From 5b5c84f0ed087f0e3c290ba306133d3a204d10f8 Mon Sep 17 00:00:00 2001
From: Amber Wang <wangamber8@gmail.com>
Date: Wed, 31 Dec 2025 17:36:04 -0500
Subject: [PATCH 1/3] Use [3:] to drop the longitude label. Use [1:] to remove
 all non-date entries

---
 .../07-python/notebook-covidspread.ipynb      | 2093 +----------------
 2-Working-With-Data/07-python/notebook.ipynb  | 1191 +---------
 2 files changed, 86 insertions(+), 3198 deletions(-)

diff --git a/2-Working-With-Data/07-python/notebook-covidspread.ipynb b/2-Working-With-Data/07-python/notebook-covidspread.ipynb
index 1118665c..06d1e69e 100644
--- a/2-Working-With-Data/07-python/notebook-covidspread.ipynb
+++ b/2-Working-With-Data/07-python/notebook-covidspread.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 124,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 125,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,209 +53,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 126,
+   "execution_count": null,
    "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",
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-       "\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>Province/State</th>\n",
-       "      <th>Country/Region</th>\n",
-       "      <th>Lat</th>\n",
-       "      <th>Long</th>\n",
-       "      <th>1/22/20</th>\n",
-       "      <th>1/23/20</th>\n",
-       "      <th>1/24/20</th>\n",
-       "      <th>1/25/20</th>\n",
-       "      <th>1/26/20</th>\n",
-       "      <th>1/27/20</th>\n",
-       "      <th>...</th>\n",
-       "      <th>8/20/21</th>\n",
-       "      <th>8/21/21</th>\n",
-       "      <th>8/22/21</th>\n",
-       "      <th>8/23/21</th>\n",
-       "      <th>8/24/21</th>\n",
-       "      <th>8/25/21</th>\n",
-       "      <th>8/26/21</th>\n",
-       "      <th>8/27/21</th>\n",
-       "      <th>8/28/21</th>\n",
-       "      <th>8/29/21</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
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-       "      <th>0</th>\n",
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-       "      <td>152960</td>\n",
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-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
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-       "      <td>Albania</td>\n",
-       "      <td>41.15330</td>\n",
-       "      <td>20.168300</td>\n",
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-       "      <td>142253</td>\n",
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-       "      <td>144079</td>\n",
-       "      <td>144847</td>\n",
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-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Algeria</td>\n",
-       "      <td>28.03390</td>\n",
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-       "      <td>0</td>\n",
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-       "      <td>193171</td>\n",
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-       "      <td>194671</td>\n",
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-       "    </tr>\n",
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-       "      <th>3</th>\n",
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-       "      <td>Andorra</td>\n",
-       "      <td>42.50630</td>\n",
-       "      <td>1.521800</td>\n",
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-       "      <td>15025</td>\n",
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-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
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-       "      <td>Angola</td>\n",
-       "      <td>-11.20270</td>\n",
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-       "      <td>46076</td>\n",
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-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 590 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  Province/State Country/Region       Lat       Long  1/22/20  1/23/20  \\\n",
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-       "1            NaN        Albania  41.15330  20.168300        0        0   \n",
-       "2            NaN        Algeria  28.03390   1.659600        0        0   \n",
-       "3            NaN        Andorra  42.50630   1.521800        0        0   \n",
-       "4            NaN         Angola -11.20270  17.873900        0        0   \n",
-       "\n",
-       "   1/24/20  1/25/20  1/26/20  1/27/20  ...  8/20/21  8/21/21  8/22/21  \\\n",
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-       "\n",
-       "   8/23/21  8/24/21  8/25/21  8/26/21  8/27/21  8/28/21  8/29/21  \n",
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-       "\n",
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-      ]
-     },
-     "execution_count": 126,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "infected = pd.read_csv(infected_dataset_url)\n",
     "infected.head()"
@@ -270,7 +70,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 127,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -289,31 +89,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 128,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Australian Capital Territory    1\n",
-       "Xinjiang                        1\n",
-       "Martinique                      1\n",
-       "Guadeloupe                      1\n",
-       "French Polynesia                1\n",
-       "                               ..\n",
-       "Fujian                          1\n",
-       "Chongqing                       1\n",
-       "Beijing                         1\n",
-       "Anhui                           1\n",
-       "Turks and Caicos Islands        1\n",
-       "Name: Province/State, Length: 87, dtype: int64"
-      ]
-     },
-     "execution_count": 128,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "infected['Province/State'].value_counts()"
    ]
@@ -327,992 +105,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 129,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
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-       "      <td>40.1824</td>\n",
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-       "      <td>1115</td>\n",
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-       "      <th>60</th>\n",
-       "      <td>Chongqing</td>\n",
-       "      <td>China</td>\n",
-       "      <td>30.0572</td>\n",
-       "      <td>107.8740</td>\n",
-       "      <td>6</td>\n",
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-       "      <td>603</td>\n",
-       "      <td>603</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>61</th>\n",
-       "      <td>Fujian</td>\n",
-       "      <td>China</td>\n",
-       "      <td>26.0789</td>\n",
-       "      <td>117.9874</td>\n",
-       "      <td>1</td>\n",
-       "      <td>5</td>\n",
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-       "      <td>...</td>\n",
-       "      <td>780</td>\n",
-       "      <td>780</td>\n",
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-       "      <td>782</td>\n",
-       "      <td>783</td>\n",
-       "      <td>783</td>\n",
-       "      <td>784</td>\n",
-       "      <td>785</td>\n",
-       "      <td>786</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>62</th>\n",
-       "      <td>Gansu</td>\n",
-       "      <td>China</td>\n",
-       "      <td>35.7518</td>\n",
-       "      <td>104.2861</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>4</td>\n",
-       "      <td>7</td>\n",
-       "      <td>14</td>\n",
-       "      <td>...</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "      <td>199</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>63</th>\n",
-       "      <td>Guangdong</td>\n",
-       "      <td>China</td>\n",
-       "      <td>23.3417</td>\n",
-       "      <td>113.4244</td>\n",
-       "      <td>26</td>\n",
-       "      <td>32</td>\n",
-       "      <td>53</td>\n",
-       "      <td>78</td>\n",
-       "      <td>111</td>\n",
-       "      <td>151</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3001</td>\n",
-       "      <td>3007</td>\n",
-       "      <td>3012</td>\n",
-       "      <td>3020</td>\n",
-       "      <td>3023</td>\n",
-       "      <td>3032</td>\n",
-       "      <td>3040</td>\n",
-       "      <td>3043</td>\n",
-       "      <td>3046</td>\n",
-       "      <td>3055</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>64</th>\n",
-       "      <td>Guangxi</td>\n",
-       "      <td>China</td>\n",
-       "      <td>23.8298</td>\n",
-       "      <td>108.7881</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5</td>\n",
-       "      <td>23</td>\n",
-       "      <td>23</td>\n",
-       "      <td>36</td>\n",
-       "      <td>46</td>\n",
-       "      <td>...</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "      <td>289</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>65</th>\n",
-       "      <td>Guizhou</td>\n",
-       "      <td>China</td>\n",
-       "      <td>26.8154</td>\n",
-       "      <td>106.8748</td>\n",
-       "      <td>1</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
-       "      <td>4</td>\n",
-       "      <td>5</td>\n",
-       "      <td>7</td>\n",
-       "      <td>...</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "      <td>147</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>66</th>\n",
-       "      <td>Hainan</td>\n",
-       "      <td>China</td>\n",
-       "      <td>19.1959</td>\n",
-       "      <td>109.7453</td>\n",
-       "      <td>4</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8</td>\n",
-       "      <td>19</td>\n",
-       "      <td>22</td>\n",
-       "      <td>33</td>\n",
-       "      <td>...</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "      <td>190</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>67</th>\n",
-       "      <td>Hebei</td>\n",
-       "      <td>China</td>\n",
-       "      <td>39.5490</td>\n",
-       "      <td>116.1306</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>8</td>\n",
-       "      <td>13</td>\n",
-       "      <td>18</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "      <td>1317</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>68</th>\n",
-       "      <td>Heilongjiang</td>\n",
-       "      <td>China</td>\n",
-       "      <td>47.8620</td>\n",
-       "      <td>127.7615</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>4</td>\n",
-       "      <td>9</td>\n",
-       "      <td>15</td>\n",
-       "      <td>21</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1614</td>\n",
-       "      <td>1614</td>\n",
-       "      <td>1614</td>\n",
-       "      <td>1614</td>\n",
-       "      <td>1614</td>\n",
-       "      <td>1614</td>\n",
-       "      <td>1615</td>\n",
-       "      <td>1615</td>\n",
-       "      <td>1615</td>\n",
-       "      <td>1615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>69</th>\n",
-       "      <td>Henan</td>\n",
-       "      <td>China</td>\n",
-       "      <td>37.8957</td>\n",
-       "      <td>114.9042</td>\n",
-       "      <td>5</td>\n",
-       "      <td>5</td>\n",
-       "      <td>9</td>\n",
-       "      <td>32</td>\n",
-       "      <td>83</td>\n",
-       "      <td>128</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1521</td>\n",
-       "      <td>1522</td>\n",
-       "      <td>1523</td>\n",
-       "      <td>1524</td>\n",
-       "      <td>1525</td>\n",
-       "      <td>1525</td>\n",
-       "      <td>1527</td>\n",
-       "      <td>1528</td>\n",
-       "      <td>1528</td>\n",
-       "      <td>1528</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>70</th>\n",
-       "      <td>Hong Kong</td>\n",
-       "      <td>China</td>\n",
-       "      <td>22.3000</td>\n",
-       "      <td>114.2000</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8</td>\n",
-       "      <td>8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>12049</td>\n",
-       "      <td>12052</td>\n",
-       "      <td>12057</td>\n",
-       "      <td>12062</td>\n",
-       "      <td>12069</td>\n",
-       "      <td>12074</td>\n",
-       "      <td>12077</td>\n",
-       "      <td>12094</td>\n",
-       "      <td>12100</td>\n",
-       "      <td>12107</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>71</th>\n",
-       "      <td>Hubei</td>\n",
-       "      <td>China</td>\n",
-       "      <td>30.9756</td>\n",
-       "      <td>112.2707</td>\n",
-       "      <td>444</td>\n",
-       "      <td>444</td>\n",
-       "      <td>549</td>\n",
-       "      <td>761</td>\n",
-       "      <td>1058</td>\n",
-       "      <td>1423</td>\n",
-       "      <td>...</td>\n",
-       "      <td>68287</td>\n",
-       "      <td>68289</td>\n",
-       "      <td>68289</td>\n",
-       "      <td>68289</td>\n",
-       "      <td>68289</td>\n",
-       "      <td>68289</td>\n",
-       "      <td>68290</td>\n",
-       "      <td>68290</td>\n",
-       "      <td>68290</td>\n",
-       "      <td>68290</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>72</th>\n",
-       "      <td>Hunan</td>\n",
-       "      <td>China</td>\n",
-       "      <td>27.6104</td>\n",
-       "      <td>111.7088</td>\n",
-       "      <td>4</td>\n",
-       "      <td>9</td>\n",
-       "      <td>24</td>\n",
-       "      <td>43</td>\n",
-       "      <td>69</td>\n",
-       "      <td>100</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1181</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>73</th>\n",
-       "      <td>Inner Mongolia</td>\n",
-       "      <td>China</td>\n",
-       "      <td>44.0935</td>\n",
-       "      <td>113.9448</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>7</td>\n",
-       "      <td>7</td>\n",
-       "      <td>11</td>\n",
-       "      <td>...</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "      <td>412</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>74</th>\n",
-       "      <td>Jiangsu</td>\n",
-       "      <td>China</td>\n",
-       "      <td>32.9711</td>\n",
-       "      <td>119.4550</td>\n",
-       "      <td>1</td>\n",
-       "      <td>5</td>\n",
-       "      <td>9</td>\n",
-       "      <td>18</td>\n",
-       "      <td>33</td>\n",
-       "      <td>47</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1583</td>\n",
-       "      <td>1584</td>\n",
-       "      <td>1584</td>\n",
-       "      <td>1584</td>\n",
-       "      <td>1586</td>\n",
-       "      <td>1586</td>\n",
-       "      <td>1587</td>\n",
-       "      <td>1587</td>\n",
-       "      <td>1589</td>\n",
-       "      <td>1589</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75</th>\n",
-       "      <td>Jiangxi</td>\n",
-       "      <td>China</td>\n",
-       "      <td>27.6140</td>\n",
-       "      <td>115.7221</td>\n",
-       "      <td>2</td>\n",
-       "      <td>7</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>36</td>\n",
-       "      <td>72</td>\n",
-       "      <td>...</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "      <td>937</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>76</th>\n",
-       "      <td>Jilin</td>\n",
-       "      <td>China</td>\n",
-       "      <td>43.6661</td>\n",
-       "      <td>126.1923</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>3</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "      <td>574</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>77</th>\n",
-       "      <td>Liaoning</td>\n",
-       "      <td>China</td>\n",
-       "      <td>41.2956</td>\n",
-       "      <td>122.6085</td>\n",
-       "      <td>2</td>\n",
-       "      <td>3</td>\n",
-       "      <td>4</td>\n",
-       "      <td>17</td>\n",
-       "      <td>21</td>\n",
-       "      <td>27</td>\n",
-       "      <td>...</td>\n",
-       "      <td>443</td>\n",
-       "      <td>443</td>\n",
-       "      <td>443</td>\n",
-       "      <td>443</td>\n",
-       "      <td>443</td>\n",
-       "      <td>444</td>\n",
-       "      <td>445</td>\n",
-       "      <td>446</td>\n",
-       "      <td>446</td>\n",
-       "      <td>446</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>78</th>\n",
-       "      <td>Macau</td>\n",
-       "      <td>China</td>\n",
-       "      <td>22.1667</td>\n",
-       "      <td>113.5500</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "      <td>63</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>79</th>\n",
-       "      <td>Ningxia</td>\n",
-       "      <td>China</td>\n",
-       "      <td>37.2692</td>\n",
-       "      <td>106.1655</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>3</td>\n",
-       "      <td>4</td>\n",
-       "      <td>7</td>\n",
-       "      <td>...</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "      <td>77</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>80</th>\n",
-       "      <td>Qinghai</td>\n",
-       "      <td>China</td>\n",
-       "      <td>35.7452</td>\n",
-       "      <td>95.9956</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>81</th>\n",
-       "      <td>Shaanxi</td>\n",
-       "      <td>China</td>\n",
-       "      <td>35.1917</td>\n",
-       "      <td>108.8701</td>\n",
-       "      <td>0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5</td>\n",
-       "      <td>15</td>\n",
-       "      <td>22</td>\n",
-       "      <td>35</td>\n",
-       "      <td>...</td>\n",
-       "      <td>668</td>\n",
-       "      <td>668</td>\n",
-       "      <td>668</td>\n",
-       "      <td>669</td>\n",
-       "      <td>669</td>\n",
-       "      <td>669</td>\n",
-       "      <td>669</td>\n",
-       "      <td>669</td>\n",
-       "      <td>669</td>\n",
-       "      <td>669</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>82</th>\n",
-       "      <td>Shandong</td>\n",
-       "      <td>China</td>\n",
-       "      <td>36.3427</td>\n",
-       "      <td>118.1498</td>\n",
-       "      <td>2</td>\n",
-       "      <td>6</td>\n",
-       "      <td>15</td>\n",
-       "      <td>27</td>\n",
-       "      <td>46</td>\n",
-       "      <td>75</td>\n",
-       "      <td>...</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>923</td>\n",
-       "      <td>924</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>Shanghai</td>\n",
-       "      <td>China</td>\n",
-       "      <td>31.2020</td>\n",
-       "      <td>121.4491</td>\n",
-       "      <td>9</td>\n",
-       "      <td>16</td>\n",
-       "      <td>20</td>\n",
-       "      <td>33</td>\n",
-       "      <td>40</td>\n",
-       "      <td>53</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2420</td>\n",
-       "      <td>2432</td>\n",
-       "      <td>2436</td>\n",
-       "      <td>2445</td>\n",
-       "      <td>2451</td>\n",
-       "      <td>2454</td>\n",
-       "      <td>2462</td>\n",
-       "      <td>2466</td>\n",
-       "      <td>2471</td>\n",
-       "      <td>2476</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>84</th>\n",
-       "      <td>Shanxi</td>\n",
-       "      <td>China</td>\n",
-       "      <td>37.5777</td>\n",
-       "      <td>112.2922</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>6</td>\n",
-       "      <td>9</td>\n",
-       "      <td>13</td>\n",
-       "      <td>...</td>\n",
-       "      <td>255</td>\n",
-       "      <td>255</td>\n",
-       "      <td>256</td>\n",
-       "      <td>256</td>\n",
-       "      <td>256</td>\n",
-       "      <td>256</td>\n",
-       "      <td>256</td>\n",
-       "      <td>258</td>\n",
-       "      <td>258</td>\n",
-       "      <td>259</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>85</th>\n",
-       "      <td>Sichuan</td>\n",
-       "      <td>China</td>\n",
-       "      <td>30.6171</td>\n",
-       "      <td>102.7103</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8</td>\n",
-       "      <td>15</td>\n",
-       "      <td>28</td>\n",
-       "      <td>44</td>\n",
-       "      <td>69</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1181</td>\n",
-       "      <td>1182</td>\n",
-       "      <td>1183</td>\n",
-       "      <td>1185</td>\n",
-       "      <td>1185</td>\n",
-       "      <td>1185</td>\n",
-       "      <td>1186</td>\n",
-       "      <td>1187</td>\n",
-       "      <td>1188</td>\n",
-       "      <td>1188</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>86</th>\n",
-       "      <td>Tianjin</td>\n",
-       "      <td>China</td>\n",
-       "      <td>39.3054</td>\n",
-       "      <td>117.3230</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>8</td>\n",
-       "      <td>10</td>\n",
-       "      <td>14</td>\n",
-       "      <td>23</td>\n",
-       "      <td>...</td>\n",
-       "      <td>458</td>\n",
-       "      <td>459</td>\n",
-       "      <td>462</td>\n",
-       "      <td>463</td>\n",
-       "      <td>464</td>\n",
-       "      <td>465</td>\n",
-       "      <td>466</td>\n",
-       "      <td>466</td>\n",
-       "      <td>470</td>\n",
-       "      <td>472</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>87</th>\n",
