "      <td>48</td>\n",
       "      <td>13</td>\n",
       "      <td>6</td>\n",
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       "      <td>55</td>\n",
       "      <td>24</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
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       "      <td>52</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2021-05-12</td>\n",
       "      <td>533</td>\n",
       "      <td>138</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>553</td>\n",
       "      <td>729</td>\n",
       "      <td>48</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>66</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>411</td>\n",
       "      <td>114</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>506</td>\n",
       "      <td>663</td>\n",
       "      <td>39</td>\n",
       "      <td>20</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>64</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>440 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    DATE_OF_INTEREST  CASE_COUNT  probable_case_count  HOSPITALIZED_COUNT  \\\n",
       "0         2020-02-29           1                    0                   1   \n",
       "1         2020-03-01           0                    0                   1   \n",
       "2         2020-03-02           0                    0                   2   \n",
       "3         2020-03-03           1                    0                   7   \n",
       "4         2020-03-04           5                    0                   2   \n",
       "..               ...         ...                  ...                 ...   \n",
       "435       2021-05-09         311                  142                  47   \n",
       "436       2021-05-10         635                  188                  52   \n",
       "437       2021-05-11         595                  168                  48   \n",
       "438       2021-05-12         533                  138                  14   \n",
       "439       2021-05-13         411                  114                   5   \n",
       "\n",
       "     DEATH_COUNT  DEATH_COUNT_PROBABLE  CASE_COUNT_7DAY_AVG  \\\n",
       "0              0                     0                    0   \n",
       "1              0                     0                    0   \n",
       "2              0                     0                    0   \n",
       "3              0                     0                    0   \n",
       "4              0                     0                    0   \n",
       "..           ...                   ...                  ...   \n",
       "435           23                     5                  658   \n",
       "436           23                     4                  621   \n",
       "437           13                     6                  586   \n",
       "438           13                     7                  553   \n",
       "439            9                    11                  506   \n",
       "\n",
       "     all_case_count_7day_avg  HOSP_COUNT_7DAY_AVG  DEATH_COUNT_7DAY_AVG  ...  \\\n",
       "0                          0                    0                     0  ...   \n",
       "1                          0                    0                     0  ...   \n",
       "2                          0                    0                     0  ...   \n",
       "3                          0                    0                     0  ...   \n",
       "4                          0                    0                     0  ...   \n",
       "..                       ...                  ...                   ...  ...   \n",
       "435                      874                   64                    26  ...   \n",
       "436                      821                   60                    26  ...   \n",
       "437                      775                   55                    24  ...   \n",
       "438                      729                   48                    22  ...   \n",
       "439                      663                   39                    20  ...   \n",
       "\n",
       "     si_probable_case_count  SI_HOSPITALIZED_COUNT  SI_DEATH_COUNT  \\\n",
       "0                         0                      0               0   \n",
       "1                         0                      0               0   \n",
       "2                         0                      0               0   \n",
       "3                         0                      0               0   \n",
       "4                         0                      0               0   \n",
       "..                      ...                    ...             ...   \n",
       "435                       9                      1               1   \n",
       "436                      10                      1               1   \n",
