diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index 3e7f7467fb91f43f35560fd43d17eb67e78af5b5..b566c6937500d1434b8138cfcdf0c69ad96db8f2 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -1468,13 +1468,361 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 54,
+   "metadata": {
+    "scrolled": true
+   },
+   "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>0</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1/22/20</th>\n",
+       "      <td>548</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/23/20</th>\n",
+       "      <td>643</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/24/20</th>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/25/20</th>\n",
+       "      <td>1406</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/26/20</th>\n",
+       "      <td>2075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/27/20</th>\n",
+       "      <td>2877</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/28/20</th>\n",
+       "      <td>5509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/29/20</th>\n",
+       "      <td>6087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/30/20</th>\n",
+       "      <td>8141</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1/31/20</th>\n",
+       "      <td>9802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/1/20</th>\n",
+       "      <td>11891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/2/20</th>\n",
+       "      <td>16630</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/3/20</th>\n",
+       "      <td>19716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/4/20</th>\n",
+       "      <td>23707</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/5/20</th>\n",
+       "      <td>27440</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/6/20</th>\n",
+       "      <td>30587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/7/20</th>\n",
+       "      <td>34110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/8/20</th>\n",
+       "      <td>36814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/9/20</th>\n",
+       "      <td>39829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/10/20</th>\n",
+       "      <td>42354</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/11/20</th>\n",
+       "      <td>44386</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/12/20</th>\n",
+       "      <td>44759</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/13/20</th>\n",
+       "      <td>59895</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/14/20</th>\n",
+       "      <td>66358</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/15/20</th>\n",
+       "      <td>68413</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/16/20</th>\n",
+       "      <td>70513</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/17/20</th>\n",
+       "      <td>72434</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/18/20</th>\n",
+       "      <td>74211</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/19/20</th>\n",
+       "      <td>74619</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2/20/20</th>\n",
+       "      <td>75077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/20/20</th>\n",
+       "      <td>83817</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/21/20</th>\n",
+       "      <td>83853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/22/20</th>\n",
+       "      <td>83868</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/23/20</th>\n",
+       "      <td>83884</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/24/20</th>\n",
+       "      <td>83899</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/25/20</th>\n",
+       "      <td>83909</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/26/20</th>\n",
+       "      <td>83912</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/27/20</th>\n",
+       "      <td>83918</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/28/20</th>\n",
+       "      <td>83940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/29/20</th>\n",
+       "      <td>83944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4/30/20</th>\n",
+       "      <td>83956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/1/20</th>\n",
+       "      <td>83959</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/2/20</th>\n",
+       "      <td>83959</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/3/20</th>\n",
+       "      <td>83964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/4/20</th>\n",
+       "      <td>83966</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/5/20</th>\n",
+       "      <td>83968</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/6/20</th>\n",
+       "      <td>83970</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/7/20</th>\n",
+       "      <td>83975</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/8/20</th>\n",
+       "      <td>83976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/9/20</th>\n",
+       "      <td>83990</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/10/20</th>\n",
+       "      <td>84010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/11/20</th>\n",
+       "      <td>84011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/12/20</th>\n",
+       "      <td>84018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/13/20</th>\n",
+       "      <td>84024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/14/20</th>\n",
+       "      <td>84029</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/15/20</th>\n",
+       "      <td>84038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/16/20</th>\n",
+       "      <td>84044</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/17/20</th>\n",
+       "      <td>84054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/18/20</th>\n",
+       "      <td>84063</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5/19/20</th>\n",
+       "      <td>84063</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>119 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             0\n",
+       "1/22/20    548\n",
+       "1/23/20    643\n",
+       "1/24/20    920\n",
+       "1/25/20   1406\n",
+       "1/26/20   2075\n",
+       "1/27/20   2877\n",
+       "1/28/20   5509\n",
+       "1/29/20   6087\n",
+       "1/30/20   8141\n",
+       "1/31/20   9802\n",
+       "2/1/20   11891\n",
+       "2/2/20   16630\n",
+       "2/3/20   19716\n",
+       "2/4/20   23707\n",
+       "2/5/20   27440\n",
+       "2/6/20   30587\n",
+       "2/7/20   34110\n",
+       "2/8/20   36814\n",
+       "2/9/20   39829\n",
+       "2/10/20  42354\n",
+       "2/11/20  44386\n",
+       "2/12/20  44759\n",
+       "2/13/20  59895\n",
+       "2/14/20  66358\n",
+       "2/15/20  68413\n",
+       "2/16/20  70513\n",
+       "2/17/20  72434\n",
+       "2/18/20  74211\n",
+       "2/19/20  74619\n",
+       "2/20/20  75077\n",
+       "...        ...\n",
+       "4/20/20  83817\n",
+       "4/21/20  83853\n",
+       "4/22/20  83868\n",
+       "4/23/20  83884\n",
+       "4/24/20  83899\n",
+       "4/25/20  83909\n",
+       "4/26/20  83912\n",
+       "4/27/20  83918\n",
+       "4/28/20  83940\n",
+       "4/29/20  83944\n",
+       "4/30/20  83956\n",
+       "5/1/20   83959\n",
+       "5/2/20   83959\n",
+       "5/3/20   83964\n",
+       "5/4/20   83966\n",
+       "5/5/20   83968\n",
+       "5/6/20   83970\n",
+       "5/7/20   83975\n",
+       "5/8/20   83976\n",
+       "5/9/20   83990\n",
+       "5/10/20  84010\n",
+       "5/11/20  84011\n",
+       "5/12/20  84018\n",
+       "5/13/20  84024\n",
+       "5/14/20  84029\n",
+       "5/15/20  84038\n",
+       "5/16/20  84044\n",
+       "5/17/20  84054\n",
+       "5/18/20  84063\n",
+       "5/19/20  84063\n",
+       "\n",
+       "[119 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "d = confirmed[confirmed[\"Country/Region\"] == \"China\"]\n",
-    "d.\n",
-    "#d.groupby(['Date','Keyword'],as_index=False).agg({'Views': 'sum'})"
+    "agg_dict = {col: 'sum' for col in d.columns[4:]}\n",
+    "d.groupby(['Country/Region'],as_index=False).agg(agg_dict).T[1:]"
    ]
   },
   {
@@ -1693,6 +2041,32 @@
     "confirmed[confirmed[\"Country/Region\"] == \"Netherlands\"]"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Korea, South\n"
+     ]
+    }
+   ],
+   "source": [
+    "for row in confirmed[\"Country/Region\"]:\n",
+    "    if \"Korea\" in row:\n",
+    "        print(row)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1703,663 +2077,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 169,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:12: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
-      "  if sys.path[0] == '':\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'Belgium':             23\n",
-      "1/22/20      0\n",
-      "1/23/20      0\n",
-      "1/24/20      0\n",
-      "1/25/20      0\n",
-      "1/26/20      0\n",
-      "1/27/20      0\n",
-      "1/28/20      0\n",
-      "1/29/20      0\n",
-      "1/30/20      0\n",
-      "1/31/20      0\n",
-      "2/1/20       0\n",
-      "2/2/20       0\n",
-      "2/3/20       0\n",
-      "2/4/20       1\n",
-      "2/5/20       1\n",
-      "2/6/20       1\n",
-      "2/7/20       1\n",
-      "2/8/20       1\n",
-      "2/9/20       1\n",
-      "2/10/20      1\n",
-      "2/11/20      1\n",
-      "2/12/20      1\n",
-      "2/13/20      1\n",
-      "2/14/20      1\n",
-      "2/15/20      1\n",
-      "2/16/20      1\n",
-      "2/17/20      1\n",
-      "2/18/20      1\n",
-      "2/19/20      1\n",
-      "2/20/20      1\n",
-      "...        ...\n",
-      "4/20/20  39983\n",
-      "4/21/20  40956\n",
-      "4/22/20  41889\n",
-      "4/23/20  42797\n",
-      "4/24/20  44293\n",
-      "4/25/20  45325\n",
-      "4/26/20  46134\n",
-      "4/27/20  46687\n",
-      "4/28/20  47334\n",
-      "4/29/20  47859\n",
-      "4/30/20  48519\n",
-      "5/1/20   49032\n",
-      "5/2/20   49517\n",
-      "5/3/20   49906\n",
-      "5/4/20   50267\n",
-      "5/5/20   50509\n",
-      "5/6/20   50781\n",
-      "5/7/20   51420\n",
-      "5/8/20   52011\n",
-      "5/9/20   52596\n",
-      "5/10/20  53081\n",
-      "5/11/20  53449\n",
-      "5/12/20  53779\n",
-      "5/13/20  53981\n",
-      "5/14/20  54288\n",
-      "5/15/20  54644\n",
-      "5/16/20  54989\n",
-      "5/17/20  55280\n",
-      "5/18/20  55559\n",
-      "5/19/20  55791\n",
-      "\n",
-      "[119 rows x 1 columns], 'France except Dom/Tom':             116\n",
-      "1/22/20       0\n",
-      "1/23/20       0\n",
-      "1/24/20       2\n",
-      "1/25/20       3\n",
-      "1/26/20       3\n",
-      "1/27/20       3\n",
-      "1/28/20       4\n",
-      "1/29/20       5\n",
-      "1/30/20       5\n",
-      "1/31/20       5\n",
-      "2/1/20        6\n",
-      "2/2/20        6\n",
-      "2/3/20        6\n",
-      "2/4/20        6\n",
-      "2/5/20        6\n",
-      "2/6/20        6\n",
-      "2/7/20        6\n",
-      "2/8/20       11\n",
-      "2/9/20       11\n",
-      "2/10/20      11\n",
-      "2/11/20      11\n",
-      "2/12/20      11\n",
-      "2/13/20      11\n",
-      "2/14/20      11\n",
-      "2/15/20      12\n",
-      "2/16/20      12\n",
-      "2/17/20      12\n",
-      "2/18/20      12\n",
-      "2/19/20      12\n",
-      "2/20/20      12\n",
-      "...         ...\n",
-      "4/20/20  154188\n",
-      "4/21/20  156921\n",
-      "4/22/20  154715\n",
