From d4472c0112549248dd0fb4a00accf3e4976732ff Mon Sep 17 00:00:00 2001
From: Neil Smith <neil.git@njae.me.uk>
Date: Tue, 17 Apr 2018 09:26:39 +0100
Subject: [PATCH] Tidying

---
 20180416/20180416.ipynb | 1158 ++++++++++++++++++++++++++++++---------
 1 file changed, 895 insertions(+), 263 deletions(-)

diff --git a/20180416/20180416.ipynb b/20180416/20180416.ipynb
index 9dd222d..1222e74 100644
--- a/20180416/20180416.ipynb
+++ b/20180416/20180416.ipynb
@@ -4,16 +4,16 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Makeover Monday, 9 April 2018\n",
+    "# Makeover Monday, 16 April 2018\n",
     "\n",
-    "Analysis and visualisation of Arctic sea ice extent for [Makeover Monday](http://www.makeovermonday.co.uk).\n",
+    "Analysis and visualisation of (simulated) malaria cases for [Makeover Monday](http://www.makeovermonday.co.uk).\n",
     "\n",
-    "Data from [US National Snow & Ice data centre](https://nsidc.org/) via [Makeover Monday](http://www.makeovermonday.co.uk/data/)."
+    "Data from [VisualizeNoMalaria](https://data.world/makeovermonday/2018w16-zambia-southern-province-confirmed-malaria-cases) via [Makeover Monday](http://www.makeovermonday.co.uk/data/)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -143,7 +143,7 @@
        "4          Health Facility      0  "
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -164,7 +164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -174,7 +174,7 @@
        "Name: country, dtype: int64"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -185,7 +185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -195,7 +195,7 @@
        "Name: province, dtype: int64"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -206,29 +206,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Monze          400\n",
-       "Choma          400\n",
-       "Kalomo         400\n",
        "Mazabuka       400\n",
+       "Kalomo         400\n",
        "Kazungula      400\n",
+       "Choma          400\n",
+       "Monze          400\n",
+       "Zimba          200\n",
        "Chikankata     200\n",
-       "Pemba          200\n",
        "Sinazongwe     200\n",
-       "Zimba          200\n",
        "Namwala        200\n",
-       "Gwembe         200\n",
        "Siavonga       200\n",
+       "Gwembe         200\n",
+       "Pemba          200\n",
        "Livingstone    186\n",
        "Name: district, dtype: int64"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -250,7 +250,7 @@
        "Name: ruralurban, dtype: int64"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -261,7 +261,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -272,7 +272,7 @@
        "Name: report, dtype: int64"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -290,7 +290,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -319,7 +319,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -338,16 +338,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fad673c6828>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b22dff4e0>"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -368,16 +368,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fad650d4780>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b20d66550>"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -398,16 +398,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fad6512e518>"
+       "<matplotlib.legend.Legend at 0x7f6b20c93dd8>"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -429,7 +429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -535,7 +535,7 @@
        "Sinazongwe   158874"
       ]
      },
-     "execution_count": 64,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -546,16 +546,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fad64e65748>"
+       "<matplotlib.legend.Legend at 0x7f6b20c07c50>"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -577,7 +577,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -606,7 +606,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -710,7 +710,7 @@
        "4          Health Facility      0  "
       ]
      },
-     "execution_count": 43,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -722,7 +722,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -826,7 +826,7 @@
        "28          Health Facility      0  "
       ]
      },
-     "execution_count": 71,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -838,7 +838,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -859,7 +859,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -880,7 +880,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -901,7 +901,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -930,7 +930,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1034,7 +1034,7 @@
