covid_time_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "plt.ion()\n",
    "import pandas as pd\n",
    "\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.width', None)\n",
    "pd.set_option('display.max_colwidth', None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data I have here is from the CSSEGISandData/COVID-19 repository on github. It's provided by Johns Hopkins University Center for Systems Science and Engineering. They are really great for putting this data set together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_country(country):\n",
    "    df = raw[raw['Country/Region'] == country]\n",
    "    df = df.drop(['Province/State', 'Country/Region', 'Lat', 'Long'], axis=1).T.apply(pd.to_numeric)\n",
    "    last_count = df.iloc[[-1]].sum().sum()\n",
    "    df.plot(legend=False, title=country + ' last count: ' + str(last_count))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for a in ['US', 'Italy', 'China']:\n",
    "    plot_country(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So compared to US and Italy, China's data looks really odd. Let's take a deeper dive on that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_cleaned(country):\n",
    "    df = raw[raw['Country/Region'] == country]\n",
    "    df = df.drop(['Province/State', 'Country/Region', 'Lat', 'Long'], axis=1).T\n",
    "\n",
    "    mapping = {}\n",
    "    mapping[list(df.columns)[0]] = \"Total Cases\"\n",
    "\n",
    "    df = df.rename(columns=mapping)\n",
    "    diff = []\n",
    "    acc = 0\n",
    "    for index, row in df.iterrows():\n",
    "        curr = row.iloc[0]\n",
    "        diff.append(curr - acc)\n",
    "        acc = curr\n",
    "    df[\"New Cases\"] = diff\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "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>Total Cases</th>\n",
       "      <th>New Cases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1/22/20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/23/20</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/24/20</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/25/20</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/26/20</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/27/20</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/28/20</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/29/20</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/30/20</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/31/20</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/1/20</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/2/20</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/3/20</th>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/4/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/5/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/6/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/7/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/8/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/9/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/10/20</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/11/20</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/12/20</th>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/13/20</th>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/14/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/15/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/16/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/17/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/18/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/19/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/20/20</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/21/20</th>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/22/20</th>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/23/20</th>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/24/20</th>\n",
       "      <td>51</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/25/20</th>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/26/20</th>\n",
       "      <td>57</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/27/20</th>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/28/20</th>\n",
       "      <td>60</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2/29/20</th>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/1/20</th>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/2/20</th>\n",
       "      <td>98</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/3/20</th>\n",
       "      <td>118</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/4/20</th>\n",
       "      <td>149</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/5/20</th>\n",
       "      <td>217</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/6/20</th>\n",
       "      <td>262</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/7/20</th>\n",
       "      <td>402</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/8/20</th>\n",
       "      <td>518</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/9/20</th>\n",
       "      <td>583</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/10/20</th>\n",
       "      <td>959</td>\n",
       "      <td>376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/11/20</th>\n",
       "      <td>1281</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/12/20</th>\n",
       "      <td>1663</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/13/20</th>\n",
       "      <td>2179</td>\n",
       "      <td>516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/14/20</th>\n",
       "      <td>2727</td>\n",
       "      <td>548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/15/20</th>\n",
       "      <td>3499</td>\n",
       "      <td>772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/16/20</th>\n",
       "      <td>4632</td>\n",