-       "      <td>Tibet</td>\n",
-       "      <td>China</td>\n",
-       "      <td>31.6927</td>\n",
-       "      <td>88.0924</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>88</th>\n",
-       "      <td>Unknown</td>\n",
-       "      <td>China</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>89</th>\n",
-       "      <td>Xinjiang</td>\n",
-       "      <td>China</td>\n",
-       "      <td>41.1129</td>\n",
-       "      <td>85.2401</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>3</td>\n",
-       "      <td>4</td>\n",
-       "      <td>5</td>\n",
-       "      <td>...</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "      <td>980</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>90</th>\n",
-       "      <td>Yunnan</td>\n",
-       "      <td>China</td>\n",
-       "      <td>24.9740</td>\n",
-       "      <td>101.4870</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5</td>\n",
-       "      <td>11</td>\n",
-       "      <td>16</td>\n",
-       "      <td>26</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1000</td>\n",
-       "      <td>1007</td>\n",
-       "      <td>1010</td>\n",
-       "      <td>1014</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>1031</td>\n",
-       "      <td>1039</td>\n",
-       "      <td>1047</td>\n",
-       "      <td>1064</td>\n",
-       "      <td>1067</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>91</th>\n",
-       "      <td>Zhejiang</td>\n",
-       "      <td>China</td>\n",
-       "      <td>29.1832</td>\n",
-       "      <td>120.0934</td>\n",
-       "      <td>10</td>\n",
-       "      <td>27</td>\n",
-       "      <td>43</td>\n",
-       "      <td>62</td>\n",
-       "      <td>104</td>\n",
-       "      <td>128</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1420</td>\n",
-       "      <td>1420</td>\n",
-       "      <td>1421</td>\n",
-       "      <td>1428</td>\n",
-       "      <td>1428</td>\n",
-       "      <td>1429</td>\n",
-       "      <td>1429</td>\n",
-       "      <td>1429</td>\n",
-       "      <td>1429</td>\n",
-       "      <td>1430</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>34 rows × 590 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    Province/State Country/Region      Lat      Long  1/22/20  1/23/20  \\\n",
-       "58           Anhui          China  31.8257  117.2264        1        9   \n",
-       "59         Beijing          China  40.1824  116.4142       14       22   \n",
-       "60       Chongqing          China  30.0572  107.8740        6        9   \n",
-       "61          Fujian          China  26.0789  117.9874        1        5   \n",
-       "62           Gansu          China  35.7518  104.2861        0        2   \n",
-       "63       Guangdong          China  23.3417  113.4244       26       32   \n",
-       "64         Guangxi          China  23.8298  108.7881        2        5   \n",
-       "65         Guizhou          China  26.8154  106.8748        1        3   \n",
-       "66          Hainan          China  19.1959  109.7453        4        5   \n",
-       "67           Hebei          China  39.5490  116.1306        1        1   \n",
-       "68    Heilongjiang          China  47.8620  127.7615        0        2   \n",
-       "69           Henan          China  37.8957  114.9042        5        5   \n",
-       "70       Hong Kong          China  22.3000  114.2000        0        2   \n",
-       "71           Hubei          China  30.9756  112.2707      444      444   \n",
-       "72           Hunan          China  27.6104  111.7088        4        9   \n",
-       "73  Inner Mongolia          China  44.0935  113.9448        0        0   \n",
-       "74         Jiangsu          China  32.9711  119.4550        1        5   \n",
-       "75         Jiangxi          China  27.6140  115.7221        2        7   \n",
-       "76           Jilin          China  43.6661  126.1923        0        1   \n",
-       "77        Liaoning          China  41.2956  122.6085        2        3   \n",
-       "78           Macau          China  22.1667  113.5500        1        2   \n",
-       "79         Ningxia          China  37.2692  106.1655        1        1   \n",
-       "80         Qinghai          China  35.7452   95.9956        0        0   \n",
-       "81         Shaanxi          China  35.1917  108.8701        0        3   \n",
-       "82        Shandong          China  36.3427  118.1498        2        6   \n",
-       "83        Shanghai          China  31.2020  121.4491        9       16   \n",
-       "84          Shanxi          China  37.5777  112.2922        1        1   \n",
-       "85         Sichuan          China  30.6171  102.7103        5        8   \n",
-       "86         Tianjin          China  39.3054  117.3230        4        4   \n",
-       "87           Tibet          China  31.6927   88.0924        0        0   \n",
-       "88         Unknown          China      NaN       NaN        0        0   \n",
-       "89        Xinjiang          China  41.1129   85.2401        0        2   \n",
-       "90          Yunnan          China  24.9740  101.4870        1        2   \n",
-       "91        Zhejiang          China  29.1832  120.0934       10       27   \n",
-       "\n",
-       "    1/24/20  1/25/20  1/26/20  1/27/20  ...  8/20/21  8/21/21  8/22/21  \\\n",
-       "58       15       39       60       70  ...     1008     1008     1008   \n",
-       "59       36       41       68       80  ...     1112     1113     1115   \n",
-       "60       27       57       75      110  ...      603      603      603   \n",
-       "61       10       18       35       59  ...      780      780      780   \n",
-       "62        2        4        7       14  ...      199      199      199   \n",
-       "63       53       78      111      151  ...     3001     3007     3012   \n",
-       "64       23       23       36       46  ...      289      289      289   \n",
-       "65        3        4        5        7  ...      147      147      147   \n",
-       "66        8       19       22       33  ...      190      190      190   \n",
-       "67        2        8       13       18  ...     1317     1317     1317   \n",
-       "68        4        9       15       21  ...     1614     1614     1614   \n",
-       "69        9       32       83      128  ...     1521     1522     1523   \n",
-       "70        2        5        8        8  ...    12049    12052    12057   \n",
-       "71      549      761     1058     1423  ...    68287    68289    68289   \n",
-       "72       24       43       69      100  ...     1181     1181     1181   \n",
-       "73        1        7        7       11  ...      412      412      412   \n",
-       "74        9       18       33       47  ...     1583     1584     1584   \n",
-       "75       18       18       36       72  ...      937      937      937   \n",
-       "76        3        4        4        6  ...      574      574      574   \n",
-       "77        4       17       21       27  ...      443      443      443   \n",
-       "78        2        2        5        6  ...       63       63       63   \n",
-       "79        2        3        4        7  ...       77       77       77   \n",
-       "80        0        1        1        6  ...       18       18       18   \n",
-       "81        5       15       22       35  ...      668      668      668   \n",
-       "82       15       27       46       75  ...      923      923      923   \n",
-       "83       20       33       40       53  ...     2420     2432     2436   \n",
-       "84        1        6        9       13  ...      255      255      256   \n",
-       "85       15       28       44       69  ...     1181     1182     1183   \n",
-       "86        8       10       14       23  ...      458      459      462   \n",
-       "87        0        0        0        0  ...        1        1        1   \n",
-       "88        0        0        0        0  ...        0        0        0   \n",
-       "89        2        3        4        5  ...      980      980      980   \n",
-       "90        5       11       16       26  ...     1000     1007     1010   \n",
-       "91       43       62      104      128  ...     1420     1420     1421   \n",
-       "\n",
-       "    8/23/21  8/24/21  8/25/21  8/26/21  8/27/21  8/28/21  8/29/21  \n",
-       "58     1008     1008     1008     1008     1008     1008     1008  \n",
-       "59     1115     1115     1115     1115     1115     1115     1115  \n",
-       "60      603      603      603      603      603      603      603  \n",
-       "61      782      782      783      783      784      785      786  \n",
-       "62      199      199      199      199      199      199      199  \n",
-       "63     3020     3023     3032     3040     3043     3046     3055  \n",
-       "64      289      289      289      289      289      289      289  \n",
-       "65      147      147      147      147      147      147      147  \n",
-       "66      190      190      190      190      190      190      190  \n",
-       "67     1317     1317     1317     1317     1317     1317     1317  \n",
-       "68     1614     1614     1614     1615     1615     1615     1615  \n",
-       "69     1524     1525     1525     1527     1528     1528     1528  \n",
-       "70    12062    12069    12074    12077    12094    12100    12107  \n",
-       "71    68289    68289    68289    68290    68290    68290    68290  \n",
-       "72     1181     1181     1181     1181     1181     1181     1181  \n",
-       "73      412      412      412      412      412      412      412  \n",
-       "74     1584     1586     1586     1587     1587     1589     1589  \n",
-       "75      937      937      937      937      937      937      937  \n",
-       "76      574      574      574      574      574      574      574  \n",
-       "77      443      443      444      445      446      446      446  \n",
-       "78       63       63       63       63       63       63       63  \n",
-       "79       77       77       77       77       77       77       77  \n",
-       "80       18       18       18       18       18       18       18  \n",
-       "81      669      669      669      669      669      669      669  \n",
-       "82      923      923      923      923      923      923      924  \n",
-       "83     2445     2451     2454     2462     2466     2471     2476  \n",
-       "84      256      256      256      256      258      258      259  \n",
-       "85     1185     1185     1185     1186     1187     1188     1188  \n",
-       "86      463      464      465      466      466      470      472  \n",
-       "87        1        1        1        1        1        1        1  \n",
-       "88        0        0        0        0        0        0        0  \n",
-       "89      980      980      980      980      980      980      980  \n",
-       "90     1014     1021     1031     1039     1047     1064     1067  \n",
-       "91     1428     1428     1429     1429     1429     1429     1430  \n",
-       "\n",
-       "[34 rows x 590 columns]"
-      ]
-     },
-     "execution_count": 129,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "infected[infected['Country/Region']=='China']"
    ]
@@ -1328,244 +123,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 130,
+   "execution_count": null,
    "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>Lat</th>\n",
-       "      <th>Long</th>\n",
-       "      <th>1/22/20</th>\n",
-       "      <th>1/23/20</th>\n",
-       "      <th>1/24/20</th>\n",
-       "      <th>1/25/20</th>\n",
-       "      <th>1/26/20</th>\n",
-       "      <th>1/27/20</th>\n",
-       "      <th>1/28/20</th>\n",
-       "      <th>1/29/20</th>\n",
-       "      <th>...</th>\n",
-       "      <th>8/20/21</th>\n",
-       "      <th>8/21/21</th>\n",
-       "      <th>8/22/21</th>\n",
-       "      <th>8/23/21</th>\n",
-       "      <th>8/24/21</th>\n",
-       "      <th>8/25/21</th>\n",
-       "      <th>8/26/21</th>\n",
-       "      <th>8/27/21</th>\n",
-       "      <th>8/28/21</th>\n",
-       "      <th>8/29/21</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Country/Region</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",
-       "      <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",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>Afghanistan</th>\n",
-       "      <td>33.93911</td>\n",
-       "      <td>67.709953</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>152448</td>\n",
-       "      <td>152448</td>\n",
-       "      <td>152448</td>\n",
-       "      <td>152583</td>\n",
-       "      <td>152660</td>\n",
-       "      <td>152722</td>\n",
-       "      <td>152822</td>\n",
-       "      <td>152960</td>\n",
-       "      <td>152960</td>\n",
-       "      <td>152960</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Albania</th>\n",
-       "      <td>41.15330</td>\n",
-       "      <td>20.168300</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>138132</td>\n",
-       "      <td>138790</td>\n",
-       "      <td>139324</td>\n",
-       "      <td>139721</td>\n",
-       "      <td>140521</td>\n",
-       "      <td>141365</td>\n",
-       "      <td>142253</td>\n",
-       "      <td>143174</td>\n",
-       "      <td>144079</td>\n",
-       "      <td>144847</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Algeria</th>\n",
-       "      <td>28.03390</td>\n",
-       "      <td>1.659600</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>190656</td>\n",
-       "      <td>191171</td>\n",
-       "      <td>191583</td>\n",
-       "      <td>192089</td>\n",
-       "      <td>192626</td>\n",
-       "      <td>193171</td>\n",
-       "      <td>193674</td>\n",
-       "      <td>194186</td>\n",
-       "      <td>194671</td>\n",
-       "      <td>195162</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Andorra</th>\n",
-       "      <td>42.50630</td>\n",
-       "      <td>1.521800</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>14988</td>\n",
-       "      <td>14988</td>\n",
-       "      <td>14988</td>\n",
-       "      <td>15002</td>\n",
-       "      <td>15003</td>\n",
-       "      <td>15014</td>\n",
-       "      <td>15016</td>\n",
-       "      <td>15025</td>\n",
-       "      <td>15025</td>\n",
-       "      <td>15025</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Angola</th>\n",
-       "      <td>-11.20270</td>\n",
-       "      <td>17.873900</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>45583</td>\n",
-       "      <td>45817</td>\n",
-       "      <td>45945</td>\n",
-       "      <td>46076</td>\n",
-       "      <td>46340</td>\n",
-       "      <td>46539</td>\n",
-       "      <td>46726</td>\n",
-       "      <td>46929</td>\n",
-       "      <td>47079</td>\n",
-       "      <td>47168</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 588 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                     Lat       Long  1/22/20  1/23/20  1/24/20  1/25/20  \\\n",
-       "Country/Region                                                            \n",
-       "Afghanistan     33.93911  67.709953        0        0        0        0   \n",
-       "Albania         41.15330  20.168300        0        0        0        0   \n",
-       "Algeria         28.03390   1.659600        0        0        0        0   \n",
-       "Andorra         42.50630   1.521800        0        0        0        0   \n",
-       "Angola         -11.20270  17.873900        0        0        0        0   \n",
-       "\n",
-       "                1/26/20  1/27/20  1/28/20  1/29/20  ...  8/20/21  8/21/21  \\\n",
-       "Country/Region                                      ...                     \n",
-       "Afghanistan           0        0        0        0  ...   152448   152448   \n",
-       "Albania               0        0        0        0  ...   138132   138790   \n",
-       "Algeria               0        0        0        0  ...   190656   191171   \n",
-       "Andorra               0        0        0        0  ...    14988    14988   \n",
-       "Angola                0        0        0        0  ...    45583    45817   \n",
-       "\n",
-       "                8/22/21  8/23/21  8/24/21  8/25/21  8/26/21  8/27/21  8/28/21  \\\n",
-       "Country/Region                                                                  \n",
-       "Afghanistan      152448   152583   152660   152722   152822   152960   152960   \n",
-       "Albania          139324   139721   140521   141365   142253   143174   144079   \n",
-       "Algeria          191583   192089   192626   193171   193674   194186   194671   \n",
-       "Andorra           14988    15002    15003    15014    15016    15025    15025   \n",
-       "Angola            45945    46076    46340    46539    46726    46929    47079   \n",
-       "\n",
-       "                8/29/21  \n",
-       "Country/Region           \n",
-       "Afghanistan      152960  \n",
-       "Albania          144847  \n",
-       "Algeria          195162  \n",
-       "Andorra           15025  \n",
-       "Angola            47168  \n",
-       "\n",
-       "[5 rows x 588 columns]"
-      ]
-     },
-     "execution_count": 130,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "infected = infected.groupby('Country/Region').sum()\n",
     "recovered = recovered.groupby('Country/Region').sum()\n",
@@ -1583,24 +143,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 131,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "infected.loc['US'][2:].plot()\n",
-    "recovered.loc['US'][2:].plot()\n",
+    "infected.loc['US'][3:].plot()\n",
+    "recovered.loc['US'][3:].plot()\n",
     "plt.show()"
    ]
   },
@@ -1608,12 +156,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "> **Note** how we use `[2:]` to remove first two elements of a sequence that contain geolocation of a country. We can also drop those two columns altogether:"
+    "> **Note** how we use `[3:]` to remove first two elements of a sequence that contain geolocation of a country. We can also drop those two columns altogether:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 132,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1633,134 +181,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
+   "execution_count": null,
    "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>infected</th>\n",
-       "      <th>recovered</th>\n",
-       "      <th>deaths</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2020-01-22</th>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-01-23</th>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-01-24</th>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-01-25</th>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-01-26</th>\n",
-       "      <td>5</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2021-08-25</th>\n",
-       "      <td>38223029</td>\n",
-       "      <td>0</td>\n",
-       "      <td>632272</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2021-08-26</th>\n",
-       "      <td>38384360</td>\n",
-       "      <td>0</td>\n",
-       "      <td>633564</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2021-08-27</th>\n",
-       "      <td>38707294</td>\n",
-       "      <td>0</td>\n",
-       "      <td>636720</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2021-08-28</th>\n",
-       "      <td>38760363</td>\n",
-       "      <td>0</td>\n",
-       "      <td>637254</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2021-08-29</th>\n",
-       "      <td>38796746</td>\n",
-       "      <td>0</td>\n",
-       "      <td>637531</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>586 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            infected  recovered  deaths\n",
-       "2020-01-22         1          0       0\n",
-       "2020-01-23         1          0       0\n",
-       "2020-01-24         2          0       0\n",
-       "2020-01-25         2          0       0\n",
-       "2020-01-26         5          0       0\n",
-       "...              ...        ...     ...\n",
-       "2021-08-25  38223029          0  632272\n",
-       "2021-08-26  38384360          0  633564\n",
-       "2021-08-27  38707294          0  636720\n",
-       "2021-08-28  38760363          0  637254\n",
-       "2021-08-29  38796746          0  637531\n",
-       "\n",
-       "[586 rows x 3 columns]"
-      ]
-     },
-     "execution_count": 133,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "def mkframe(country):\n",
-    "    df = pd.DataFrame({ 'infected' : infected.loc[country] ,\n",
-    "                        'recovered' : recovered.loc[country],\n",
-    "                        'deaths' : deaths.loc[country]})\n",
+    "    df = pd.DataFrame({ 'infected' : infected.loc[country][1:] ,\n",
+    "                        'recovered' : recovered.loc[country][1:],\n",
+    "                        'deaths' : deaths.loc[country][1:]})\n",