        "3190          Health Facility      0  "
       ]
      },
-     "execution_count": 65,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1046,7 +1046,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1150,7 +1150,7 @@
        "4          Health Facility      0  "
       ]
      },
-     "execution_count": 66,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1162,16 +1162,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fad5ea092e8>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b22e78080>"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1192,16 +1192,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fad5e9ff048>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b22e629e8>"
       ]
      },
-     "execution_count": 68,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1222,7 +1222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -1250,7 +1250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 155,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -1416,7 +1416,7 @@
        "2014-05-01 00:00:00        8058    773  "
       ]
      },
-     "execution_count": 155,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1428,7 +1428,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 156,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -1459,7 +1459,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 186,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -1546,7 +1546,7 @@
        "2014-05-01        8058    2900      1318   13497"
       ]
      },
-     "execution_count": 186,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1562,7 +1562,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 187,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1587,7 +1587,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 189,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1596,7 +1596,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 188,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -1625,7 +1625,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 122,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -1783,7 +1783,7 @@
        "2018        161       57    159       731        9569    328  "
       ]
      },
-     "execution_count": 122,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1795,179 +1795,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 33,
    "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 tr th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead tr:last-of-type th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr>\n",
-       "      <th></th>\n",
-       "      <th colspan=\"13\" halign=\"left\">cases</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>district</th>\n",
-       "      <th>Chikankata</th>\n",
-       "      <th>Choma</th>\n",
-       "      <th>Gwembe</th>\n",
-       "      <th>Kalomo</th>\n",
-       "      <th>Kazungula</th>\n",
-       "      <th>Livingstone</th>\n",
-       "      <th>Mazabuka</th>\n",
-       "      <th>Monze</th>\n",
-       "      <th>Namwala</th>\n",
-       "      <th>Pemba</th>\n",
-       "      <th>Siavonga</th>\n",
-       "      <th>Sinazongwe</th>\n",
-       "      <th>Zimba</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>date</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2014</th>\n",
-       "      <td>5852</td>\n",
-       "      <td>21810</td>\n",
-       "      <td>29523</td>\n",
-       "      <td>14410</td>\n",
-       "      <td>8093</td>\n",
-       "      <td>1752</td>\n",
-       "      <td>2919</td>\n",
-       "      <td>4152</td>\n",
-       "      <td>1073</td>\n",
-       "      <td>24984</td>\n",
-       "      <td>15995</td>\n",
-       "      <td>70664</td>\n",
-       "      <td>8326</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2015</th>\n",
-       "      <td>2717</td>\n",
-       "      <td>4030</td>\n",
-       "      <td>15349</td>\n",
-       "      <td>4005</td>\n",
-       "      <td>3623</td>\n",
-       "      <td>837</td>\n",
-       "      <td>1297</td>\n",
-       "      <td>1539</td>\n",
-       "      <td>695</td>\n",
-       "      <td>6925</td>\n",
-       "      <td>6295</td>\n",
-       "      <td>43057</td>\n",
-       "      <td>3930</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2016</th>\n",
-       "      <td>2178</td>\n",
-       "      <td>3940</td>\n",
-       "      <td>4963</td>\n",