       "      <td>1133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/17/20</th>\n",
       "      <td>6421</td>\n",
       "      <td>1789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/18/20</th>\n",
       "      <td>7783</td>\n",
       "      <td>1362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/19/20</th>\n",
       "      <td>13677</td>\n",
       "      <td>5894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/20/20</th>\n",
       "      <td>19100</td>\n",
       "      <td>5423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/21/20</th>\n",
       "      <td>25489</td>\n",
       "      <td>6389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/22/20</th>\n",
       "      <td>33276</td>\n",
       "      <td>7787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/23/20</th>\n",
       "      <td>43847</td>\n",
       "      <td>10571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/24/20</th>\n",
       "      <td>53740</td>\n",
       "      <td>9893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/25/20</th>\n",
       "      <td>65778</td>\n",
       "      <td>12038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/26/20</th>\n",
       "      <td>83836</td>\n",
       "      <td>18058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/27/20</th>\n",
       "      <td>101657</td>\n",
       "      <td>17821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/28/20</th>\n",
       "      <td>121478</td>\n",
       "      <td>19821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/29/20</th>\n",
       "      <td>140886</td>\n",
       "      <td>19408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/30/20</th>\n",
       "      <td>161807</td>\n",
       "      <td>20921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3/31/20</th>\n",
       "      <td>188172</td>\n",
       "      <td>26365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4/1/20</th>\n",
       "      <td>213372</td>\n",
       "      <td>25200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4/2/20</th>\n",
       "      <td>243453</td>\n",
       "      <td>30081</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Total Cases  New Cases\n",
       "1/22/20            1          1\n",
       "1/23/20            1          0\n",
       "1/24/20            2          1\n",
       "1/25/20            2          0\n",
       "1/26/20            5          3\n",
       "1/27/20            5          0\n",
       "1/28/20            5          0\n",
       "1/29/20            5          0\n",
       "1/30/20            5          0\n",
       "1/31/20            7          2\n",
       "2/1/20             8          1\n",
       "2/2/20             8          0\n",
       "2/3/20            11          3\n",
       "2/4/20            11          0\n",
       "2/5/20            11          0\n",
       "2/6/20            11          0\n",
       "2/7/20            11          0\n",
       "2/8/20            11          0\n",
       "2/9/20            11          0\n",
       "2/10/20           11          0\n",
       "2/11/20           12          1\n",
       "2/12/20           12          0\n",
       "2/13/20           13          1\n",
       "2/14/20           13          0\n",
       "2/15/20           13          0\n",
       "2/16/20           13          0\n",
       "2/17/20           13          0\n",
       "2/18/20           13          0\n",
       "2/19/20           13          0\n",
       "2/20/20           13          0\n",
       "2/21/20           15          2\n",
       "2/22/20           15          0\n",
       "2/23/20           15          0\n",
       "2/24/20           51         36\n",
       "2/25/20           51          0\n",
       "2/26/20           57          6\n",
       "2/27/20           58          1\n",
       "2/28/20           60          2\n",
       "2/29/20           68          8\n",
       "3/1/20            74          6\n",
       "3/2/20            98         24\n",
       "3/3/20           118         20\n",
       "3/4/20           149         31\n",
       "3/5/20           217         68\n",
       "3/6/20           262         45\n",
       "3/7/20           402        140\n",
       "3/8/20           518        116\n",
       "3/9/20           583         65\n",
       "3/10/20          959        376\n",
       "3/11/20         1281        322\n",
       "3/12/20         1663        382\n",
       "3/13/20         2179        516\n",
       "3/14/20         2727        548\n",
       "3/15/20         3499        772\n",
       "3/16/20         4632       1133\n",
       "3/17/20         6421       1789\n",
       "3/18/20         7783       1362\n",
       "3/19/20        13677       5894\n",
       "3/20/20        19100       5423\n",
       "3/21/20        25489       6389\n",
       "3/22/20        33276       7787\n",
       "3/23/20        43847      10571\n",
       "3/24/20        53740       9893\n",
       "3/25/20        65778      12038\n",
       "3/26/20        83836      18058\n",
       "3/27/20       101657      17821\n",
       "3/28/20       121478      19821\n",
       "3/29/20       140886      19408\n",
       "3/30/20       161807      20921\n",
       "3/31/20       188172      26365\n",
       "4/1/20        213372      25200\n",
       "4/2/20        243453      30081"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us = get_cleaned('US')\n",
    "us"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x16012b0>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "us.plot(figsize=(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x5266e08>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "get_cleaned('Italy').plot(figsize=(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12263940>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "get_cleaned('Japan').plot(figsize=(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}