     "    df.index = pd.to_datetime(df.index)\n",
     "    return df\n",
     "\n",
@@ -1770,21 +198,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df.plot()\n",
     "plt.show()"
@@ -1799,21 +215,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 135,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['ninfected'] = df['infected'].diff()\n",
     "df['ninfected'].plot()\n",
@@ -1829,21 +233,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 136,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df[(df.index.year==2020) & (df.index.month==7)]['ninfected'].plot()\n",
     "plt.show()"
@@ -1858,21 +250,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 137,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['ninfav'] = df['ninfected'].rolling(window=7).mean()\n",
     "df['ninfav'].plot()\n",
@@ -1888,263 +268,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 138,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
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-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Albania</td>\n",
-       "      <td>41.153300</td>\n",
-       "      <td>20.168300</td>\n",
-       "      <td>Albania</td>\n",
-       "      <td>2877800.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>12</td>\n",
-       "      <td>DZ</td>\n",
-       "      <td>DZA</td>\n",
-       "      <td>12.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Algeria</td>\n",
-       "      <td>28.033900</td>\n",
-       "      <td>1.659600</td>\n",
-       "      <td>Algeria</td>\n",
-       "      <td>43851043.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>20</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>AND</td>\n",
-       "      <td>20.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>42.506300</td>\n",
-       "      <td>1.521800</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>77265.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>24</td>\n",
-       "      <td>AO</td>\n",
-       "      <td>AGO</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Angola</td>\n",
-       "      <td>-11.202700</td>\n",
-       "      <td>17.873900</td>\n",
-       "      <td>Angola</td>\n",
-       "      <td>32866268.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4191</th>\n",
-       "      <td>84056037</td>\n",
-       "      <td>US</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>840.0</td>\n",
-       "      <td>56037.0</td>\n",
-       "      <td>Sweetwater</td>\n",
-       "      <td>Wyoming</td>\n",
-       "      <td>US</td>\n",
-       "      <td>41.659439</td>\n",
-       "      <td>-108.882788</td>\n",
-       "      <td>Sweetwater, Wyoming, US</td>\n",
-       "      <td>42343.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4192</th>\n",
-       "      <td>84056039</td>\n",
-       "      <td>US</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>840.0</td>\n",
-       "      <td>56039.0</td>\n",
-       "      <td>Teton</td>\n",
-       "      <td>Wyoming</td>\n",
-       "      <td>US</td>\n",
-       "      <td>43.935225</td>\n",
-       "      <td>-110.589080</td>\n",
-       "      <td>Teton, Wyoming, US</td>\n",
-       "      <td>23464.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4193</th>\n",
-       "      <td>84056041</td>\n",
-       "      <td>US</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>840.0</td>\n",
-       "      <td>56041.0</td>\n",
-       "      <td>Uinta</td>\n",
-       "      <td>Wyoming</td>\n",
-       "      <td>US</td>\n",
-       "      <td>41.287818</td>\n",
-       "      <td>-110.547578</td>\n",
-       "      <td>Uinta, Wyoming, US</td>\n",
-       "      <td>20226.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4194</th>\n",
-       "      <td>84056043</td>\n",
-       "      <td>US</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>840.0</td>\n",
-       "      <td>56043.0</td>\n",
-       "      <td>Washakie</td>\n",
-       "      <td>Wyoming</td>\n",
-       "      <td>US</td>\n",
-       "      <td>43.904516</td>\n",
-       "      <td>-107.680187</td>\n",
-       "      <td>Washakie, Wyoming, US</td>\n",
-       "      <td>7805.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4195</th>\n",
-       "      <td>84056045</td>\n",
-       "      <td>US</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>840.0</td>\n",
-       "      <td>56045.0</td>\n",
-       "      <td>Weston</td>\n",
-       "      <td>Wyoming</td>\n",
-       "      <td>US</td>\n",
-       "      <td>43.839612</td>\n",
-       "      <td>-104.567488</td>\n",
-       "      <td>Weston, Wyoming, US</td>\n",
-       "      <td>6927.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>4196 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "           UID iso2 iso3  code3     FIPS      Admin2 Province_State  \\\n",
-       "0            4   AF  AFG    4.0      NaN         NaN            NaN   \n",
-       "1            8   AL  ALB    8.0      NaN         NaN            NaN   \n",
-       "2           12   DZ  DZA   12.0      NaN         NaN            NaN   \n",
-       "3           20   AD  AND   20.0      NaN         NaN            NaN   \n",
-       "4           24   AO  AGO   24.0      NaN         NaN            NaN   \n",
-       "...        ...  ...  ...    ...      ...         ...            ...   \n",
-       "4191  84056037   US  USA  840.0  56037.0  Sweetwater        Wyoming   \n",
-       "4192  84056039   US  USA  840.0  56039.0       Teton        Wyoming   \n",
-       "4193  84056041   US  USA  840.0  56041.0       Uinta        Wyoming   \n",
-       "4194  84056043   US  USA  840.0  56043.0    Washakie        Wyoming   \n",
-       "4195  84056045   US  USA  840.0  56045.0      Weston        Wyoming   \n",
-       "\n",
-       "     Country_Region        Lat       Long_             Combined_Key  \\\n",
-       "0       Afghanistan  33.939110   67.709953              Afghanistan   \n",
-       "1           Albania  41.153300   20.168300                  Albania   \n",
-       "2           Algeria  28.033900    1.659600                  Algeria   \n",
-       "3           Andorra  42.506300    1.521800                  Andorra   \n",
-       "4            Angola -11.202700   17.873900                   Angola   \n",
-       "...             ...        ...         ...                      ...   \n",
-       "4191             US  41.659439 -108.882788  Sweetwater, Wyoming, US   \n",
-       "4192             US  43.935225 -110.589080       Teton, Wyoming, US   \n",
-       "4193             US  41.287818 -110.547578       Uinta, Wyoming, US   \n",
-       "4194             US  43.904516 -107.680187    Washakie, Wyoming, US   \n",
-       "4195             US  43.839612 -104.567488      Weston, Wyoming, US   \n",
-       "\n",
-       "      Population  \n",
-       "0     38928341.0  \n",
-       "1      2877800.0  \n",
-       "2     43851043.0  \n",
-       "3        77265.0  \n",
-       "4     32866268.0  \n",
-       "...          ...  \n",
-       "4191     42343.0  \n",
-       "4192     23464.0  \n",
-       "4193     20226.0  \n",
-       "4194      7805.0  \n",
-       "4195      6927.0  \n",
-       "\n",
-       "[4196 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 138,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "countries = pd.read_csv(countries_dataset_url)\n",
     "countries"
@@ -2159,98 +285,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": null,
    "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>UID</th>\n",
-       "      <th>iso2</th>\n",
-       "      <th>iso3</th>\n",
-       "      <th>code3</th>\n",
-       "      <th>FIPS</th>\n",
-       "      <th>Admin2</th>\n",
-       "      <th>Province_State</th>\n",
-       "      <th>Country_Region</th>\n",
-       "      <th>Lat</th>\n",
-       "      <th>Long_</th>\n",
-       "      <th>Combined_Key</th>\n",
-       "      <th>Population</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>790</th>\n",
-       "      <td>840</td>\n",
-       "      <td>US</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>840.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>US</td>\n",
-       "      <td>40.0</td>\n",
-       "      <td>-100.0</td>\n",
-       "      <td>US</td>\n",
-       "      <td>329466283.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     UID iso2 iso3  code3  FIPS Admin2 Province_State Country_Region   Lat  \\\n",
-       "790  840   US  USA  840.0   NaN    NaN            NaN             US  40.0   \n",
-       "\n",
-       "     Long_ Combined_Key   Population  \n",
-       "790 -100.0           US  329466283.0  "
-      ]
-     },
-     "execution_count": 139,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "countries[(countries['Country_Region']=='US') & countries['Province_State'].isna()]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pop = countries[(countries['Country_Region']=='US') & countries['Province_State'].isna()]['Population'].iloc[0]\n",
     "df['pinfected'] = df['infected']*100 / pop\n",
@@ -2275,21 +321,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 141,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['Rt'] = df['ninfected'].rolling(8).apply(lambda x: x[4:].sum()/x[:4].sum())\n",
     "df['Rt'].plot()\n",
@@ -2307,21 +341,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "ax = df[df.index<\"2020-05-01\"]['Rt'].replace(np.inf,np.nan).fillna(method='pad').plot(figsize=(10,3))\n",
     "ax.set_ylim([0,6])\n",
@@ -2338,21 +360,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 143,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['ninfected'].diff().plot()\n",
     "plt.show()"
@@ -2367,21 +377,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 150,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "ax=df[df.index<\"2020-06-01\"]['ninfected'].diff().rolling(7).mean().plot()\n",
     "ax.axhline(0,linestyle='-.',color='red')\n",
@@ -2442,8 +440,7 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.8.8"
-  },
-  "orig_nbformat": 4
+  }
  },
  "nbformat": 4,
  "nbformat_minor": 2
diff --git a/2-Working-With-Data/07-python/notebook.ipynb b/2-Working-With-Data/07-python/notebook.ipynb
index 17cfe156..b1a2b46e 100644
--- a/2-Working-With-Data/07-python/notebook.ipynb
+++ b/2-Working-With-Data/07-python/notebook.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -31,35 +31,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0    1\n",
-      "1    2\n",
-      "2    3\n",
-      "3    4\n",
-      "4    5\n",
-      "5    6\n",
-      "6    7\n",
-      "7    8\n",
-      "8    9\n",
-      "dtype: int64 0         I\n",
-      "1      like\n",
-      "2        to\n",
-      "3       use\n",
-      "4    Python\n",
-      "5       and\n",
-      "6    Pandas\n",
-      "7      very\n",
-      "8      much\n",
-      "dtype: object\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "a = pd.Series(range(1,10))\n",
     "b = pd.Series([\"I\",\"like\",\"to\",\"use\",\"Python\",\"and\",\"Pandas\",\"very\",\"much\"],index=range(0,9))\n",
@@ -77,28 +51,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Length of index is 366\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
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+   "outputs": [],
    "source": [
     "start_date = \"Jan 1, 2020\"\n",
     "end_date = \"Dec 31, 2020\"\n",
@@ -111,83 +66,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Additional items (10 item each week):\n",
-      "2020-01-05    10\n",
-      "2020-01-12    10\n",
-      "2020-01-19    10\n",
-      "2020-01-26    10\n",
-      "2020-02-02    10\n",
-      "2020-02-09    10\n",
-      "2020-02-16    10\n",
-      "2020-02-23    10\n",
-      "2020-03-01    10\n",
-      "2020-03-08    10\n",
-      "2020-03-15    10\n",
-      "2020-03-22    10\n",
-      "2020-03-29    10\n",
-      "2020-04-05    10\n",
-      "2020-04-12    10\n",
-      "2020-04-19    10\n",
-      "2020-04-26    10\n",
-      "2020-05-03    10\n",
-      "2020-05-10    10\n",
-      "2020-05-17    10\n",
-      "2020-05-24    10\n",
-      "2020-05-31    10\n",
-      "2020-06-07    10\n",
-      "2020-06-14    10\n",
-      "2020-06-21    10\n",
-      "2020-06-28    10\n",
-      "2020-07-05    10\n",
-      "2020-07-12    10\n",
-      "2020-07-19    10\n",
-      "2020-07-26    10\n",
-      "2020-08-02    10\n",
-      "2020-08-09    10\n",
-      "2020-08-16    10\n",
-      "2020-08-23    10\n",
-      "2020-08-30    10\n",
-      "2020-09-06    10\n",
-      "2020-09-13    10\n",
-      "2020-09-20    10\n",
-      "2020-09-27    10\n",
-      "2020-10-04    10\n",
-      "2020-10-11    10\n",
-      "2020-10-18    10\n",
-      "2020-10-25    10\n",
-      "2020-11-01    10\n",
-      "2020-11-08    10\n",
-      "2020-11-15    10\n",
-      "2020-11-22    10\n",
-      "2020-11-29    10\n",
-      "2020-12-06    10\n",
-      "2020-12-13    10\n",
-      "2020-12-20    10\n",
-      "2020-12-27    10\n",
-      "Freq: W-SUN, dtype: int64\n",
-      "Total items (sum of two series):\n",
-      "2020-01-01     NaN\n",
-      "2020-01-02     NaN\n",
-      "2020-01-03     NaN\n",
-      "2020-01-04     NaN\n",
-      "2020-01-05    54.0\n",
-      "              ... \n",
-      "2020-12-27    43.0\n",
-      "2020-12-28     NaN\n",
-      "2020-12-29     NaN\n",
-      "2020-12-30     NaN\n",
-      "2020-12-31     NaN\n",
-      "Length: 366, dtype: float64\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "additional_items = pd.Series(10,index=pd.date_range(start_date,end_date,freq=\"W\"))\n",
     "print(f\"Additional items (10 item each week):\\n{additional_items}\")\n",
@@ -204,39 +85,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2020-01-01    26.0\n",
-      "2020-01-02    25.0\n",
-      "2020-01-03    37.0\n",
-      "2020-01-04    30.0\n",
-      "2020-01-05    54.0\n",
-      "              ... \n",
-      "2020-12-27    43.0\n",
-      "2020-12-28    44.0\n",
-      "2020-12-29    36.0\n",
-      "2020-12-30    38.0\n",
-      "2020-12-31    34.0\n",
-      "Length: 366, dtype: float64\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "total_items = items_sold.add(additional_items,fill_value=0)\n",
     "print(total_items)\n",
@@ -246,21 +97,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "monthly = total_items.resample(\"1M\").mean()\n",
     "ax = monthly.plot(kind='bar',figsize=(10,3))\n",
@@ -279,81 +118,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
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-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
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-   ],
+   "outputs": [],
    "source": [
     "df = pd.DataFrame([a,b])\n",
     "df"
@@ -368,102 +135,9 @@
   },
   {
    "cell_type": "code",
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+   "execution_count": null,
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-       "3  4     use\n",
-       "4  5  Python\n",
-       "5  6     and\n",
-       "6  7  Pandas\n",
-       "7  8    very\n",
-       "8  9    much"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df = pd.DataFrame({ 'A' : a, 'B' : b })\n",
     "df"
@@ -478,102 +152,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": null,
    "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>A</th>\n",
-       "      <th>B</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>I</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>like</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>to</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>use</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Python</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
-       "      <td>and</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
-       "      <td>Pandas</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8</td>\n",
-       "      <td>very</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>9</td>\n",
-       "      <td>much</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A       B\n",
-       "0  1       I\n",
-       "1  2    like\n",
-       "2  3      to\n",
-       "3  4     use\n",
-       "4  5  Python\n",
-       "5  6     and\n",
-       "6  7  Pandas\n",
-       "7  8    very\n",
-       "8  9    much"
-      ]
-     },
-     "execution_count": 44,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pd.DataFrame([a,b]).T.rename(columns={ 0 : 'A', 1 : 'B' })"
    ]
@@ -587,38 +168,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Column A (series):\n",
-      "0    1\n",
-      "1    2\n",
-      "2    3\n",
-      "3    4\n",
-      "4    5\n",
-      "5    6\n",
-      "6    7\n",
-      "7    8\n",
-      "8    9\n",
-      "Name: A, dtype: int64\n",
-      "Columns B and A (DataFrame):\n",
-      "        B  A\n",
-      "0       I  1\n",
-      "1    like  2\n",
-      "2      to  3\n",
-      "3     use  4\n",
-      "4  Python  5\n",
-      "5     and  6\n",
-      "6  Pandas  7\n",
-      "7    very  8\n",
-      "8    much  9\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(f\"Column A (series):\\n{df['A']}\")\n",
     "print(f\"Columns B and A (DataFrame):\\n{df[['B','A']]}\")"
@@ -633,72 +185,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": null,
    "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>A</th>\n",
-       "      <th>B</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>I</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>like</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>to</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>use</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A     B\n",
-       "0  1     I\n",
-       "1  2  like\n",
-       "2  3    to\n",
-       "3  4   use"
-      ]
-     },
-     "execution_count": 46,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df[df['A']<5]"
    ]
@@ -712,54 +201,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": null,
    "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>A</th>\n",
-       "      <th>B</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
-       "      <td>and</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A    B\n",
-       "5  6  and"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df[(df['A']>5) & (df['A']<7)]"
    ]
@@ -773,112 +217,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": null,
    "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>A</th>\n",
-       "      <th>B</th>\n",
-       "      <th>DivA</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>I</td>\n",
-       "      <td>-4.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>like</td>\n",
-       "      <td>-3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>to</td>\n",
-       "      <td>-2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>use</td>\n",
-       "      <td>-1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Python</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
-       "      <td>and</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
-       "      <td>Pandas</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8</td>\n",
-       "      <td>very</td>\n",
-       "      <td>3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>9</td>\n",
-       "      <td>much</td>\n",
-       "      <td>4.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A       B  DivA\n",
-       "0  1       I  -4.0\n",
-       "1  2    like  -3.0\n",
-       "2  3      to  -2.0\n",
-       "3  4     use  -1.0\n",
-       "4  5  Python   0.0\n",
-       "5  6     and   1.0\n",
-       "6  7  Pandas   2.0\n",
-       "7  8    very   3.0\n",
-       "8  9    much   4.0"
-      ]
-     },
-     "execution_count": 48,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['DivA'] = df['A']-df['A'].mean()\n",
     "df"
@@ -893,7 +234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -903,122 +244,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
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-       "\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>A</th>\n",
-       "      <th>B</th>\n",
-       "      <th>DivA</th>\n",
-       "      <th>LenB</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>I</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>like</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>to</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>use</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Python</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
-       "      <td>and</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
-       "      <td>Pandas</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8</td>\n",
-       "      <td>very</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>9</td>\n",
-       "      <td>much</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A       B  DivA  LenB\n",
-       "0  1       I  -4.0     1\n",
-       "1  2    like  -3.0     4\n",
-       "2  3      to  -2.0     2\n",
-       "3  4     use  -1.0     3\n",
-       "4  5  Python   0.0     6\n",
-       "5  6     and   1.0     3\n",
-       "6  7  Pandas   2.0     6\n",
-       "7  8    very   3.0     4\n",