-      "4/23/20  157026\n",
-      "4/24/20  158636\n",
-      "4/25/20  160292\n",
-      "4/26/20  160847\n",
-      "4/27/20  164589\n",
-      "4/28/20  167605\n",
-      "4/29/20  165093\n",
-      "4/30/20  165764\n",
-      "5/1/20   165764\n",
-      "5/2/20   166976\n",
-      "5/3/20   167272\n",
-      "5/4/20   167886\n",
-      "5/5/20   168935\n",
-      "5/6/20   172465\n",
-      "5/7/20   173040\n",
-      "5/8/20   174318\n",
-      "5/9/20   174758\n",
-      "5/10/20  175027\n",
-      "5/11/20  175479\n",
-      "5/12/20  176207\n",
-      "5/13/20  175981\n",
-      "5/14/20  176712\n",
-      "5/15/20  177319\n",
-      "5/16/20  177207\n",
-      "5/17/20  177240\n",
-      "5/18/20  177554\n",
-      "5/19/20  178428\n",
-      "\n",
-      "[119 rows x 1 columns], 'Germany':             120\n",
-      "1/22/20       0\n",
-      "1/23/20       0\n",
-      "1/24/20       0\n",
-      "1/25/20       0\n",
-      "1/26/20       0\n",
-      "1/27/20       1\n",
-      "1/28/20       4\n",
-      "1/29/20       4\n",
-      "1/30/20       4\n",
-      "1/31/20       5\n",
-      "2/1/20        8\n",
-      "2/2/20       10\n",
-      "2/3/20       12\n",
-      "2/4/20       12\n",
-      "2/5/20       12\n",
-      "2/6/20       12\n",
-      "2/7/20       13\n",
-      "2/8/20       13\n",
-      "2/9/20       14\n",
-      "2/10/20      14\n",
-      "2/11/20      16\n",
-      "2/12/20      16\n",
-      "2/13/20      16\n",
-      "2/14/20      16\n",
-      "2/15/20      16\n",
-      "2/16/20      16\n",
-      "2/17/20      16\n",
-      "2/18/20      16\n",
-      "2/19/20      16\n",
-      "2/20/20      16\n",
-      "...         ...\n",
-      "4/20/20  147065\n",
-      "4/21/20  148291\n",
-      "4/22/20  150648\n",
-      "4/23/20  153129\n",
-      "4/24/20  154999\n",
-      "4/25/20  156513\n",
-      "4/26/20  157770\n",
-      "4/27/20  158758\n",
-      "4/28/20  159912\n",
-      "4/29/20  161539\n",
-      "4/30/20  163009\n",
-      "5/1/20   164077\n",
-      "5/2/20   164967\n",
-      "5/3/20   165664\n",
-      "5/4/20   166152\n",
-      "5/5/20   167007\n",
-      "5/6/20   168162\n",
-      "5/7/20   169430\n",
-      "5/8/20   170588\n",
-      "5/9/20   171324\n",
-      "5/10/20  171879\n",
-      "5/11/20  172576\n",
-      "5/12/20  173171\n",
-      "5/13/20  174098\n",
-      "5/14/20  174478\n",
-      "5/15/20  175233\n",
-      "5/16/20  175752\n",
-      "5/17/20  176369\n",
-      "5/18/20  176551\n",
-      "5/19/20  177778\n",
-      "\n",
-      "[119 rows x 1 columns], 'Iran':             133\n",
-      "1/22/20       0\n",
-      "1/23/20       0\n",
-      "1/24/20       0\n",
-      "1/25/20       0\n",
-      "1/26/20       0\n",
-      "1/27/20       0\n",
-      "1/28/20       0\n",
-      "1/29/20       0\n",
-      "1/30/20       0\n",
-      "1/31/20       0\n",
-      "2/1/20        0\n",
-      "2/2/20        0\n",
-      "2/3/20        0\n",
-      "2/4/20        0\n",
-      "2/5/20        0\n",
-      "2/6/20        0\n",
-      "2/7/20        0\n",
-      "2/8/20        0\n",
-      "2/9/20        0\n",
-      "2/10/20       0\n",
-      "2/11/20       0\n",
-      "2/12/20       0\n",
-      "2/13/20       0\n",
-      "2/14/20       0\n",
-      "2/15/20       0\n",
-      "2/16/20       0\n",
-      "2/17/20       0\n",
-      "2/18/20       0\n",
-      "2/19/20       2\n",
-      "2/20/20       5\n",
-      "...         ...\n",
-      "4/20/20   83505\n",
-      "4/21/20   84802\n",
-      "4/22/20   85996\n",
-      "4/23/20   87026\n",
-      "4/24/20   88194\n",
-      "4/25/20   89328\n",
-      "4/26/20   90481\n",
-      "4/27/20   91472\n",
-      "4/28/20   92584\n",
-      "4/29/20   93657\n",
-      "4/30/20   94640\n",
-      "5/1/20    95646\n",
-      "5/2/20    96448\n",
-      "5/3/20    97424\n",
-      "5/4/20    98647\n",
-      "5/5/20    99970\n",
-      "5/6/20   101650\n",
-      "5/7/20   103135\n",
-      "5/8/20   104691\n",
-      "5/9/20   106220\n",
-      "5/10/20  107603\n",
-      "5/11/20  109286\n",
-      "5/12/20  110767\n",
-      "5/13/20  112725\n",
-      "5/14/20  114533\n",
-      "5/15/20  116635\n",
-      "5/16/20  118392\n",
-      "5/17/20  120198\n",
-      "5/18/20  122492\n",
-      "5/19/20  124603\n",
-      "\n",
-      "[119 rows x 1 columns], 'Italy':             137\n",
-      "1/22/20       0\n",
-      "1/23/20       0\n",
-      "1/24/20       0\n",
-      "1/25/20       0\n",
-      "1/26/20       0\n",
-      "1/27/20       0\n",
-      "1/28/20       0\n",
-      "1/29/20       0\n",
-      "1/30/20       0\n",
-      "1/31/20       2\n",
-      "2/1/20        2\n",
-      "2/2/20        2\n",
-      "2/3/20        2\n",
-      "2/4/20        2\n",
-      "2/5/20        2\n",
-      "2/6/20        2\n",
-      "2/7/20        3\n",
-      "2/8/20        3\n",
-      "2/9/20        3\n",
-      "2/10/20       3\n",
-      "2/11/20       3\n",
-      "2/12/20       3\n",
-      "2/13/20       3\n",
-      "2/14/20       3\n",
-      "2/15/20       3\n",
-      "2/16/20       3\n",
-      "2/17/20       3\n",
-      "2/18/20       3\n",
-      "2/19/20       3\n",
-      "2/20/20       3\n",
-      "...         ...\n",
-      "4/20/20  181228\n",
-      "4/21/20  183957\n",
-      "4/22/20  187327\n",
-      "4/23/20  189973\n",
-      "4/24/20  192994\n",
-      "4/25/20  195351\n",
-      "4/26/20  197675\n",
-      "4/27/20  199414\n",
-      "4/28/20  201505\n",
-      "4/29/20  203591\n",
-      "4/30/20  205463\n",
-      "5/1/20   207428\n",
-      "5/2/20   209328\n",
-      "5/3/20   210717\n",
-      "5/4/20   211938\n",
-      "5/5/20   213013\n",
-      "5/6/20   214457\n",
-      "5/7/20   215858\n",
-      "5/8/20   217185\n",
-      "5/9/20   218268\n",
-      "5/10/20  219070\n",
-      "5/11/20  219814\n",
-      "5/12/20  221216\n",
-      "5/13/20  222104\n",
-      "5/14/20  223096\n",
-      "5/15/20  223885\n",
-      "5/16/20  224760\n",
-      "5/17/20  225435\n",
-      "5/18/20  225886\n",
-      "5/19/20  226699\n",
-      "\n",
-      "[119 rows x 1 columns], 'Japan':            139\n",
-      "1/22/20      2\n",
-      "1/23/20      2\n",
-      "1/24/20      2\n",
-      "1/25/20      2\n",
-      "1/26/20      4\n",
-      "1/27/20      4\n",
-      "1/28/20      7\n",
-      "1/29/20      7\n",
-      "1/30/20     11\n",
-      "1/31/20     15\n",
-      "2/1/20      20\n",
-      "2/2/20      20\n",
-      "2/3/20      20\n",
-      "2/4/20      22\n",
-      "2/5/20      22\n",
-      "2/6/20      22\n",
-      "2/7/20      25\n",
-      "2/8/20      25\n",
-      "2/9/20      26\n",
-      "2/10/20     26\n",
-      "2/11/20     26\n",
-      "2/12/20     28\n",
-      "2/13/20     28\n",
-      "2/14/20     29\n",
-      "2/15/20     43\n",
-      "2/16/20     59\n",
-      "2/17/20     66\n",
-      "2/18/20     74\n",
-      "2/19/20     84\n",
-      "2/20/20     94\n",
-      "...        ...\n",
-      "4/20/20  10797\n",
-      "4/21/20  11135\n",
-      "4/22/20  11512\n",
-      "4/23/20  12368\n",
-      "4/24/20  12829\n",
-      "4/25/20  13231\n",
-      "4/26/20  13441\n",
-      "4/27/20  14153\n",
-      "4/28/20  13736\n",
-      "4/29/20  13895\n",
-      "4/30/20  14088\n",
-      "5/1/20   14305\n",
-      "5/2/20   14571\n",
-      "5/3/20   14877\n",
-      "5/4/20   15078\n",
-      "5/5/20   15253\n",
-      "5/6/20   15253\n",
-      "5/7/20   15477\n",
-      "5/8/20   15575\n",
-      "5/9/20   15663\n",
-      "5/10/20  15777\n",
-      "5/11/20  15847\n",
-      "5/12/20  15968\n",
-      "5/13/20  16049\n",
-      "5/14/20  16120\n",
-      "5/15/20  16203\n",
-      "5/16/20  16237\n",
-      "5/17/20  16285\n",
-      "5/18/20  16305\n",
-      "5/19/20  16367\n",
-      "\n",
-      "[119 rows x 1 columns], 'Netherlands without the colonies':            169\n",
-      "1/22/20      0\n",
-      "1/23/20      0\n",
-      "1/24/20      0\n",
-      "1/25/20      0\n",
-      "1/26/20      0\n",
-      "1/27/20      0\n",
-      "1/28/20      0\n",
-      "1/29/20      0\n",
-      "1/30/20      0\n",
-      "1/31/20      0\n",
-      "2/1/20       0\n",
-      "2/2/20       0\n",
-      "2/3/20       0\n",
-      "2/4/20       0\n",
-      "2/5/20       0\n",
-      "2/6/20       0\n",
-      "2/7/20       0\n",
-      "2/8/20       0\n",
-      "2/9/20       0\n",
-      "2/10/20      0\n",
-      "2/11/20      0\n",
-      "2/12/20      0\n",
-      "2/13/20      0\n",
-      "2/14/20      0\n",
-      "2/15/20      0\n",
-      "2/16/20      0\n",
-      "2/17/20      0\n",
-      "2/18/20      0\n",
-      "2/19/20      0\n",
-      "2/20/20      0\n",
-      "...        ...\n",
-      "4/20/20  33405\n",
-      "4/21/20  34134\n",
-      "4/22/20  34842\n",
-      "4/23/20  35729\n",
-      "4/24/20  36535\n",
-      "4/25/20  37190\n",
-      "4/26/20  37845\n",
-      "4/27/20  38245\n",
-      "4/28/20  38416\n",
-      "4/29/20  38802\n",
-      "4/30/20  39316\n",
-      "5/1/20   39791\n",
-      "5/2/20   40236\n",
-      "5/3/20   40571\n",
-      "5/4/20   40770\n",
-      "5/5/20   41087\n",
-      "5/6/20   41319\n",
-      "5/7/20   41774\n",
-      "5/8/20   42093\n",
-      "5/9/20   42382\n",
-      "5/10/20  42627\n",
-      "5/11/20  42788\n",
-      "5/12/20  42984\n",
-      "5/13/20  43211\n",
-      "5/14/20  43481\n",
-      "5/15/20  43681\n",
-      "5/16/20  43870\n",
-      "5/17/20  43995\n",
-      "5/18/20  44141\n",
-      "5/19/20  44249\n",
-      "\n",
-      "[119 rows x 1 columns], 'Portugal':            184\n",
-      "1/22/20      0\n",
-      "1/23/20      0\n",
-      "1/24/20      0\n",
-      "1/25/20      0\n",
-      "1/26/20      0\n",
-      "1/27/20      0\n",
-      "1/28/20      0\n",
-      "1/29/20      0\n",
-      "1/30/20      0\n",
-      "1/31/20      0\n",
-      "2/1/20       0\n",
-      "2/2/20       0\n",
-      "2/3/20       0\n",
-      "2/4/20       0\n",
-      "2/5/20       0\n",
-      "2/6/20       0\n",
-      "2/7/20       0\n",
-      "2/8/20       0\n",
-      "2/9/20       0\n",
-      "2/10/20      0\n",
-      "2/11/20      0\n",
-      "2/12/20      0\n",
-      "2/13/20      0\n",
-      "2/14/20      0\n",
-      "2/15/20      0\n",
-      "2/16/20      0\n",
-      "2/17/20      0\n",
-      "2/18/20      0\n",
-      "2/19/20      0\n",
-      "2/20/20      0\n",
-      "...        ...\n",
-      "4/20/20  20863\n",
-      "4/21/20  21379\n",
-      "4/22/20  21982\n",
-      "4/23/20  22353\n",
-      "4/24/20  22797\n",
-      "4/25/20  23392\n",
-      "4/26/20  23864\n",
-      "4/27/20  24027\n",
-      "4/28/20  24322\n",
-      "4/29/20  24505\n",
-      "4/30/20  25045\n",
-      "5/1/20   25351\n",
-      "5/2/20   25190\n",
-      "5/3/20   25282\n",
-      "5/4/20   25524\n",
-      "5/5/20   25702\n",
-      "5/6/20   26182\n",
-      "5/7/20   26715\n",
-      "5/8/20   27268\n",
-      "5/9/20   27406\n",
-      "5/10/20  27581\n",
-      "5/11/20  27679\n",
-      "5/12/20  27913\n",
-      "5/13/20  28132\n",
-      "5/14/20  28319\n",
-      "5/15/20  28583\n",
-      "5/16/20  28810\n",
-      "5/17/20  29036\n",
-      "5/18/20  29209\n",
-      "5/19/20  29432\n",
-      "\n",
-      "[119 rows x 1 columns], 'Spain':             201\n",
-      "1/22/20       0\n",
-      "1/23/20       0\n",
-      "1/24/20       0\n",
-      "1/25/20       0\n",
-      "1/26/20       0\n",
-      "1/27/20       0\n",