-       "      <td>9690</td>\n",
-       "      <td>13009</td>\n",
-       "      <td>1255</td>\n",
-       "      <td>2328</td>\n",
-       "      <td>1939</td>\n",
-       "      <td>2801</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>7087</td>\n",
-       "      <td>16823</td>\n",
-       "      <td>1306</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2017</th>\n",
-       "      <td>2073</td>\n",
-       "      <td>2396</td>\n",
-       "      <td>9899</td>\n",
-       "      <td>6983</td>\n",
-       "      <td>8627</td>\n",
-       "      <td>845</td>\n",
-       "      <td>1322</td>\n",
-       "      <td>1452</td>\n",
-       "      <td>1813</td>\n",
-       "      <td>994</td>\n",
-       "      <td>10595</td>\n",
-       "      <td>18761</td>\n",
-       "      <td>1094</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2018</th>\n",
-       "      <td>1097</td>\n",
-       "      <td>221</td>\n",
-       "      <td>4325</td>\n",
-       "      <td>441</td>\n",
-       "      <td>379</td>\n",
-       "      <td>101</td>\n",
-       "      <td>202</td>\n",
-       "      <td>161</td>\n",
-       "      <td>57</td>\n",
-       "      <td>159</td>\n",
-       "      <td>731</td>\n",
-       "      <td>9569</td>\n",
-       "      <td>328</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "              cases                                                            \\\n",
-       "district Chikankata  Choma Gwembe Kalomo Kazungula Livingstone Mazabuka Monze   \n",
-       "date                                                                            \n",
-       "2014           5852  21810  29523  14410      8093        1752     2919  4152   \n",
-       "2015           2717   4030  15349   4005      3623         837     1297  1539   \n",
-       "2016           2178   3940   4963   9690     13009        1255     2328  1939   \n",
-       "2017           2073   2396   9899   6983      8627         845     1322  1452   \n",
-       "2018           1097    221   4325    441       379         101      202   161   \n",
-       "\n",
-       "                                                   \n",
-       "district Namwala  Pemba Siavonga Sinazongwe Zimba  \n",
-       "date                                               \n",
-       "2014        1073  24984    15995      70664  8326  \n",
-       "2015         695   6925     6295      43057  3930  \n",
-       "2016        2801   2019     7087      16823  1306  \n",
-       "2017        1813    994    10595      18761  1094  \n",
-       "2018          57    159      731       9569   328  "
-      ]
-     },
-     "execution_count": 83,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# district_year = malaria_raw.groupby([malaria_raw.date.dt.year, 'district']).sum().unstack()\n",
     "# district_year"
@@ -1975,7 +1805,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -1996,7 +1826,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -2017,7 +1847,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 151,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -2040,7 +1870,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 126,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -2069,7 +1899,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 165,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
@@ -2093,10 +1923,10 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>others</th>\n",
-       "      <th>siavonga</th>\n",
-       "      <th>gwembe</th>\n",
-       "      <th>sinazongwe</th>\n",
+       "      <th>Others</th>\n",
+       "      <th>Siavonga</th>\n",
+       "      <th>Gwembe</th>\n",
+       "      <th>Sinazongwe</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
@@ -2147,7 +1977,7 @@
        "</div>"
       ],
       "text/plain": [
-       "      others  siavonga  gwembe  sinazongwe\n",
+       "      Others  Siavonga  Gwembe  Sinazongwe\n",
        "date                                      \n",
        "2014   93371     15995   29523       70664\n",
        "2015   29598      6295   15349       43057\n",
@@ -2156,38 +1986,38 @@
        "2018    3146       731    4325        9569"
       ]
      },
-     "execution_count": 165,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "d2_year = pd.DataFrame()\n",
-    "d2_year['others'] = district_year.drop(['Sinazongwe', 'Gwembe', 'Siavonga'], axis=1).sum(axis=1)\n",
-    "d2_year['siavonga'] = district_year['Siavonga']\n",
-    "d2_year['gwembe'] = district_year['Gwembe']\n",
-    "d2_year['sinazongwe'] = district_year['Sinazongwe']\n",