-       "8  9    much   4.0     4"
-      ]
-     },
-     "execution_count": 50,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['LenB'] = df['B'].apply(lambda x: len(x))\n",
     "# or\n",
@@ -1035,90 +263,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
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-       "\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>A</th>\n",
-       "      <th>B</th>\n",
-       "      <th>DivA</th>\n",
-       "      <th>LenB</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>I</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>like</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>to</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>use</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Python</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A       B  DivA  LenB\n",
-       "0  1       I  -4.0     1\n",
-       "1  2    like  -3.0     4\n",
-       "2  3      to  -2.0     2\n",
-       "3  4     use  -1.0     3\n",
-       "4  5  Python   0.0     6"
-      ]
-     },
-     "execution_count": 52,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df.iloc[:5]"
    ]
@@ -1132,84 +279,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\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>A</th>\n",
-       "      <th>DivA</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>LenB</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>-4.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>-2.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>6.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>6.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "             A      DivA\n",
-       "LenB                    \n",
-       "1     1.000000 -4.000000\n",
-       "2     3.000000 -2.000000\n",
-       "3     5.000000  0.000000\n",
-       "4     6.333333  1.333333\n",
-       "6     6.000000  1.000000"
-      ]
-     },
-     "execution_count": 53,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df.groupby(by='LenB').mean()"
    ]
@@ -1223,84 +295,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": null,
    "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>Count</th>\n",
-       "      <th>Mean</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>LenB</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1</td>\n",
-       "      <td>3.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2</td>\n",
-       "      <td>5.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3</td>\n",
-       "      <td>6.333333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>2</td>\n",
-       "      <td>6.000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      Count      Mean\n",
-       "LenB                 \n",
-       "1         1  1.000000\n",
-       "2         1  3.000000\n",
-       "3         2  5.000000\n",
-       "4         3  6.333333\n",
-       "6         2  6.000000"
-      ]
-     },
-     "execution_count": 58,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df.groupby(by='LenB') \\\n",
     " .aggregate({ 'DivA' : len, 'A' : lambda x: x.mean() }) \\\n",
@@ -1318,90 +315,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": null,
    "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>A</th>\n",
-       "      <th>B</th>\n",
-       "      <th>DivA</th>\n",
-       "      <th>LenB</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>I</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>like</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>to</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>use</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Python</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A       B  DivA  LenB\n",
-       "0  1       I  -4.0     1\n",
-       "1  2    like  -3.0     4\n",
-       "2  3      to  -2.0     2\n",
-       "3  4     use  -1.0     3\n",
-       "4  5  Python   0.0     6"
-      ]
-     },
-     "execution_count": 59,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df.head()"
    ]
@@ -1416,21 +332,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['A'].plot()\n",
     "plt.show()"
@@ -1438,21 +342,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
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-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df['A'].plot(kind='bar')\n",
     "plt.show()"
@@ -1491,8 +383,7 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.8.8"
-  },
-  "orig_nbformat": 4
+  }
  },
  "nbformat": 4,
  "nbformat_minor": 2

From 6df2b1a2ad849ef7a59acbafd70ec63b73d5540c Mon Sep 17 00:00:00 2001
From: Amber Wang <wangamber8@gmail.com>
Date: Fri, 2 Jan 2026 13:29:28 -0500
Subject: [PATCH 2/3] fix/incorrect-indexing-handling in
 notebook-covidspread.ipynb changed [2:] to [3:] to drop the correct columns
 and dropped the province column to ensure the function works properly

---
 .../07-python/notebook-covidspread.ipynb      | 2093 ++++++++++++++++-
 1 file changed, 2048 insertions(+), 45 deletions(-)

diff --git a/2-Working-With-Data/07-python/notebook-covidspread.ipynb b/2-Working-With-Data/07-python/notebook-covidspread.ipynb
index 06d1e69e..64f29f20 100644
--- a/2-Working-With-Data/07-python/notebook-covidspread.ipynb
+++ b/2-Working-With-Data/07-python/notebook-covidspread.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 124,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 125,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,9 +53,209 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 126,
    "metadata": {},
-   "outputs": [],
+   "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>Province/State</th>\n",
+       "      <th>Country/Region</th>\n",
+       "      <th>Lat</th>\n",
+       "      <th>Long</th>\n",
+       "      <th>1/22/20</th>\n",
+       "      <th>1/23/20</th>\n",
+       "      <th>1/24/20</th>\n",
+       "      <th>1/25/20</th>\n",
+       "      <th>1/26/20</th>\n",
+       "      <th>1/27/20</th>\n",
+       "      <th>...</th>\n",
+       "      <th>8/20/21</th>\n",
+       "      <th>8/21/21</th>\n",
+       "      <th>8/22/21</th>\n",
+       "      <th>8/23/21</th>\n",
+       "      <th>8/24/21</th>\n",
+       "      <th>8/25/21</th>\n",
+       "      <th>8/26/21</th>\n",
+       "      <th>8/27/21</th>\n",
+       "      <th>8/28/21</th>\n",
+       "      <th>8/29/21</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>33.93911</td>\n",
+       "      <td>67.709953</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>152448</td>\n",
+       "      <td>152448</td>\n",
+       "      <td>152448</td>\n",
+       "      <td>152583</td>\n",
+       "      <td>152660</td>\n",
+       "      <td>152722</td>\n",
+       "      <td>152822</td>\n",
+       "      <td>152960</td>\n",
+       "      <td>152960</td>\n",
+       "      <td>152960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>41.15330</td>\n",
+       "      <td>20.168300</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>138132</td>\n",
+       "      <td>138790</td>\n",
+       "      <td>139324</td>\n",
+       "      <td>139721</td>\n",
+       "      <td>140521</td>\n",
+       "      <td>141365</td>\n",
+       "      <td>142253</td>\n",
+       "      <td>143174</td>\n",
+       "      <td>144079</td>\n",
+       "      <td>144847</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Algeria</td>\n",
+       "      <td>28.03390</td>\n",
+       "      <td>1.659600</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>190656</td>\n",
+       "      <td>191171</td>\n",
+       "      <td>191583</td>\n",
+       "      <td>192089</td>\n",
+       "      <td>192626</td>\n",
+       "      <td>193171</td>\n",
+       "      <td>193674</td>\n",
+       "      <td>194186</td>\n",
+       "      <td>194671</td>\n",
+       "      <td>195162</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Andorra</td>\n",
+       "      <td>42.50630</td>\n",
+       "      <td>1.521800</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>14988</td>\n",
+       "      <td>14988</td>\n",
+       "      <td>14988</td>\n",
+       "      <td>15002</td>\n",
+       "      <td>15003</td>\n",
+       "      <td>15014</td>\n",
+       "      <td>15016</td>\n",
+       "      <td>15025</td>\n",
+       "      <td>15025</td>\n",
+       "      <td>15025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Angola</td>\n",
+       "      <td>-11.20270</td>\n",
+       "      <td>17.873900</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>45583</td>\n",
+       "      <td>45817</td>\n",
+       "      <td>45945</td>\n",
+       "      <td>46076</td>\n",
+       "      <td>46340</td>\n",
+       "      <td>46539</td>\n",
+       "      <td>46726</td>\n",
+       "      <td>46929</td>\n",
+       "      <td>47079</td>\n",
+       "      <td>47168</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 590 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Province/State Country/Region       Lat       Long  1/22/20  1/23/20  \\\n",
+       "0            NaN    Afghanistan  33.93911  67.709953        0        0   \n",
+       "1            NaN        Albania  41.15330  20.168300        0        0   \n",
+       "2            NaN        Algeria  28.03390   1.659600        0        0   \n",
+       "3            NaN        Andorra  42.50630   1.521800        0        0   \n",
+       "4            NaN         Angola -11.20270  17.873900        0        0   \n",
+       "\n",
+       "   1/24/20  1/25/20  1/26/20  1/27/20  ...  8/20/21  8/21/21  8/22/21  \\\n",
+       "0        0        0        0        0  ...   152448   152448   152448   \n",
+       "1        0        0        0        0  ...   138132   138790   139324   \n",
+       "2        0        0        0        0  ...   190656   191171   191583   \n",
+       "3        0        0        0        0  ...    14988    14988    14988   \n",
+       "4        0        0        0        0  ...    45583    45817    45945   \n",
+       "\n",
+       "   8/23/21  8/24/21  8/25/21  8/26/21  8/27/21  8/28/21  8/29/21  \n",
+       "0   152583   152660   152722   152822   152960   152960   152960  \n",
+       "1   139721   140521   141365   142253   143174   144079   144847  \n",
+       "2   192089   192626   193171   193674   194186   194671   195162  \n",
+       "3    15002    15003    15014    15016    15025    15025    15025  \n",
+       "4    46076    46340    46539    46726    46929    47079    47168  \n",
+       "\n",
+       "[5 rows x 590 columns]"
+      ]
+     },
+     "execution_count": 126,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "infected = pd.read_csv(infected_dataset_url)\n",
     "infected.head()"
@@ -70,7 +270,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 127,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -89,9 +289,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 128,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Australian Capital Territory    1\n",
+       "Xinjiang                        1\n",
+       "Martinique                      1\n",
+       "Guadeloupe                      1\n",
+       "French Polynesia                1\n",
+       "                               ..\n",
+       "Fujian                          1\n",
+       "Chongqing                       1\n",
+       "Beijing                         1\n",
+       "Anhui                           1\n",
+       "Turks and Caicos Islands        1\n",
+       "Name: Province/State, Length: 87, dtype: int64"
+      ]
+     },
+     "execution_count": 128,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "infected['Province/State'].value_counts()"
    ]
@@ -105,9 +327,992 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 129,
    "metadata": {},
-   "outputs": [],
+   "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>Province/State</th>\n",
+       "      <th>Country/Region</th>\n",
+       "      <th>Lat</th>\n",
+       "      <th>Long</th>\n",
+       "      <th>1/22/20</th>\n",
+       "      <th>1/23/20</th>\n",
+       "      <th>1/24/20</th>\n",
+       "      <th>1/25/20</th>\n",
+       "      <th>1/26/20</th>\n",
+       "      <th>1/27/20</th>\n",
+       "      <th>...</th>\n",
+       "      <th>8/20/21</th>\n",
+       "      <th>8/21/21</th>\n",
+       "      <th>8/22/21</th>\n",
+       "      <th>8/23/21</th>\n",
+       "      <th>8/24/21</th>\n",
+       "      <th>8/25/21</th>\n",
+       "      <th>8/26/21</th>\n",
+       "      <th>8/27/21</th>\n",
+       "      <th>8/28/21</th>\n",
+       "      <th>8/29/21</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>Anhui</td>\n",
+       "      <td>China</td>\n",
+       "      <td>31.8257</td>\n",
+       "      <td>117.2264</td>\n",
+       "      <td>1</td>\n",
+       "      <td>9</td>\n",
+       "      <td>15</td>\n",
+       "      <td>39</td>\n",
+       "      <td>60</td>\n",
+       "      <td>70</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>Beijing</td>\n",
+       "      <td>China</td>\n",
+       "      <td>40.1824</td>\n",
+       "      <td>116.4142</td>\n",
+       "      <td>14</td>\n",
+       "      <td>22</td>\n",
+       "      <td>36</td>\n",
+       "      <td>41</td>\n",
+       "      <td>68</td>\n",
+       "      <td>80</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1115</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>Chongqing</td>\n",
+       "      <td>China</td>\n",
+       "      <td>30.0572</td>\n",
+       "      <td>107.8740</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "      <td>27</td>\n",
+       "      <td>57</td>\n",
+       "      <td>75</td>\n",
+       "      <td>110</td>\n",
+       "      <td>...</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "      <td>603</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>61</th>\n",
+       "      <td>Fujian</td>\n",
+       "      <td>China</td>\n",
+       "      <td>26.0789</td>\n",
+       "      <td>117.9874</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>18</td>\n",
+       "      <td>35</td>\n",
+       "      <td>59</td>\n",
+       "      <td>...</td>\n",
+       "      <td>780</td>\n",
+       "      <td>780</td>\n",
+       "      <td>780</td>\n",
+       "      <td>782</td>\n",
+       "      <td>782</td>\n",
+       "      <td>783</td>\n",
+       "      <td>783</td>\n",
+       "      <td>784</td>\n",
+       "      <td>785</td>\n",
+       "      <td>786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>62</th>\n",
+       "      <td>Gansu</td>\n",
+       "      <td>China</td>\n",
+       "      <td>35.7518</td>\n",
+       "      <td>104.2861</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14</td>\n",
+       "      <td>...</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "      <td>199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>63</th>\n",
+       "      <td>Guangdong</td>\n",
+       "      <td>China</td>\n",
+       "      <td>23.3417</td>\n",
+       "      <td>113.4244</td>\n",
+       "      <td>26</td>\n",
+       "      <td>32</td>\n",
+       "      <td>53</td>\n",
+       "      <td>78</td>\n",
+       "      <td>111</td>\n",
+       "      <td>151</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3001</td>\n",
+       "      <td>3007</td>\n",
+       "      <td>3012</td>\n",
+       "      <td>3020</td>\n",
+       "      <td>3023</td>\n",
+       "      <td>3032</td>\n",
+       "      <td>3040</td>\n",
+       "      <td>3043</td>\n",
+       "      <td>3046</td>\n",
+       "      <td>3055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>Guangxi</td>\n",
+       "      <td>China</td>\n",
+       "      <td>23.8298</td>\n",
+       "      <td>108.7881</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>23</td>\n",
+       "      <td>23</td>\n",
+       "      <td>36</td>\n",
+       "      <td>46</td>\n",
+       "      <td>...</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>65</th>\n",
+       "      <td>Guizhou</td>\n",
+       "      <td>China</td>\n",
+       "      <td>26.8154</td>\n",
+       "      <td>106.8748</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>...</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "      <td>147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>66</th>\n",
+       "      <td>Hainan</td>\n",
+       "      <td>China</td>\n",
+       "      <td>19.1959</td>\n",
+       "      <td>109.7453</td>\n",
+       "      <td>4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>19</td>\n",
+       "      <td>22</td>\n",
+       "      <td>33</td>\n",
+       "      <td>...</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "      <td>190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>67</th>\n",
+       "      <td>Hebei</td>\n",
+       "      <td>China</td>\n",
+       "      <td>39.5490</td>\n",
+       "      <td>116.1306</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>13</td>\n",
+       "      <td>18</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>68</th>\n",
+       "      <td>Heilongjiang</td>\n",
+       "      <td>China</td>\n",
+       "      <td>47.8620</td>\n",
+       "      <td>127.7615</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9</td>\n",
+       "      <td>15</td>\n",
+       "      <td>21</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1615</td>\n",
+       "      <td>1615</td>\n",
+       "      <td>1615</td>\n",
+       "      <td>1615</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>69</th>\n",
+       "      <td>Henan</td>\n",
+       "      <td>China</td>\n",
+       "      <td>37.8957</td>\n",
+       "      <td>114.9042</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>32</td>\n",
+       "      <td>83</td>\n",
+       "      <td>128</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1521</td>\n",
+       "      <td>1522</td>\n",
+       "      <td>1523</td>\n",
+       "      <td>1524</td>\n",
+       "      <td>1525</td>\n",
+       "      <td>1525</td>\n",
+       "      <td>1527</td>\n",
+       "      <td>1528</td>\n",
+       "      <td>1528</td>\n",
+       "      <td>1528</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>70</th>\n",
+       "      <td>Hong Kong</td>\n",
+       "      <td>China</td>\n",
+       "      <td>22.3000</td>\n",
+       "      <td>114.2000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12049</td>\n",
+       "      <td>12052</td>\n",
+       "      <td>12057</td>\n",
+       "      <td>12062</td>\n",
+       "      <td>12069</td>\n",
+       "      <td>12074</td>\n",
+       "      <td>12077</td>\n",
+       "      <td>12094</td>\n",
+       "      <td>12100</td>\n",
+       "      <td>12107</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>71</th>\n",
+       "      <td>Hubei</td>\n",
+       "      <td>China</td>\n",
+       "      <td>30.9756</td>\n",
+       "      <td>112.2707</td>\n",
+       "      <td>444</td>\n",
+       "      <td>444</td>\n",
+       "      <td>549</td>\n",
+       "      <td>761</td>\n",
+       "      <td>1058</td>\n",
+       "      <td>1423</td>\n",
+       "      <td>...</td>\n",
+       "      <td>68287</td>\n",
+       "      <td>68289</td>\n",
+       "      <td>68289</td>\n",
+       "      <td>68289</td>\n",
+       "      <td>68289</td>\n",
+       "      <td>68289</td>\n",
+       "      <td>68290</td>\n",
+       "      <td>68290</td>\n",
+       "      <td>68290</td>\n",
+       "      <td>68290</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>Hunan</td>\n",
+       "      <td>China</td>\n",
+       "      <td>27.6104</td>\n",
+       "      <td>111.7088</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9</td>\n",
+       "      <td>24</td>\n",
+       "      <td>43</td>\n",
+       "      <td>69</td>\n",
+       "      <td>100</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1181</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>73</th>\n",
+       "      <td>Inner Mongolia</td>\n",
+       "      <td>China</td>\n",
+       "      <td>44.0935</td>\n",
+       "      <td>113.9448</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11</td>\n",
+       "      <td>...</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "      <td>412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>74</th>\n",
+       "      <td>Jiangsu</td>\n",
+       "      <td>China</td>\n",
+       "      <td>32.9711</td>\n",
+       "      <td>119.4550</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>18</td>\n",
+       "      <td>33</td>\n",
+       "      <td>47</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1583</td>\n",
+       "      <td>1584</td>\n",
+       "      <td>1584</td>\n",
+       "      <td>1584</td>\n",
+       "      <td>1586</td>\n",
+       "      <td>1586</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1589</td>\n",
+       "      <td>1589</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75</th>\n",
+       "      <td>Jiangxi</td>\n",
+       "      <td>China</td>\n",
+       "      <td>27.6140</td>\n",
+       "      <td>115.7221</td>\n",
+       "      <td>2</td>\n",
+       "      <td>7</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>36</td>\n",
+       "      <td>72</td>\n",
