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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Case Study: Unusual Deaths in Mexico\n",
+    "\n",
+    "> The following case study illustrates how tidy data and tidy tools make data analysis easier by easing the transitions between manipulation, visualisation and modelling. You will not see any code that exists solely to get the output of one function into the right format to input to another.\n",
+    "\n",
+    "> The case study uses individual-level mortality data from Mexico. The goal is to find causes of death with unusual temporal patterns within a day."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## \"Housekeeping\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2018-08-27 11:47:22 CEST\n",
+      "\n",
+      "CPython 3.6.5\n",
+      "IPython 6.5.0\n",
+      "\n",
+      "matplotlib 2.2.3\n",
+      "numpy 1.15.1\n",
+      "pandas 0.23.4\n",
+      "seaborn 0.9.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "% load_ext watermark\n",
+    "% watermark -d -t -v -z -p matplotlib,numpy,pandas,seaborn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import math\n",
+    "import textwrap\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import rpy2.robjects as robjects\n",
+    "import rpy2.robjects.pandas2ri as pandas2ri\n",
+    "import seaborn as sns\n",
+    "\n",
+    "from sklearn.linear_model import HuberRegressor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "% matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.set()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load the Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deaths = pandas2ri.ri2py(robjects.r['readRDS']('data/deaths.rds'))\n",
+    "deaths = deaths[(deaths['yod'] == 2008) & (deaths['mod'] != 0)\n",
+    "                & (deaths['dod'] != 0)]\n",
+    "#deaths.loc[(deaths['hod'] < 0), 'hod'] = 0\n",
+    "deaths = deaths[~(deaths['hod'] < 0)]\n",
+    "deaths = deaths.reset_index(drop=True)\n",
+    "assert set(deaths['hod'].unique()) <= set(range(24))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(502520, 5)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "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>yod</th>\n",
+       "      <th>mod</th>\n",
+       "      <th>dod</th>\n",
+       "      <th>hod</th>\n",
+       "      <th>cod</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>B20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>B22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>C18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>C34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2008</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>C50</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    yod  mod  dod  hod  cod\n",
+       "0  2008    1    1    1  B20\n",
+       "1  2008    1    1    1  B22\n",
+       "2  2008    1    1    1  C18\n",
+       "3  2008    1    1    1  C34\n",
+       "4  2008    1    1    1  C50"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Note that this file contains 7 duplicates that are removed.\n",
+    "codes = pd.read_csv('data/icd-main.csv')\n",
+    "codes = codes[(codes['code'] != codes['code'].shift())].set_index('code')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1851, 1)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "codes.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "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>disease</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>code</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A00</th>\n",
+       "      <td>Cholera</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A01</th>\n",
+       "      <td>Typhoid and paratyphoid fevers</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A02</th>\n",
+       "      <td>Other salmonella infections</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A03</th>\n",
+       "      <td>Shigellosis</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A04</th>\n",
+       "      <td>Other bacterial intestinal infections</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                    disease\n",
+       "code                                       \n",
+       "A00                                 Cholera\n",
+       "A01          Typhoid and paratyphoid fevers\n",
+       "A02             Other salmonella infections\n",
+       "A03                             Shigellosis\n",
+       "A04   Other bacterial intestinal infections"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "codes.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Counts\n",
+    "\n",
+    "Count the number of deaths by *hour of the day* and *cause of death* (and also join in the more descriptive labels for the various causes)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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>hod</th>\n",
+       "      <th>cod</th>\n",
+       "      <th>freq</th>\n",