+    "d2_year['Others'] = district_year.drop(['Sinazongwe', 'Gwembe', 'Siavonga'], axis=1).sum(axis=1)\n",
+    "d2_year['Siavonga'] = district_year['Siavonga']\n",
+    "d2_year['Gwembe'] = district_year['Gwembe']\n",
+    "d2_year['Sinazongwe'] = district_year['Sinazongwe']\n",
     "d2_year"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 166,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fad5dd73c50>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b1acca2b0>"
       ]
      },
-     "execution_count": 166,
+     "execution_count": 50,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -2202,22 +2032,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 167,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fad5e0c45c0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b22fc58d0>"
       ]
      },
-     "execution_count": 167,
+     "execution_count": 51,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -2230,6 +2060,808 @@
     "d2_year.plot.area(xticks=[x for x in range(2014, 2019)])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Cyclic changes\n",
+    "What if we plot how cases each month change over the five years?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>country</th>\n",
+       "      <th>province</th>\n",
+       "      <th>district</th>\n",
+       "      <th>ruralurban</th>\n",
+       "      <th>date</th>\n",
+       "      <th>report</th>\n",
+       "      <th>cases</th>\n",
+       "      <th>month</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Zambia</td>\n",
+       "      <td>Southern</td>\n",
+       "      <td>Chikankata</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>2014-01-01</td>\n",
+       "      <td>Health Facility</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Zambia</td>\n",
+       "      <td>Southern</td>\n",
+       "      <td>Chikankata</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>2014-01-01</td>\n",
+       "      <td>Community Health Worker</td>\n",
+       "      <td>288</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Zambia</td>\n",
+       "      <td>Southern</td>\n",
+       "      <td>Chikankata</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>2014-02-01</td>\n",
+       "      <td>Health Facility</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Zambia</td>\n",
+       "      <td>Southern</td>\n",
+       "      <td>Chikankata</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>2014-02-01</td>\n",
+       "      <td>Community Health Worker</td>\n",
+       "      <td>251</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Zambia</td>\n",
+       "      <td>Southern</td>\n",
+       "      <td>Chikankata</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>2014-03-01</td>\n",
+       "      <td>Health Facility</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  country  province    district ruralurban       date  \\\n",
+       "0  Zambia  Southern  Chikankata      Rural 2014-01-01   \n",
+       "1  Zambia  Southern  Chikankata      Rural 2014-01-01   \n",
+       "2  Zambia  Southern  Chikankata      Rural 2014-02-01   \n",
+       "3  Zambia  Southern  Chikankata      Rural 2014-02-01   \n",
+       "4  Zambia  Southern  Chikankata      Rural 2014-03-01   \n",
+       "\n",
+       "                    report  cases  month  \n",
+       "0          Health Facility      0      1  \n",
+       "1  Community Health Worker    288      1  \n",
+       "2          Health Facility      0      2  \n",
+       "3  Community Health Worker    251      2  \n",
+       "4          Health Facility      0      3  "
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "malaria_raw['month'] = malaria_raw['date'].dt.month\n",
+    "malaria_raw.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "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>district</th>\n",
+       "      <th>Chikankata</th>\n",
+       "      <th>Choma</th>\n",
+       "      <th>Gwembe</th>\n",
+       "      <th>Kalomo</th>\n",
+       "      <th>Kazungula</th>\n",
+       "      <th>Livingstone</th>\n",
+       "      <th>Mazabuka</th>\n",
+       "      <th>Monze</th>\n",
+       "      <th>Namwala</th>\n",
+       "      <th>Pemba</th>\n",
+       "      <th>Siavonga</th>\n",
+       "      <th>Sinazongwe</th>\n",
+       "      <th>Zimba</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>month</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2556</td>\n",
+       "      <td>2766</td>\n",
+       "      <td>6381</td>\n",
+       "      <td>2633</td>\n",