+       "      <td>...</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "      <td>937</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>76</th>\n",
+       "      <td>Jilin</td>\n",
+       "      <td>China</td>\n",
+       "      <td>43.6661</td>\n",
+       "      <td>126.1923</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "      <td>574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>77</th>\n",
+       "      <td>Liaoning</td>\n",
+       "      <td>China</td>\n",
+       "      <td>41.2956</td>\n",
+       "      <td>122.6085</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>17</td>\n",
+       "      <td>21</td>\n",
+       "      <td>27</td>\n",
+       "      <td>...</td>\n",
+       "      <td>443</td>\n",
+       "      <td>443</td>\n",
+       "      <td>443</td>\n",
+       "      <td>443</td>\n",
+       "      <td>443</td>\n",
+       "      <td>444</td>\n",
+       "      <td>445</td>\n",
+       "      <td>446</td>\n",
+       "      <td>446</td>\n",
+       "      <td>446</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>78</th>\n",
+       "      <td>Macau</td>\n",
+       "      <td>China</td>\n",
+       "      <td>22.1667</td>\n",
+       "      <td>113.5500</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "      <td>63</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>79</th>\n",
+       "      <td>Ningxia</td>\n",
+       "      <td>China</td>\n",
+       "      <td>37.2692</td>\n",
+       "      <td>106.1655</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>7</td>\n",
+       "      <td>...</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80</th>\n",
+       "      <td>Qinghai</td>\n",
+       "      <td>China</td>\n",
+       "      <td>35.7452</td>\n",
+       "      <td>95.9956</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>81</th>\n",
+       "      <td>Shaanxi</td>\n",
+       "      <td>China</td>\n",
+       "      <td>35.1917</td>\n",
+       "      <td>108.8701</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>22</td>\n",
+       "      <td>35</td>\n",
+       "      <td>...</td>\n",
+       "      <td>668</td>\n",
+       "      <td>668</td>\n",
+       "      <td>668</td>\n",
+       "      <td>669</td>\n",
+       "      <td>669</td>\n",
+       "      <td>669</td>\n",
+       "      <td>669</td>\n",
+       "      <td>669</td>\n",
+       "      <td>669</td>\n",
+       "      <td>669</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>82</th>\n",
+       "      <td>Shandong</td>\n",
+       "      <td>China</td>\n",
+       "      <td>36.3427</td>\n",
+       "      <td>118.1498</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>15</td>\n",
+       "      <td>27</td>\n",
+       "      <td>46</td>\n",
+       "      <td>75</td>\n",
+       "      <td>...</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>923</td>\n",
+       "      <td>924</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>83</th>\n",
+       "      <td>Shanghai</td>\n",
+       "      <td>China</td>\n",
+       "      <td>31.2020</td>\n",
+       "      <td>121.4491</td>\n",
+       "      <td>9</td>\n",
+       "      <td>16</td>\n",
+       "      <td>20</td>\n",
+       "      <td>33</td>\n",
+       "      <td>40</td>\n",
+       "      <td>53</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2420</td>\n",
+       "      <td>2432</td>\n",
+       "      <td>2436</td>\n",
+       "      <td>2445</td>\n",
+       "      <td>2451</td>\n",
+       "      <td>2454</td>\n",
+       "      <td>2462</td>\n",
+       "      <td>2466</td>\n",
+       "      <td>2471</td>\n",
+       "      <td>2476</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>84</th>\n",
+       "      <td>Shanxi</td>\n",
+       "      <td>China</td>\n",
+       "      <td>37.5777</td>\n",
+       "      <td>112.2922</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "      <td>13</td>\n",
+       "      <td>...</td>\n",
+       "      <td>255</td>\n",
+       "      <td>255</td>\n",
+       "      <td>256</td>\n",
+       "      <td>256</td>\n",
+       "      <td>256</td>\n",
+       "      <td>256</td>\n",
+       "      <td>256</td>\n",
+       "      <td>258</td>\n",
+       "      <td>258</td>\n",
+       "      <td>259</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85</th>\n",
+       "      <td>Sichuan</td>\n",
+       "      <td>China</td>\n",
+       "      <td>30.6171</td>\n",
+       "      <td>102.7103</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>15</td>\n",
+       "      <td>28</td>\n",
+       "      <td>44</td>\n",
+       "      <td>69</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1181</td>\n",
+       "      <td>1182</td>\n",
+       "      <td>1183</td>\n",
+       "      <td>1185</td>\n",
+       "      <td>1185</td>\n",
+       "      <td>1185</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1188</td>\n",
+       "      <td>1188</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>86</th>\n",
+       "      <td>Tianjin</td>\n",
+       "      <td>China</td>\n",
+       "      <td>39.3054</td>\n",
+       "      <td>117.3230</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>8</td>\n",
+       "      <td>10</td>\n",
+       "      <td>14</td>\n",
+       "      <td>23</td>\n",
+       "      <td>...</td>\n",
+       "      <td>458</td>\n",
+       "      <td>459</td>\n",
+       "      <td>462</td>\n",
+       "      <td>463</td>\n",
+       "      <td>464</td>\n",
+       "      <td>465</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>470</td>\n",
+       "      <td>472</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>87</th>\n",
+       "      <td>Tibet</td>\n",
+       "      <td>China</td>\n",
+       "      <td>31.6927</td>\n",
+       "      <td>88.0924</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>88</th>\n",
+       "      <td>Unknown</td>\n",
+       "      <td>China</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>89</th>\n",
+       "      <td>Xinjiang</td>\n",
+       "      <td>China</td>\n",
+       "      <td>41.1129</td>\n",
+       "      <td>85.2401</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "      <td>980</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90</th>\n",
+       "      <td>Yunnan</td>\n",
+       "      <td>China</td>\n",
+       "      <td>24.9740</td>\n",
+       "      <td>101.4870</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</td>\n",
+       "      <td>16</td>\n",
+       "      <td>26</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>1007</td>\n",
+       "      <td>1010</td>\n",
+       "      <td>1014</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>1039</td>\n",
+       "      <td>1047</td>\n",
+       "      <td>1064</td>\n",
+       "      <td>1067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>Zhejiang</td>\n",
+       "      <td>China</td>\n",
+       "      <td>29.1832</td>\n",
+       "      <td>120.0934</td>\n",
+       "      <td>10</td>\n",
+       "      <td>27</td>\n",
+       "      <td>43</td>\n",
+       "      <td>62</td>\n",
+       "      <td>104</td>\n",
+       "      <td>128</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1420</td>\n",
+       "      <td>1420</td>\n",
+       "      <td>1421</td>\n",
+       "      <td>1428</td>\n",
+       "      <td>1428</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>1430</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>34 rows × 590 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Province/State Country/Region      Lat      Long  1/22/20  1/23/20  \\\n",
+       "58           Anhui          China  31.8257  117.2264        1        9   \n",
+       "59         Beijing          China  40.1824  116.4142       14       22   \n",
+       "60       Chongqing          China  30.0572  107.8740        6        9   \n",
+       "61          Fujian          China  26.0789  117.9874        1        5   \n",
+       "62           Gansu          China  35.7518  104.2861        0        2   \n",
+       "63       Guangdong          China  23.3417  113.4244       26       32   \n",
+       "64         Guangxi          China  23.8298  108.7881        2        5   \n",
+       "65         Guizhou          China  26.8154  106.8748        1        3   \n",
+       "66          Hainan          China  19.1959  109.7453        4        5   \n",
+       "67           Hebei          China  39.5490  116.1306        1        1   \n",
+       "68    Heilongjiang          China  47.8620  127.7615        0        2   \n",
+       "69           Henan          China  37.8957  114.9042        5        5   \n",
+       "70       Hong Kong          China  22.3000  114.2000        0        2   \n",
+       "71           Hubei          China  30.9756  112.2707      444      444   \n",
+       "72           Hunan          China  27.6104  111.7088        4        9   \n",
+       "73  Inner Mongolia          China  44.0935  113.9448        0        0   \n",
+       "74         Jiangsu          China  32.9711  119.4550        1        5   \n",
+       "75         Jiangxi          China  27.6140  115.7221        2        7   \n",
+       "76           Jilin          China  43.6661  126.1923        0        1   \n",
+       "77        Liaoning          China  41.2956  122.6085        2        3   \n",
+       "78           Macau          China  22.1667  113.5500        1        2   \n",
+       "79         Ningxia          China  37.2692  106.1655        1        1   \n",
+       "80         Qinghai          China  35.7452   95.9956        0        0   \n",
+       "81         Shaanxi          China  35.1917  108.8701        0        3   \n",
+       "82        Shandong          China  36.3427  118.1498        2        6   \n",
+       "83        Shanghai          China  31.2020  121.4491        9       16   \n",
+       "84          Shanxi          China  37.5777  112.2922        1        1   \n",
+       "85         Sichuan          China  30.6171  102.7103        5        8   \n",
+       "86         Tianjin          China  39.3054  117.3230        4        4   \n",
+       "87           Tibet          China  31.6927   88.0924        0        0   \n",
+       "88         Unknown          China      NaN       NaN        0        0   \n",
+       "89        Xinjiang          China  41.1129   85.2401        0        2   \n",
+       "90          Yunnan          China  24.9740  101.4870        1        2   \n",
+       "91        Zhejiang          China  29.1832  120.0934       10       27   \n",
+       "\n",
+       "    1/24/20  1/25/20  1/26/20  1/27/20  ...  8/20/21  8/21/21  8/22/21  \\\n",
+       "58       15       39       60       70  ...     1008     1008     1008   \n",
+       "59       36       41       68       80  ...     1112     1113     1115   \n",
+       "60       27       57       75      110  ...      603      603      603   \n",
+       "61       10       18       35       59  ...      780      780      780   \n",
+       "62        2        4        7       14  ...      199      199      199   \n",
+       "63       53       78      111      151  ...     3001     3007     3012   \n",
+       "64       23       23       36       46  ...      289      289      289   \n",
+       "65        3        4        5        7  ...      147      147      147   \n",
+       "66        8       19       22       33  ...      190      190      190   \n",
+       "67        2        8       13       18  ...     1317     1317     1317   \n",
+       "68        4        9       15       21  ...     1614     1614     1614   \n",
+       "69        9       32       83      128  ...     1521     1522     1523   \n",
+       "70        2        5        8        8  ...    12049    12052    12057   \n",
+       "71      549      761     1058     1423  ...    68287    68289    68289   \n",
+       "72       24       43       69      100  ...     1181     1181     1181   \n",
+       "73        1        7        7       11  ...      412      412      412   \n",
+       "74        9       18       33       47  ...     1583     1584     1584   \n",
+       "75       18       18       36       72  ...      937      937      937   \n",
+       "76        3        4        4        6  ...      574      574      574   \n",
+       "77        4       17       21       27  ...      443      443      443   \n",
+       "78        2        2        5        6  ...       63       63       63   \n",
+       "79        2        3        4        7  ...       77       77       77   \n",
+       "80        0        1        1        6  ...       18       18       18   \n",
+       "81        5       15       22       35  ...      668      668      668   \n",
+       "82       15       27       46       75  ...      923      923      923   \n",
+       "83       20       33       40       53  ...     2420     2432     2436   \n",
+       "84        1        6        9       13  ...      255      255      256   \n",
+       "85       15       28       44       69  ...     1181     1182     1183   \n",
+       "86        8       10       14       23  ...      458      459      462   \n",
+       "87        0        0        0        0  ...        1        1        1   \n",
+       "88        0        0        0        0  ...        0        0        0   \n",
+       "89        2        3        4        5  ...      980      980      980   \n",
+       "90        5       11       16       26  ...     1000     1007     1010   \n",
+       "91       43       62      104      128  ...     1420     1420     1421   \n",
+       "\n",
+       "    8/23/21  8/24/21  8/25/21  8/26/21  8/27/21  8/28/21  8/29/21  \n",
+       "58     1008     1008     1008     1008     1008     1008     1008  \n",
+       "59     1115     1115     1115     1115     1115     1115     1115  \n",
+       "60      603      603      603      603      603      603      603  \n",
+       "61      782      782      783      783      784      785      786  \n",
+       "62      199      199      199      199      199      199      199  \n",
+       "63     3020     3023     3032     3040     3043     3046     3055  \n",
+       "64      289      289      289      289      289      289      289  \n",
+       "65      147      147      147      147      147      147      147  \n",
+       "66      190      190      190      190      190      190      190  \n",
+       "67     1317     1317     1317     1317     1317     1317     1317  \n",
+       "68     1614     1614     1614     1615     1615     1615     1615  \n",
+       "69     1524     1525     1525     1527     1528     1528     1528  \n",
+       "70    12062    12069    12074    12077    12094    12100    12107  \n",
+       "71    68289    68289    68289    68290    68290    68290    68290  \n",
+       "72     1181     1181     1181     1181     1181     1181     1181  \n",
+       "73      412      412      412      412      412      412      412  \n",
+       "74     1584     1586     1586     1587     1587     1589     1589  \n",
+       "75      937      937      937      937      937      937      937  \n",
+       "76      574      574      574      574      574      574      574  \n",
+       "77      443      443      444      445      446      446      446  \n",
+       "78       63       63       63       63       63       63       63  \n",
+       "79       77       77       77       77       77       77       77  \n",
+       "80       18       18       18       18       18       18       18  \n",
+       "81      669      669      669      669      669      669      669  \n",
+       "82      923      923      923      923      923      923      924  \n",
+       "83     2445     2451     2454     2462     2466     2471     2476  \n",
+       "84      256      256      256      256      258      258      259  \n",
+       "85     1185     1185     1185     1186     1187     1188     1188  \n",
+       "86      463      464      465      466      466      470      472  \n",
+       "87        1        1        1        1        1        1        1  \n",
+       "88        0        0        0        0        0        0        0  \n",
+       "89      980      980      980      980      980      980      980  \n",
+       "90     1014     1021     1031     1039     1047     1064     1067  \n",
+       "91     1428     1428     1429     1429     1429     1429     1430  \n",
+       "\n",
+       "[34 rows x 590 columns]"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "infected[infected['Country/Region']=='China']"
    ]
@@ -123,9 +1328,244 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 130,
    "metadata": {},
-   "outputs": [],
+   "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>Lat</th>\n",
+       "      <th>Long</th>\n",
+       "      <th>1/22/20</th>\n",
+       "      <th>1/23/20</th>\n",
+       "      <th>1/24/20</th>\n",
+       "      <th>1/25/20</th>\n",
+       "      <th>1/26/20</th>\n",
+       "      <th>1/27/20</th>\n",
+       "      <th>1/28/20</th>\n",
+       "      <th>1/29/20</th>\n",
+       "      <th>...</th>\n",
+       "      <th>8/20/21</th>\n",
+       "      <th>8/21/21</th>\n",
+       "      <th>8/22/21</th>\n",
+       "      <th>8/23/21</th>\n",
+       "      <th>8/24/21</th>\n",
+       "      <th>8/25/21</th>\n",
+       "      <th>8/26/21</th>\n",
+       "      <th>8/27/21</th>\n",
+       "      <th>8/28/21</th>\n",
+       "      <th>8/29/21</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Country/Region</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",
+       "      <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",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Afghanistan</th>\n",
+       "      <td>33.93911</td>\n",
+       "      <td>67.709953</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>152448</td>\n",
+       "      <td>152448</td>\n",
+       "      <td>152448</td>\n",
+       "      <td>152583</td>\n",
+       "      <td>152660</td>\n",
+       "      <td>152722</td>\n",
+       "      <td>152822</td>\n",
+       "      <td>152960</td>\n",
+       "      <td>152960</td>\n",
+       "      <td>152960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Albania</th>\n",
+       "      <td>41.15330</td>\n",
+       "      <td>20.168300</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>138132</td>\n",
+       "      <td>138790</td>\n",
+       "      <td>139324</td>\n",
+       "      <td>139721</td>\n",
+       "      <td>140521</td>\n",
+       "      <td>141365</td>\n",
+       "      <td>142253</td>\n",
+       "      <td>143174</td>\n",
+       "      <td>144079</td>\n",
+       "      <td>144847</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Algeria</th>\n",
+       "      <td>28.03390</td>\n",
+       "      <td>1.659600</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>190656</td>\n",
+       "      <td>191171</td>\n",
+       "      <td>191583</td>\n",
+       "      <td>192089</td>\n",
+       "      <td>192626</td>\n",
+       "      <td>193171</td>\n",
+       "      <td>193674</td>\n",
+       "      <td>194186</td>\n",
+       "      <td>194671</td>\n",
+       "      <td>195162</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Andorra</th>\n",
+       "      <td>42.50630</td>\n",
+       "      <td>1.521800</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>14988</td>\n",
+       "      <td>14988</td>\n",
+       "      <td>14988</td>\n",
+       "      <td>15002</td>\n",
+       "      <td>15003</td>\n",
+       "      <td>15014</td>\n",
+       "      <td>15016</td>\n",
+       "      <td>15025</td>\n",
+       "      <td>15025</td>\n",
+       "      <td>15025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Angola</th>\n",
+       "      <td>-11.20270</td>\n",
+       "      <td>17.873900</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>45583</td>\n",
+       "      <td>45817</td>\n",
+       "      <td>45945</td>\n",
+       "      <td>46076</td>\n",
+       "      <td>46340</td>\n",
+       "      <td>46539</td>\n",
+       "      <td>46726</td>\n",
+       "      <td>46929</td>\n",
+       "      <td>47079</td>\n",
+       "      <td>47168</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 588 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     Lat       Long  1/22/20  1/23/20  1/24/20  1/25/20  \\\n",
+       "Country/Region                                                            \n",
+       "Afghanistan     33.93911  67.709953        0        0        0        0   \n",
+       "Albania         41.15330  20.168300        0        0        0        0   \n",
+       "Algeria         28.03390   1.659600        0        0        0        0   \n",
+       "Andorra         42.50630   1.521800        0        0        0        0   \n",
+       "Angola         -11.20270  17.873900        0        0        0        0   \n",
+       "\n",
+       "                1/26/20  1/27/20  1/28/20  1/29/20  ...  8/20/21  8/21/21  \\\n",
+       "Country/Region                                      ...                     \n",