-      "1/28/20       0\n",
-      "1/29/20       0\n",
-      "1/30/20       0\n",
-      "1/31/20       0\n",
-      "2/1/20        1\n",
-      "2/2/20        1\n",
-      "2/3/20        1\n",
-      "2/4/20        1\n",
-      "2/5/20        1\n",
-      "2/6/20        1\n",
-      "2/7/20        1\n",
-      "2/8/20        1\n",
-      "2/9/20        2\n",
-      "2/10/20       2\n",
-      "2/11/20       2\n",
-      "2/12/20       2\n",
-      "2/13/20       2\n",
-      "2/14/20       2\n",
-      "2/15/20       2\n",
-      "2/16/20       2\n",
-      "2/17/20       2\n",
-      "2/18/20       2\n",
-      "2/19/20       2\n",
-      "2/20/20       2\n",
-      "...         ...\n",
-      "4/20/20  200210\n",
-      "4/21/20  204178\n",
-      "4/22/20  208389\n",
-      "4/23/20  213024\n",
-      "4/24/20  202990\n",
-      "4/25/20  205905\n",
-      "4/26/20  207634\n",
-      "4/27/20  209465\n",
-      "4/28/20  210773\n",
-      "4/29/20  212917\n",
-      "4/30/20  213435\n",
-      "5/1/20   215216\n",
-      "5/2/20   216582\n",
-      "5/3/20   217466\n",
-      "5/4/20   218011\n",
-      "5/5/20   219329\n",
-      "5/6/20   220325\n",
-      "5/7/20   221447\n",
-      "5/8/20   222857\n",
-      "5/9/20   223578\n",
-      "5/10/20  224350\n",
-      "5/11/20  227436\n",
-      "5/12/20  228030\n",
-      "5/13/20  228691\n",
-      "5/14/20  229540\n",
-      "5/15/20  230183\n",
-      "5/16/20  230698\n",
-      "5/17/20  230698\n",
-      "5/18/20  231606\n",
-      "5/19/20  232037\n",
-      "\n",
-      "[119 rows x 1 columns], 'US':              225\n",
-      "1/22/20        1\n",
-      "1/23/20        1\n",
-      "1/24/20        2\n",
-      "1/25/20        2\n",
-      "1/26/20        5\n",
-      "1/27/20        5\n",
-      "1/28/20        5\n",
-      "1/29/20        5\n",
-      "1/30/20        5\n",
-      "1/31/20        7\n",
-      "2/1/20         8\n",
-      "2/2/20         8\n",
-      "2/3/20        11\n",
-      "2/4/20        11\n",
-      "2/5/20        11\n",
-      "2/6/20        11\n",
-      "2/7/20        11\n",
-      "2/8/20        11\n",
-      "2/9/20        11\n",
-      "2/10/20       11\n",
-      "2/11/20       12\n",
-      "2/12/20       12\n",
-      "2/13/20       13\n",
-      "2/14/20       13\n",
-      "2/15/20       13\n",
-      "2/16/20       13\n",
-      "2/17/20       13\n",
-      "2/18/20       13\n",
-      "2/19/20       13\n",
-      "2/20/20       13\n",
-      "...          ...\n",
-      "4/20/20   784326\n",
-      "4/21/20   811865\n",
-      "4/22/20   840351\n",
-      "4/23/20   869170\n",
-      "4/24/20   905358\n",
-      "4/25/20   938154\n",
-      "4/26/20   965785\n",
-      "4/27/20   988197\n",
-      "4/28/20  1012582\n",
-      "4/29/20  1039909\n",
-      "4/30/20  1069424\n",
-      "5/1/20   1103461\n",
-      "5/2/20   1132539\n",
-      "5/3/20   1158040\n",
-      "5/4/20   1180375\n",
-      "5/5/20   1204351\n",
-      "5/6/20   1229331\n",
-      "5/7/20   1257023\n",
-      "5/8/20   1283929\n",
-      "5/9/20   1309550\n",
-      "5/10/20  1329260\n",
-      "5/11/20  1347881\n",
-      "5/12/20  1369376\n",
-      "5/13/20  1390406\n",
-      "5/14/20  1417774\n",
-      "5/15/20  1442824\n",
-      "5/16/20  1467820\n",
-      "5/17/20  1486757\n",
-      "5/18/20  1508308\n",
-      "5/19/20  1528568\n",
-      "\n",
-      "[119 rows x 1 columns]}\n"
-     ]
-    },
-    {
-     "ename": "AssertionError",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-46-e9fe60806b76>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mto_plot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mto_plot\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mregions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mAssertionError\u001b[0m: "
+      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:18: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:30: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:15: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  from ipykernel import kernelapp as app\n"
      ]
     }
    ],
@@ -2373,43 +2101,2072 @@
     "        region_name = \"France\" \n",
     "    if \"Netherlands\" in region:\n",
     "        region_name = \"Netherlands\" \n",
-    "    if \"Unied Kingdom\" in region:\n",
-    "        region_name = \"United Kingdom\"\n",
-    "    d = confirmed[confirmed[\"Country/Region\"] == region_name][confirmed['Province/State'].isnull()]\n",
+    "    if \"United Kingdom\" in region:\n",
+    "        region_name = \"United Kingdom\"   \n",
+    "    if \"Korea South\" in region:\n",
+    "        region_name = \"Korea, South\"    \n",
+    "    if region == \"Hong-Kong\":\n",
+    "        d = confirmed[confirmed[\"Country/Region\"] == \"China\"][confirmed['Province/State'] == \"Hong Kong\"]\n",
+    "        assert len(d) == 1\n",
+    "    else:\n",
+    "        d = confirmed[confirmed[\"Country/Region\"] == region_name][confirmed['Province/State'].isnull()]\n",
+    "    \n",
     "    if len(d) == 1:\n",
     "        to_plot[region] = d.T[4:]\n",
+    "    else:\n",
+    "        # more special cases: China\n",
+    "        if region == \"China\":\n",
+    "            d = confirmed[confirmed[\"Country/Region\"] == \"China\"]\n",
+    "            agg_dict = {col: 'sum' for col in d.columns[4:]}\n",
+    "            to_plot[region] = d.groupby(['Country/Region'],as_index=False).agg(agg_dict).T[1:]\n",
+    "\n",
+    "        if region == \"China (all provinces except Hong Kong)\":\n",
+    "            d = confirmed[confirmed[\"Country/Region\"] == \"China\"][confirmed['Province/State'] != \"Hong Kong\"]\n",
+    "            agg_dict = {col: 'sum' for col in d.columns[4:]}\n",
+    "            to_plot[region] = d.groupby(['Country/Region'],as_index=False).agg(agg_dict).T[1:]\n",
+    "            \n",
+    "    to_plot[region].index = pd.to_datetime(to_plot[region].index)\n",
+    "    col_name = to_plot[region].columns[0]\n",
+    "    to_plot[region] = to_plot[region].rename(columns={col_name: \"confirmed cases\"})\n",
     "    \n",
-    "    # more special cases: China\n",
-    "    if region == \"China\":\n",
-    "        d = confirmed[confirmed[\"Country/Region\"] == region_name]\n",
-    "        \n",
     "        \n",
     "    \n",
-    "print(to_plot)        \n",
-    "assert len(to_plot) == len(regions)"
+    "#print(to_plot)        \n",
+    "#print(len(to_plot) , len(regions))\n",
+    "assert len(to_plot) == len(regions)\n",
+    "#to_plot"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 170,
    "metadata": {
     "scrolled": true
    },
+   "outputs": [],
+   "source": [
+    "tmp = to_plot[\"France except Dom/Tom\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 171,
+   "metadata": {},
    "outputs": [
     {
-     "ename": "KeyError",
-     "evalue": "'France'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-41-5b37c91e0548>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mto_plot\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"France\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mKeyError\u001b[0m: 'France'"
-     ]
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "to_plot[\"France\"]"
+    "fig = plt.figure()\n",
+    "ax = plt.subplot(111)\n",
+    "\n",
+    "for region, data in to_plot.items():\n",
+    "    ax.plot(data[\"confirmed cases\"], label=region)\n",
+    "    \n",
+    "box = ax.get_position()\n",
+    "ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])\n",
+    "\n",
+    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now lets cut of the days where less than 150 cases are available:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 172,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Belgium':            confirmed cases\n",
+       " 2020-03-07             169\n",
+       " 2020-03-08             200\n",
+       " 2020-03-09             239\n",
+       " 2020-03-10             267\n",
+       " 2020-03-11             314\n",
+       " 2020-03-12             314\n",
+       " 2020-03-13             559\n",
+       " 2020-03-14             689\n",
+       " 2020-03-15             886\n",
+       " 2020-03-16            1058\n",
+       " 2020-03-17            1243\n",
+       " 2020-03-18            1486\n",
+       " 2020-03-19            1795\n",
+       " 2020-03-20            2257\n",
+       " 2020-03-21            2815\n",
+       " 2020-03-22            3401\n",
+       " 2020-03-23            3743\n",
+       " 2020-03-24            4269\n",
+       " 2020-03-25            4937\n",
+       " 2020-03-26            6235\n",
+       " 2020-03-27            7284\n",
+       " 2020-03-28            9134\n",
+       " 2020-03-29           10836\n",
+       " 2020-03-30           11899\n",
+       " 2020-03-31           12775\n",
+       " 2020-04-01           13964\n",
+       " 2020-04-02           15348\n",
+       " 2020-04-03           16770\n",
+       " 2020-04-04           18431\n",
+       " 2020-04-05           19691\n",
+       " ...                    ...\n",
+       " 2020-04-20           39983\n",
+       " 2020-04-21           40956\n",
+       " 2020-04-22           41889\n",
+       " 2020-04-23           42797\n",
+       " 2020-04-24           44293\n",
+       " 2020-04-25           45325\n",
+       " 2020-04-26           46134\n",
+       " 2020-04-27           46687\n",
+       " 2020-04-28           47334\n",
+       " 2020-04-29           47859\n",
+       " 2020-04-30           48519\n",
+       " 2020-05-01           49032\n",
+       " 2020-05-02           49517\n",
+       " 2020-05-03           49906\n",
+       " 2020-05-04           50267\n",
+       " 2020-05-05           50509\n",
+       " 2020-05-06           50781\n",
+       " 2020-05-07           51420\n",
+       " 2020-05-08           52011\n",
+       " 2020-05-09           52596\n",
+       " 2020-05-10           53081\n",
+       " 2020-05-11           53449\n",
+       " 2020-05-12           53779\n",
+       " 2020-05-13           53981\n",
+       " 2020-05-14           54288\n",
+       " 2020-05-15           54644\n",
+       " 2020-05-16           54989\n",
+       " 2020-05-17           55280\n",
+       " 2020-05-18           55559\n",
+       " 2020-05-19           55791\n",
+       " \n",
+       " [74 rows x 1 columns],\n",
+       " 'China (all provinces except Hong Kong)':            confirmed cases\n",
+       " 2020-01-22             548\n",
+       " 2020-01-23             641\n",
+       " 2020-01-24             918\n",
+       " 2020-01-25            1401\n",
+       " 2020-01-26            2067\n",
+       " 2020-01-27            2869\n",
+       " 2020-01-28            5501\n",
+       " 2020-01-29            6077\n",
+       " 2020-01-30            8131\n",
+       " 2020-01-31            9790\n",
+       " 2020-02-01           11878\n",
+       " 2020-02-02           16615\n",
+       " 2020-02-03           19701\n",
+       " 2020-02-04           23690\n",
+       " 2020-02-05           27419\n",
+       " 2020-02-06           30563\n",
+       " 2020-02-07           34085\n",
+       " 2020-02-08           36788\n",
+       " 2020-02-09           39800\n",
+       " 2020-02-10           42316\n",
+       " 2020-02-11           44337\n",
+       " 2020-02-12           44709\n",
+       " 2020-02-13           59842\n",
+       " 2020-02-14           66302\n",
+       " 2020-02-15           68357\n",
+       " 2020-02-16           70456\n",