       "437                      19                      3               1   \n",
       "438                      12                      0               2   \n",
       "439                       8                      0               0   \n",
       "\n",
       "     si_probable_death_count  SI_CASE_COUNT_7DAY_AVG  \\\n",
       "0                          0                       0   \n",
       "1                          0                       0   \n",
       "2                          0                       0   \n",
       "3                          0                       0   \n",
       "4                          0                       0   \n",
       "..                       ...                     ...   \n",
       "435                        0                      57   \n",
       "436                        1                      54   \n",
       "437                        0                      52   \n",
       "438                        0                      52   \n",
       "439                        0                      50   \n",
       "\n",
       "     si_all_case_count_7day_avg  SI_HOSPITALIZED_COUNT_7DAY_AVG  \\\n",
       "0                             0                               0   \n",
       "1                             0                               0   \n",
       "2                             0                               0   \n",
       "3                             0                               0   \n",
       "4                             0                               0   \n",
       "..                          ...                             ...   \n",
       "435                          74                               3   \n",
       "436                          70                               2   \n",
       "437                          67                               2   \n",
       "438                          66                               2   \n",
       "439                          64                               1   \n",
       "\n",
       "     SI_DEATH_COUNT_7DAY_AVG  si_all_death_count_7day_avg  INCOMPLETE  \n",
       "0                          0                            0           0  \n",
       "1                          0                            0           0  \n",
       "2                          0                            0           0  \n",
       "3                          0                            0           0  \n",
       "4                          0                            0           0  \n",
       "..                       ...                          ...         ...  \n",
       "435                        3                            3       11000  \n",
       "436                        2                            3       11000  \n",
       "437                        2                            2       11000  \n",
       "438                        2                            2       11000  \n",
       "439                        2                            2       11000  \n",
       "\n",
       "[440 rows x 62 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e93abd61-e5e0-4220-91c9-23cadcdeba86",
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc.rename(columns={'DATE_OF_INTEREST': 'date'}, inplace=True)\n",
    "nyc['date'] = pd.to_datetime(nyc['date'])\n",
    "nyc.set_index('date', inplace = True)\n",
    "nyc.sort_index(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "48ebb6db-13a4-409e-8033-df06972638b8",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 440 entries, 2020-02-29 to 2021-05-13\n",
      "Data columns (total 61 columns):\n",
      " #   Column                          Non-Null Count  Dtype\n",
      "---  ------                          --------------  -----\n",
      " 0   CASE_COUNT                      440 non-null    int64\n",
      " 1   probable_case_count             440 non-null    int64\n",
      " 2   HOSPITALIZED_COUNT              440 non-null    int64\n",
      " 3   DEATH_COUNT                     440 non-null    int64\n",
      " 4   DEATH_COUNT_PROBABLE            440 non-null    int64\n",
      " 5   CASE_COUNT_7DAY_AVG             440 non-null    int64\n",
      " 6   all_case_count_7day_avg         440 non-null    int64\n",
      " 7   HOSP_COUNT_7DAY_AVG             440 non-null    int64\n",
      " 8   DEATH_COUNT_7DAY_AVG            440 non-null    int64\n",
      " 9   all_death_count_7day_avg        440 non-null    int64\n",
      " 10  BX_CASE_COUNT                   440 non-null    int64\n",
      " 11  bx_probable_case_count          440 non-null    int64\n",
      " 12  BX_HOSPITALIZED_COUNT           440 non-null    int64\n",
      " 13  BX_DEATH_COUNT                  440 non-null    int64\n",
      " 14  bx_probable_death_count         440 non-null    int64\n",
      " 15  BX_CASE_COUNT_7DAY_AVG          440 non-null    int64\n",
      " 16  bx_all_case_count_7day_avg      440 non-null    int64\n",