+       "Afghanistan           0        0        0        0  ...   152448   152448   \n",
+       "Albania               0        0        0        0  ...   138132   138790   \n",
+       "Algeria               0        0        0        0  ...   190656   191171   \n",
+       "Andorra               0        0        0        0  ...    14988    14988   \n",
+       "Angola                0        0        0        0  ...    45583    45817   \n",
+       "\n",
+       "                8/22/21  8/23/21  8/24/21  8/25/21  8/26/21  8/27/21  8/28/21  \\\n",
+       "Country/Region                                                                  \n",
+       "Afghanistan      152448   152583   152660   152722   152822   152960   152960   \n",
+       "Albania          139324   139721   140521   141365   142253   143174   144079   \n",
+       "Algeria          191583   192089   192626   193171   193674   194186   194671   \n",
+       "Andorra           14988    15002    15003    15014    15016    15025    15025   \n",
+       "Angola            45945    46076    46340    46539    46726    46929    47079   \n",
+       "\n",
+       "                8/29/21  \n",
+       "Country/Region           \n",
+       "Afghanistan      152960  \n",
+       "Albania          144847  \n",
+       "Algeria          195162  \n",
+       "Andorra           15025  \n",
+       "Angola            47168  \n",
+       "\n",
+       "[5 rows x 588 columns]"
+      ]
+     },
+     "execution_count": 130,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "infected = infected.groupby('Country/Region').sum()\n",
     "recovered = recovered.groupby('Country/Region').sum()\n",
@@ -143,9 +1583,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 131,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "infected.loc['US'][3:].plot()\n",
     "recovered.loc['US'][3:].plot()\n",
@@ -161,13 +1613,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 132,
    "metadata": {},
    "outputs": [],
    "source": [
-    "infected.drop(columns=['Lat','Long'],inplace=True)\n",
-    "recovered.drop(columns=['Lat','Long'],inplace=True)\n",
-    "deaths.drop(columns=['Lat','Long'],inplace=True)"
+    "infected.drop(columns=['Lat','Long','Province/State'],inplace=True)\n",
+    "recovered.drop(columns=['Lat','Long','Province/State'],inplace=True)\n",
+    "deaths.drop(columns=['Lat','Long','Province/State'],inplace=True)"
    ]
   },
   {
@@ -181,14 +1633,134 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 133,
    "metadata": {},
-   "outputs": [],
+   "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>infected</th>\n",
+       "      <th>recovered</th>\n",
+       "      <th>deaths</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-01-22</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-23</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-24</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-25</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-26</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-08-25</th>\n",
+       "      <td>38223029</td>\n",
+       "      <td>0</td>\n",
+       "      <td>632272</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-08-26</th>\n",
+       "      <td>38384360</td>\n",
+       "      <td>0</td>\n",
+       "      <td>633564</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-08-27</th>\n",
+       "      <td>38707294</td>\n",
+       "      <td>0</td>\n",
+       "      <td>636720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-08-28</th>\n",
+       "      <td>38760363</td>\n",
+       "      <td>0</td>\n",
+       "      <td>637254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-08-29</th>\n",
+       "      <td>38796746</td>\n",
+       "      <td>0</td>\n",
+       "      <td>637531</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>586 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            infected  recovered  deaths\n",
+       "2020-01-22         1          0       0\n",
+       "2020-01-23         1          0       0\n",
+       "2020-01-24         2          0       0\n",
+       "2020-01-25         2          0       0\n",
+       "2020-01-26         5          0       0\n",
+       "...              ...        ...     ...\n",
+       "2021-08-25  38223029          0  632272\n",
+       "2021-08-26  38384360          0  633564\n",
+       "2021-08-27  38707294          0  636720\n",
+       "2021-08-28  38760363          0  637254\n",
+       "2021-08-29  38796746          0  637531\n",
+       "\n",
+       "[586 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 133,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "def mkframe(country):\n",
-    "    df = pd.DataFrame({ 'infected' : infected.loc[country][1:] ,\n",
-    "                        'recovered' : recovered.loc[country][1:],\n",
-    "                        'deaths' : deaths.loc[country][1:]})\n",
+    "    df = pd.DataFrame({ 'infected' : infected.loc[country],\n",
+    "                        'recovered' : recovered.loc[country],\n",
+    "                        'deaths' : deaths.loc[country]})\n",
     "    df.index = pd.to_datetime(df.index)\n",
     "    return df\n",
     "\n",
@@ -198,9 +1770,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 134,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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/z9133826desIDg7mvPPO46mnniImJgYAl8vFE088wUsvvcThw4eJj4/nl7/8JQ888AAAW7duZcGCBXz99dfYbDYuv/xynnzySUJCQvj444+5+OKLycrKIiIiwlPHr3/9a7Zs2cLatWsBWL9+Pb/97W/ZuHEjMTExXHrppSxZsoTg4GDA3aXr5ptvZu/evaxcuZJLLrmE11577YTr5eTkcNNNN/Hpp5+SkJDAo48+2onvtoiIiEj7c7oMd9Cobd2oCxru4FFNSWUNZQ4npY7qBkGkwbK1y9cfW9IWMSEBJEcGMTQxjGmDY4kJsRIc4EdiWBDhNv92fsVdi2+HFsOA6nLv7NvfBm3oB/jaa69x22238dVXX1FQUMDUqVO55ZZbePLJJ6moqGDRokX87Gc/47PPPgPgvvvu46WXXuKpp57irLPOIjMzk127dgFQXl7OrFmzmDRpEhs3biQnJ4ebb76Z22+/nVdffZUZM2YQERHBO++8w0033QSA0+nkrbfe4uGHHwbcoWfmzJk88sgjvPLKK+Tm5nL77bdz++23s2zZMk/dTzzxBL///e/53e9+1+r1rr/+eg4fPsxnn32G1Wrl17/+NTk5Oaf+nouIiIi0UVWNC3tlNfaKauyVNbX37pBR97i0soaKaiflVU4qa+/rt4SUOmoor3K2a10mEwRb/QgJ8CMk0H0fGuhHn+hgekfbCPC3EOBnJi40gORIG70ignpUy0lbmQzDOLkoeJLsdjvh4eEUFxcTFhbWYF5lZSXp6en07duXwMBAqCqDx5M6s7xj7s8Aa3CrFp02bRrFxcX88MMPAPzhD3/gm2++4eOPP/Ysc+TIEVJSUkhLSyMxMZHY2FieffZZbr755ibbe+mll1i0aBGHDx/2tG785z//4aKLLiIjI4P4+HgWLFjAtm3bWL16NQCffPIJF110EVlZWURGRjJ37lyCgoJ44YUXPNv98ssvmTp1KmVlZQQGBtKnTx/Gjh3LypUrPcucaL1Dhw4xePBgNmzYwMSJEwHYtWsXQ4cO5amnnmpxIH6Tz1ZERESkVrXTRUFZFbklDvLLqsgrcZBf5qC0soayKidlDvd9STPhpLLa1a61WC1mT8ioCxyhAX4E13tcP4g0DiUhAf6EBPph87d0qeugeMvxskF9vt3S0oWcdtppnsebNm3i888/JyQkpMly+/bto6ioCIfDwTnnnNPstnbu3Mno0aM9gQXgzDPPxOVykZaWRnx8PHPmzGHy5MlkZGSQlJTE8uXLOf/884mMjPTUsHfvXpYvX+7ZhmEYuFwu0tPTGTp0aJO6W7Pe7t278fPza7DekCFDGnRTExEREQH3FdmziivJLK4ky17hvq+9FZZXUVBWRX5ZFUXl1ae8r9AAP8KC/AkNdN+HBfoTFuRHWKA/IQF+BFktBPlbsFktBFktjUKJO2gEB1gI8FNrhy/y7dDib3O3eHhr321QP2C4XC4uuugi/uu//qvJcomJiezfv/+42zIMo8VT1NVNP/300+nfvz8rVqzgtttuY+XKlQ26fblcLn75y1/y61//usk2UlNTm627NeulpaU1qENERER6rhqniyx7JYcLKjhcWM6RgnIO154B63BhOdn2pqflbYnFbCIq2EpMSAAxIVaig62EBfljs/oREmDBZvVrNpCEBblDiUWtGt2ab4cWk6nVXbR8ybhx43jnnXfo06cPfn5N3+KBAwcSFBTE6tWrm+0eNmzYMF577TXKyso8oeKrr77CbDYzaNAgz3LXXHMNy5cvJzk5GbPZzAUXXNCghu3btzNgwIA213689YYOHUpNTQ3fffcdp59+OgBpaWkUFRW1aT8iIiLSNThqnOzLKSMt287B/HKOFlZwtMgdUjKLKk846DzQ30xSeBAJ4YEkhAeSGB5IQlgg0SEBRNqsRIe4g0pEkL+6U0mLfDu0dFHz58/npZde4uqrr+aee+4hJiaGvXv3smLFCl566SUCAwNZtGgR9957L1arlTPPPJPc3Fy2b9/OTTfdxJw5c3jwwQeZN28eDz30ELm5udxxxx1cd911xMfHe/YzZ84cFi9ezGOPPcYVV1zRYKzIokWLmDRpEvPnz+eWW24hODiYnTt3smrVKv7yl7+0WPuJ1hs8eDCzZs3illtu4cUXX8TPz4+FCxcSFNT1r7QqIiLS0xWUVbH1aDHbjhazK6uEtCw7+3PLjhtM/C0mekUEkRJlIznSRkpUECmRNlKibKREBhEVbFUPDTllCi0dICkpia+++opFixYxc+ZMHA4HvXv3ZtasWZjNZgB+//vf4+fnxx/+8AcyMjJITEzk1ltvBcBms/Hxxx+zYMECJkyY0OCUx/UNHDiQCRMmsHHjRp5++ukG80aNGsXatWt54IEHmDJlCoZh0L9/f6666qrj1t6a9ZYtW8bNN9/M1KlTiY+P59FHH+X3v/99O7xzIiIi0llySxxsqw0odUElo7iy2WXDAv0YkhBG35hgekUG0SsiiORId1CJDwtU1yzpcL599jDpNvTZioiIeIfTZXCooJw92SXsyLSz7aidbUeLybI3H1D6xQQzvFc4wxLDGJIQyuCEUBLDA9VaIh1CZw8TERER6YEqq518f7CQDfvz+Xp/PluOFFNV0/S0wCaTO6CM7BXOiNrb8KQwQgN79kUMxTcptIiIiIh0YcUV1fxwqJBNBwv5Jr2AzYeKqHI2DCkBfmYGxIUwOD6UEb3CGZkcztDEMEIC9FNQugb9SRURERHpQorLq/ksLZtv0wvZdLCAPTmlNO7snxAWyKR+UUzuH82EPlH0jg7WuBPp0hRaRERERHyYYRjsyLSzbncea3fn8N2BwiZn8+oTbWN87yhO6xPJ5H7R9I62aQyKdCsKLSIiIiI+pqCsii/25LJudx7r9uSSW9LwIo1DEkI5e1As43tHMr53JDEhAV6qVKRzKLSIiIiIeJlhGOzMLOHTndms3pXDj0eKGnT5slktnNE/mrMHxXL2wFj6xHS9i2+LnAqFFhEREREvqHa6+Da9gFU7slm1I5ujRRUN5g9JCGXq4Fim1raoBPhZvFSpiPcptIiIiIh0gspqJxsPFPDN/gL25JSwfl8+JZU1nvmB/mbOGhDLucPimDY4jvgwXddMpE6bQsvzzz/P888/z4EDBwAYPnw4f/jDH5g9e3ZH1CYiIiLSZRmGwb7cMtbtzmXt7ly+Sc+nsrrhqYijg62cMzSOc4clcNaAGIKsak0RaU6bQktycjJ//OMfGTBgAACvvfYaF198MT/88APDhw/vkAK7smnTpjFmzBiefvrpDtvHmjVrmD59OoWFhURERHTYfkREROT4DMPgSGEF244Ws25PHut25zbp8pUQFshZA2MYmhjGmJRwxqRE6lTEIq3QptBy0UUXNXj+2GOP8fzzz7NhwwaFlk7QGSFIREREWq/MUcMXe3JZk+a+ZdkrG8y3Wsyc3jeKqYNiOXtQLIPiQ3QqYpGTcNJjWpxOJ2+//TZlZWVMnjy5xeUcDgcOx7HT9Nnt9pPdpYiIiIhXOV0Ge3JK+P5gEZ/tyuaLPXk4ao51+fK3mOgfG8KkftFMHRzLpL7R6vIl0g7MbV1h69athISEEBAQwK233srKlSsZNmxYi8svWbKE8PBwzy0lJeWUCvZVZWVlzJ07l5CQEBITE1m6dGmD+VVVVdx777306tWL4OBgJk6cyJo1azzz8/Pzufrqq0lOTsZmszFy5Ej++c9/euZff/31rF27lmeeeQaTyYTJZPKMLQLYtGkTp512GjabjTPOOIO0tDTPvC1btjB9+nRCQ0MJCwtj/PjxfPfddx32XoiIiHQX+aUOVu/M5k8fp3HNSxsY9dDHzHr6C+5fuZVPd+bgqHGRGmXjhjP78NqNp7P1oZl8tPBsHvrpcKYPjlNgEWknbW5pGTx4MJs3b6aoqIh33nmHefPmsXbt2haDy3333cedd97peW6321sdXAzDoKKm4sQLdoAgv6A2Nd/ec889fP7556xcuZKEhATuv/9+Nm3axJgxYwC44YYbOHDgACtWrCApKYmVK1cya9Ystm7dysCBA6msrGT8+PEsWrSIsLAwPvzwQ6677jr69evHxIkTeeaZZ9i9ezcjRozg4YcfBiA2NtYTXB544AGWLl1KbGwst956KzfeeCNfffUVAHPmzGHs2LE8//zzWCwWNm/ejL+/f7u+XyIiIl1dtdPFrswSfjhcyPcHC/nhcBEH88ubLBdstTA6JYKJfaOZOSKewfGh6vIl0sFMhlH/0kVtN2PGDPr3788LL7zQquXtdjvh4eEUFxcTFhbWYF5lZSXp6en07duXwMBAyqvLmfjGxFMp76R9c8032PxtrVq2tLSU6OhoXn/9da666ioACgoKSE5O5he/+AV33HEHAwcO5MiRIyQlJXnWmzFjBqeffjqPP/54s9u94IILGDp0KH/605+A5se01A3E//TTTznnnHMA+M9//sMFF1xARUUFgYGBhIWF8Ze//IV58+adzFvRLhp/tiIiIt6WX+rg+0NFbDpYyPeHCvnxSFGTs3sBDIgLYWxKBON6RzI2NYKBcaEaPC/STo6XDeo75eu0GIbRYMxKT7Rv3z6qqqoajO2Jiopi8ODBAHz//fcYhsGgQYMarOdwOIiOjgbcY4T++Mc/8uabb3L06FHPWKDg4NZd8XbUqFGex4mJiQDk5OSQmprKnXfeyc0338zf//53ZsyYwZVXXkn//v1P6TWLiIh0JZXVTnZnl7DlSDE/1IaUA820ooQF+jE21R1OxqVGMjolgvAg9U4Q8bY2hZb777+f2bNnk5KSQklJCStWrGDNmjV89NFHHVJckF8Q31zzTYdsuzX7bq0TNVa5XC4sFgubNm3CYmnYtzUkJASApUuX8tRTT/H0008zcuRIgoODWbhwIVVVVa2qoX53r7omapfLfbTooYce4pprruHDDz/k//7v/3jwwQdZsWIFl156aatfo4iISFeSWVzBV3vz+WZ/Ptsy7OzJLqHG1fT7emBcCONSIxnfO5JxvSPoFxOCWa0oIj6nTaElOzub6667jszMTMLDwxk1ahQfffQR5557bocUZzKZWt1Fy5sGDBiAv78/GzZsIDU1FYDCwkJ2797N1KlTGTt2LE6nk5ycHKZMmdLsNr744gsuvvhirr32WsAdOPbs2cPQoUM9y1itVpxO50nVOGjQIAYNGsRvfvMbrr76apYtW6bQIiIi3UZxeTXfpOfz1d48vtybx77csibLRNr8GdErnLGpkYxLjWBsSiThNrWiiHQFbQotr7zySkfV0aWFhIRw0003cc899xAdHU18fDwPPPAAZrP75GyDBg1izpw5zJ07l6VLlzJ27Fjy8vL47LPPGDlyJOeffz4DBgzgnXfeYf369URGRvLkk0+SlZXVILT06dOHb775hgMHDhASEkJUVNQJa6uoqOCee+7hiiuuoG/fvhw5coSNGzdy+eWXd9j7ISIi0tGOFJazfl8+3x8sZNPBQvbklDaYbzbByOQIzugfzZiUCEb0CicpPFAD5kW6qFMe0yJuTzzxBKWlpfz0pz8lNDSUu+66i+LiYs/8ZcuW8eijj3LXXXdx9OhRoqOjmTx5Mueffz4Av//970lPT2fmzJnYbDZ+8YtfcMkllzTYxt133828efMYNmwYFRUVpKenn7Aui8VCfn4+c+fOJTs7m5iYGC677DIWL17c/m+CiIhIB3G6DDYfLmT1zhxW78whLbukyTL9YoI5c0AMZw6IYXK/aLWiiHQjp3z2sLZqy9nDpPvQZysiIm11pLCcL/fk8cUed5ev4opqzzyL2cSYlAgm9Ilyj0dJjSA6JMCL1YrIyei0s4eJiIiItIdSRw0b9uXzxZ5cvtiTx/68huNSQgP9mDY4jhlD45g6KJYIm9VLlYpIZ1NoEREREa9wugx+PFLkaU35/lBhgzN81bWmTBkYw5SBsYxODsfPYvZixSLiLQotIiIi0mmOFJbzxZ48vtiTy1d78xt0+QLoE23jrNqQMrl/NGGBGpciIgotIiIi0sHKHDW8t/kob393hM2HixrMCw3048z+MUwZFMOUAbGkRvv+pQ5EpPP5ZGjp5HMDSCfQZyoi0vPsyrLz5sbD/O+mI5RU1gDuUxGPS41kysBYpgyKYVQvdfkSkRPzqdBSd7X4qqoqgoJaf0V68X1VVVXAsc9YRES6p6LyKt7fksHb3x1h69Fjp+3vE23j2km9uXhML2JDdZYvEWkbnwotfn5+2Gw2cnNz8ff391ycUbo2l8tFbm4uNpsNPz+f+iMnIiLt5LsDBSxbf4BV27OpcroA8DObOGdoHFefnsrZA2Mxm3VhRxE5OT71C9JkMpGYmEh6ejoHDx70djnSjsxmM6mpqboSsYhIN/PN/nyeWb2H9fvyPdOGJIRy5WkpXDImSddOEZF24VOhBcBqtTJw4EBPdyLpHqxWq1rORES6ka/35fPM6t1s2F8AuFtVLh+XzHWTezM8KUwHqUSkXflcaAH3UXldNV1ERMT3bNifz5OrdvNtujus+FtM/Oy0FG6b1p/kSJ35S0Q6hk+GFhEREfEdhmHwTXoBf/lsD1/tdXcDs1rM/Pz0FG6d2p+kCJ08R0Q6lkKLiIiItOjHI0U8/O8dfHewEHC3rFw1IYX50weQGK6wIiKdQ6FFREREmqisdvLkqt289MV+DAMC/MxcMT6ZW6f2JyVK3cBEpHMptIiIiEgD244Wc+dbm9mdXQrAxWOSuG/2UBLCNd5URLxDoUVEREQAKHXU8OQnu3l1fTouA2JCrCy5bBTnDov3dmki0sMptIiIiPRwhmHwwY+ZPPbhTrLslQBcMCqRh386XNdZERGfoNAiIiLSg207Wszif29n4wH3QPve0TYevngEUwfFerkyEZFjFFpERER6IKfL4H8+38vTn+7GZUCgv5nbpg7gl1P7Eehv8XZ5IiINKLSIiIj0MNn2Shau2MzX+93XXLlgVCIPnD9U11sREZ+l0CIiItKDrNudy2/e3Ex+WRU2q4VHLh7B5eOTvV2WiMhxKbSIiIj0AE6XwTOf7uYvn+/FMGBoYhjPXjOW/rEh3i5NROSEFFpERES6uZySShb881h3sKtPT+XBi4Zp7IqIdBkKLSIiIt2Uy2Xw9w0HWfpJGvbKGmxWC0suG8nFY3p5uzQRkTZRaBEREemG8ksdLHxzM1/syQNgeFIYz/x8LAPi1B1MRLoehRYREZFu5mhRBde9/A3788oI9Ddz//lDmTOxNxazyduliYicFIUWERGRbmRvTinXvfINmcWV9IoIYtkNExgUH+rtskRETolCi4iISDex9Ugx85Z9S0FZFf1jg/nHzRNJDNe1V0Sk61NoERER6Qa+3pfPLa9/R6mjhlHJ4bx6w+lEBVu9XZaISLtQaBEREeniPt2Rza/e+J6qGheT+kXx0tzTCA3093ZZIiLtRqFFRESkC1vx7SHuX7kVlwEzhsbz7DVjdf0VEel2FFpERES6IMMweGb1Hp7+dA8AV45PZsllI/GzmL1cmYhI+1NoERER6WJqnC5+9942Vmw8DMAdPxnAnecOwmTSKY1FpHtSaBEREelCapwubn/jBz7anoXZBA9fPIJrJ/X2dlkiIh1KoUVERKSLMAyDe9/5kY+2Z2H1M/OXq8cyc3iCt8sSEelwCi0iIiJdxJ9X7+Xd749iMZv4n2vGce6weG+XJCLSKTRaT0REpAt4f0sGT326G4DHLhmhwCIiPYpCi4iIiI9btzuXu97aDMCNZ/bl56enercgEZFOptAiIiLiw344VMit/9hEtdPgwlGJ/O6Cod4uSUSk0ym0iIiI+Khv9udz/bKNlFc5mTIwhid/NgazWac1FpGeRwPxRUREfNC73x9h0Ts/Uu00GJcawV+vHY/VT8caRaRnUmgRERHxIYZh8NSq3fz5s70AnD8ygSd/NoZAf4uXKxMR8Z42HbJZsmQJEyZMIDQ0lLi4OC655BLS0tI6qjYREZEexekyuPOtLZ7Actu0/jx79TgFFhHp8doUWtauXcv8+fPZsGEDq1atoqamhvPOO4+ysrKOqk9ERKTHeHJVGit/OIqf2cR/XT6SRbOGaAyLiAhgMgzDONmVc3NziYuLY+3atZx99tmtWsdutxMeHk5xcTFhYWEnu2sREZFuo9RRw58+TuPV9QcAeOqq0Vw6Ntm7RYmIdILWZoNTGtNSXFwMQFRUVIvLOBwOHA5Hg8JERETELa/UwXWvfMvOTPf34x0/GaDAIiLSyEmfhsQwDO68807OOussRowY0eJyS5YsITw83HNLSUk52V2KiIh0K9n2Sq564Wt2ZtqJCQng9RtP567zBnu7LBERn3PS3cPmz5/Phx9+yJdffklycstHhJpraUlJSVH3MBER6dEO5JUxb9m3HMwvJzE8kOU3T6RfbIi3yxIR6VQd2j3sjjvu4P3332fdunXHDSwAAQEBBAQEnMxuREREuqXPdmXzmze3UFxRTUpUEG/cPImUKJu3yxIR8VltCi2GYXDHHXewcuVK1qxZQ9++fTuqLhERkW6npLKaRz/YyZvfHQZgbGoEL1w7nriwQC9XJiLi29oUWubPn88bb7zBv/71L0JDQ8nKygIgPDycoKCgDilQRESkO9ieUcwvXt/E0aIKTCa48cy+3DNzsK7BIiLSCm0a02IyNX+u+GXLlnH99de3ahs65bGIiPQkldVOPvgxk8Xvb6fEUUPvaBtPXDGa0/u2fOZNEZGeokPGtJzCJV1ERER6nG1Hi7n1H5s4UlgBwOl9onj5+tMIC/T3cmUiIl3LKV2nRURERJq3akc2t7/xPY4aFwlhgVw7KZWbp/RTdzARkZOg0CIiItLO3tx4iPtXbsPpMpg2OJZnfj6W8CC1roiInCyFFhERkXZSVeNi8b+3s/ybQwBcNq4X/335KPwsJ30tZxERQaFFRESkXWTbK/nV8u/ZdLAQkwl+M2MQt08fgNnc/ElsRESk9RRaRERETtF3Bwq4bfn35JY4CA30488/H8v0IXHeLktEpNtQaBERETkF//z2EL9/bxs1LoPB8aG8cN14+sQEe7ssEZFuRaFFRETkJC37Kp3F/94BwAWjEvnvy0cRHKCvVhGR9qZ/WUVERE7Ca+sPeALLbdP6c+/MwS1ehFlERE6NTmciIiLSRq9/fYAH398OKLCIiHQGhRYREZE2eG39Af7wL3dguXWqAouISGdQ9zAREZFWqHG6eOSDHbz29UEAfnl2PxbNUmAREekMCi0iIiInUFxezfw3vufLvXkA3H3eIOZPH6DAIiLSSRRaREREjiOjqIJ5f/uWPTml2KwWnrpqDDOHJ3i7LBGRHkWhRUREpAW7s0uY97dvySyuJCEskGU3TGBoYpi3yxIR6XEUWkRERJrx3YECbnx1I/bKGgbEhfDajafTKyLI22WJiPRICi0iIiKNrNqRze1vfI+jxsW41Aj+dv0EImxWb5clItJjKbSIiIjUs+LbQ9y/cisuA84ZEsez14wjyGrxdlkiIj2aQouIiAhgGAZ/+WwvT67aDcDPTkvm8UtH4mfRJc1ERLxNoUVERHo8p8vgwfe38Y8NhwC44ycDuPPcQTqlsYiIj1BoERGRHi2/1MHCNzfzxZ48TCZY/NPhzJ3cx9tliYhIPQotIiLSY206WMjtb3xPZnElQf4Wlv5sNOePTPR2WSIi0ohCi4iI9Egf/JjBb97cTLXToF9sMM/PGc/ghFBvlyUiIs1QaBERkR7n718f4A/vb8cwYObweJb+bAwhAfpKFBHxVfoXWkREegzDMHj60z08s3oPANdOSmXxT0dgMWvAvYiIL1NoERGRHqGqxsX9K7fyv5uOALDgnIEsnDFQZwgTEekCFFpERKTbKyqvYv4b3/PV3nwsZhOPXDyCayamerssERFpJYUWERHp1j7alsnv3ttOXqkDm9XC/8wZx/TBcd4uS0RE2kChRUREuqW8UgcPvr+dD3/MBGBgXAhP/3wMw5PCvVyZiIi0lUKLiIh0K4Zh8P6WDB56fzuF5dVYzCZum9qfO84ZQICfxdvliYjISVBoERGRbqOy2smid37kX5szABiSEMqfrhzNiF5qXRER6coUWkREpMszDIPVO3N46tPdbM+w42c2cftPBvCraQOw+pm9XZ6IiJwihRYREenSCsuqWPTOj3yyIxuA8CB/nr92HGf0j/FyZSIi0l4UWkREpMvasD+f37y5mcziSvwtJm48qy83ndWXuNBAb5cmIiLtSKFFRES6nGqni798tpdnP9uDy4B+McH8+eqxGrsiItJNKbSIiEiXsulgIb9950f25JQC8LPTknnwouEEB+grTUSku9K/8CIi0iUYhsGyrw7w+H92UuMyiA628uBPh/PT0UneLk1ERDqYQouIiPi8UkcNi9750XOhyAtHJfLYJSMJt/l7uTIREekMCi0iIuLTdmeX8Kvl37M3pxQ/s4kHLhjK9Wf0wWQyebs0ERHpJAotIiLik5wug1e+3M+fPtlNVY2L+LAAnpszjvG9o7xdmoiIdDKFFhER8TkH88u4++0tbDxQCMC0wbE8ccVoYkMDvFyZiIh4g0KLiIj4DEeNk9fWH+DpT/dQXuUk2Grh9xcO46oJKeoOJiLSgym0iIiIT9hyuIjfvLmZ/XllAEzqF8UTV4wmJcrm5cpERMTbFFpERMSrnC6Dv67dx1OrdlPjMogLDeDu8wZzxfhkzGa1roiICJjbusK6deu46KKLSEpKwmQy8d5773VAWSIi0hOkZZVwxV/X88THadS4DM4fmcAnvzmbn01IUWARERGPNre0lJWVMXr0aG644QYuv/zyjqhJRES6uTJHDc+v2cdf1+6jxmUQbLXw4E+Hc+X4ZI1dERGRJtocWmbPns3s2bM7ohYREenmqmpcrNh4iD+v3kteqQOAGUPjeeSS4SSGB3m5OhER8VUdPqbF4XDgcDg8z+12e0fvUkREfEyN08XKH47y58/2cLigAoDe0Tbumz2EmcMT1LoiIiLH1eGhZcmSJSxevLijdyMiIj7I6TL495YMnlm9h/Tas4LFhASw4JwBXDUhFatfm4dWiohID9ThoeW+++7jzjvv9Dy32+2kpKR09G5FRMSLapwu/m9bFn9evYc9OaUARNr8uXVqf66b3BubVSevFBGR1uvwb42AgAACAnQFYxGRniDHXsmKjYd545tDZNkrAQgL9OMXZ/fj+jP7EhKgsCIiIm2nbw8RETklhmHwbXoBr284yMfbsqhxGQBEB1u5dlJvbprSl7BAfy9XKSIiXVmbQ0tpaSl79+71PE9PT2fz5s1ERUWRmprarsWJiIjvKnXUsPKHo/zj64OkZZd4po/vHcl1k3oze2QCAX4WL1YoIiLdRZtDy3fffcf06dM9z+vGq8ybN49XX3213QoTERHfU1xezepd2Xy8PYt1u/OoqHYCEORv4ZKxSVw7qTfDk8K9XKWIiHQ3bQ4t06ZNwzCMjqhFRER8UFZxJZ/syOLj7Vls2F+A03XsO6BfTDDXTurN5eOTCQ9SFzAREekYGtMiIiJN7M0p5ePtWXyyI5sth4sazBscH8rM4fGcNzyB4UlhusaKiIh0OIUWERGhuKKajekFfL0/nzVpOezLLfPMM5lgbEoEM4cnMHN4An1igr1YqYiI9EQKLSIiPZC9sprvDhTw9b58NuwvYHtGMfV6feFvMTG5fwwzh8dz7tB44sICvVesiIj0eAotIiI9QKmjho0HCtiwL58N+/PZerRhSAH3+JSJ/aKZ3D+aaYNjdZpiERHxGQotIiLdTEWVk20ZxWw+VMTWo8VszygmPa+sSUjpE21jcv9oJvWLZmLfaBLC1ZoiIiK+SaFFRKQLq6x2siurhG1Hi9meYWfL4SLSsksanOGrTu9oG5P6ultSJvaLIjE8yAsVi4iItJ1Ci4hIF1FSWc2ODDvbMuxszyhm+1E7e3NLmw0osaEBjEmJYHRyOMN7hTM8KYy4ULWkiIhI16TQIiLiYyqrnaTnlbEvt5S9OaXsyS5le0YxB/LLm10+OtjqCSYje4UzJiWCxPBAnYpYRES6DYUWEREvMQyDI4UV7MoqYVemnV1ZJezMsnOgmfEndXpFBDEsKYwRSe6QMqJXOPFhAQooIiLSrSm0iIh0gpLKanZnl7Azs4RdWXZ2ZZaQllVCiaOm2eXDAv0YEBdC/9gQBsSFMDwpnGFJYUQFWzu5chEREe9TaBERaUeV1U4O5JexN6eU3Vkl7Mxyh5TDBRXNLu9vMTEgLpShCaEMSQxlSEIYQxJCiQ1V64mIiEgdhRYRkZNQXFHN3pxS9uWUesae7M0t5XBBeYtduxLCAj3BZGjtfb/YYPwt5s4tXkREpItRaBERaYZhGOSWOEjLLmF3dilHCyvIKKogs7iCo0UV5JVWtbhuaG3XroFxIQxNDPO0nkSqa1fXZM+EfZ9BWQ6Mmwe2KG9XJCLS4yi0iEiPZhgGuaUOT6vJnpxS0rJKSMsuoai8+rjrJoYHesac9I8LoX9sMAPiQogNUdeubsGeCZ89Aj++Ca7asUcuJ5x9t3frEhHpgRRaRKTHKCqvYldWCbuz3YPg02of2yubHwxvNkGf6GAGxofQOzqYpPBAkiKCSIoIok9MMCEB+ie02zEMyNwCW1bAD/+AqpKG88vzvVOXiEgPp29cEel2isur2Z3jDiR7skvZk+Pu4pVb4mh2eZMJUqNsDKhtNRmcEMqg+FAGxIUQ6G/p5OrFK+yZsPUtd1jJ2XFseq/xMPu/3d3DPn8Mqpu/Vo6IiHQshRYR6bIqqpzszSklLbuEtCw7adnuM3Zl2StbXCc5MojB8aEMSghlcHwoA+PdpxVWOOmB8vbAd8vg0Hp364rhck+3BMCQ82H01TDgXDCb4dDX7nnVzZ8FTkREOpZCi4h0CQVlVWw+XMjmw8WkZdnZnV3KgfwyjBbO1JUUHsjA+FAGxYcwMD6UgXHue3Xp6uEKD8KOf8GO9+DopobzUifD6J/DsEsgKKLhPP8g971aWkREvELf3iLic6qdLnZm2vnhUBE/HCrkh8NFHMxv/sdipM2fwQnu0wcPjA9hSEIoA+NDCQv07+SqxWcVHoDt77mDSsYP9WaYYPBsGHkFJJ8OESktb8Pf5r5XS4uIiFcotIiI12UWVxwLKIeK2Hq0GEeNq8ly/WODGZMSybCkMAbHhzI4IZSYEKvO1CUNlRfAnk9g76eQtRVydx2bZzJD7zNh2MUw9KcQGt+6bXpaWhRaRES8QaFFRDpVRZWTbRnFnoDyw6GiZseghAf5MzY1grEpkYxJjWBMcgThNrWeSAuyd8CG59yD6DM2g+E8Ns9khj5nubt9Db0IQuLavn1PS4u6h4mIeINCi4h0GJfLIC27hC2Hi9hypIgth4tJyy7B2eiS8RaziSEJoZ6QMjY1gr4xwWpBkeOrtLvP9rX7I9j/+bGB9ABxw92D6ZNPh17jIDjm1PallhYREa9SaBGRdlVUXsW6PXmsTctl7e5c8kqbnmY4LjSAMSkRjOsdydiUCEYmh2Oz6p8jOY6SbPdZvg6uh4NfQ16a+4KP9YPK0ItgxBWQOBqi+rbv/tXSIiLiVfqVICKnpNRRwzf78/l6Xz5f789nR6a9wRm9bFYLY1IiGJUcwejkcMakRpAYHuS9gsX3GQYUHXKfZvjAl+6gUrCv+WVjBsG4uTBgBsQN7biaPC0tLZ9OW0REOo5Ci4i0SbXTxZbDRXy5N48v9+Sx+XARNY26ew2OD2Xq4FimDYrltD5RWP3MXqpWfJrLBUUHIW+3+5azCzK+h/y94KxqtLAJ4kdA7zPct6Qx7uuphCa4rw7a0dQ9TETEqxRaROS4DMM9LuWrvfms35vHN+kFlDpqGizTO9rGGf1jmNw/mkl9o4gLC/RSteKTahzuIJK3G3J3u7t25e6G/D1Q00LLhdkPksa6A0rqGZA6qem1UzpT/e5hhtE5QUlERDwUWkSkidwSB+t257JuTy5f7c1vMi4l0ubPGQNiOKv2lhJl81Kl4jNqqqA8331NlPw97qvN5+1xB5TCAw3HntRnCYDoARA7CGIGQ+Iod4tKaCL4WTvzFRyfX20QN5zgrPat2kREegCFFhGhqsbF5sNFfLknlzW7c/nxSHGD+YH+Zk7vG82Z/aM5c0AMwxLDMJt1pLlHqSyGosNQfLj2/lDD52U5x18/IMw9/iR2cMP7yD5gtnTKSzgl/vWCeXW5QouISCdTaBHpgWqcLrYeLWb9vnw27M9n44ECKqsbHgkf0SuMaYPiOGtgDGNTIwjw6wI/LKXtnDVQlgslmVCa7b4vyT72vPiIO5Q4ik+8LZMZwpIhZgBED4SYgccCSkh81+5SZfEHk8Xd0lJd4d2uaiIiPZBCi0gP4HIZ7Mi0s2F/Puv35fNtM+NSYkKsTOoXzbTBcZw9KIa4UI1L6dKcNe7Wj8YhpPHzstyWu241FhQFESkQngIRqbX3tc/Dk93zzd30pAsmk7u1papEpz0WEfEChRaRbqiiysnOLDtbjxTz9b58NqTnU1Re3WCZ8CB/JvWL8gygHxgXoos5+jqX091Nq6LQfWsuhNQ9L8sFjBNuEnC3IITEuc/EFZLgvq+7hfU6FkoCQjr05fk8/6Da0KIziImIdDaFFpEurqi8iu0ZdrZnFNfe29mfW0qjsxATbLVwet9jIWVoYhgWjUvxPsNwBxB7hvtWkgnleVCW5w4epdnuEFKaDZVFbdu2yeLullU/hDQOJSEJ7qvFd4VxJd6m0x6LiHiNQotIF2EYBpnFlQ0Cyo4MO0eLmv8BFRNiZXhSOKf3jWJy/2hG9grH39JNu+74GsNwt4iU5riDR3m++1ZRAOUF7ml1IcWeATVt/BFsDXWPqQiOdZ9lKzTefR8S3/C5LVphpD3VP+2xiIh0KoUWER9T7XRxpLCCg/llHCoo52B+OWlZJezItFNQ1viCe24pUUEMTwxneFIYw3uFMTwpnLjQAHX3ak/Vle6w0eSW1/B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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df.plot()\n",
     "plt.show()"
@@ -215,9 +1799,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 135,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df['ninfected'] = df['infected'].diff()\n",
     "df['ninfected'].plot()\n",
@@ -233,9 +1829,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 136,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df[(df.index.year==2020) & (df.index.month==7)]['ninfected'].plot()\n",
     "plt.show()"
@@ -250,9 +1858,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 137,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df['ninfav'] = df['ninfected'].rolling(window=7).mean()\n",
     "df['ninfav'].plot()\n",