+       " 2020-02-17           72374\n",
+       " 2020-02-18           74149\n",
+       " 2020-02-19           74556\n",
+       " 2020-02-20           75009\n",
+       " ...                    ...\n",
+       " 2020-04-20           82792\n",
+       " 2020-04-21           82824\n",
+       " 2020-04-22           82835\n",
+       " 2020-04-23           82849\n",
+       " 2020-04-24           82864\n",
+       " 2020-04-25           82872\n",
+       " 2020-04-26           82875\n",
+       " 2020-04-27           82881\n",
+       " 2020-04-28           82903\n",
+       " 2020-04-29           82907\n",
+       " 2020-04-30           82919\n",
+       " 2020-05-01           82920\n",
+       " 2020-05-02           82920\n",
+       " 2020-05-03           82925\n",
+       " 2020-05-04           82926\n",
+       " 2020-05-05           82928\n",
+       " 2020-05-06           82930\n",
+       " 2020-05-07           82931\n",
+       " 2020-05-08           82932\n",
+       " 2020-05-09           82946\n",
+       " 2020-05-10           82963\n",
+       " 2020-05-11           82964\n",
+       " 2020-05-12           82971\n",
+       " 2020-05-13           82974\n",
+       " 2020-05-14           82978\n",
+       " 2020-05-15           82986\n",
+       " 2020-05-16           82992\n",
+       " 2020-05-17           82999\n",
+       " 2020-05-18           83008\n",
+       " 2020-05-19           83008\n",
+       " \n",
+       " [119 rows x 1 columns],\n",
+       " 'China':            confirmed cases\n",
+       " 2020-01-22             548\n",
+       " 2020-01-23             643\n",
+       " 2020-01-24             920\n",
+       " 2020-01-25            1406\n",
+       " 2020-01-26            2075\n",
+       " 2020-01-27            2877\n",
+       " 2020-01-28            5509\n",
+       " 2020-01-29            6087\n",
+       " 2020-01-30            8141\n",
+       " 2020-01-31            9802\n",
+       " 2020-02-01           11891\n",
+       " 2020-02-02           16630\n",
+       " 2020-02-03           19716\n",
+       " 2020-02-04           23707\n",
+       " 2020-02-05           27440\n",
+       " 2020-02-06           30587\n",
+       " 2020-02-07           34110\n",
+       " 2020-02-08           36814\n",
+       " 2020-02-09           39829\n",
+       " 2020-02-10           42354\n",
+       " 2020-02-11           44386\n",
+       " 2020-02-12           44759\n",
+       " 2020-02-13           59895\n",
+       " 2020-02-14           66358\n",
+       " 2020-02-15           68413\n",
+       " 2020-02-16           70513\n",
+       " 2020-02-17           72434\n",
+       " 2020-02-18           74211\n",
+       " 2020-02-19           74619\n",
+       " 2020-02-20           75077\n",
+       " ...                    ...\n",
+       " 2020-04-20           83817\n",
+       " 2020-04-21           83853\n",
+       " 2020-04-22           83868\n",
+       " 2020-04-23           83884\n",
+       " 2020-04-24           83899\n",
+       " 2020-04-25           83909\n",
+       " 2020-04-26           83912\n",
+       " 2020-04-27           83918\n",
+       " 2020-04-28           83940\n",
+       " 2020-04-29           83944\n",
+       " 2020-04-30           83956\n",
+       " 2020-05-01           83959\n",
+       " 2020-05-02           83959\n",
+       " 2020-05-03           83964\n",
+       " 2020-05-04           83966\n",
+       " 2020-05-05           83968\n",
+       " 2020-05-06           83970\n",
+       " 2020-05-07           83975\n",
+       " 2020-05-08           83976\n",
+       " 2020-05-09           83990\n",
+       " 2020-05-10           84010\n",
+       " 2020-05-11           84011\n",
+       " 2020-05-12           84018\n",
+       " 2020-05-13           84024\n",
+       " 2020-05-14           84029\n",
+       " 2020-05-15           84038\n",
+       " 2020-05-16           84044\n",
+       " 2020-05-17           84054\n",
+       " 2020-05-18           84063\n",
+       " 2020-05-19           84063\n",
+       " \n",
+       " [119 rows x 1 columns],\n",
+       " 'Hong-Kong':            confirmed cases\n",
+       " 2020-03-16             155\n",
+       " 2020-03-17             162\n",
+       " 2020-03-18             181\n",
+       " 2020-03-19             208\n",
+       " 2020-03-20             256\n",
+       " 2020-03-21             273\n",
+       " 2020-03-22             317\n",
+       " 2020-03-23             356\n",
+       " 2020-03-24             386\n",
+       " 2020-03-25             410\n",
+       " 2020-03-26             453\n",
+       " 2020-03-27             519\n",
+       " 2020-03-28             561\n",
+       " 2020-03-29             641\n",
+       " 2020-03-30             682\n",
+       " 2020-03-31             714\n",
+       " 2020-04-01             765\n",
+       " 2020-04-02             802\n",
+       " 2020-04-03             845\n",
+       " 2020-04-04             862\n",
+       " 2020-04-05             890\n",
+       " 2020-04-06             914\n",
+       " 2020-04-07             935\n",
+       " 2020-04-08             960\n",
+       " 2020-04-09             973\n",
+       " 2020-04-10             989\n",
+       " 2020-04-11            1000\n",
+       " 2020-04-12            1004\n",
+       " 2020-04-13            1009\n",
+       " 2020-04-14            1012\n",
+       " ...                    ...\n",
+       " 2020-04-20            1025\n",
+       " 2020-04-21            1029\n",
+       " 2020-04-22            1033\n",
+       " 2020-04-23            1035\n",
+       " 2020-04-24            1035\n",
+       " 2020-04-25            1037\n",
+       " 2020-04-26            1037\n",
+       " 2020-04-27            1037\n",
+       " 2020-04-28            1037\n",
+       " 2020-04-29            1037\n",
+       " 2020-04-30            1037\n",
+       " 2020-05-01            1039\n",
+       " 2020-05-02            1039\n",
+       " 2020-05-03            1039\n",
+       " 2020-05-04            1040\n",
+       " 2020-05-05            1040\n",
+       " 2020-05-06            1040\n",
+       " 2020-05-07            1044\n",
+       " 2020-05-08            1044\n",
+       " 2020-05-09            1044\n",
+       " 2020-05-10            1047\n",
+       " 2020-05-11            1047\n",
+       " 2020-05-12            1047\n",
+       " 2020-05-13            1050\n",
+       " 2020-05-14            1051\n",
+       " 2020-05-15            1052\n",
+       " 2020-05-16            1052\n",
+       " 2020-05-17            1055\n",
+       " 2020-05-18            1055\n",
+       " 2020-05-19            1055\n",
+       " \n",
+       " [65 rows x 1 columns],\n",
+       " 'France except Dom/Tom':            confirmed cases\n",
+       " 2020-03-02             191\n",
+       " 2020-03-03             204\n",
+       " 2020-03-04             285\n",
+       " 2020-03-05             377\n",
+       " 2020-03-06             653\n",
+       " 2020-03-07             949\n",
+       " 2020-03-08            1126\n",
+       " 2020-03-09            1209\n",
+       " 2020-03-10            1784\n",
+       " 2020-03-11            2281\n",
+       " 2020-03-12            2281\n",
+       " 2020-03-13            3661\n",
+       " 2020-03-14            4469\n",
+       " 2020-03-15            4499\n",
+       " 2020-03-16            6633\n",
+       " 2020-03-17            7652\n",
+       " 2020-03-18            9043\n",
+       " 2020-03-19           10871\n",
+       " 2020-03-20           12612\n",
+       " 2020-03-21           14282\n",
+       " 2020-03-22           16018\n",
+       " 2020-03-23           19856\n",
+       " 2020-03-24           22304\n",
+       " 2020-03-25           25233\n",
+       " 2020-03-26           29155\n",
+       " 2020-03-27           32964\n",
+       " 2020-03-28           37575\n",
+       " 2020-03-29           40174\n",
+       " 2020-03-30           44550\n",
+       " 2020-03-31           52128\n",
+       " ...                    ...\n",
+       " 2020-04-20          154188\n",
+       " 2020-04-21          156921\n",
+       " 2020-04-22          154715\n",
+       " 2020-04-23          157026\n",
+       " 2020-04-24          158636\n",
+       " 2020-04-25          160292\n",
+       " 2020-04-26          160847\n",
+       " 2020-04-27          164589\n",
+       " 2020-04-28          167605\n",
+       " 2020-04-29          165093\n",
+       " 2020-04-30          165764\n",
+       " 2020-05-01          165764\n",
+       " 2020-05-02          166976\n",
+       " 2020-05-03          167272\n",
+       " 2020-05-04          167886\n",
+       " 2020-05-05          168935\n",
+       " 2020-05-06          172465\n",
+       " 2020-05-07          173040\n",
+       " 2020-05-08          174318\n",
+       " 2020-05-09          174758\n",
+       " 2020-05-10          175027\n",
+       " 2020-05-11          175479\n",
+       " 2020-05-12          176207\n",
+       " 2020-05-13          175981\n",
+       " 2020-05-14          176712\n",
+       " 2020-05-15          177319\n",
+       " 2020-05-16          177207\n",
+       " 2020-05-17          177240\n",
+       " 2020-05-18          177554\n",
+       " 2020-05-19          178428\n",
+       " \n",
+       " [79 rows x 1 columns],\n",
+       " 'Germany':            confirmed cases\n",
+       " 2020-03-02             159\n",
+       " 2020-03-03             196\n",
+       " 2020-03-04             262\n",
+       " 2020-03-05             482\n",
+       " 2020-03-06             670\n",
+       " 2020-03-07             799\n",
+       " 2020-03-08            1040\n",
+       " 2020-03-09            1176\n",
+       " 2020-03-10            1457\n",
+       " 2020-03-11            1908\n",
+       " 2020-03-12            2078\n",
+       " 2020-03-13            3675\n",
+       " 2020-03-14            4585\n",
+       " 2020-03-15            5795\n",
+       " 2020-03-16            7272\n",
+       " 2020-03-17            9257\n",
+       " 2020-03-18           12327\n",
+       " 2020-03-19           15320\n",
+       " 2020-03-20           19848\n",
+       " 2020-03-21           22213\n",
+       " 2020-03-22           24873\n",
+       " 2020-03-23           29056\n",
+       " 2020-03-24           32986\n",
+       " 2020-03-25           37323\n",
+       " 2020-03-26           43938\n",
+       " 2020-03-27           50871\n",
+       " 2020-03-28           57695\n",
+       " 2020-03-29           62095\n",
+       " 2020-03-30           66885\n",
+       " 2020-03-31           71808\n",
+       " ...                    ...\n",
+       " 2020-04-20          147065\n",
+       " 2020-04-21          148291\n",
+       " 2020-04-22          150648\n",
+       " 2020-04-23          153129\n",
+       " 2020-04-24          154999\n",
+       " 2020-04-25          156513\n",
+       " 2020-04-26          157770\n",
+       " 2020-04-27          158758\n",
+       " 2020-04-28          159912\n",
+       " 2020-04-29          161539\n",
+       " 2020-04-30          163009\n",
+       " 2020-05-01          164077\n",
+       " 2020-05-02          164967\n",
+       " 2020-05-03          165664\n",
+       " 2020-05-04          166152\n",
+       " 2020-05-05          167007\n",
+       " 2020-05-06          168162\n",
+       " 2020-05-07          169430\n",
+       " 2020-05-08          170588\n",
+       " 2020-05-09          171324\n",
+       " 2020-05-10          171879\n",
+       " 2020-05-11          172576\n",