+       "      <th>disease</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A01</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Typhoid and paratyphoid fevers</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A02</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Other salmonella infections</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A04</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Other bacterial intestinal infections</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A05</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Other bacterial foodborne intoxications, not e...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A06</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Amebiasis</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   hod  cod  freq                                            disease\n",
+       "0    1  A01     3                     Typhoid and paratyphoid fevers\n",
+       "1    1  A02     3                        Other salmonella infections\n",
+       "2    1  A04     7              Other bacterial intestinal infections\n",
+       "3    1  A05     1  Other bacterial foodborne intoxications, not e...\n",
+       "4    1  A06     2                                          Amebiasis"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "counts = (\n",
+    "    pd.DataFrame(deaths.groupby(['hod', 'cod']).size(), columns=['freq'])\n",
+    "    .reset_index()\n",
+    "    .join(codes, on='cod')\n",
+    ")\n",
+    "# This is to ensure that no duplicates are created\n",
+    "# because of duplicate entries in the codes DataFrame.\n",
+    "assert counts['cod'].value_counts().max() <= 24\n",
+    "\n",
+    "# Keep only causes where a death happened in every hour.\n",
+    "counts = counts[counts['cod'].isin(list((counts['cod'].value_counts() == 24).index))]\n",
+    "\n",
+    "counts.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Add a *prop* column indicating the relative frequency of a given *cause of death* on an hourly basis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "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>hod</th>\n",
+       "      <th>cod</th>\n",
+       "      <th>freq</th>\n",
+       "      <th>disease</th>\n",
+       "      <th>prop</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A01</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Typhoid and paratyphoid fevers</td>\n",
+       "      <td>0.062500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A02</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Other salmonella infections</td>\n",
+       "      <td>0.048387</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A04</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Other bacterial intestinal infections</td>\n",
+       "      <td>0.051095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A05</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Other bacterial foodborne intoxications, not e...</td>\n",
+       "      <td>0.050000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A06</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Amebiasis</td>\n",
+       "      <td>0.024390</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   hod  cod  freq                                            disease      prop\n",
+       "0    1  A01     3                     Typhoid and paratyphoid fevers  0.062500\n",
+       "1    1  A02     3                        Other salmonella infections  0.048387\n",
+       "2    1  A04     7              Other bacterial intestinal infections  0.051095\n",
+       "3    1  A05     1  Other bacterial foodborne intoxications, not e...  0.050000\n",
+       "4    1  A06     2                                          Amebiasis  0.024390"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "counts = counts.set_index('cod')\n",
+    "counts['prop'] = (\n",
+    "    counts['freq']\n",
+    "    / deaths.groupby(['cod']).size().reindex(counts.index)\n",
+    ")\n",
+    "counts = counts.reset_index()\n",
+    "# Re-order the columns as in the paper.\n",
+    "counts = counts[['hod', 'cod', 'freq', 'disease', 'prop']]\n",
+    "\n",
+    "counts.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Add *freq_all* and *prop_all* columns that show the absolute number of deaths for a given *hour of day* (disregarding *cause of death*) and the proportion of deaths for a certain *hour of day* with respect to the whole day."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "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>hod</th>\n",
+       "      <th>cod</th>\n",
+       "      <th>freq</th>\n",
+       "      <th>disease</th>\n",
+       "      <th>prop</th>\n",
+       "      <th>freq_all</th>\n",
+       "      <th>prop_all</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A01</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Typhoid and paratyphoid fevers</td>\n",
+       "      <td>0.062500</td>\n",
+       "      <td>20038</td>\n",
+       "      <td>0.039875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A02</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Other salmonella infections</td>\n",
+       "      <td>0.048387</td>\n",
+       "      <td>20038</td>\n",
+       "      <td>0.039875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A04</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Other bacterial intestinal infections</td>\n",
+       "      <td>0.051095</td>\n",
+       "      <td>20038</td>\n",