@@ -268,9 +1888,263 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 138,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "      <th></th>\n",
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+       "      <th>iso2</th>\n",
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+       "      <th>0</th>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>41.153300</td>\n",
+       "      <td>20.168300</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>2877800.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>12</td>\n",
+       "      <td>DZ</td>\n",
+       "      <td>DZA</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Algeria</td>\n",
+       "      <td>28.033900</td>\n",
+       "      <td>1.659600</td>\n",
+       "      <td>Algeria</td>\n",
+       "      <td>43851043.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>20</td>\n",
+       "      <td>AD</td>\n",
+       "      <td>AND</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Andorra</td>\n",
+       "      <td>42.506300</td>\n",
+       "      <td>1.521800</td>\n",
+       "      <td>Andorra</td>\n",
+       "      <td>77265.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>24</td>\n",
+       "      <td>AO</td>\n",
+       "      <td>AGO</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Angola</td>\n",
+       "      <td>-11.202700</td>\n",
+       "      <td>17.873900</td>\n",
+       "      <td>Angola</td>\n",
+       "      <td>32866268.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4191</th>\n",
+       "      <td>84056037</td>\n",
+       "      <td>US</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>56037.0</td>\n",
+       "      <td>Sweetwater</td>\n",
+       "      <td>Wyoming</td>\n",
+       "      <td>US</td>\n",
+       "      <td>41.659439</td>\n",
+       "      <td>-108.882788</td>\n",
+       "      <td>Sweetwater, Wyoming, US</td>\n",
+       "      <td>42343.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4192</th>\n",
+       "      <td>84056039</td>\n",
+       "      <td>US</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>56039.0</td>\n",
+       "      <td>Teton</td>\n",
+       "      <td>Wyoming</td>\n",
+       "      <td>US</td>\n",
+       "      <td>43.935225</td>\n",
+       "      <td>-110.589080</td>\n",
+       "      <td>Teton, Wyoming, US</td>\n",
+       "      <td>23464.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4193</th>\n",
+       "      <td>84056041</td>\n",
+       "      <td>US</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>56041.0</td>\n",
+       "      <td>Uinta</td>\n",
+       "      <td>Wyoming</td>\n",
+       "      <td>US</td>\n",
+       "      <td>41.287818</td>\n",
+       "      <td>-110.547578</td>\n",
+       "      <td>Uinta, Wyoming, US</td>\n",
+       "      <td>20226.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4194</th>\n",
+       "      <td>84056043</td>\n",
+       "      <td>US</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>56043.0</td>\n",
+       "      <td>Washakie</td>\n",
+       "      <td>Wyoming</td>\n",
+       "      <td>US</td>\n",
+       "      <td>43.904516</td>\n",
+       "      <td>-107.680187</td>\n",
+       "      <td>Washakie, Wyoming, US</td>\n",
+       "      <td>7805.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4195</th>\n",
+       "      <td>84056045</td>\n",
+       "      <td>US</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>56045.0</td>\n",
+       "      <td>Weston</td>\n",
+       "      <td>Wyoming</td>\n",
+       "      <td>US</td>\n",
+       "      <td>43.839612</td>\n",
+       "      <td>-104.567488</td>\n",
+       "      <td>Weston, Wyoming, US</td>\n",
+       "      <td>6927.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4196 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           UID iso2 iso3  code3     FIPS      Admin2 Province_State  \\\n",
+       "0            4   AF  AFG    4.0      NaN         NaN            NaN   \n",
+       "1            8   AL  ALB    8.0      NaN         NaN            NaN   \n",
+       "2           12   DZ  DZA   12.0      NaN         NaN            NaN   \n",
+       "3           20   AD  AND   20.0      NaN         NaN            NaN   \n",
+       "4           24   AO  AGO   24.0      NaN         NaN            NaN   \n",
+       "...        ...  ...  ...    ...      ...         ...            ...   \n",
+       "4191  84056037   US  USA  840.0  56037.0  Sweetwater        Wyoming   \n",
+       "4192  84056039   US  USA  840.0  56039.0       Teton        Wyoming   \n",
+       "4193  84056041   US  USA  840.0  56041.0       Uinta        Wyoming   \n",
+       "4194  84056043   US  USA  840.0  56043.0    Washakie        Wyoming   \n",
+       "4195  84056045   US  USA  840.0  56045.0      Weston        Wyoming   \n",
+       "\n",
+       "     Country_Region        Lat       Long_             Combined_Key  \\\n",
+       "0       Afghanistan  33.939110   67.709953              Afghanistan   \n",
+       "1           Albania  41.153300   20.168300                  Albania   \n",
+       "2           Algeria  28.033900    1.659600                  Algeria   \n",
+       "3           Andorra  42.506300    1.521800                  Andorra   \n",
+       "4            Angola -11.202700   17.873900                   Angola   \n",
+       "...             ...        ...         ...                      ...   \n",
+       "4191             US  41.659439 -108.882788  Sweetwater, Wyoming, US   \n",
+       "4192             US  43.935225 -110.589080       Teton, Wyoming, US   \n",
+       "4193             US  41.287818 -110.547578       Uinta, Wyoming, US   \n",
+       "4194             US  43.904516 -107.680187    Washakie, Wyoming, US   \n",
+       "4195             US  43.839612 -104.567488      Weston, Wyoming, US   \n",
+       "\n",
+       "      Population  \n",
+       "0     38928341.0  \n",
+       "1      2877800.0  \n",
+       "2     43851043.0  \n",
+       "3        77265.0  \n",
+       "4     32866268.0  \n",
+       "...          ...  \n",
+       "4191     42343.0  \n",
+       "4192     23464.0  \n",
+       "4193     20226.0  \n",
+       "4194      7805.0  \n",
+       "4195      6927.0  \n",
+       "\n",
+       "[4196 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 138,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "countries = pd.read_csv(countries_dataset_url)\n",
     "countries"
@@ -285,18 +2159,98 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 139,
    "metadata": {},
-   "outputs": [],
+   "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>UID</th>\n",
+       "      <th>iso2</th>\n",
+       "      <th>iso3</th>\n",
+       "      <th>code3</th>\n",
+       "      <th>FIPS</th>\n",
+       "      <th>Admin2</th>\n",
+       "      <th>Province_State</th>\n",
+       "      <th>Country_Region</th>\n",
+       "      <th>Lat</th>\n",
+       "      <th>Long_</th>\n",
+       "      <th>Combined_Key</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>790</th>\n",
+       "      <td>840</td>\n",
+       "      <td>US</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>US</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>-100.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>329466283.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     UID iso2 iso3  code3  FIPS Admin2 Province_State Country_Region   Lat  \\\n",
+       "790  840   US  USA  840.0   NaN    NaN            NaN             US  40.0   \n",
+       "\n",
+       "     Long_ Combined_Key   Population  \n",
+       "790 -100.0           US  329466283.0  "
+      ]
+     },
+     "execution_count": 139,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "countries[(countries['Country_Region']=='US') & countries['Province_State'].isna()]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 140,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "pop = countries[(countries['Country_Region']=='US') & countries['Province_State'].isna()]['Population'].iloc[0]\n",
     "df['pinfected'] = df['infected']*100 / pop\n",
@@ -321,9 +2275,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 141,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df['Rt'] = df['ninfected'].rolling(8).apply(lambda x: x[4:].sum()/x[:4].sum())\n",
     "df['Rt'].plot()\n",
@@ -341,9 +2307,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 142,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "ax = df[df.index<\"2020-05-01\"]['Rt'].replace(np.inf,np.nan).fillna(method='pad').plot(figsize=(10,3))\n",
     "ax.set_ylim([0,6])\n",
@@ -360,9 +2338,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 143,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df['ninfected'].diff().plot()\n",
     "plt.show()"
@@ -377,9 +2367,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 150,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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++27ExMQgOjoa99xzDyZOnIjzzz8fADB27FgsXrwYN998M9atWwcAuOWWW3DxxRd71cmPiIiGlie+ysM3Ryuwt6gWG27Jhlbj/rvFXQU1eH9XWzZqb1Gdz4/VW5kpZ8uz01HfasXjX+XhL18cQYQ+CFfN4NxfIqK+5tfM1AsvvACj0YgFCxZg2LBhys97772n7HPvvfdi1apVWLFiBaZPn44zZ87g66+/Rnh42zd4Tz31FC677DJcddVVmDNnDkJCQvDZZ59BrW6rPX/77bcxceJELFq0CIsWLcJZZ52FN998059Pj4iIBiBRFLHvdB0AYE9RHdb+54jb/Sw2O/740UEAwM8mSmXp+VVNqGky+/R4JxxrTGXG905mSrZiwUjccs4IAMD9H+7Hfw6U9urxiYioa326zlR/xnWmiIiGhpK6Fsz+v28hCID8F/CZa6bg55OSXPZ76fuTWPPlUUSHavHN6vm48sWtOFnZhFevm47zxrqfj9teTZMZUx+RytQPP3whQrS9WxAiiiJ+/+EBbNhZDK1ahVevn455mXG9+hhERENRv1xnioiIKND2n5bWPByTGIEVC0YCAO77936ccJTjAVLA9fR/jwMA7l8yBlGhWkxNlZbo2FPk/bwpeX2plOjgXg+kAKkpxaOXT8RFE4fBbLPjln/u7ta8LiIi6h4GU0RENKQcOFMHADgr2YDVF4zG7JExaDbbcNtbe9BksgIAHv7sMJrNNkxPi8KVU6UutFPTHMFUYZ3Xj3XcTyV+ztQqAU9dPRnnjI5Di8WGG9/YCaOjYQYREfkXgykiIhpS5MzUxOEGaNQq/OOaKUiI0OFERSPu//AANh+twMZDZVCrBPzl8glQqaT1CuXM1L7TdbDa7F49lpyZ6s3mE+5oNSq8uGwqRsWHoa7Zgrd3FPr18YiISMJgioiIhgxRFHHgjBRMTRoeCQCIDdPh+WunQqMS8Nm+Etzxzh4AwI1zMzAmsa1OPjM+DOE6DZrNNuSVN3Q4tjtKZqqX2qJ3JkSrwe3zpbLF9T8VwGT1fYFhIiLyDYMpIiIaMoprWlDXbIFWrcLoxLZs0bS0aPzhZ9JiuM1mG4YZ9PjNeZku91WpBExOjQQgdQH0RluZn38zU7KfT0pCYoQeFQ0mfJJb0iePSUQ0lDGYIiKiIWO/Y77UmGHh0GnULrf9ek46rpiSDLVKwCOXTkCormPDiCmOUr+9XjR5qGs2o7LBBAAY1UfBlFajwq/npAMAXv7+FOx2NuwlIvInBlNERDRkHJDnSyUbOtwmCAL+dtUk7PnfC3D+OPetz6c6MlN7i+u6fCw5K5UcGew2MPOXa2amIkynwfGKRnx3rKLPHpeIaChiMEVEREOG3HzirOEdgylACqgMIUEe7z8lRcpMebN47/Fyeb5U32SlZBH6ICydmQoAeOn7U3362EREQw2DKSIiGhLsdhEHz8jBVGS3jmEICVJK9vZ2sd7UsT7q5OfO9bPToVEJyDlVg/2n6/r88YmIhgoGU0RENCTkVzehwWSFTqPqUYAzJSUSQNeL957ow05+7SVFBuOSSUkAgHXMThER+Q2DKSIiGhLk+VLjkyKgUXf/z5+3i/cerwhcZgoAbj5nBADgPwdKUVTdHJAxEBENdgymiIhoSGibLxXZo+N4s3ivscWC8vq+7eTX3thhEThndBzsIvDaT/kBGQMR0WDHYIqIiIaEA4626O46+fnCm8V7TziyUkkGPcL1nhta+NutjuzUezuLUdtFwwwiIvIdgykiIhr0bHYRB8/UAwAmpfQsmPJm8V65k9+oAMyXcjZ7ZAzGDYtAi8WGt3IKAzoWIqLBiMEUERENeicqGtFisSFUq0ZGbM/L7rpavPeY3BY9QCV+MkEQcOt8KTv1xrYCtFpsAR0PEdFgw2CKiIgGPbk9+PhkA9QqocfHm6pkpjoGU3a7iNxiaXuggykA+NnEYUiODEZVoxkf7CoO9HCIiAYVBlNERDToHZDXl+rhfCmZvHhvQXUzqhtNyna7XcQfPz6IPUV1UAnAjIzoXnm8nghSq3CbIzv14pZTsHhomkFERL5jMEVERIOe0snPsUZUT7ku3lsHABBFEX/65CDe3VEElQA8edVkjIwLfGYKAH45PQWxYTqcqWvBJ7klgR4OEdGgwWCKiIgGNYvNjsOlUvOJ3spMAa6lfqIo4s+fHMLb24sgCMATv5yEy6Yk99pj9ZQ+SI2b52UAAJ7/7gRsdjHAIyIiGhwYTBER0aB2rLwBZqsd4XoN0mJCeu248npTuwtr8dBnh/FmTiEEAXj8ykm4YurwXnuc3nLtrDRE6DU4VdmErw6VBXo4RESDAoMpIiIa1NoW6zVAEHrefEI2NU0Kprbn12D91gIIAvDYL87CldP6XyAFAGE6Da6fI2Wnntt8AqLI7BQRUU8xmCIiokFNDqYmJkf26nFHxYUhXK9R/v1/V0zEVdNTevUxetuvZ6cjRKvGoZJ6bDlWGejhEBENeAymiIhoUDtwpg4AMGl4782XAqTFe88bEw+VAKy5fCKunpHaq8f3h6hQLa6dKY3z+c0nAzwaIqKBj8EUERENGJ/vL8Hcx77Fh3tOe7V/q8WGvLIGAMDEXg6mAKnRxPY/nI+lM/t/ICW7ad4IaNUq7CiowY78mkAPh4hoQGMwRUREA8Kpykb87oP9OF3bgnv/td+rQCCvrAEWm4joUC2SI4N7fUwatQpx4bpeP64/JUToceV0aV7Xc5tPBHg0REQDG4MpIiLq9yw2O377Xi5aLDbog1Sw2kXc/tZunKlr6fR++8/I86V6t/nEQHfbOSOhVgnYcqwSBx2vERER+Y7BFBER9Xt//+9x7DtthCE4CF+unIdxwyJQ3WTGLf/chRazze199hbV4rlvpcxLb8+XGuhSY0JwyaQkAMxOERH1BIMpIiLq13bk1+C576QP/GuvmIgRcWF4+brpiAnV4lBJPX73r30d2ny/t7MIV6/LQVl9K0bGhWJZdloght6v3TZ/JADgq0NlHgNSIiLqHIMpIiLqt4wtFvz2vVyIInDltOH42cRhAIDkyGC8sGwaNCoBn+8vxfPfSZ3pTFYb/vDRAdz37wMw2+y4cHwCPr5jDuLD9YF8Gv1SVmI4okO1sIvAycrGQA+HiGhAYjBFRET91p8/OYgzdS1IjQ7Bg5eMd7nt7IxoPHSptO2Jr/OwYUcRrnkpB+9sL4IgAL+7MAsvXDsN4fqgQAx9QBgVHwYAOF7REOCREBENTAymiIioX/p47xl8klsCtUrA0/8zGWE6TYd9rp2ZhmWzUiGKwP0fHsCeojpE6DV47foZuGPhKKhUbDrRmdEJUjB1rJyZKSKi7mAwRURE/c7p2mb86eODAICV52ZiamqUx30f+Pl4nJ0RDQAYkxiOz+6ai4VZ8X0yzoEuMz4cAHCcwRQRUbd0/JqPiIgowN7cVogGkxVTUyNxx8KRne4bpFbhjV+fjR9PVGHOqBiEaPmnzVuZjszUCZb5ERF1C//iEBFRv7OjQFqQd9msNGjUXRdRBGvVuGBcgr+HNejImanCmma0WmzQB6kDPCIiooGFZX5ERNSvtJhtOHBaWkh2Rnp0gEczuMWGaREZEgSRHf2IiLqFwRQREfUrucV1sNpFJEboMTwqONDDGdQEQcBoR3bqRAWDKSIiXzGYIiKifmWno8RvenoUBIHd+PxtlNLRj/OmiIh8xWCKiIj6FTmYkjv0kX9lymtNsaMfEZHPGEwREVG/YbXZsaewFgAwPY3BVF8YneBoj84yPyIinzGYIiKifuNoWQOazDaE6zTISgwP9HCGBDkzVVjdhFaLLcCjISIaWBhMERFRvyGX+E1Lj4JaxflSfSEuXIcIvQZ2Ecivagr0cIiIBhS/BlPff/89fv7znyMpKQmCIODjjz92uV0URTz44INISkpCcHAwFixYgEOHDrnsYzKZcNdddyE2NhahoaG45JJLcPr0aZd9amtrsXz5chgMBhgMBixfvhx1dXX+fGpEROQHuwqkEj+2RO87giAopX5sQkFE5Bu/BlNNTU2YNGkSnn32Wbe3//Wvf8WTTz6JZ599Fjt37kRiYiIuuOACNDS0XcxXrVqFjz76CBs2bMCPP/6IxsZGXHzxxbDZ2koRli5ditzcXGzcuBEbN25Ebm4uli9f7s+nRkREvUwURWWxXgZTfSvT0dGP7dGJiHyj8efBlyxZgiVLlri9TRRFPP300/jjH/+IK664AgDwxhtvICEhAe+88w5uvfVWGI1GvPrqq3jzzTdx/vnnAwDeeustpKSk4L///S8uvPBCHDlyBBs3bkROTg5mzpwJAHj55ZeRnZ2NvLw8ZGVl+fMpEhFRLymqaUZlgwlatQpnDTcEejhDyijHWlPs6EdE5JuAzZnKz89HWVkZFi1apGzT6XSYP38+tm7dCgDYvXs3LBaLyz5JSUmYMGGCss+2bdtgMBiUQAoAZs2aBYPBoOzjjslkQn19vcsPEREFzo58KSs1cbgB+iB1gEcztIyW15qqYJkfEZEvAhZMlZWVAQASEhJctickJCi3lZWVQavVIioqqtN94uPjOxw/Pj5e2cedtWvXKnOsDAYDUlJSevR8iIioZzhfKnAyHZmpwupmmKzs6EdE5K2Ad/Nrv7q9KIpdrnjffh93+3d1nN///vcwGo3KT3FxsY8jJyKi3rSzUJ4vFdXFntTbEiJ0CNdrYLOLKKhqDvRwiIgGjIAFU4mJiQDQIXtUUVGhZKsSExNhNptRW1vb6T7l5eUdjl9ZWdkh6+VMp9MhIiLC5YeIiAKjqtGEU5VSW24u1tv3BEFQ1ptiRz8iIu8FLJjKyMhAYmIiNm3apGwzm83YsmULZs+eDQCYNm0agoKCXPYpLS3FwYMHlX2ys7NhNBqxY8cOZZ/t27fDaDQq+xARUf8ml/hlJYTDEBIU4NEMTXKp33F29CMi8ppfu/k1NjbixIkTyr/z8/ORm5uL6OhopKamYtWqVVizZg0yMzORmZmJNWvWICQkBEuXLgUAGAwG3Hjjjbj77rsRExOD6Oho3HPPPZg4caLS3W/s2LFYvHgxbr75Zqxbtw4AcMstt+Diiy9mJz8iogFCXqx3Okv8AkZuj36cmSkiIq/5NZjatWsXFi5cqPx79erVAIDrrrsO69evx7333ouWlhasWLECtbW1mDlzJr7++muEh4cr93nqqaeg0Whw1VVXoaWlBeeddx7Wr18Ptbqt09Pbb7+NlStXKl3/LrnkEo9rWxERUf+zyxFMnZ3BEr9AyUxgZoqIyFeCKIpioAfRH9TX18NgMMBoNHL+FBFRH2o2WzHxwa9hs4v46f5zkRwZHOghDUkldS2Y/X/fQqMScPjhxdBqAt6jiogoYLyNDXilJCKigNpbVAebXURyZDADqQAaZtAjTKeB1S6ioLop0MMhIhoQGEwREZHf7SqowYxH/4uV7+5FRX2ry22cL9U/CIKAUfHyvCmW+hEReYPBFBER+ZUoiljz5RFUNpjw6b4SnPe3LXhzWwFsdqnKvC2Y4nypQJPbox+vYBMKIiJvMJgiIiK/2p5fgz1FddBqVJiYbECDyYo/fXIIV7ywFfuK67C3qA4AcDaDqYAbLTehYGaKiMgrDKaIiMivntssLZFx1fTh+PiOOXjokvEI02mwr7gOlz73E5rNNkToNUpWhAJnVAIzU0REvmAwRUREfrOvuA4/HK+CWiXg1nNGQq0ScN3sdHxz93xcNHGYst/09GioVEIAR0pAW2Yqv6oJFps9wKMhIur/GEwREZHfyFmpSycnISU6RNmeEKHHc9dOxeu/noELxiXgjoUjAzVEcpJk0CNUq4bFJqKQHf2IiLrk10V7iYho6DpW3oCvD5dDEIAVC9wHSwuz4rEwK76PR0aeyB399p024nh5I0bFhwd6SERE/RozU0RE5BcvfHcSALB4fCI/lA8gmY5Sv2NsQkFE1CUGU0RE1OuKqpvx6b4SAMCKBaMCPBryBdujExF5j8EUERH1uhe/PwmbXcQ5o+Mwcbgh0MMhH2Q6OvqdqGBmioioKwymiIioV5UZW/GvXacBAHcuZFZqoMl0lGSeqmxSFlYmIiL3GEwREVGveuWHUzDb7JiRHoWzM7gQ70CTFBkMrVoFs82OkrqWQA+HiKhfYzBFRES9prbJjLe3FwEA7mBWakBSqwSkxUht7POr2B6diKgzDKaIiKjXvLGtAC0WG8YnRWD+6LhAD4e6KT02FACDKSKirjCYIiKiXtFituGf2woBALfNHwlBEAI8IuquDB+DKVEUIYqcX0VEQw+DKSIi6hX/3nMaNU1mDI8KxpIJiYEeDvVAeowUTBVUdx1MGZstmPvYZtz+1h4GVD1kstpwsrIRpyrZSZFooNAEegBERDTw2ewiXvnhFADgxrkZ0Kj5Xd1AJmemCrzITO0sqMGZuhacqWvBTyeqMTcz1t/DGxTK61vxr92nUVDVhKKaZhTXNKO0vhVyPPrBbdmYkc4GLkT9HYMpIiLqsU2Hy1FQ3QxDcBCump4S6OFQD8nBVHFtCyw2O4I6CY6POS3u+/dvjmHOqBiWeHrhkc8P4/P9pR5v/+lEFYMpogGAwRQREfXYS9+fBAAsn5WGUB3/tAx0CRE6BAep0WKxobimGSPiwjzue7y8rSRtZ0Ettp2qxuyRzE51RV4U+X9mpCB7ZAxSokOQGh2Cj/eewV++OIIjpfUBHiEReYN1GERE1CO7Cmqwp6gOWrUKv5qdFujhUC8QhLb26F3NmzpWLmWm5GzWP7457t/BDQKiKOJ0rbSG103zRuDSycmYmhqF2DAdxiVFAAAOM5iiXmJsseCnE1Wc0+gnDKaIiKhHXvpemit1xdRkxIfrAzwa6i0j4uSOfs0e97HZRSXDsubyidCqVcg5VYPtp6r7ZIwDlbHFgkaTFQAwPCrY5bZxw6RgqrimBQ2tlj4fGw0+D3xyENe+sh1fHy4P9FAGJQZTRETUbacqG7HpiPQH+qZ5GQEeDfUmuaNffpXnznLFNc0wWe3QaVQ4OyMav5w+HADw9yGYndp6ogrXvJSjBJedkbNSsWE66IPULrdFhmgxzCB9KXG0rKHDfYl8IYoivj9eBQDYU1Qb4NEMTgymiIio2175MR+iCJw/Nh6j4sMDPRzqRelKRz/PmSm5xG9UfBjUKgErFo5CkFrA1pPV2FlQ0yfj7C9e/TEf205V46O9p7vct7hGek1TooPd3i5npzhvinoqv6oJNU1mAMBJLwJ98h2DKSIi6paqRhP+tVv64HjzvBEBHg31thFeLNx73PHhbHSCFEgnRwbjymlSdmqozZ06WGIEABRWew4+ZXJmanhUiNvbxzqCqcMlAy+Y+njvGXy890ygh0EOuwvbslHeZE2HovL6VtT3oKSWwRQREXXLP7cWwGy1Y1JKJM7OYAvnwUbOTJUYW9BqsbndR85MZSa0dftbsWAUNCoBPxyvcvkgN5hVNLSivN4EACiq8SaYkvZpP19KNtaHzNRHe09j5bt7+8X8qoZWC+7+YB/u/mBfjz6cUu9x/h0sqmn2+Ls8VBVUNeHcJ77DNS/ldPsYDKaIiMhnzWYr/plTCAC49ZwRXFdoEIoJ1SJcp4Eoeg4Q8hxzekY7lXimRIfgiqnJAIZOdurQmbagx5uFjtsyU56CKen1zCtvgM3uuQObKIp49Iuj+HRfCd7dUeTLkP2ipK4VNrsIm1306nUg/9vlFEzZxa67cwLAmboWfH2ozJ/D6jfWfX8STWYbDpXUo9TY0q1jMJgiIiKfVNS3Ytkr21HXbEFqdAguHJ8Y6CGRHwiCoGSn3JX6WW12nKqUtstlfrI7Fo6CWiVgy7FK5BbX+X2sgXbwjFH5//pWK+qazZ3u31WZX1pMKEK0arRa7J2WWZ6sbEJVo5QR27CzOOCtr0vq2j6MFnhR7kj+VddsVkr70h1LHZys6DqYuvdf+3DLm7uxOa/Cr+MLtPL6Vvx7d1tJ6t6ium4dh8EUERF5bW9RLS5+5kfsKapDhF6Dv155FtQqZqUGqwylCUXHD2CFNc0w2+wIDlJ3yLCkxYTisslSduq5zSf8P9AAO+AUTAGdBxLSGlOdl/mpVQKyEqUAtbP1pnKcWtCfqmzCzoLAllWWOH2zz8xU4Mnd+0bEhmJ6ulSK3dW8KZtdxJ7COgDAD8eq/Dq+QHv1x3yYbXbl33u6WZbMYIqIiLzy/q5iXL0uBxUNJmTGh+GTO+di1oiYQA+L/KizzNRxp05+KjcB9XWOBZy3n6oOeMbE3w45GkXog6SPVYWdlFLVNVvQZJbmrSRHug+mAO/mTcnBlE4jPe6GnYEt9XPJTDGYCjh5vtS0tCiMipfmNZ6o7DyYyq9qQotjXtWOgsG7Xpyx2YK3HaXqP5+UBKD7reMZTBERUacsNjse+OQg7v3Xfphtdiwal4CP7pijZC1o8MqIlUqD3AVTx8qlD2XOzSecZTrmUdW3WlHbPHibEdQ0mXHGEUQszIoH0HlHP7nELz684xpTzroKpkRRRM4pqf386gtGAwC+PFAKY0vgXuvSulbl/72Zm0P+tavAKZiKcwRTXWSmnDOhh0vq+0VjE3/457YCNJltGJMYjt+enwkAOFhSD5PV9wYdDKaIiMitZrMVGw+WYunLOXhjm/QN3m/PH40Xl01DmE4T4NFRX5AX7nX3wVju5Nd+vpQsWKtGkmPx2c4W/h3o5PlSGbGhmJBsANB5IFHcRYmfrKu1puT5UjqNCtfPSUdWQjhaLXZ8mhu4tuQuZX6cMxVQFpsd+07XAQCmp7dlpk5VNnba1ORQSVvJql2EXzpy/u6DfbjoHz8ErLNgi9mG17cWAABuXzASGbGhiA7Vwmy1d2s5AgZTRESkqG0y44NdxbjpjV2Y8vAm3PbWHuwsqEWoVo2Xlk/Db87PdFvSRYOTnH0srzehyWR1ue14ubzGlPvMFABkxEn3lxtVDEbyfKkJyQakRkuZvKJOM1NyMOW++YRsTGI4BEF67asdTSacbXOU+E1Li4JOo8bVM1IASI0oAqXEKTNV02QOaJZsqDtcUo9Wix2G4CCMiA1DSnQItGoVTFa7Szmmu/sBQLAja9rbi2+3Wmz4957TOFRS32GuYV/ZsLMINU1mpEaH4KKJwyAIAqakRAIA9nSjCQWDKSIigrHZgpve2Inpj/4Xv/vXfvz3SDlMVjtSooNx09wMfLFyHhaxa9+QExmiRVRIEADXbIvFZscpR7YpM959ZgpoC8Y660g30Mnf5E9IinDK5HVd5tdVZipUp0GaIzg7UtrQ4XZ5vpQ8b/GKqcnQalTSh9TTff8h1W4XUWaUgimN4wuXzuaOkX/tcpovpVIJUKsE5ffRU6mfKIpKMCUvb7Ajv3eDqZOVjZATY/kB+JLFYrPj5e9PAQBunT8CGrUUCk1JjQQgNVnyFYMpIiLCmi+P4L9HKmCzixg7LAKrzs/Ef34zD9//biH+9+JxSiMCGnrSlY5+bQFCYXUTLDYRIVp1p00UMmKlrNVgDqYOOtaYmphsQKqj/XRVowmN7TJ5sq7aojvzNG9KFEVsbxdMRYZosdjxhUcgGlFUNZlgttkhCMDE4VK542B+3/u7PU7BlExpQuEhmKpoMKG6yQy1SsDybKmBzL5iY6+W48kZbQA4FYDz45PcEpQYWxEXrsMvpg5Xtk9NlV6n7rRHZzBFRDTE5Zyqxnu7pNKgd26aif/8Zh5WnT8aY4dFcDFeamuP7pRlUJpPeOjkJxsRN7gzU8Zmi7Kg8fgkAwzBQUomz1OpX1dt0Z15mjd1srIRVY1m6DQqTEoxKNv/x1Hq90luCZrN7oM5f5GbT8SH65RmB5014iD/EUURuwqljJJzMDWyi2BKzrKOjAtFVkI44sJ1MNvs2NeLa8XllbdlWft6LqXdLuLFLScBADfOzXBpAHNWSiRUgrRgcXl9q6dDuMVgiohoCDNZbfjDRwcAAEtnpmL2qNgAj4j6m4yYjgFRV80nZCOcyvzsnUx6H6jkD58p0cEwOIKoNMfr5a7ETVpjyrsyP6AtM9V+raltp9o+KOs0bR8IZ42IQVpMCBpNVnyxv9TXp9Mj8jycpMhgp2zm4Ayi+zspIDBBoxIwaXiksr2r9uhyid84xxdpZ2dIa1P1ZqnfcZdgqm/Pj01HynGiohHheg2unZnqcluYTqNcz3wt9WMwRUQ0hD2/+SROVTYhLlyH+xaPCfRwqB9yt9ZUW/OJzoOp5MhgBKkFmKx2lPr4be9AIE+gn5jclh1Kc5T6FdZ0zMrUNlvQLK8x5U0wlSQFUycqGl1aNrefLyVTqQRcNV3KTr3Xx40oShzzpZIMwcrcsXzOmQoIuQPf+KQIBGvbgm3n9uju1n6T10sbnySdz2c7Fvrd0YtNKJwzUwXVzZ12FuxNoiji+e+krNSvstMQrg/qsM9URxbP1yYUDKaIiIaoExUNeP67EwCAB34+Dobgjn9ciDLcZBnkzJSnNaZkGrVK6XAXiMnm/naw3YdPoPPMVLEjwEqI0LlklDxJMuhhCA6C1S4qpVnu5ks5++W04VCrBOwqrHXJAvhbqZKZ0iPdsT4Zy/wCo219qWiX7SPiQiEIgLHFguomc4f7yRnQcY4gXs5M7SmshdVm7/G4ms1WFNdI54lKAMxddBbsTQXVzdhXXAetWoVfz8lwu488b2qPj+3guVAIEdEAJIoiCqub8cOJKmw9UYXqRjOsdjusdhFWmwibXYRNFDE9LQqrF41GfLje5f52u4g/fHgQFpuIc8fE46KJwwL0TKi/kzNT1Y5W18FBaiVL1VVmCpCaUJysbEJ+VSPmZg6uMtKDbjJT6Y7MlHPDDpkvzScAQBAEjB0WjpxTNThS2oDxSQaP86Vk8RF6nDsmHpsOl+O9ncX434vH+fy8ukNeY2qYU2ZKbo/OL2r61m43zScAQB+kxvCoYBTXtOBERSNiw3TKbfWtFiX4lefqZSWEI0KvQX2rFYdL63GWU8lgd8gZ7dgwLSJDtDhR0Yj8qiakRHv3+9ATcknuuKQIl+ftTO7od+CMEWar98Ejgykion7MbhdhstrRYrGh2WzFgdNG/HCiCj8cr1S+4evMiYpGfL6/FKvOz8R1s9MR5GgD+/6uYuwoqEFwkBoPXzqejSbIozCdBnHhOlQ2mFBQ1QR9kBpWu4hwnQbDDPou7z8iLhQ4EpjOXf7U0GpRgsoJbsr8ityU+fnSfEI2dlgEck7VSPNZpnmeL+Xsf2akYNPhcvx7z2n8bnGWV1mwnpLXmEqK1CO03TkzybGGD/lfo8mKo2VShml6elSH20fFhSnBlHNm86ij/X6SQY+oUC0AqWx0Rno0vjlagR35NT0OppznWobqNEowdc7ouB4d1xvKfDBH1s2dEbGhiAwJQl2zBUdK65Fh8K6Ab1AFU88//zwef/xxlJaWYvz48Xj66acxb968QA+LiKhTLWYbDpcasf+0EQfOGHHgtBGVjSa0mG0wdfLtWJBawNTUKMzLjMWIuDBoVAI0agFqlQoalYBmsw3Pfnsc+04b8ZcvjmDDzmI8+PPxGJ0YhjVfHgEA3L1otNffktPQlRETKn0wrm6CyhF4j0oI8yoIl8sEB9vCvfL8kuTIYEQ7PnwCbWV+JcYWmKw2l0DGl+YTsvbt0T3Nl3I2f3ScEszsLarrdN/e4tyAAnA9Z3wNpowtFlz23E8AgNvnj8TlU5OVL4Koc7lFdbCL0jmWENHxy45R8WHYnFfZoaPfYafMjbMZGVIwtT2/BjfNG9GjsTkHUzqN9H72VRMKpYRxmOdgSl68d3NeJfYU1SJjone/N4MmmHrvvfewatUqPP/885gzZw7WrVuHJUuW4PDhw0hNTe36AEQ0pImi6PGDYavFhjN1LSiqacbpmmYU1TSj2WxDRHAQDO1+IvRt/x+u17i0jW5otaCgqhn51U3Ir2xCQXUTjpTW41h5A7yZgxukFpAWE4p5mbGYlxmLmRkxCNV1fhk/b0w8PthdjMc25uFERSOWvbodiRF61LdaMSE5AtfPTvflZaIhKj02BDsKaly68o3uZLFeZ4N14V65xG98uw+fMaFahGrVaDLbUFzTonRQA5wzU95/gaG0Ry+r73K+lEyjVmFMYjgqG0xKAOdPZqsdlY0mAFKZHyBl6HYU1Lgtd+zK14fKlPPl3n/vxzObj+OuhZkMqrzgriW6M/l8PNmuo98hJXPjWjoqz5vaVVADu13sdCmErhxzalwjH6bPgikvMlMAMCU1CpvzKrG3qA6/GGrB1JNPPokbb7wRN910EwDg6aefxldffYUXXngBa9eu9