+       " 2020-05-12          173171\n",
+       " 2020-05-13          174098\n",
+       " 2020-05-14          174478\n",
+       " 2020-05-15          175233\n",
+       " 2020-05-16          175752\n",
+       " 2020-05-17          176369\n",
+       " 2020-05-18          176551\n",
+       " 2020-05-19          177778\n",
+       " \n",
+       " [79 rows x 1 columns],\n",
+       " 'Iran':            confirmed cases\n",
+       " 2020-02-27             245\n",
+       " 2020-02-28             388\n",
+       " 2020-02-29             593\n",
+       " 2020-03-01             978\n",
+       " 2020-03-02            1501\n",
+       " 2020-03-03            2336\n",
+       " 2020-03-04            2922\n",
+       " 2020-03-05            3513\n",
+       " 2020-03-06            4747\n",
+       " 2020-03-07            5823\n",
+       " 2020-03-08            6566\n",
+       " 2020-03-09            7161\n",
+       " 2020-03-10            8042\n",
+       " 2020-03-11            9000\n",
+       " 2020-03-12           10075\n",
+       " 2020-03-13           11364\n",
+       " 2020-03-14           12729\n",
+       " 2020-03-15           13938\n",
+       " 2020-03-16           14991\n",
+       " 2020-03-17           16169\n",
+       " 2020-03-18           17361\n",
+       " 2020-03-19           18407\n",
+       " 2020-03-20           19644\n",
+       " 2020-03-21           20610\n",
+       " 2020-03-22           21638\n",
+       " 2020-03-23           23049\n",
+       " 2020-03-24           24811\n",
+       " 2020-03-25           27017\n",
+       " 2020-03-26           29406\n",
+       " 2020-03-27           32332\n",
+       " ...                    ...\n",
+       " 2020-04-20           83505\n",
+       " 2020-04-21           84802\n",
+       " 2020-04-22           85996\n",
+       " 2020-04-23           87026\n",
+       " 2020-04-24           88194\n",
+       " 2020-04-25           89328\n",
+       " 2020-04-26           90481\n",
+       " 2020-04-27           91472\n",
+       " 2020-04-28           92584\n",
+       " 2020-04-29           93657\n",
+       " 2020-04-30           94640\n",
+       " 2020-05-01           95646\n",
+       " 2020-05-02           96448\n",
+       " 2020-05-03           97424\n",
+       " 2020-05-04           98647\n",
+       " 2020-05-05           99970\n",
+       " 2020-05-06          101650\n",
+       " 2020-05-07          103135\n",
+       " 2020-05-08          104691\n",
+       " 2020-05-09          106220\n",
+       " 2020-05-10          107603\n",
+       " 2020-05-11          109286\n",
+       " 2020-05-12          110767\n",
+       " 2020-05-13          112725\n",
+       " 2020-05-14          114533\n",
+       " 2020-05-15          116635\n",
+       " 2020-05-16          118392\n",
+       " 2020-05-17          120198\n",
+       " 2020-05-18          122492\n",
+       " 2020-05-19          124603\n",
+       " \n",
+       " [83 rows x 1 columns],\n",
+       " 'Italy':            confirmed cases\n",
+       " 2020-02-23             155\n",
+       " 2020-02-24             229\n",
+       " 2020-02-25             322\n",
+       " 2020-02-26             453\n",
+       " 2020-02-27             655\n",
+       " 2020-02-28             888\n",
+       " 2020-02-29            1128\n",
+       " 2020-03-01            1694\n",
+       " 2020-03-02            2036\n",
+       " 2020-03-03            2502\n",
+       " 2020-03-04            3089\n",
+       " 2020-03-05            3858\n",
+       " 2020-03-06            4636\n",
+       " 2020-03-07            5883\n",
+       " 2020-03-08            7375\n",
+       " 2020-03-09            9172\n",
+       " 2020-03-10           10149\n",
+       " 2020-03-11           12462\n",
+       " 2020-03-12           12462\n",
+       " 2020-03-13           17660\n",
+       " 2020-03-14           21157\n",
+       " 2020-03-15           24747\n",
+       " 2020-03-16           27980\n",
+       " 2020-03-17           31506\n",
+       " 2020-03-18           35713\n",
+       " 2020-03-19           41035\n",
+       " 2020-03-20           47021\n",
+       " 2020-03-21           53578\n",
+       " 2020-03-22           59138\n",
+       " 2020-03-23           63927\n",
+       " ...                    ...\n",
+       " 2020-04-20          181228\n",
+       " 2020-04-21          183957\n",
+       " 2020-04-22          187327\n",
+       " 2020-04-23          189973\n",
+       " 2020-04-24          192994\n",
+       " 2020-04-25          195351\n",
+       " 2020-04-26          197675\n",
+       " 2020-04-27          199414\n",
+       " 2020-04-28          201505\n",
+       " 2020-04-29          203591\n",
+       " 2020-04-30          205463\n",
+       " 2020-05-01          207428\n",
+       " 2020-05-02          209328\n",
+       " 2020-05-03          210717\n",
+       " 2020-05-04          211938\n",
+       " 2020-05-05          213013\n",
+       " 2020-05-06          214457\n",
+       " 2020-05-07          215858\n",
+       " 2020-05-08          217185\n",
+       " 2020-05-09          218268\n",
+       " 2020-05-10          219070\n",
+       " 2020-05-11          219814\n",
+       " 2020-05-12          221216\n",
+       " 2020-05-13          222104\n",
+       " 2020-05-14          223096\n",
+       " 2020-05-15          223885\n",
+       " 2020-05-16          224760\n",
+       " 2020-05-17          225435\n",
+       " 2020-05-18          225886\n",
+       " 2020-05-19          226699\n",
+       " \n",
+       " [87 rows x 1 columns],\n",
+       " 'Japan':            confirmed cases\n",
+       " 2020-02-24             159\n",
+       " 2020-02-25             170\n",
+       " 2020-02-26             189\n",
+       " 2020-02-27             214\n",
+       " 2020-02-28             228\n",
+       " 2020-02-29             241\n",
+       " 2020-03-01             256\n",
+       " 2020-03-02             274\n",
+       " 2020-03-03             293\n",
+       " 2020-03-04             331\n",
+       " 2020-03-05             360\n",
+       " 2020-03-06             420\n",
+       " 2020-03-07             461\n",
+       " 2020-03-08             502\n",
+       " 2020-03-09             511\n",
+       " 2020-03-10             581\n",
+       " 2020-03-11             639\n",
+       " 2020-03-12             639\n",
+       " 2020-03-13             701\n",
+       " 2020-03-14             773\n",
+       " 2020-03-15             839\n",
+       " 2020-03-16             839\n",
+       " 2020-03-17             878\n",
+       " 2020-03-18             889\n",
+       " 2020-03-19             924\n",
+       " 2020-03-20             963\n",
+       " 2020-03-21            1007\n",
+       " 2020-03-22            1101\n",
+       " 2020-03-23            1128\n",
+       " 2020-03-24            1193\n",
+       " ...                    ...\n",
+       " 2020-04-20           10797\n",
+       " 2020-04-21           11135\n",
+       " 2020-04-22           11512\n",
+       " 2020-04-23           12368\n",
+       " 2020-04-24           12829\n",
+       " 2020-04-25           13231\n",
+       " 2020-04-26           13441\n",
+       " 2020-04-27           14153\n",
+       " 2020-04-28           13736\n",
+       " 2020-04-29           13895\n",
+       " 2020-04-30           14088\n",
+       " 2020-05-01           14305\n",
+       " 2020-05-02           14571\n",
+       " 2020-05-03           14877\n",
+       " 2020-05-04           15078\n",
+       " 2020-05-05           15253\n",
+       " 2020-05-06           15253\n",
+       " 2020-05-07           15477\n",
+       " 2020-05-08           15575\n",
+       " 2020-05-09           15663\n",
+       " 2020-05-10           15777\n",
+       " 2020-05-11           15847\n",
+       " 2020-05-12           15968\n",
+       " 2020-05-13           16049\n",
+       " 2020-05-14           16120\n",
+       " 2020-05-15           16203\n",
+       " 2020-05-16           16237\n",
+       " 2020-05-17           16285\n",
+       " 2020-05-18           16305\n",
+       " 2020-05-19           16367\n",
+       " \n",
+       " [86 rows x 1 columns],\n",
+       " 'Korea South':            confirmed cases\n",
+       " 2020-02-21             204\n",
+       " 2020-02-22             433\n",
+       " 2020-02-23             602\n",
+       " 2020-02-24             833\n",
+       " 2020-02-25             977\n",
+       " 2020-02-26            1261\n",
+       " 2020-02-27            1766\n",
+       " 2020-02-28            2337\n",
+       " 2020-02-29            3150\n",
+       " 2020-03-01            3736\n",
+       " 2020-03-02            4335\n",
+       " 2020-03-03            5186\n",
+       " 2020-03-04            5621\n",
+       " 2020-03-05            6088\n",
+       " 2020-03-06            6593\n",
+       " 2020-03-07            7041\n",
+       " 2020-03-08            7314\n",
+       " 2020-03-09            7478\n",
+       " 2020-03-10            7513\n",
+       " 2020-03-11            7755\n",
+       " 2020-03-12            7869\n",
+       " 2020-03-13            7979\n",
+       " 2020-03-14            8086\n",
+       " 2020-03-15            8162\n",
+       " 2020-03-16            8236\n",
+       " 2020-03-17            8320\n",
+       " 2020-03-18            8413\n",
+       " 2020-03-19            8565\n",
+       " 2020-03-20            8652\n",
+       " 2020-03-21            8799\n",
+       " ...                    ...\n",
+       " 2020-04-20           10674\n",
+       " 2020-04-21           10683\n",
+       " 2020-04-22           10694\n",
+       " 2020-04-23           10708\n",
+       " 2020-04-24           10718\n",
+       " 2020-04-25           10728\n",
+       " 2020-04-26           10738\n",
+       " 2020-04-27           10752\n",
+       " 2020-04-28           10761\n",
+       " 2020-04-29           10765\n",
+       " 2020-04-30           10774\n",
+       " 2020-05-01           10780\n",
+       " 2020-05-02           10793\n",
+       " 2020-05-03           10801\n",
+       " 2020-05-04           10804\n",
+       " 2020-05-05           10806\n",
+       " 2020-05-06           10810\n",
+       " 2020-05-07           10822\n",
+       " 2020-05-08           10840\n",
+       " 2020-05-09           10874\n",
+       " 2020-05-10           10909\n",
+       " 2020-05-11           10936\n",
+       " 2020-05-12           10962\n",
+       " 2020-05-13           10991\n",
+       " 2020-05-14           11018\n",
+       " 2020-05-15           11037\n",
+       " 2020-05-16           11050\n",
+       " 2020-05-17           11065\n",
+       " 2020-05-18           11078\n",
+       " 2020-05-19           11110\n",
+       " \n",
+       " [89 rows x 1 columns],\n",
+       " 'Netherlands without the colonies':            confirmed cases\n",
+       " 2020-03-07             188\n",
+       " 2020-03-08             265\n",
+       " 2020-03-09             321\n",
+       " 2020-03-10             382\n",
+       " 2020-03-11             503\n",
+       " 2020-03-12             503\n",
+       " 2020-03-13             804\n",
+       " 2020-03-14             959\n",
+       " 2020-03-15            1135\n",
+       " 2020-03-16            1413\n",
+       " 2020-03-17            1705\n",
+       " 2020-03-18            2051\n",
+       " 2020-03-19            2460\n",
+       " 2020-03-20            2994\n",
+       " 2020-03-21            3631\n",
+       " 2020-03-22            4204\n",