      " 17  BX_HOSPITALIZED_COUNT_7DAY_AVG  440 non-null    int64\n",
      " 18  BX_DEATH_COUNT_7DAY_AVG         440 non-null    int64\n",
      " 19  bx_all_death_count_7day_avg     440 non-null    int64\n",
      " 20  BK_CASE_COUNT                   440 non-null    int64\n",
      " 21  bk_probable_case_count          440 non-null    int64\n",
      " 22  BK_HOSPITALIZED_COUNT           440 non-null    int64\n",
      " 23  BK_DEATH_COUNT                  440 non-null    int64\n",
      " 24  bk_probable_death_count         440 non-null    int64\n",
      " 25  BK_CASE_COUNT_7DAY_AVG          440 non-null    int64\n",
      " 26  bk_all_case_count_7day_avg      440 non-null    int64\n",
      " 27  BK_HOSPITALIZED_COUNT_7DAY_AVG  440 non-null    int64\n",
      " 28  BK_DEATH_COUNT_7DAY_AVG         440 non-null    int64\n",
      " 29  bk_all_death_count_7day_avg     440 non-null    int64\n",
      " 30  MN_CASE_COUNT                   440 non-null    int64\n",
      " 31  mn_probable_case_count          440 non-null    int64\n",
      " 32  MN_HOSPITALIZED_COUNT           440 non-null    int64\n",
      " 33  MN_DEATH_COUNT                  440 non-null    int64\n",
      " 34  mn_probable_death_count         440 non-null    int64\n",
      " 35  MN_CASE_COUNT_7DAY_AVG          440 non-null    int64\n",
      " 36  mn_all_case_count_7day_avg      440 non-null    int64\n",
      " 37  MN_HOSPITALIZED_COUNT_7DAY_AVG  440 non-null    int64\n",
      " 38  MN_DEATH_COUNT_7DAY_AVG         440 non-null    int64\n",
      " 39  mn_all_death_count_7day_avg     440 non-null    int64\n",
      " 40  QN_CASE_COUNT                   440 non-null    int64\n",
      " 41  qn_probable_case_count          440 non-null    int64\n",
      " 42  QN_HOSPITALIZED_COUNT           440 non-null    int64\n",
      " 43  QN_DEATH_COUNT                  440 non-null    int64\n",
      " 44  qn_probable_death_count         440 non-null    int64\n",
      " 45  QN_CASE_COUNT_7DAY_AVG          440 non-null    int64\n",
      " 46  qn_all_case_count_7day_avg      440 non-null    int64\n",
      " 47  QN_HOSPITALIZED_COUNT_7DAY_AVG  440 non-null    int64\n",
      " 48  QN_DEATH_COUNT_7DAY_AVG         440 non-null    int64\n",
      " 49  qn_all_death_count_7day_avg     440 non-null    int64\n",
      " 50  SI_CASE_COUNT                   440 non-null    int64\n",
      " 51  si_probable_case_count          440 non-null    int64\n",
      " 52  SI_HOSPITALIZED_COUNT           440 non-null    int64\n",
      " 53  SI_DEATH_COUNT                  440 non-null    int64\n",
      " 54  si_probable_death_count         440 non-null    int64\n",
      " 55  SI_CASE_COUNT_7DAY_AVG          440 non-null    int64\n",
      " 56  si_all_case_count_7day_avg      440 non-null    int64\n",
      " 57  SI_HOSPITALIZED_COUNT_7DAY_AVG  440 non-null    int64\n",
      " 58  SI_DEATH_COUNT_7DAY_AVG         440 non-null    int64\n",
      " 59  si_all_death_count_7day_avg     440 non-null    int64\n",
      " 60  INCOMPLETE                      440 non-null    int64\n",
      "dtypes: int64(61)\n",
      "memory usage: 213.1 KB\n"
     ]
    }
   ],
   "source": [
    "nyc.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d3b5173f-c0e5-47e1-9f9b-c48e8eca21ff",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 307 entries, 2020-02-29 to 2020-12-31\n",
      "Data columns (total 61 columns):\n",
      " #   Column                          Non-Null Count  Dtype\n",
      "---  ------                          --------------  -----\n",
      " 0   CASE_COUNT                      307 non-null    int64\n",
      " 1   probable_case_count             307 non-null    int64\n",
      " 2   HOSPITALIZED_COUNT              307 non-null    int64\n",
      " 3   DEATH_COUNT                     307 non-null    int64\n",
      " 4   DEATH_COUNT_PROBABLE            307 non-null    int64\n",
      " 5   CASE_COUNT_7DAY_AVG             307 non-null    int64\n",
      " 6   all_case_count_7day_avg         307 non-null    int64\n",
      " 7   HOSP_COUNT_7DAY_AVG             307 non-null    int64\n",
      " 8   DEATH_COUNT_7DAY_AVG            307 non-null    int64\n",
      " 9   all_death_count_7day_avg        307 non-null    int64\n",
      " 10  BX_CASE_COUNT                   307 non-null    int64\n",
      " 11  bx_probable_case_count          307 non-null    int64\n",
      " 12  BX_HOSPITALIZED_COUNT           307 non-null    int64\n",
      " 13  BX_DEATH_COUNT                  307 non-null    int64\n",
      " 14  bx_probable_death_count         307 non-null    int64\n",
      " 15  BX_CASE_COUNT_7DAY_AVG          307 non-null    int64\n",
      " 16  bx_all_case_count_7day_avg      307 non-null    int64\n",
      " 17  BX_HOSPITALIZED_COUNT_7DAY_AVG  307 non-null    int64\n",
      " 18  BX_DEATH_COUNT_7DAY_AVG         307 non-null    int64\n",