+       "      <td>2618</td>\n",
+       "      <td>509</td>\n",
+       "      <td>1074</td>\n",
+       "      <td>1274</td>\n",
+       "      <td>765</td>\n",
+       "      <td>5064</td>\n",
+       "      <td>2074</td>\n",
+       "      <td>16561</td>\n",
+       "      <td>1640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1903</td>\n",
+       "      <td>3516</td>\n",
+       "      <td>4958</td>\n",
+       "      <td>3480</td>\n",
+       "      <td>4200</td>\n",
+       "      <td>466</td>\n",
+       "      <td>784</td>\n",
+       "      <td>888</td>\n",
+       "      <td>585</td>\n",
+       "      <td>5972</td>\n",
+       "      <td>1998</td>\n",
+       "      <td>11983</td>\n",
+       "      <td>2202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2051</td>\n",
+       "      <td>7604</td>\n",
+       "      <td>7330</td>\n",
+       "      <td>5937</td>\n",
+       "      <td>6528</td>\n",
+       "      <td>614</td>\n",
+       "      <td>1070</td>\n",
+       "      <td>1215</td>\n",
+       "      <td>1091</td>\n",
+       "      <td>6593</td>\n",
+       "      <td>4837</td>\n",
+       "      <td>18379</td>\n",
+       "      <td>3508</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2267</td>\n",
+       "      <td>6994</td>\n",
+       "      <td>8352</td>\n",
+       "      <td>9419</td>\n",
+       "      <td>8215</td>\n",
+       "      <td>799</td>\n",
+       "      <td>1546</td>\n",
+       "      <td>1676</td>\n",
+       "      <td>1194</td>\n",
+       "      <td>5423</td>\n",
+       "      <td>5955</td>\n",
+       "      <td>20070</td>\n",
+       "      <td>3447</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1738</td>\n",
+       "      <td>5294</td>\n",
+       "      <td>8341</td>\n",
+       "      <td>6923</td>\n",
+       "      <td>7708</td>\n",
+       "      <td>1081</td>\n",
+       "      <td>1571</td>\n",
+       "      <td>1825</td>\n",
+       "      <td>1668</td>\n",
+       "      <td>5247</td>\n",
+       "      <td>7246</td>\n",
+       "      <td>21220</td>\n",
+       "      <td>1739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>599</td>\n",
+       "      <td>2209</td>\n",
+       "      <td>5534</td>\n",
+       "      <td>2835</td>\n",
+       "      <td>2215</td>\n",
+       "      <td>393</td>\n",
+       "      <td>587</td>\n",
+       "      <td>817</td>\n",
+       "      <td>472</td>\n",
+       "      <td>2686</td>\n",
+       "      <td>4542</td>\n",
+       "      <td>17599</td>\n",
+       "      <td>652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>378</td>\n",
+       "      <td>769</td>\n",
+       "      <td>7538</td>\n",
+       "      <td>1193</td>\n",
+       "      <td>645</td>\n",
+       "      <td>140</td>\n",
+       "      <td>255</td>\n",
+       "      <td>353</td>\n",
+       "      <td>161</td>\n",
+       "      <td>1083</td>\n",
+       "      <td>3694</td>\n",
+       "      <td>9924</td>\n",
+       "      <td>243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>260</td>\n",
+       "      <td>422</td>\n",
+       "      <td>4998</td>\n",
+       "      <td>605</td>\n",
+       "      <td>260</td>\n",
+       "      <td>137</td>\n",
+       "      <td>223</td>\n",
+       "      <td>266</td>\n",
+       "      <td>73</td>\n",
+       "      <td>553</td>\n",
+       "      <td>3995</td>\n",
+       "      <td>8765</td>\n",
+       "      <td>179</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>391</td>\n",
+       "      <td>489</td>\n",
+       "      <td>4205</td>\n",
+       "      <td>439</td>\n",
+       "      <td>156</td>\n",
+       "      <td>124</td>\n",
+       "      <td>210</td>\n",
+       "      <td>234</td>\n",
+       "      <td>57</td>\n",
+       "      <td>458</td>\n",
+       "      <td>3045</td>\n",
+       "      <td>12220</td>\n",
+       "      <td>158</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>515</td>\n",
+       "      <td>731</td>\n",
+       "      <td>2716</td>\n",
+       "      <td>472</td>\n",
+       "      <td>208</td>\n",
+       "      <td>95</td>\n",
+       "      <td>163</td>\n",
+       "      <td>236</td>\n",
+       "      <td>49</td>\n",
+       "      <td>470</td>\n",
+       "      <td>1667</td>\n",
+       "      <td>10442</td>\n",
+       "      <td>285</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>398</td>\n",
+       "      <td>661</td>\n",
+       "      <td>1731</td>\n",
+       "      <td>540</td>\n",
+       "      <td>173</td>\n",
+       "      <td>167</td>\n",