+       " 2020-03-23            4749\n",
+       " 2020-03-24            5560\n",
+       " 2020-03-25            6412\n",
+       " 2020-03-26            7431\n",
+       " 2020-03-27            8603\n",
+       " 2020-03-28            9762\n",
+       " 2020-03-29           10866\n",
+       " 2020-03-30           11750\n",
+       " 2020-03-31           12595\n",
+       " 2020-04-01           13614\n",
+       " 2020-04-02           14697\n",
+       " 2020-04-03           15723\n",
+       " 2020-04-04           16627\n",
+       " 2020-04-05           17851\n",
+       " ...                    ...\n",
+       " 2020-04-20           33405\n",
+       " 2020-04-21           34134\n",
+       " 2020-04-22           34842\n",
+       " 2020-04-23           35729\n",
+       " 2020-04-24           36535\n",
+       " 2020-04-25           37190\n",
+       " 2020-04-26           37845\n",
+       " 2020-04-27           38245\n",
+       " 2020-04-28           38416\n",
+       " 2020-04-29           38802\n",
+       " 2020-04-30           39316\n",
+       " 2020-05-01           39791\n",
+       " 2020-05-02           40236\n",
+       " 2020-05-03           40571\n",
+       " 2020-05-04           40770\n",
+       " 2020-05-05           41087\n",
+       " 2020-05-06           41319\n",
+       " 2020-05-07           41774\n",
+       " 2020-05-08           42093\n",
+       " 2020-05-09           42382\n",
+       " 2020-05-10           42627\n",
+       " 2020-05-11           42788\n",
+       " 2020-05-12           42984\n",
+       " 2020-05-13           43211\n",
+       " 2020-05-14           43481\n",
+       " 2020-05-15           43681\n",
+       " 2020-05-16           43870\n",
+       " 2020-05-17           43995\n",
+       " 2020-05-18           44141\n",
+       " 2020-05-19           44249\n",
+       " \n",
+       " [74 rows x 1 columns],\n",
+       " 'Portugal':            confirmed cases\n",
+       " 2020-03-14             169\n",
+       " 2020-03-15             245\n",
+       " 2020-03-16             331\n",
+       " 2020-03-17             448\n",
+       " 2020-03-18             448\n",
+       " 2020-03-19             785\n",
+       " 2020-03-20            1020\n",
+       " 2020-03-21            1280\n",
+       " 2020-03-22            1600\n",
+       " 2020-03-23            2060\n",
+       " 2020-03-24            2362\n",
+       " 2020-03-25            2995\n",
+       " 2020-03-26            3544\n",
+       " 2020-03-27            4268\n",
+       " 2020-03-28            5170\n",
+       " 2020-03-29            5962\n",
+       " 2020-03-30            6408\n",
+       " 2020-03-31            7443\n",
+       " 2020-04-01            8251\n",
+       " 2020-04-02            9034\n",
+       " 2020-04-03            9886\n",
+       " 2020-04-04           10524\n",
+       " 2020-04-05           11278\n",
+       " 2020-04-06           11730\n",
+       " 2020-04-07           12442\n",
+       " 2020-04-08           13141\n",
+       " 2020-04-09           13956\n",
+       " 2020-04-10           15472\n",
+       " 2020-04-11           15987\n",
+       " 2020-04-12           16585\n",
+       " ...                    ...\n",
+       " 2020-04-20           20863\n",
+       " 2020-04-21           21379\n",
+       " 2020-04-22           21982\n",
+       " 2020-04-23           22353\n",
+       " 2020-04-24           22797\n",
+       " 2020-04-25           23392\n",
+       " 2020-04-26           23864\n",
+       " 2020-04-27           24027\n",
+       " 2020-04-28           24322\n",
+       " 2020-04-29           24505\n",
+       " 2020-04-30           25045\n",
+       " 2020-05-01           25351\n",
+       " 2020-05-02           25190\n",
+       " 2020-05-03           25282\n",
+       " 2020-05-04           25524\n",
+       " 2020-05-05           25702\n",
+       " 2020-05-06           26182\n",
+       " 2020-05-07           26715\n",
+       " 2020-05-08           27268\n",
+       " 2020-05-09           27406\n",
+       " 2020-05-10           27581\n",
+       " 2020-05-11           27679\n",
+       " 2020-05-12           27913\n",
+       " 2020-05-13           28132\n",
+       " 2020-05-14           28319\n",
+       " 2020-05-15           28583\n",
+       " 2020-05-16           28810\n",
+       " 2020-05-17           29036\n",
+       " 2020-05-18           29209\n",
+       " 2020-05-19           29432\n",
+       " \n",
+       " [67 rows x 1 columns],\n",
+       " 'Spain':            confirmed cases\n",
+       " 2020-03-03             165\n",
+       " 2020-03-04             222\n",
+       " 2020-03-05             259\n",
+       " 2020-03-06             400\n",
+       " 2020-03-07             500\n",
+       " 2020-03-08             673\n",
+       " 2020-03-09            1073\n",
+       " 2020-03-10            1695\n",
+       " 2020-03-11            2277\n",
+       " 2020-03-12            2277\n",
+       " 2020-03-13            5232\n",
+       " 2020-03-14            6391\n",
+       " 2020-03-15            7798\n",
+       " 2020-03-16            9942\n",
+       " 2020-03-17           11748\n",
+       " 2020-03-18           13910\n",
+       " 2020-03-19           17963\n",
+       " 2020-03-20           20410\n",
+       " 2020-03-21           25374\n",
+       " 2020-03-22           28768\n",
+       " 2020-03-23           35136\n",
+       " 2020-03-24           39885\n",
+       " 2020-03-25           49515\n",
+       " 2020-03-26           57786\n",
+       " 2020-03-27           65719\n",
+       " 2020-03-28           73235\n",
+       " 2020-03-29           80110\n",
+       " 2020-03-30           87956\n",
+       " 2020-03-31           95923\n",
+       " 2020-04-01          104118\n",
+       " ...                    ...\n",
+       " 2020-04-20          200210\n",
+       " 2020-04-21          204178\n",
+       " 2020-04-22          208389\n",
+       " 2020-04-23          213024\n",
+       " 2020-04-24          202990\n",
+       " 2020-04-25          205905\n",
+       " 2020-04-26          207634\n",
+       " 2020-04-27          209465\n",
+       " 2020-04-28          210773\n",
+       " 2020-04-29          212917\n",
+       " 2020-04-30          213435\n",
+       " 2020-05-01          215216\n",
+       " 2020-05-02          216582\n",
+       " 2020-05-03          217466\n",
+       " 2020-05-04          218011\n",
+       " 2020-05-05          219329\n",
+       " 2020-05-06          220325\n",
+       " 2020-05-07          221447\n",
+       " 2020-05-08          222857\n",
+       " 2020-05-09          223578\n",
+       " 2020-05-10          224350\n",
+       " 2020-05-11          227436\n",
+       " 2020-05-12          228030\n",
+       " 2020-05-13          228691\n",
+       " 2020-05-14          229540\n",
+       " 2020-05-15          230183\n",
+       " 2020-05-16          230698\n",
+       " 2020-05-17          230698\n",
+       " 2020-05-18          231606\n",
+       " 2020-05-19          232037\n",
+       " \n",
+       " [78 rows x 1 columns],\n",
+       " 'United Kingdom without the colonies':            confirmed cases\n",
+       " 2020-03-06             163\n",
+       " 2020-03-07             206\n",
+       " 2020-03-08             273\n",
+       " 2020-03-09             321\n",
+       " 2020-03-10             382\n",
+       " 2020-03-11             456\n",
+       " 2020-03-12             456\n",
+       " 2020-03-13             798\n",
+       " 2020-03-14            1140\n",
+       " 2020-03-15            1140\n",
+       " 2020-03-16            1543\n",
+       " 2020-03-17            1950\n",
+       " 2020-03-18            2626\n",
+       " 2020-03-19            2689\n",
+       " 2020-03-20            3983\n",
+       " 2020-03-21            5018\n",
+       " 2020-03-22            5683\n",
+       " 2020-03-23            6650\n",
+       " 2020-03-24            8077\n",
+       " 2020-03-25            9529\n",
+       " 2020-03-26           11658\n",
+       " 2020-03-27           14543\n",
+       " 2020-03-28           17089\n",
+       " 2020-03-29           19522\n",
+       " 2020-03-30           22141\n",
+       " 2020-03-31           25150\n",
+       " 2020-04-01           29474\n",
+       " 2020-04-02           33718\n",
+       " 2020-04-03           38168\n",
+       " 2020-04-04           41903\n",
+       " ...                    ...\n",
+       " 2020-04-20          124743\n",
+       " 2020-04-21          129044\n",
+       " 2020-04-22          133495\n",
+       " 2020-04-23          138078\n",
+       " 2020-04-24          143464\n",
+       " 2020-04-25          148377\n",
+       " 2020-04-26          152840\n",
+       " 2020-04-27          157149\n",
+       " 2020-04-28          161145\n",
+       " 2020-04-29          165221\n",
+       " 2020-04-30          171253\n",
+       " 2020-05-01          177454\n",
+       " 2020-05-02          182260\n",
+       " 2020-05-03          186599\n",
+       " 2020-05-04          190584\n",
+       " 2020-05-05          194990\n",
+       " 2020-05-06          201101\n",
+       " 2020-05-07          206715\n",
+       " 2020-05-08          211364\n",
+       " 2020-05-09          215260\n",
+       " 2020-05-10          219183\n",
+       " 2020-05-11          223060\n",
+       " 2020-05-12          226463\n",
+       " 2020-05-13          229705\n",
+       " 2020-05-14          233151\n",
+       " 2020-05-15          236711\n",
+       " 2020-05-16          240161\n",
+       " 2020-05-17          243695\n",
+       " 2020-05-18          246406\n",
+       " 2020-05-19          248818\n",
+       " \n",
+       " [75 rows x 1 columns],\n",
+       " 'US':            confirmed cases\n",
+       " 2020-03-05             217\n",
+       " 2020-03-06             262\n",
+       " 2020-03-07             402\n",
+       " 2020-03-08             518\n",
+       " 2020-03-09             583\n",
+       " 2020-03-10             959\n",
+       " 2020-03-11            1281\n",
+       " 2020-03-12            1663\n",
+       " 2020-03-13            2179\n",
+       " 2020-03-14            2727\n",
+       " 2020-03-15            3499\n",
+       " 2020-03-16            4632\n",
+       " 2020-03-17            6421\n",
+       " 2020-03-18            7783\n",
+       " 2020-03-19           13747\n",
+       " 2020-03-20           19273\n",
+       " 2020-03-21           25600\n",
+       " 2020-03-22           33276\n",
+       " 2020-03-23           43843\n",
+       " 2020-03-24           53736\n",
+       " 2020-03-25           65778\n",
+       " 2020-03-26           83836\n",
+       " 2020-03-27          101657\n",
+       " 2020-03-28          121465\n",
+       " 2020-03-29          140909\n",
+       " 2020-03-30          161831\n",
+       " 2020-03-31          188172\n",
+       " 2020-04-01          213242\n",
+       " 2020-04-02          243622\n",
+       " 2020-04-03          275367\n",
+       " ...                    ...\n",
+       " 2020-04-20          784326\n",
+       " 2020-04-21          811865\n",
+       " 2020-04-22          840351\n",
+       " 2020-04-23          869170\n",
+       " 2020-04-24          905358\n",
+       " 2020-04-25          938154\n",
+       " 2020-04-26          965785\n",
+       " 2020-04-27          988197\n",
+       " 2020-04-28         1012582\n",
+       " 2020-04-29         1039909\n",
+       " 2020-04-30         1069424\n",
+       " 2020-05-01         1103461\n",