f5ATU2A2od0uE4HaBwvo9UKmEyASgUEO33r1NSNE0WrBYIcNcY2G9DaCggCEOJ0AW5uBkQRe4tqvV4DwK7RwB7k+AbNbofGJKXlrcFtx1WbWiHYfZtoaFerYdc6alBFEZrWFjfHNUGw+7bwm6hSw6Zrq23VtEgXZas+WHo9AKjMJqhsvh5XBZuu7Rsb5bg6vfT+AVBZzFBZO67T4aYBTtttggCrvu246tYWCKIIm1YH0XFeCRYLVBaL52N42G4NDlEeW36PbFotRLV0/gk2K1Rmk+fBeRi7y3tkNkGw2WAPCoJdE+Q4rg1qx3Hddf/xdGzX98gMwWb1eP55GpszuyjCJtrRotbBIgqw2u2wt5oBixl2tQaiTgtAgAARWpN0/tnsImx2wGpzzCWyizDb7GhqtaLRZEWT2fFfkw0NUEOjDYJOrUKIYEeoYIMmKAj10KDM0YUs2OxbNzJBAHShwQgL06PFbEdtfTO0VgvsggBTUNt5HWxuRUyYFhOTDRifFIEJyREYHhmCYK0auiA1goPU0AepoXb+I6bVAkGOa08n1wiVKOLqcTFYnD4Dz24+jne2F8FY1YpQAXhs8RTld1URFCQd2/EeocVxe6jTor0tLdJtvtBopOslIL3Zzc0dj9vaKj0XX6jVgNPvnHK9DQlRzj+YTNL12ReeruPBwco1AmYz0MnvslseruPQ69v+9lgs0rF95e49cvc3qhvHlRffPV1SA7PZCo3N2tZ8Qj7/PBgRLJ3j1eWtMBnr2zI17t4jT+efL9y9R57OP1+0e4+OnyqHzmp2mS+FpiYIAEaHqXC0rAnFxRUYFdr2e1tVVoNgcytSdfa2c6qLzxGZCWEIt5pgqmvFT/sK0VRTj0iNCpOiNZ1+vkgJk455ura5y88RPnHzHlXUNEMUAa1GhZhQLdDSglGhAoLNrSg9UwU0JXV9XKf36KuDZQg2t+LsjCgcMkpB6b3/3o91Xx/C7fPScelkH4KqIXaNOHisBMHmVsyK13U8P0JDMdLR0a/4TLV0u+P8O1xaD7XdhokG1/NqgkGDaNGClrpWnCwoR6a7eZLuruNuPscWFVcg2GzCmHABNrsonR8lVZ7P4166RlQ2mNBQbUSIAIwJV0n383CNmJoaBYgiDp8oAZoSuzw2AEAcBEwmk6hWq8UPP/zQZfvKlSvFc845x+19WltbRaPRqPwUFxeLAESjdMp6//P++20Hff99adv8+a4PFhvr2zEBUXz22bb7b94sbRs3zvW448b5fNyn5lwjpt33uZh23+fi+Tc8J4qAWBUcoWxLu+9zcVvKBJ+P+8aUi5T7T7nrbWW783E/z5rj83E/z5rjcgx5+5S73la2vTHlIp+Puy1lgstxq4IjRBEQz7/hOWXbU3Ou8fm4eTGpLsfNi0kVRUC8+po1yrb/veA2n4/r6T26/dL7lW23X3q/7+eZh/fofy+4Tdl29TVrunVcd++Ru/PP1x9375Gn88+XH3fvkfP5N/ZP/+nWcd29Rwczp4j3vJ8rPvvtcfGrg6WiLab/XCPEBx5ou//Bg9K22FjX486f7/txV6xou39FRdt2Z1de6ftxr7zS9Rjy9oqKtm0rVvh+XE/X8YMH27Y98IDvx/X0Hm3e3Lbt2Wd9P66n98jd3yhff0RR/M+BEjHtvs/FHycvEEVI14gteY7XWD7/fP1x9x65O/98/XH3Hnk6/3z5cfMefZ41R/z2SHnb9u4c14vPEbWhBp+Pu/muP4tp930u3vN+rt+vEeboGDHtvs/Fc/76rev558uP4z1qbLWIZ696V9neZLKIL205KU575OtufY7gNcLx47hG1DaZXD/rvf++aLLYxFF/+KLbnyNcyNdxd3+jfP0JwDWivsUsTl0pfY4wAiIA0Wg0ip0ZFJmpqqoq2Gw2JCQkuGxPSEhAWVmZ2/usXbsWDz30UF8Mr1/JSgzHpZOlb4gSi6VoXqdRKdsAIOZT911OOpMRG6IcI7S+7Zsa5+Mmfed9jbhyn8hgl2PIFk9IRFOElMLO2OP7fI+YMJ3LceXa3XPHxGNcirR9zAnvSlicRQRrcPmUZAhO/waAeaPikDQ+GQAwuSLS5+PqNGr8YupwANKXNHGfSe/RrBHRCJkmbT/LHO3x/p25avpw5f9Ttkjv0bTUKJgda5WMCHb/O9SVK6YkockgjSlzn/RN2IRkA645Wyq7jS/qxjfvAH4xdTjqRoyEVi0guyQG+EnqwHP3BaMhAtDX1gDP+H7cF5ZNQ/PseTBZbAh55SiwCcgeEYOP75iDlCjHnIhHfD/uny4ehxsvmA2tWoWRW+qBT6SyoMd/OaltJ/Z+oH5O7ujXaGr79t6bTn6DldlqgzxLanxy52VDvUHTjdKqSMciwqdrWwA/z++XSz+TDL7/nW/vu7xKWJzacIdoNbj5nBFYNisNpd88BeT1+CGGtMgQLWLDtC7bTlQ0wmITERzEEspwfRBGxna+5EN7giiKop/G02dKSkqQnJyMrVu3Ijs7W9n+6KOP4s0338TRo0c73MdkMsHkVO5QX1+PlJQUGEtKEBHhw4WxH5T5+YQlPJJ+mp7vlB9LeBSdpOd9NsBLeGA2ez7/fMFrhITXCMkAvUa0mG0Y++eN0FnNUNnt0Ifqsefhn0nzDL24Rtz9/j58eaAU9ywajRvlSewD+Bqx+3g5lr3wI2INwfjhgZ+17eM4Tz7YVYw/f3IIczNj8fKvpgMA9p+uw9XrcpAQocN3v1vYdh8vrhGvfXUAj391TPn3mzeejenpnX+BtvNMI3752i6kRofg+7vP8es1Yt2Wk1j7fTGumJqMJ6+aDLS0oKnFjOl/+S8AIOf358EQ0kV7dMd7tPLdvfg09wzunDkM91w4psM14g8f5OKjvWewZEIinrx6ctfjHULXiHd3FOHhzw5j9sgYvHr9jI7HdryWV6/bhtxjpfjrFRNw6cwR+CC3FL/7137MTovAO7+a2uFuOSer8Ov1u5AQocPmexZ0nF/sxeeI9388jgc+OYQ5mbF4xfE7ceULW3GopB7PXjMF541zTYgA6LVrhHz9+e0FmbjlnJFdXiN+/+99+PinE7h2Wiz+tGwBjEZjp7HBoMhMxcbGQq1Wd8hCVVRUdMhWyXQ6HXQ6NxmY0FDXk8IXGk3bBbH9MXtCrXZ/jBDfMzIuVCr3xw3u4TdLguD+uM4Xs+5yd1ydru2PZG8eV6tt+4XtLnfvUVBQ2wWmu9y9R57OP1+4e488nX++cPceeTr/fOHuPfJ0/vnC03vU0+PyGiHhNaLNALlGBGvVSDLo4Wj4hXFJUW0fqLy4RiQPj0VLXi2ON4nev0f9+BpxoKIZLVo9Rqe1S/k4jjt8eBxatHqccHq+RSYjWrR6xCZEeX58D+9R5ohEtGiLAEiVFBOzkoAu2p0nx0sfFkuNLbAJKqj9eI0oNkvngpKZCg5GaHAwwmIMUke/VmBSXNevuclqw7dHKwBBwLnTR3R8nfR6LDtvHN45VI1PThjxO6tKaXjhtUF6jTh4xohnt5eiRavHhNFJnZ7jo+LDsD1fh2ONdmW+FACMGR7j9n6Txuhh0R9CQauI02ZV5+tCefgccdhoQ4tWj/SUOOUxkpJjsavKjBPNIs7r6neyB9eI3Bqz9Ps6IrHj/m7eoylp0Xh3px67K7wLhAdFPk+r1WLatGnYtGmTy/ZNmzZh9uzZARoVERHR4CGX+gHA6ATfymBGyO3RB0lHvwNnpA+fzutLOZPXmiquaYbVUbLWnbbosrFO7Zw7W1/KWUKEHhqVAItNREVDN6oLfNC2xpTrc8twtIkvqPbufd96shqNJiviw3WY7GFNo3FJEZg1Iho2u4h/bivs/qD7kV0FNbj4mR+w7WR1t+7//s5iXPHCVpypa0FqdAiWzuy8i7XchEJujy538mvfmVIWrFVj4nDpXN+RX9OtMR6vcLRFT2wrD+6LTp/NZqty3emqk59sqmPx3oOlRq/2HxTBFACsXr0ar7zyCl577TUcOXIEv/3tb1FUVITbbrst0EMjIiIa8JyDqUwv26LLBlt79EOOFJ2nYCoxQg+tRgWrXUSpUQo0utMWXRYbpkNcuDxX1rt2zWqVgGGRUpbgjJ/bo8trTMmPJ0uPlZ6rt+3RvzooVRhdOD6x0xbcN8zJACCVtbWYfSwN7ofe2FaIg2fqcf+H+13mi3Wl1WLD/f/ej3v/vR9mqx3njYnHZ3fOdbu+lDO5PfqJikaIoogjXrQNl1ukdzeYyitra4suGxHn/y9Z8soaIIrS71B8uHfVDyNiwxCh18Bk8e69GDTB1NVXX42nn34aDz/8MCZPnozvv/8eX375JdLS0gI9NCIiogFvhFMwlZXoYzDl+NBU2WBCQ6uPc0j6mVaLDccd3+hP9BBMqVQCUh2lUHJWpieZKQD42YREBAep8bOJXrZrhrSgsPNj+4scMCa3y0yl+ZCZstlFbDpcDkBqMtWZ88YmICU6GHXNFny090x3htyv7CmsBQAUVjdjw44ir+5TXNOMK1/cig07iyEIwD2LRuPlX03vem4a2oKpwupmnKpqQoPJCq1a5bImWntnO+bo7SjwPZiqaTKjyrEOWabTY6TH+P9LFmWxXi+zUoD0+zsl1f06Xe4MijlTshUrVmDFihWBHgYREdGgI3/wAdC2xpSXIvRBiA3ToarRhIKqZqVkaCA6UloPm11EbJgWCRGe59mkx4TgREUjCqqbMS+zLaDpdL5JJx68ZDz+eNE4aDXefw8uZcFqcKbOf8FUk8kKY4sUIA8zuH7zL2ckvQmmdhXUoLrJDENwkJIF8UStEnD97Aw88vlhvP5TPq45O8Xjouv9XamxxeX9+fs3x3H51OEI62RB9p0FNbj5n7tQ12xBVEgQ/nHNFMzL9L5l4zCDXllY+j8HSgEAoxPDOl27a3paNARBCnzu/dc+hOmCEKJVI1irRqhWjYy4MMwf7X4Mx8qlEr/hUcEuC83L2W75S5ZwfQ/nirqhLNY7zLeum1NSI7H5gHdlpIMqmCIiIiL/yEoMhyAACeF6xIX5Pll/RGwoqhpNOFXV2G+DKVEUcbq2BftPG3HgjBEnKhohCIBWrYJGLSBIrVJK5sYnGTr9AC9nZYqqmxzHlcv8upeZEgQBWo1vAUNbZqob3Qu9VGqUXo9wnabDh2E5AC/wIvPw1SEpK3X+2ASvFuT95fThePLrPByvaMSPJ6p8Cib6k92OrFRWQjhMVhsKqpvxyg+nsOr80W73LzO24rY3d6Ou2YJJww14ftm0DhnBrgiCgJHxYdh/2ohP95UAAMYP6/x30hAShLOSDdh32oj3d512u8+GW2a5LUM97gimstotp2AIDkJsmBZVjWa/fcnSncwUAGnxXi8xmCIiIqIupUSH4PXrZyA+XN+tLEBGbCh2FNT0u3lTxhYLXv3hFPYU1eFgiRF1zd6VIU5xTFL3RG5CUVDdjKpGM1otdggCfO8+1wNy4OZNmd+pykbUNJm7bLne3hkPzSeAttegttkCY7PFYwmaKIr46pA8X8p9F+b2IvRB+OX0FKzfWoDXfswf8MHUzBHRmJkRgzve2YOXvz+Fa2emKfPkZBabHXe9uwfVTWaMHRaB927Nhj6o62Yk7oyMk4KpY+VSyao3wcazS6di0+FyNJmsaLbY0Gyyotlsw8GSehwprcc/txW4DabyHMFUppu16TJiQ1HVaO70S5YPdhWjxWLDr7LTfXiGUuno0VLpsX3NTE1OjcTwqGAUe7EvgykiIiLyyoKs+G7fV5431d+Cqdd/ysc/vj2h/DtILWBMYgQmJBswdlg4NCoVrHY7zFY7LDYRVpsduiAV/ufszjumtWWmmpXMkNyYoq8kO4KprhpQiKKIX722A6drW7Bu+TRcON77eVmlHppPAECoToP4cB0qGkwoqG7CpJBIt8c4VFKPM3UtCA5S4xwPpWLuXD87HW9sK8DmvEqcqmzEiDjfyk/7A3m+1LS0KPxsYiImpURiX3Ednvn2OB6+dILLvk98nYedBbUI02nw/LVTux1IAegwP8qbYColOgQ3zM3osP1oWT0WP/0Dvj5UjvL61g4NMOSALSux4/uTERuKnQW1Hq8LpcYW/O5f+wEAs0fGdjqvq72C6ia0WGzQB6mUklNvReiDsHHVOTA80PW+DKaIiIjI7/prR7+DjjbnV09PwbJZaRidGOZV6/GupDuyMoU1TSiq6VmJX3elODoHnqlrgSiKHjOKVY1mJXt177/2Y2KywW2myZ0So+fMFCCV+inBVEqk2302Orr4LciK8ylASI8NxXlj4vHfIxVYv7WgQ/ARKC1mG97KKcSlU5I67SDXYrYpbcmnpUlrt92/eAyueTkH72wvwg1zMpR5RZsOl2PdllMAgMevPMvn4KC9ke0Cz7E+Zm6cjUmMwPS0KOwqrMWGHcX4zfmZym2iKCpzptx1Ac2Ilcbh6brw5YG2NWS3HKv0KZiS50uNSYyAupPukD01aLr5ERERUf8ldwPMr5TmEPUXeeXSB67LpiRj4nBDrwRSgBRcqFUCWi127C2qA9C9tug9kWjQQyUAJqsdlY5uau7Ic1oAqexx1Xu5sNm9e4/ktuhJBvdBg9wevbMgeqOjxK+rLn7uyG3S/7X7tNIIA5A+xFc1mnDgtLHP26e//MMpPPrlETz06eFO99t3ug5Wu4iECJ0y7yl7ZAwWZMXBahfxxNd5AKTOfXe/nwsA+PWcdCyZOKzHYxzl0lUvpNOGF95Yni11z353R5GythoAVDaaUNdsgUromA0Duv6S5UtHgwxACqZ80d35Ur5iZoqIiIj8LjUmBIIANJisqGo0d5gPEghNJiuKa6RgwNd2710JUqswPCoYhdXN+OlEFQAgpY8zU0FqFRIj9CgxtuJMbYvHLImcOZiQHIH8yibsyK/Bs9+ecMkweCI3oPCYmXJ8WC6sdt8E40RFI05UNCJILWDhGN/LSLNHxiArIRx55Q1Y/V4u9Fo1CqubUFjVjAaTFQBwwbgEvPyr6T4fu7t+PC69398erUCrxeYx2ybPl5I65bVlTu5bPAZbjlXi8/2luH52DR7+/DDqW62YnBKJ3y8Z2ytjTIsJgUYlwGoXMT6p540fFk9IREyoFmX1rfjmaIVSKnrMsb5UWkyo29dhhFP5b/vsaamxRXmNAGD7qepOX8/2utvJz1fMTBEREZHf6TRqpcytN0r9Ttc24+p125TWzt0hBxFx4TpEh2p7PKb25LWm5HWp+jozBbTNm+qsCUWeY07L/NFx+MvlUqnc37855tUCrSWOBhSeGmt0tZaQ3Hhi9shYRHSjNbYgCLhhbjoA4JujFfhifykOnqlXAikA2FtU6+Heva/FbMPeYunxWiw2/OAIrNyRA4Wpaa6d48YOi8DlU5IBAMtf3YH9p42IDAnCc9dO7bU5d0FqldIgpDcyNzqNGr+cngIAeCunraW4/Ds22sNyCqnRji9ZWq2objK73PYfR4nfjPQoDDPoYbLasd2HRYP7KjPFYIqIiIj6RNv8iMYeH2v9TwXYnl+DF7ec7PYx8sqkD3pjejkrJXNemwvo+zlT0mO2zZvy5LjygTccl08ZjiumJsMuAqs27EVds9nj/URRbCvzc9OAAmh7DQo9rDX1tdLFz/cSP9kVU4fjlnNG4NqZqfjfi8bi5V9Nx6bfnoMdfzwPgDQnrNls7eIokqNl9WgyebevO7sLa2GxtZVIyvPB2rPbRewpams+0d7di7Kg1ajQYpFKFJ+8apLPLdC78rOJw6DTqHDBOO86KHbl2pmpEATgh+NVSvB8zOncckcfpFaeV/uA+wvHFyU/mzhMWcNqS553pX4VDa2obDBBEPz3+y1jMEVERER9Qp43daqyZ5kpURTxH8eH1COlDTBb7V3cw728Lj7o9ZT8zb8sIJmpLtaacm4QIL8Oj1w6ARmxoSgxtuK+f+/3OMetpskMk+O1T/QwZ6p9e3RnXx4oxb7TRggCevSBPkitwh9+NhaPXj4RN80bgQvGJSAzIRzx4XqE66UZLd60h9+RX4PFT/+AP350oNtjyTlVDaDteX9ztNxlDpHsVFUT6pot0AepMN5N5iQ5Mhi3zBsBALjr3FE4d0zvBDzO7l6UhaOPLO618z8lOgQLHEHPO9ul7FRXwRTgNG/K6brgXOK3ZIJTMHWswquxHHG0RM+IDUWI1r+zmhhMERERUZ+QPzSd6mGZn9xKGwDMNjuOltV36zhyZqq350vJ0pwyUyrBc8DhT121R69oMKG+1Qq1SlDmr4TqNHjmmikIUgv46lA53tpe5Pa+pY5OfrFhOo+NO+T26ACQ75Sd+v5YJX6zYS8A4LrsdL/NoZM7GnqzcPGuQqmE7JsjFV434GhvmyOYum3+SESFBKGu2eK2XHK347HOGh7pcZHi1ReMxpbfLcDdi7K6NRZvdGfNuM4smyU1onh/12m0mG047igh7SyYGuHmuuBc4pdo0GP2qFioVQJOVjahuKbr97Kv5ksBDKaIiIioj/RWe/T/HHSdJ7XvtLFbx5G/NfdfmV9bJqqv15iSdbVwrxxQpsWEuAREE5INuN/R7OAvnx9GRX1rh/vKJX7JHkr8ZG1NKKT3fXdhLW59czcsNhEXnzUMf7p4nC9PySfy85cbjXRG/pDeYLJ2K0BvMlmxr7gOADB3VCzOHytlk+R5Yc52F3ou8ZOpVIJLQD4QLMiKR3JkMIwtFrzywyk0mKzQqIROW7m3XRfayn+/dCrxAwBDcBCmOhbK/v5416V+fTVfCmAwRURERH0kw+lDdftv/g+VGPHr13fgo72nuzyOPA9F/kZb/gDri6pGE6oazRAE9+vf9IaU6LZgKhAlfkBbmZ+81lR7ShmWm9fghjnpmJIaCZPVjg07izvcLgdTnppPyOSgMr+qCUfL6vHr13egxWLD/NFxePKqyX5dA0h+D7zJTDl3HPSm+UZ7uwprYbWLSI4MRkp0iDIP7OvD5R1e+7ZOfp6DqYFIrRKwdKa0oPXz30nzGTNiQzv9IiEjznWtqVJjC3Y5lfjJfJk3dbhE+oKFmSkiIiIaNJIig6HVqGCxiS5lZxsPluLKF7Zhc14l/vejg6hvtXg8xvHyBpysbIJWrcJd540CAOw/XefzWJSMTHQIgrW9s7ZUe/ogNYY5SvuGR/d98wmgrWV5s9mGuuaOr6tShuUmOycIAq7LTgfQcf0goK3Mb5iXmamtJ6ux/NUdqG+1YlpaFF5Y1nvd6TxJ8SEz5RxM7SzwPZjadlIq8cseGQMAmJsZixCtGqXGVux3yp7WNplx0jE/aErq4AqmAODqGSkIUgtK8wx355Yz+UuRgupm2OyiUuI3PS3KpTR2/mipdf7Wk9WdzpNsNluVkkFmpoiIiGjQUKsEZMTI8yMaIYoi/vHNcdz21h60WGxQCUCT2Yb33WRBZHJWas6oGMwZGQtAWqvI1w5scjDlr+YTMrkRQaAyU/ogtTIfyV2p37GKzltXL5mYiOhQLUqNrfj2qOvk/zNKmV/ngaL8nu/Ir0FlgwljEsPx2nUz/N4YAGh73Yu7yEyZrXZlzSxAGquvi0vLzSeyR0jBlD5IjQVZUjbFudRP7uI3Ii7ULy35Ay02TIfFThkld1lPZ0mRwdCqVTBb7Sipa1FK/C46y3Vx4vFJEYgJ1aLRZFVeQ3fyyhogitI4PK2t1psYTBEREVGfkUv9DpfW46539+LJTccAAL+ek45HLpPWOHr9pwK3HdAAKF38lkwYhvgIPYYZ9LCLwMEzvs2b8ndbdNn80fFQqwTMGhHt18fpjDxv6Eyda0AhimKXDQKk9YOGA0CHRhRKZqqLMj/neT9pMSH45w1nwxDi+5pS3dFW5td5Zup0bTPsIqAPUkGrUaGq0ezT3L5GkxUHHOfgLEdmCmhr+e4cTA3WEj9nyxylfgCQleg+UJepVYLypcO2U9VuS/wAaQ7ZOUpXP8+lfn05XwpgMEVERER9KMPRMe6Jr/Lw+f5SaFQC1l4xEQ/8fDx+MXU4YkK1OFPXgq8OlXe4b1F1Mw6X1kOtEnC+o5X2WcMNAOBSRuWNo+VyJz//fuC6fcFIHHzwQsx2ZNECoa09umtAUWJsRaOjQUD7NbGcXXt2GgRB6sDnvF5UaRdrTMlGxIVimEGPJIMeb904E/ERfdfVUA4kjS2WTstHixzNJ9KiQzF5eCQA3+ZN7cyvgc0uIjU6xCVTt3BMPILUUhe6E47Fm3d50XxioDs7Ixpnp0cjXKfpsCixO3IpqLxuXPsSP9k5o6Xfo87mTfVlJz+AwRQRERH1ITkzZReB6FAt3r5pJq45W/oWWx+kxrWO1sqv/Hiqw303HpLKf2ZmRCvlUWc5Pvju82HelN0uKgvVdvWteW/w15wsbw2Pcp+dkZtPdNUgIDUmBOdkyusHSdkpq82OMkeHv6Quyvz0QWpsvmcBvr1ngUtTjr4QqtMo58rpTuZNycFUakwIzs6Qsog7fJg3ta1diZ8sQh+kBNJfHSqDxWZXGqYM5mBKEAT888azsfX353pVatd+DTq5i1978xzn4eHSercdJuXbAGamiIiIaBCakR6NILWAMYnh+OSOOZjZ7sPn8llp0KpV2FtU12FeRFuJX6KybVI3gqnTtS1oNtug1ag6zcgMFske2qPLAWVXDQIA5/WDitFqsaGiwQS7CGhUAmLDul4jSh+khj4oMEGl0oSik3lTcvOJtOgQzHAEU740oWjffMKZ0tXvUBkOl9TDZLUjMiQII2L9H8gHkj5IjXC9d+Wc7VunL5mY6Ha/2DAdJiZL2ejvj1d1uL2+1YKjjgV7mZkiIiKiQScjNhQ7/3g+vlg5z22WIi5ch0snJwEAXv0xX9leZmzF3qI6AMCi8W0ftCY6yvyKa1pQ02T2agx5jiBiVFwYNB4WTB1M2uZMtc9MOeZLedEa/twx8Ugy6FHbbMGXB0qVtuiJBr1fW5v3BqUJRSeLvSrBVEwIpqVFQSVI55RzUwpPjC0WHHK04nYXTF0wLgGCIK2H9vn+EgDA1NQoqPr569aXnIOp6WlRnc7Dm+9h3lR5fSuuenEbWiw2JEToOl3bqjcN/isIERER9SuRIdpOP4DfOC8DAPCfA6XK+kDyBP5paVFIcJpzYwgOUkqEvG2RnudYkDXLz80n+ovhypwp12BCWWPKQyc/Z2qVoJRjvpVTiBJH84mkLppP9AdyW/rOmlAU1UjlZSnRIQjTaTA+SQrSvZk3tTO/BnZRKlVLcDMfLC5ch2mOFuhvbCsEMLhL/LpDnksJeC7xk813dEj84Xilsl7dycpGXPH8Vhwta0BcuA6vXT+jz4J8BlNERETUr4xJjMDcUbGwi8AbWwsAtLVEXzy+Y/mPr00ojpbJ86WGRjAll/k1tFphbJGaMEjzxqTMVKaX7eGvPjsFGpWAPUV1+OaI1CCkq+YT/UFKVOcL94qi2NaAwlH2qcyb8iKYkudLzXKTlZLJpX7y+kgMplzFhemQFhOCUK26y2BqSkokwvUa1DVbsP90HXKL63DlC1txpq4FGbGh+PD22Uow3BcYTBEREVG/c+NcKTu1YUcxiqqbsT1f+sC6eIK7YCoSgPeZqWPlQyuYCtG2NWGQF0s+U9eCFosNWrUK6THeNYWID9crQcGn+6RytWFdNJ/oD4Z3sXBvZYMJrRY7VEJb58MZ6d7Pm1LmS43oOpgCpCyfPNePJIIg4P1bs/Hlb+a57eLnTKNWYe4oqanH3785jmteykFtswVnDTfgX7dl93mTEwZTRERE1O/MHx2HkXGhaDBZccc7e2AXpUU73X1QmpQifQudW2zscqFVs9WudAzL8vOCvf1J+3lTckA5Ii7Up3lj186SSv3kl7mrTn79QdtaU81uz49CR1YqKTJY6Wo4I13KHB0rb0RtJ3Px6prNOOIoG53ZyVpiqTEhyppm45MiAt7hsT9KiNC7rEnWGXne1Hd5lWix2DAvMxbv3jwLMV40Q+ltDKaIiIio31GpBNzgyE7Ji6EucZOVAoBxwwxQqwRUNZqUhWQ9OVnZCKtdRLheg2FdfAM+mCS3mzeVp8yX8i2gzB4Rg5FO81uSBsBrKD/3JrMNtc0d15pybj4hiwnTYVS8NJess+xUzqkaiCIwKj6syxbgl09JBgAscAQC1H3nOL2Gl01OwqvXzUCoThOQsTCYIiIion7piinDERXS1lp58QT3cymCtWolKOiq1E8p8UsIhyAMnW5qckAhl/nJ86W8aT7hTBAEpU06gE67rvUX+iA14sOljIW7eVNFjoWIU9tlPb0p9cvxsL6UOzfPG4F3b56FO84d5d3AyaOkyGCsvWIi/nzxODx51eRO10nzNwZTRERE1C8Fa9W4dqb0wX1UfJiSKXBnkqMJxb4umlAMteYTsuHt1pqSg0pvm084u2LqcEToNQjXaZDq5XyrQJNL/dzNm1IW7I12LTGb6UUTCiWY6qT5hEylEpA9MgY6DUv8esM1Z6fihrkZAW8xH5h8GBEREZEXbp0/Ao0mq8cSP9mklEhs2FncdWbKEUyNGWLBVLKjo92ZuhbY7CJOVMiZKd9fB0NwED69cy6sdjvCAlRa5avhUcHYXVjrduHewpqOZX4AlMV7D5bUo8lk7VBGVt1oUoLzWV5kpmhwGhi/AURERDQkheuD8OAl47vcz7k9ut0uevy2Wv7w250gYiBzbkBRVNMMk9UOnUbVobTNW+l9tCBqb+msPXpRtZyZcn0tkiODkRwZjDN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+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "ax=df[df.index<\"2020-06-01\"]['ninfected'].diff().rolling(7).mean().plot()\n",
     "ax.axhline(0,linestyle='-.',color='red')\n",
@@ -440,7 +2442,8 @@
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From ebf274d3c4abe68d5ef2f921dfc4b6555e607964 Mon Sep 17 00:00:00 2001
From: wangamber8-collab <wangamber8@gmail.com>
Date: Fri, 2 Jan 2026 13:37:51 -0500
Subject: [PATCH 3/3] Delete 2-Working-With-Data/07-python/notebook.ipynb

---
 2-Working-With-Data/07-python/notebook.ipynb | 390 -------------------
 1 file changed, 390 deletions(-)
 delete mode 100644 2-Working-With-Data/07-python/notebook.ipynb

diff --git a/2-Working-With-Data/07-python/notebook.ipynb b/2-Working-With-Data/07-python/notebook.ipynb
deleted file mode 100644
index b1a2b46e..00000000
--- a/2-Working-With-Data/07-python/notebook.ipynb
+++ /dev/null
@@ -1,390 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Basic Pandas Examples\n",
-    "\n",
-    "This notebook will walk you through some very basic Pandas concepts. We will start with importing typical data science libraries:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Series\n",
-    "\n",
-    "Series is like a list or 1D-array, but with index. All operations are index-aligned."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "a = pd.Series(range(1,10))\n",
-    "b = pd.Series([\"I\",\"like\",\"to\",\"use\",\"Python\",\"and\",\"Pandas\",\"very\",\"much\"],index=range(0,9))\n",
-    "print(a,b)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "One of the frequent usage of series is **time series**. In time series, index has a special structure - typically a range of dates or datetimes. We can create such an index with `pd.date_range`.\n",
-    "\n",
-    "Suppose we have a series that shows the amount of product bought every day, and we know that every sunday we also need to take one item for ourselves. Here is how to model that using series:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "start_date = \"Jan 1, 2020\"\n",
-    "end_date = \"Dec 31, 2020\"\n",
-    "idx = pd.date_range(start_date,end_date)\n",
-    "print(f\"Length of index is {len(idx)}\")\n",
-    "items_sold = pd.Series(np.random.randint(25,50,size=len(idx)),index=idx)\n",
-    "items_sold.plot(figsize=(10,3))\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "additional_items = pd.Series(10,index=pd.date_range(start_date,end_date,freq=\"W\"))\n",
-    "print(f\"Additional items (10 item each week):\\n{additional_items}\")\n",
-    "total_items = items_sold+additional_items\n",
-    "print(f\"Total items (sum of two series):\\n{total_items}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "As you can see, we are having problems here, because in the weekly series non-mentioned days are considered to be missing (`NaN`), and adding `NaN` to a number gives us `NaN`. In order to get correct result, we need to specify `fill_value` when adding series:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "total_items = items_sold.add(additional_items,fill_value=0)\n",
-    "print(total_items)\n",
-    "total_items.plot(figsize=(10,3))\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "monthly = total_items.resample(\"1M\").mean()\n",
-    "ax = monthly.plot(kind='bar',figsize=(10,3))\n",
-    "ax.set_xticklabels([x.strftime(\"%b-%Y\") for x in monthly.index], rotation=45)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## DataFrame\n",
-    "\n",
-    "A dataframe is essentially a collection of series with the same index. We can combine several series together into a dataframe. Given `a` and `b` series defined above:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = pd.DataFrame([a,b])\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can also use Series as columns, and specify column names using dictionary:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = pd.DataFrame({ 'A' : a, 'B' : b })\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The same result can be achieved by transposing (and then renaming columns, to match the previous example):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pd.DataFrame([a,b]).T.rename(columns={ 0 : 'A', 1 : 'B' })"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Selecting columns** from DataFrame can be done like this:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print(f\"Column A (series):\\n{df['A']}\")\n",
-    "print(f\"Columns B and A (DataFrame):\\n{df[['B','A']]}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Selecting rows** based on filter expression:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df[df['A']<5]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The way it works is that expression `df['A']<5` returns a boolean series, which indicates whether expression is `True` or `False` for each elements of the series. When series is used as an index, it returns subset of rows in the DataFrame. Thus it is not possible to use arbitrary Python boolean expression, for example, writing `df[df['A']>5 and df['A']<7]` would be wrong. Instead, you should use special `&` operation on boolean series:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df[(df['A']>5) & (df['A']<7)]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Creating new computable columns**. We can easily create new computable columns for our DataFrame by using intuitive expressions. The code below calculates divergence of A from its mean value."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['DivA'] = df['A']-df['A'].mean()\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "What actually happens is we are computing a series, and then assigning this series to the left-hand-side, creating another column."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# WRONG: df['ADescr'] = \"Low\" if df['A'] < 5 else \"Hi\"\n",
-    "df['LenB'] = len(df['B']) # Wrong result"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['LenB'] = df['B'].apply(lambda x: len(x))\n",
-    "# or\n",
-    "df['LenB'] = df['B'].apply(len)\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Selecting rows based on numbers** can be done using `iloc` construct. For example, to select first 5 rows from the DataFrame:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.iloc[:5]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Grouping** is often used to get a result similar to *pivot tables* in Excel. Suppose that we want to compute mean value of column `A` for each given number of `LenB`. Then we can group our DataFrame by `LenB`, and call `mean`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.groupby(by='LenB').mean()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If we need to compute mean and the number of elements in the group, then we can use more complex `aggregate` function:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.groupby(by='LenB') \\\n",
-    " .aggregate({ 'DivA' : len, 'A' : lambda x: x.mean() }) \\\n",
-    " .rename(columns={ 'DivA' : 'Count', 'A' : 'Mean'})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Printing and Plotting\n",
-    "\n",
-    "Data Scientist often has to explore the data, thus it is important to be able to visualize it. When DataFrame is big, many times we want just to make sure we are doing everything correctly by printing out the first few rows. This can be done by calling `df.head()`. If you are running it from Jupyter Notebook, it will print out the DataFrame in a nice tabular form."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "We have also seen the usage of `plot` function to visualize some columns. While `plot` is very useful for many tasks, and supports many different graph types via `kind=` parameter, you can always use raw `matplotlib` library to plot something more complex. We will cover data visualization in detail in separate course lessons.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['A'].plot()\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['A'].plot(kind='bar')\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "This overview covers most important concepts of Pandas, however, the library is very rich, and there is no limit to what you can do with it! Let's now apply this knowledge for solving specific problem."
-   ]
-  },
-  {
-   "cell_type": "markdown",
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-   "source": []
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