+       "      <td>218</td>\n",
+       "      <td>141</td>\n",
+       "      <td>69</td>\n",
+       "      <td>570</td>\n",
+       "      <td>880</td>\n",
+       "      <td>5352</td>\n",
+       "      <td>323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>861</td>\n",
+       "      <td>942</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>805</td>\n",
+       "      <td>265</td>\n",
+       "      <td>367</td>\n",
+       "      <td>318</td>\n",
+       "      <td>255</td>\n",
+       "      <td>962</td>\n",
+       "      <td>770</td>\n",
+       "      <td>6359</td>\n",
+       "      <td>608</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "district  Chikankata  Choma  Gwembe  Kalomo  Kazungula  Livingstone  Mazabuka  \\\n",
+       "month                                                                           \n",
+       "1               2556   2766    6381    2633       2618          509      1074   \n",
+       "2               1903   3516    4958    3480       4200          466       784   \n",
+       "3               2051   7604    7330    5937       6528          614      1070   \n",
+       "4               2267   6994    8352    9419       8215          799      1546   \n",
+       "5               1738   5294    8341    6923       7708         1081      1571   \n",
+       "6                599   2209    5534    2835       2215          393       587   \n",
+       "7                378    769    7538    1193        645          140       255   \n",
+       "8                260    422    4998     605        260          137       223   \n",
+       "9                391    489    4205     439        156          124       210   \n",
+       "10               515    731    2716     472        208           95       163   \n",
+       "11               398    661    1731     540        173          167       218   \n",
+       "12               861    942    1975    1053        805          265       367   \n",
+       "\n",
+       "district  Monze  Namwala  Pemba  Siavonga  Sinazongwe  Zimba  \n",
+       "month                                                         \n",
+       "1          1274      765   5064      2074       16561   1640  \n",
+       "2           888      585   5972      1998       11983   2202  \n",
+       "3          1215     1091   6593      4837       18379   3508  \n",
+       "4          1676     1194   5423      5955       20070   3447  \n",
+       "5          1825     1668   5247      7246       21220   1739  \n",
+       "6           817      472   2686      4542       17599    652  \n",
+       "7           353      161   1083      3694        9924    243  \n",
+       "8           266       73    553      3995        8765    179  \n",
+       "9           234       57    458      3045       12220    158  \n",
+       "10          236       49    470      1667       10442    285  \n",
+       "11          141       69    570       880        5352    323  \n",
+       "12          318      255    962       770        6359    608  "
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "malaria_month_year = pd.pivot_table(malaria_raw,index='month',columns='district',values='cases', aggfunc=np.sum)\n",
+    "malaria_month_year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6b230446d8>"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "malaria_month_year.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Normalise the data, so that scores are fraction of that district's cases in each month."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "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>district</th>\n",
+       "      <th>Chikankata</th>\n",
+       "      <th>Choma</th>\n",
+       "      <th>Gwembe</th>\n",
+       "      <th>Kalomo</th>\n",
+       "      <th>Kazungula</th>\n",
+       "      <th>Livingstone</th>\n",
+       "      <th>Mazabuka</th>\n",
+       "      <th>Monze</th>\n",
+       "      <th>Namwala</th>\n",
+       "      <th>Pemba</th>\n",
+       "      <th>Siavonga</th>\n",
+       "      <th>Sinazongwe</th>\n",
+       "      <th>Zimba</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>month</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.183660</td>\n",
+       "      <td>0.085378</td>\n",
+       "      <td>0.099611</td>\n",
+       "      <td>0.074108</td>\n",
+       "      <td>0.077614</td>\n",
+       "      <td>0.106263</td>\n",
+       "      <td>0.133118</td>\n",
+       "      <td>0.137834</td>\n",
+       "      <td>0.118807</td>\n",