      " 19  bx_all_death_count_7day_avg     307 non-null    int64\n",
      " 20  BK_CASE_COUNT                   307 non-null    int64\n",
      " 21  bk_probable_case_count          307 non-null    int64\n",
      " 22  BK_HOSPITALIZED_COUNT           307 non-null    int64\n",
      " 23  BK_DEATH_COUNT                  307 non-null    int64\n",
      " 24  bk_probable_death_count         307 non-null    int64\n",
      " 25  BK_CASE_COUNT_7DAY_AVG          307 non-null    int64\n",
      " 26  bk_all_case_count_7day_avg      307 non-null    int64\n",
      " 27  BK_HOSPITALIZED_COUNT_7DAY_AVG  307 non-null    int64\n",
      " 28  BK_DEATH_COUNT_7DAY_AVG         307 non-null    int64\n",
      " 29  bk_all_death_count_7day_avg     307 non-null    int64\n",
      " 30  MN_CASE_COUNT                   307 non-null    int64\n",
      " 31  mn_probable_case_count          307 non-null    int64\n",
      " 32  MN_HOSPITALIZED_COUNT           307 non-null    int64\n",
      " 33  MN_DEATH_COUNT                  307 non-null    int64\n",
      " 34  mn_probable_death_count         307 non-null    int64\n",
      " 35  MN_CASE_COUNT_7DAY_AVG          307 non-null    int64\n",
      " 36  mn_all_case_count_7day_avg      307 non-null    int64\n",
      " 37  MN_HOSPITALIZED_COUNT_7DAY_AVG  307 non-null    int64\n",
      " 38  MN_DEATH_COUNT_7DAY_AVG         307 non-null    int64\n",
      " 39  mn_all_death_count_7day_avg     307 non-null    int64\n",
      " 40  QN_CASE_COUNT                   307 non-null    int64\n",
      " 41  qn_probable_case_count          307 non-null    int64\n",
      " 42  QN_HOSPITALIZED_COUNT           307 non-null    int64\n",
      " 43  QN_DEATH_COUNT                  307 non-null    int64\n",
      " 44  qn_probable_death_count         307 non-null    int64\n",
      " 45  QN_CASE_COUNT_7DAY_AVG          307 non-null    int64\n",
      " 46  qn_all_case_count_7day_avg      307 non-null    int64\n",
      " 47  QN_HOSPITALIZED_COUNT_7DAY_AVG  307 non-null    int64\n",
      " 48  QN_DEATH_COUNT_7DAY_AVG         307 non-null    int64\n",
      " 49  qn_all_death_count_7day_avg     307 non-null    int64\n",
      " 50  SI_CASE_COUNT                   307 non-null    int64\n",
      " 51  si_probable_case_count          307 non-null    int64\n",
      " 52  SI_HOSPITALIZED_COUNT           307 non-null    int64\n",
      " 53  SI_DEATH_COUNT                  307 non-null    int64\n",
      " 54  si_probable_death_count         307 non-null    int64\n",
      " 55  SI_CASE_COUNT_7DAY_AVG          307 non-null    int64\n",
      " 56  si_all_case_count_7day_avg      307 non-null    int64\n",
      " 57  SI_HOSPITALIZED_COUNT_7DAY_AVG  307 non-null    int64\n",
      " 58  SI_DEATH_COUNT_7DAY_AVG         307 non-null    int64\n",
      " 59  si_all_death_count_7day_avg     307 non-null    int64\n",
      " 60  INCOMPLETE                      307 non-null    int64\n",
      "dtypes: int64(61)\n",
      "memory usage: 148.7 KB\n"
     ]
    }
   ],
   "source": [
    "# locate only 2020 rows\n",
    "# first case in NYC was on Feb 29 2020\n",
    "nyc_boroughs_2020 = nyc.loc['2020']\n",
    "nyc_boroughs_2020.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "db7f189f-f655-48a0-9eba-bb866e7bf8eb",
   "metadata": {},
   "outputs": [
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       "      <th>2020-02-29</th>\n",
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       "            CASE_COUNT  probable_case_count  HOSPITALIZED_COUNT  DEATH_COUNT  \\\n",
       "date                                                                           \n",
       "2020-02-29           1                    0                   1            0   \n",
       "2020-03-01           0                    0                   1            0   \n",
       "\n",
       "            DEATH_COUNT_PROBABLE  CASE_COUNT_7DAY_AVG  \\\n",
       "date                                                    \n",
       "2020-02-29                     0                    0   \n",
       "2020-03-01                     0                    0   \n",
       "\n",
       "            all_case_count_7day_avg  HOSP_COUNT_7DAY_AVG  \\\n",
       "date                                                       \n",
       "2020-02-29                        0                    0   \n",
       "2020-03-01                        0                    0   \n",
       "\n",
       "            DEATH_COUNT_7DAY_AVG  all_death_count_7day_avg  ...  \\\n",
       "date                                                        ...   \n",
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       "2020-03-01                     0                         0  ...   \n",
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       "            si_probable_case_count  SI_HOSPITALIZED_COUNT  SI_DEATH_COUNT  \\\n",