+       " 2020-05-02         1132539\n",
+       " 2020-05-03         1158040\n",
+       " 2020-05-04         1180375\n",
+       " 2020-05-05         1204351\n",
+       " 2020-05-06         1229331\n",
+       " 2020-05-07         1257023\n",
+       " 2020-05-08         1283929\n",
+       " 2020-05-09         1309550\n",
+       " 2020-05-10         1329260\n",
+       " 2020-05-11         1347881\n",
+       " 2020-05-12         1369376\n",
+       " 2020-05-13         1390406\n",
+       " 2020-05-14         1417774\n",
+       " 2020-05-15         1442824\n",
+       " 2020-05-16         1467820\n",
+       " 2020-05-17         1486757\n",
+       " 2020-05-18         1508308\n",
+       " 2020-05-19         1528568\n",
+       " \n",
+       " [76 rows x 1 columns]}"
+      ]
+     },
+     "execution_count": 172,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "to_plot_cut = {}\n",
+    "for region, data in to_plot.items():  # something is wrong here!\n",
+    "    cutpoint = -1    \n",
+    "    col = data.columns[0]    \n",
+    "    for i, val in enumerate(data[\"confirmed cases\"]):\n",
+    "        #print(val)\n",
+    "        if val >= 150:\n",
+    "            cutpoint = i            \n",
+    "            break\n",
+    "    assert cutpoint != -1\n",
+    "#     print(cutpoint)\n",
+    "#     print(\"-------\")\n",
+    "#     print(region)\n",
+    "#     print(to_plot[region][:])\n",
+    "#     print(\",,,,\")\n",
+    "#     print(data.iloc[cutpoint:cutpoint+5])\n",
+    "    to_plot_cut[region] = data.iloc[cutpoint:]  \n",
+    "to_plot_cut"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And plot it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 179,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 1440x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(20,10))\n",
+    "ax = plt.subplot(111)\n",
+    "\n",
+    "\n",
+    "for region, data in to_plot_cut.items():\n",
+    "    xs = np.arange(0,len(data[\"confirmed cases\"]),1)\n",
+    "    ys = data[\"confirmed cases\"][:]\n",
+    "    ax.plot(xs, ys, label=region)\n",
+    "    ax.annotate(region, xy=(xs[-1], ys[-1]),  xycoords='data',\n",
+    "            xytext=(xs[-1], ys[-1]), textcoords='data',\n",
+    "            arrowprops=dict(facecolor='black', shrink=0.05),\n",
+    "            horizontalalignment='right', verticalalignment='top',\n",
+    "            )\n",
+    "    \n",
+    "#box = ax.get_position()\n",
+    "#ax.set_position([box.x0, box.y0, box.width, box.height])\n",
+    "\n",
+    "#ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "\n",
+    "\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Its really hard to see who is who. So lets try with a logarithmic scale:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 191,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(20,10))\n",
+    "ax = plt.subplot(111)\n",
+    "\n",
+    "\n",
+    "for region, data in to_plot_cut.items():\n",
+    "    xs = np.arange(0,len(data[\"confirmed cases\"]),1)\n",
+    "    ys = data[\"confirmed cases\"][:]\n",
+    "    p = ax.plot(xs, ys, label=region)\n",
+    "    annotation_text = region\n",
+    "    if \"except Hong Kong\" in region:\n",
+    "        annotation_text = \"\\n\"+annotation_text\n",
+    "    ax.annotate(annotation_text, xy=(xs[-1], ys[-1]),  xycoords='data',\n",
+    "            xytext=(xs[-1], ys[-1]), textcoords='data',\n",
+    "            arrowprops=dict(facecolor='black', shrink=-0.05),\n",
+    "            horizontalalignment='right', verticalalignment='top', color = p[0].get_color()\n",
+    "            )\n",
+    "\n",
+    "plt.grid()\n",
+    "plt.yscale(\"log\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Is there a problem with the spain curve? it seems to start very high?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 200,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "nan\n",
+      "Spain\n",
+      "40.0\n",
+      "-4.0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "0\n",
+      "1\n",
+      "1\n",
+      "1\n",
+      "1\n",
+      "1\n",
+      "1\n",
+      "1\n",
+      "1\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "2\n",
+      "6\n",
+      "13\n",
+      "15\n",
+      "32\n",
+      "45\n",
+      "84\n",
+      "120\n",
+      "165\n",
+      "222\n",
+      "259\n",
+      "400\n",
+      "500\n",
+      "673\n",
+      "1073\n",
+      "1695\n",
+      "2277\n",
+      "2277\n",
+      "5232\n",
+      "6391\n",
+      "7798\n",
+      "9942\n",
+      "11748\n",
+      "13910\n",
+      "17963\n",
+      "20410\n",
+      "25374\n",
+      "28768\n",
+      "35136\n",
+      "39885\n",
+      "49515\n",
+      "57786\n",
+      "65719\n",
+      "73235\n",
+      "80110\n",
+      "87956\n",
+      "95923\n",
+      "104118\n",
+      "112065\n",
+      "119199\n",
+      "126168\n",
+      "131646\n",
+      "136675\n",
+      "141942\n",
+      "148220\n",
+      "153222\n",
+      "158273\n",
+      "163027\n",
+      "166831\n",
+      "170099\n",
+      "172541\n",
+      "177644\n",
+      "184948\n",
+      "190839\n",
+      "191726\n",
+      "198674\n",
+      "200210\n",
+      "204178\n",
+      "208389\n",
+      "213024\n",
+      "202990\n",
+      "205905\n",
+      "207634\n",
+      "209465\n",
+      "210773\n",
+      "212917\n",
+      "213435\n",
+      "215216\n",
+      "216582\n",
+      "217466\n",
+      "218011\n",
+      "219329\n",
+      "220325\n",
+      "221447\n",
+      "222857\n",
+      "223578\n",
+      "224350\n",
+      "227436\n",
+      "228030\n",
+      "228691\n",
+      "229540\n",
+      "230183\n",
+      "230698\n",
+      "230698\n",
+      "231606\n",
+      "232037\n"
+     ]
+    }
+   ],
+   "source": [
+    "for row in confirmed[confirmed[\"Country/Region\"] == \"Spain\"].T[201]:\n",
+    "    print(row)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There seems to be a problem..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 201,
+   "metadata": {
+    "scrolled": true
+   },
+   "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>confirmed cases</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-03-03</th>\n",
+       "      <td>165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-04</th>\n",
+       "      <td>222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-05</th>\n",
+       "      <td>259</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-06</th>\n",
+       "      <td>400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-07</th>\n",
+       "      <td>500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-08</th>\n",
+       "      <td>673</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-09</th>\n",
+       "      <td>1073</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-10</th>\n",
+       "      <td>1695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-11</th>\n",
+       "      <td>2277</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-12</th>\n",
+       "      <td>2277</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-13</th>\n",
+       "      <td>5232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-14</th>\n",
+       "      <td>6391</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-15</th>\n",
+       "      <td>7798</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-16</th>\n",
+       "      <td>9942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-17</th>\n",
+       "      <td>11748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-18</th>\n",
+       "      <td>13910</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-19</th>\n",
+       "      <td>17963</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-20</th>\n",
+       "      <td>20410</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-21</th>\n",
+       "      <td>25374</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-22</th>\n",
+       "      <td>28768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-23</th>\n",
+       "      <td>35136</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-24</th>\n",
+       "      <td>39885</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-25</th>\n",
+       "      <td>49515</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-26</th>\n",
+       "      <td>57786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-27</th>\n",
+       "      <td>65719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-28</th>\n",
+       "      <td>73235</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-29</th>\n",
+       "      <td>80110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-30</th>\n",
+       "      <td>87956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-31</th>\n",
+       "      <td>95923</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-01</th>\n",
+       "      <td>104118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-20</th>\n",
+       "      <td>200210</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-21</th>\n",
+       "      <td>204178</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-22</th>\n",
+       "      <td>208389</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-23</th>\n",
+       "      <td>213024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-24</th>\n",
+       "      <td>202990</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-25</th>\n",
+       "      <td>205905</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-26</th>\n",
+       "      <td>207634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-27</th>\n",
+       "      <td>209465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-28</th>\n",
+       "      <td>210773</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-29</th>\n",
+       "      <td>212917</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-30</th>\n",
+       "      <td>213435</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-01</th>\n",
+       "      <td>215216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-02</th>\n",
+       "      <td>216582</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-03</th>\n",
+       "      <td>217466</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-04</th>\n",
+       "      <td>218011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-05</th>\n",
+       "      <td>219329</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-06</th>\n",
+       "      <td>220325</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-07</th>\n",
+       "      <td>221447</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-08</th>\n",
+       "      <td>222857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-09</th>\n",
+       "      <td>223578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-10</th>\n",
+       "      <td>224350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-11</th>\n",
+       "      <td>227436</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-12</th>\n",
+       "      <td>228030</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-13</th>\n",
+       "      <td>228691</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-14</th>\n",
+       "      <td>229540</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-15</th>\n",
+       "      <td>230183</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-16</th>\n",
+       "      <td>230698</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-17</th>\n",
+       "      <td>230698</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-18</th>\n",