+       "      <td>0.144352</td>\n",
+       "      <td>0.050954</td>\n",
+       "      <td>0.104240</td>\n",
+       "      <td>0.109450</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.136739</td>\n",
+       "      <td>0.108529</td>\n",
+       "      <td>0.077397</td>\n",
+       "      <td>0.097948</td>\n",
+       "      <td>0.124515</td>\n",
+       "      <td>0.097286</td>\n",
+       "      <td>0.097174</td>\n",
+       "      <td>0.096073</td>\n",
+       "      <td>0.090853</td>\n",
+       "      <td>0.170235</td>\n",
+       "      <td>0.049087</td>\n",
+       "      <td>0.075425</td>\n",
+       "      <td>0.146957</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.147374</td>\n",
+       "      <td>0.234713</td>\n",
+       "      <td>0.114426</td>\n",
+       "      <td>0.167103</td>\n",
+       "      <td>0.193531</td>\n",
+       "      <td>0.128184</td>\n",
+       "      <td>0.132623</td>\n",
+       "      <td>0.131451</td>\n",
+       "      <td>0.169436</td>\n",
+       "      <td>0.187936</td>\n",
+       "      <td>0.118836</td>\n",
+       "      <td>0.115683</td>\n",
+       "      <td>0.234116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.162894</td>\n",
+       "      <td>0.215884</td>\n",
+       "      <td>0.130380</td>\n",
+       "      <td>0.265107</td>\n",
+       "      <td>0.243545</td>\n",
+       "      <td>0.166806</td>\n",
+       "      <td>0.191621</td>\n",
+       "      <td>0.181326</td>\n",
+       "      <td>0.185433</td>\n",
+       "      <td>0.154585</td>\n",
+       "      <td>0.146304</td>\n",
+       "      <td>0.126327</td>\n",
+       "      <td>0.230045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.124883</td>\n",
+       "      <td>0.163410</td>\n",
+       "      <td>0.130208</td>\n",
+       "      <td>0.194855</td>\n",
+       "      <td>0.228514</td>\n",
+       "      <td>0.225678</td>\n",
+       "      <td>0.194720</td>\n",
+       "      <td>0.197447</td>\n",
+       "      <td>0.259046</td>\n",
+       "      <td>0.149568</td>\n",
+       "      <td>0.178021</td>\n",
+       "      <td>0.133565</td>\n",
+       "      <td>0.116057</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0.043041</td>\n",
+       "      <td>0.068185</td>\n",
+       "      <td>0.086389</td>\n",
+       "      <td>0.079794</td>\n",
+       "      <td>0.065667</td>\n",
+       "      <td>0.082046</td>\n",
+       "      <td>0.072757</td>\n",
+       "      <td>0.088391</td>\n",
+       "      <td>0.073303</td>\n",
+       "      <td>0.076566</td>\n",
+       "      <td>0.111589</td>\n",
+       "      <td>0.110773</td>\n",
+       "      <td>0.043513</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.027161</td>\n",
+       "      <td>0.023737</td>\n",
+       "      <td>0.117673</td>\n",
+       "      <td>0.033578</td>\n",
+       "      <td>0.019122</td>\n",
+       "      <td>0.029228</td>\n",
+       "      <td>0.031606</td>\n",
+       "      <td>0.038191</td>\n",
+       "      <td>0.025004</td>\n",
+       "      <td>0.030871</td>\n",
+       "      <td>0.090755</td>\n",
+       "      <td>0.062465</td>\n",
+       "      <td>0.016217</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0.018682</td>\n",
+       "      <td>0.013026</td>\n",
+       "      <td>0.078022</td>\n",
+       "      <td>0.017028</td>\n",
+       "      <td>0.007708</td>\n",
+       "      <td>0.028601</td>\n",
+       "      <td>0.027640</td>\n",
+       "      <td>0.028779</td>\n",
+       "      <td>0.011337</td>\n",
+       "      <td>0.015764</td>\n",
+       "      <td>0.098150</td>\n",
+       "      <td>0.055170</td>\n",
+       "      <td>0.011946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0.028095</td>\n",
+       "      <td>0.015094</td>\n",
+       "      <td>0.065643</td>\n",
+       "      <td>0.012356</td>\n",
+       "      <td>0.004625</td>\n",
+       "      <td>0.025887</td>\n",
+       "      <td>0.026029</td>\n",
+       "      <td>0.025316</td>\n",
+       "      <td>0.008852</td>\n",
+       "      <td>0.013056</td>\n",
+       "      <td>0.074810</td>\n",
+       "      <td>0.076916</td>\n",
+       "      <td>0.010545</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0.037005</td>\n",
+       "      <td>0.022564</td>\n",
+       "      <td>0.042398</td>\n",
+       "      <td>0.013285</td>\n",
+       "      <td>0.006166</td>\n",
+       "      <td>0.019833</td>\n",
+       "      <td>0.020203</td>\n",
+       "      <td>0.025533</td>\n",
+       "      <td>0.007610</td>\n",