       "date                                                                        \n",
       "2020-02-29                       0                      0               0   \n",
       "2020-03-01                       0                      0               0   \n",
       "\n",
       "            si_probable_death_count  SI_CASE_COUNT_7DAY_AVG  \\\n",
       "date                                                          \n",
       "2020-02-29                        0                       0   \n",
       "2020-03-01                        0                       0   \n",
       "\n",
       "            si_all_case_count_7day_avg  SI_HOSPITALIZED_COUNT_7DAY_AVG  \\\n",
       "date                                                                     \n",
       "2020-02-29                           0                               0   \n",
       "2020-03-01                           0                               0   \n",
       "\n",
       "            SI_DEATH_COUNT_7DAY_AVG  si_all_death_count_7day_avg  INCOMPLETE  \n",
       "date                                                                          \n",
       "2020-02-29                        0                            0           0  \n",
       "2020-03-01                        0                            0           0  \n",
       "\n",
       "[2 rows x 61 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "nyc_boroughs_2020.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "47cedb45-8ffb-41e6-be10-a0eec19640dd",
   "metadata": {},
   "outputs": [
    {
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       "      <td>481</td>\n",
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      ],
      "text/plain": [
       "            CASE_COUNT  probable_case_count  HOSPITALIZED_COUNT  DEATH_COUNT  \\\n",
       "date                                                                           \n",
       "2020-12-30        4975                 1062                 320           40   \n",
       "2020-12-31        3386                  780                 287           41   \n",
       "\n",
       "            DEATH_COUNT_PROBABLE  CASE_COUNT_7DAY_AVG  \\\n",
       "date                                                    \n",
       "2020-12-30                     5                 3710   \n",
       "2020-12-31                     1                 3762   \n",
       "\n",
       "            all_case_count_7day_avg  HOSP_COUNT_7DAY_AVG  \\\n",
       "date                                                       \n",
       "2020-12-30                     4614                  294   \n",
       "2020-12-31                     4687                  295   \n",
       "\n",
       "            DEATH_COUNT_7DAY_AVG  all_death_count_7day_avg  ...  \\\n",
       "date                                                        ...   \n",
       "2020-12-30                    41                        44  ...   \n",
       "2020-12-31                    42                        44  ...   \n",
       "\n",
       "            si_probable_case_count  SI_HOSPITALIZED_COUNT  SI_DEATH_COUNT  \\\n",
       "date                                                                        \n",
       "2020-12-30                      92                     19               4   \n",
       "2020-12-31                      71                     19               3   \n",
       "\n",
       "            si_probable_death_count  SI_CASE_COUNT_7DAY_AVG  \\\n",
       "date                                                          \n",
       "2020-12-30                        1                     378   \n",
       "2020-12-31                        0                     399   \n",
       "\n",
       "            si_all_case_count_7day_avg  SI_HOSPITALIZED_COUNT_7DAY_AVG  \\\n",
       "date                                                                     \n",
       "2020-12-30                         457                              17   \n",
       "2020-12-31                         481                              18   \n",
       "\n",
       "            SI_DEATH_COUNT_7DAY_AVG  si_all_death_count_7day_avg  INCOMPLETE  \n",
       "date                                                                          \n",
       "2020-12-30                        6                            6           0  \n",
       "2020-12-31                        6                            6           0  \n",
       "\n",
       "[2 rows x 61 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_boroughs_2020.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "62ce7ead-ef50-44ae-9a2d-5520e4d002a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc_boroughs_2020.to_csv('./datasets/Covid-19-Data/NYC_all_boroughs_covid_2020.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "909d6b83-4473-4319-b425-c45615f7a093",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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