+       "      <td>231606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-19</th>\n",
+       "      <td>232037</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>78 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           confirmed cases\n",
+       "2020-03-03             165\n",
+       "2020-03-04             222\n",
+       "2020-03-05             259\n",
+       "2020-03-06             400\n",
+       "2020-03-07             500\n",
+       "2020-03-08             673\n",
+       "2020-03-09            1073\n",
+       "2020-03-10            1695\n",
+       "2020-03-11            2277\n",
+       "2020-03-12            2277\n",
+       "2020-03-13            5232\n",
+       "2020-03-14            6391\n",
+       "2020-03-15            7798\n",
+       "2020-03-16            9942\n",
+       "2020-03-17           11748\n",
+       "2020-03-18           13910\n",
+       "2020-03-19           17963\n",
+       "2020-03-20           20410\n",
+       "2020-03-21           25374\n",
+       "2020-03-22           28768\n",
+       "2020-03-23           35136\n",
+       "2020-03-24           39885\n",
+       "2020-03-25           49515\n",
+       "2020-03-26           57786\n",
+       "2020-03-27           65719\n",
+       "2020-03-28           73235\n",
+       "2020-03-29           80110\n",
+       "2020-03-30           87956\n",
+       "2020-03-31           95923\n",
+       "2020-04-01          104118\n",
+       "...                    ...\n",
+       "2020-04-20          200210\n",
+       "2020-04-21          204178\n",
+       "2020-04-22          208389\n",
+       "2020-04-23          213024\n",
+       "2020-04-24          202990\n",
+       "2020-04-25          205905\n",
+       "2020-04-26          207634\n",
+       "2020-04-27          209465\n",
+       "2020-04-28          210773\n",
+       "2020-04-29          212917\n",
+       "2020-04-30          213435\n",
+       "2020-05-01          215216\n",
+       "2020-05-02          216582\n",
+       "2020-05-03          217466\n",
+       "2020-05-04          218011\n",
+       "2020-05-05          219329\n",
+       "2020-05-06          220325\n",
+       "2020-05-07          221447\n",
+       "2020-05-08          222857\n",
+       "2020-05-09          223578\n",
+       "2020-05-10          224350\n",
+       "2020-05-11          227436\n",
+       "2020-05-12          228030\n",
+       "2020-05-13          228691\n",
+       "2020-05-14          229540\n",
+       "2020-05-15          230183\n",
+       "2020-05-16          230698\n",
+       "2020-05-17          230698\n",
+       "2020-05-18          231606\n",
+       "2020-05-19          232037\n",
+       "\n",
+       "[78 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 201,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "to_plot_cut[\"Spain\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ok I see its the chinese curve which jsut got a very similar color"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 203,
+   "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>confirmed cases</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-01-22</th>\n",
+       "      <td>548</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-23</th>\n",
+       "      <td>643</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-24</th>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-25</th>\n",
+       "      <td>1406</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-26</th>\n",
+       "      <td>2075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-27</th>\n",
+       "      <td>2877</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-28</th>\n",
+       "      <td>5509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-29</th>\n",
+       "      <td>6087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-30</th>\n",
+       "      <td>8141</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-31</th>\n",
+       "      <td>9802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-01</th>\n",
+       "      <td>11891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-02</th>\n",
+       "      <td>16630</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-03</th>\n",
+       "      <td>19716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-04</th>\n",
+       "      <td>23707</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-05</th>\n",
+       "      <td>27440</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-06</th>\n",
+       "      <td>30587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-07</th>\n",
+       "      <td>34110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-08</th>\n",
+       "      <td>36814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-09</th>\n",
+       "      <td>39829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-10</th>\n",
+       "      <td>42354</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-11</th>\n",
+       "      <td>44386</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-12</th>\n",
+       "      <td>44759</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-13</th>\n",
+       "      <td>59895</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-14</th>\n",
+       "      <td>66358</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-15</th>\n",
+       "      <td>68413</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-16</th>\n",
+       "      <td>70513</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-17</th>\n",
+       "      <td>72434</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-18</th>\n",
+       "      <td>74211</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-19</th>\n",
+       "      <td>74619</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-20</th>\n",
+       "      <td>75077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-20</th>\n",
+       "      <td>83817</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-21</th>\n",
+       "      <td>83853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-22</th>\n",
+       "      <td>83868</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-23</th>\n",
+       "      <td>83884</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-24</th>\n",
+       "      <td>83899</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-25</th>\n",
+       "      <td>83909</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-26</th>\n",
+       "      <td>83912</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-27</th>\n",
+       "      <td>83918</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-28</th>\n",
+       "      <td>83940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-29</th>\n",
+       "      <td>83944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-30</th>\n",
+       "      <td>83956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-01</th>\n",
+       "      <td>83959</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-02</th>\n",
+       "      <td>83959</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-03</th>\n",
+       "      <td>83964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-04</th>\n",
+       "      <td>83966</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-05</th>\n",
+       "      <td>83968</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-06</th>\n",
+       "      <td>83970</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-07</th>\n",
+       "      <td>83975</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-08</th>\n",
+       "      <td>83976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-09</th>\n",
+       "      <td>83990</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-10</th>\n",
+       "      <td>84010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-11</th>\n",
+       "      <td>84011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-12</th>\n",
+       "      <td>84018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-13</th>\n",
+       "      <td>84024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-14</th>\n",
+       "      <td>84029</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-15</th>\n",
+       "      <td>84038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-16</th>\n",
+       "      <td>84044</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-17</th>\n",
+       "      <td>84054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-18</th>\n",
+       "      <td>84063</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-19</th>\n",
+       "      <td>84063</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>119 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           confirmed cases\n",
+       "2020-01-22             548\n",
+       "2020-01-23             643\n",
+       "2020-01-24             920\n",
+       "2020-01-25            1406\n",
+       "2020-01-26            2075\n",
+       "2020-01-27            2877\n",
+       "2020-01-28            5509\n",
+       "2020-01-29            6087\n",
+       "2020-01-30            8141\n",
+       "2020-01-31            9802\n",
+       "2020-02-01           11891\n",
+       "2020-02-02           16630\n",
+       "2020-02-03           19716\n",
+       "2020-02-04           23707\n",
+       "2020-02-05           27440\n",
+       "2020-02-06           30587\n",
+       "2020-02-07           34110\n",
+       "2020-02-08           36814\n",
+       "2020-02-09           39829\n",
+       "2020-02-10           42354\n",
+       "2020-02-11           44386\n",
+       "2020-02-12           44759\n",
+       "2020-02-13           59895\n",
+       "2020-02-14           66358\n",
+       "2020-02-15           68413\n",
+       "2020-02-16           70513\n",
+       "2020-02-17           72434\n",
+       "2020-02-18           74211\n",
+       "2020-02-19           74619\n",
+       "2020-02-20           75077\n",
+       "...                    ...\n",
+       "2020-04-20           83817\n",
+       "2020-04-21           83853\n",
+       "2020-04-22           83868\n",
+       "2020-04-23           83884\n",
+       "2020-04-24           83899\n",
+       "2020-04-25           83909\n",
+       "2020-04-26           83912\n",
+       "2020-04-27           83918\n",
+       "2020-04-28           83940\n",
+       "2020-04-29           83944\n",
+       "2020-04-30           83956\n",
+       "2020-05-01           83959\n",
+       "2020-05-02           83959\n",
+       "2020-05-03           83964\n",
+       "2020-05-04           83966\n",
+       "2020-05-05           83968\n",
+       "2020-05-06           83970\n",
+       "2020-05-07           83975\n",
+       "2020-05-08           83976\n",
+       "2020-05-09           83990\n",
+       "2020-05-10           84010\n",
+       "2020-05-11           84011\n",
+       "2020-05-12           84018\n",
+       "2020-05-13           84024\n",
+       "2020-05-14           84029\n",
+       "2020-05-15           84038\n",
+       "2020-05-16           84044\n",
+       "2020-05-17           84054\n",
+       "2020-05-18           84063\n",
+       "2020-05-19           84063\n",
+       "\n",
+       "[119 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 203,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "to_plot[\"China\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "After validation with the data from the csv It appears correct. There are no earlier values for china than 22 of january 2022"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## now lets do the same thing for the deaths:"
    ]
   },
   {