+       "      <td>0.013398</td>\n",
+       "      <td>0.040955</td>\n",
+       "      <td>0.065725</td>\n",
+       "      <td>0.019020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>0.028598</td>\n",
+       "      <td>0.020403</td>\n",
+       "      <td>0.027022</td>\n",
+       "      <td>0.015199</td>\n",
+       "      <td>0.005129</td>\n",
+       "      <td>0.034864</td>\n",
+       "      <td>0.027020</td>\n",
+       "      <td>0.015255</td>\n",
+       "      <td>0.010716</td>\n",
+       "      <td>0.016248</td>\n",
+       "      <td>0.021620</td>\n",
+       "      <td>0.033687</td>\n",
+       "      <td>0.021556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.061867</td>\n",
+       "      <td>0.029077</td>\n",
+       "      <td>0.030831</td>\n",
+       "      <td>0.029638</td>\n",
+       "      <td>0.023865</td>\n",
+       "      <td>0.055324</td>\n",
+       "      <td>0.045488</td>\n",
+       "      <td>0.034404</td>\n",
+       "      <td>0.039602</td>\n",
+       "      <td>0.027422</td>\n",
+       "      <td>0.018918</td>\n",
+       "      <td>0.040025</td>\n",
+       "      <td>0.040577</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "district  Chikankata     Choma    Gwembe    Kalomo  Kazungula  Livingstone  \\\n",
+       "month                                                                        \n",
+       "1           0.183660  0.085378  0.099611  0.074108   0.077614     0.106263   \n",
+       "2           0.136739  0.108529  0.077397  0.097948   0.124515     0.097286   \n",
+       "3           0.147374  0.234713  0.114426  0.167103   0.193531     0.128184   \n",
+       "4           0.162894  0.215884  0.130380  0.265107   0.243545     0.166806   \n",
+       "5           0.124883  0.163410  0.130208  0.194855   0.228514     0.225678   \n",
+       "6           0.043041  0.068185  0.086389  0.079794   0.065667     0.082046   \n",
+       "7           0.027161  0.023737  0.117673  0.033578   0.019122     0.029228   \n",
+       "8           0.018682  0.013026  0.078022  0.017028   0.007708     0.028601   \n",
+       "9           0.028095  0.015094  0.065643  0.012356   0.004625     0.025887   \n",
+       "10          0.037005  0.022564  0.042398  0.013285   0.006166     0.019833   \n",
+       "11          0.028598  0.020403  0.027022  0.015199   0.005129     0.034864   \n",
+       "12          0.061867  0.029077  0.030831  0.029638   0.023865     0.055324   \n",
+       "\n",
+       "district  Mazabuka     Monze   Namwala     Pemba  Siavonga  Sinazongwe  \\\n",
+       "month                                                                    \n",
+       "1         0.133118  0.137834  0.118807  0.144352  0.050954    0.104240   \n",
+       "2         0.097174  0.096073  0.090853  0.170235  0.049087    0.075425   \n",
+       "3         0.132623  0.131451  0.169436  0.187936  0.118836    0.115683   \n",
+       "4         0.191621  0.181326  0.185433  0.154585  0.146304    0.126327   \n",
+       "5         0.194720  0.197447  0.259046  0.149568  0.178021    0.133565   \n",
+       "6         0.072757  0.088391  0.073303  0.076566  0.111589    0.110773   \n",
+       "7         0.031606  0.038191  0.025004  0.030871  0.090755    0.062465   \n",
+       "8         0.027640  0.028779  0.011337  0.015764  0.098150    0.055170   \n",
+       "9         0.026029  0.025316  0.008852  0.013056  0.074810    0.076916   \n",
+       "10        0.020203  0.025533  0.007610  0.013398  0.040955    0.065725   \n",
+       "11        0.027020  0.015255  0.010716  0.016248  0.021620    0.033687   \n",
+       "12        0.045488  0.034404  0.039602  0.027422  0.018918    0.040025   \n",
+       "\n",
+       "district     Zimba  \n",
+       "month               \n",
+       "1         0.109450  \n",
+       "2         0.146957  \n",
+       "3         0.234116  \n",
+       "4         0.230045  \n",
+       "5         0.116057  \n",
+       "6         0.043513  \n",
+       "7         0.016217  \n",
+       "8         0.011946  \n",
+       "9         0.010545  \n",
+       "10        0.019020  \n",
+       "11        0.021556  \n",
+       "12        0.040577  "
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mmy_norm = malaria_month_year / malaria_month_year.sum()\n",
+    "mmy_norm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = mmy_norm.plot()\n",
+    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "and a very clear seasonal pattern emerges."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-- 
2.34.1