+       "      <td>0.039875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A05</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Other bacterial foodborne intoxications, not e...</td>\n",
+       "      <td>0.050000</td>\n",
+       "      <td>20038</td>\n",
+       "      <td>0.039875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>A06</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Amebiasis</td>\n",
+       "      <td>0.024390</td>\n",
+       "      <td>20038</td>\n",
+       "      <td>0.039875</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   hod  cod  freq                                            disease  \\\n",
+       "0    1  A01     3                     Typhoid and paratyphoid fevers   \n",
+       "1    1  A02     3                        Other salmonella infections   \n",
+       "2    1  A04     7              Other bacterial intestinal infections   \n",
+       "3    1  A05     1  Other bacterial foodborne intoxications, not e...   \n",
+       "4    1  A06     2                                          Amebiasis   \n",
+       "\n",
+       "       prop  freq_all  prop_all  \n",
+       "0  0.062500     20038  0.039875  \n",
+       "1  0.048387     20038  0.039875  \n",
+       "2  0.051095     20038  0.039875  \n",
+       "3  0.050000     20038  0.039875  \n",
+       "4  0.024390     20038  0.039875  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "counts = counts.set_index('hod')\n",
+    "counts['freq_all'] = deaths.groupby('hod').size()\n",
+    "counts['prop_all'] = counts['freq_all'] / deaths.shape[0]\n",
+    "counts = counts.reset_index()\n",
+    "\n",
+    "counts.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Distance between temporal Patterns\n",
+    "\n",
+    "> Next we compute a distance between the temporal pattern of each cause of death and the overall temporal pattern. There are many ways to measure this distance, but I found a simple mean squared deviation to be revealing. We also record the sample size, the total number of deaths from that cause. To ensure that the diseases we consider are sufficiently representative we’ll only work with diseases with more than 50 total deaths (∼2/hour)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "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>disease</th>\n",
+       "      <th>n</th>\n",
+       "      <th>dist</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A02</th>\n",
+       "      <td>Other salmonella infections</td>\n",
+       "      <td>62</td>\n",
+       "      <td>0.000738</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A04</th>\n",
+       "      <td>Other bacterial intestinal infections</td>\n",
+       "      <td>137</td>\n",
+       "      <td>0.000208</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A06</th>\n",
+       "      <td>Amebiasis</td>\n",
+       "      <td>82</td>\n",
+       "      <td>0.000405</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A09</th>\n",
+       "      <td>Diarrhea and gastroenteritis of infectious origin</td>\n",
+       "      <td>3016</td>\n",
+       "      <td>0.000028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A16</th>\n",
+       "      <td>Respiratory tuberculosis, not confirmed bacter...</td>\n",
+       "      <td>1642</td>\n",
+       "      <td>0.000029</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                               disease     n      dist\n",
+       "A02                        Other salmonella infections    62  0.000738\n",
+       "A04              Other bacterial intestinal infections   137  0.000208\n",
+       "A06                                          Amebiasis    82  0.000405\n",
+       "A09  Diarrhea and gastroenteritis of infectious origin  3016  0.000028\n",
+       "A16  Respiratory tuberculosis, not confirmed bacter...  1642  0.000029"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "devi = (\n",
+    "    codes\n",
+    "    .join(\n",
+    "        deaths.groupby('cod')\n",
+    "        .count()['yod']\n",
+    "        .to_frame(),\n",
+    "        how='inner',\n",
+    "    )\n",
+    "    .join(\n",
+    "        counts.groupby('cod')\n",
+    "        .apply(lambda x: ((x['prop'] - x['prop_all']) ** 2).mean())\n",
+    "        .to_frame(),\n",
+    "        how='inner',\n",
+    "    )\n",
+    "    .rename(columns={'yod': 'n', 0: 'dist'})\n",
+    ")\n",
+    "devi = devi[(devi['n'] > 50)]\n",
+    "\n",
+    "devi.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot *dist* vs. *n*. Not a whole lot can be seen here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_, ax = plt.subplots(figsize=(4, 4))\n",
+    "ax.set_xlim(0, 50000)\n",
+    "ax.set_ylim(0, 0.006)\n",
+    "sns.regplot(\n",
+    "    x='n', y='dist', data=devi, ax=ax, fit_reg=False, scatter_kws={'s': 1}\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The relationship becomes more obvious if one plots the same points on a log-log scale."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_, ax = plt.subplots(figsize=(4, 4))\n",
+    "ax.set_xscale('log')\n",
+    "ax.set_yscale('log')\n",
+    "ax.set_xlim(30, 150000)\n",
+    "ax.set_ylim(0.00001, 0.1)\n",
+    "sns.regplot(\n",
+    "    'n', 'dist', data=devi, ax=ax, fit_reg=False, scatter_kws={'s': 1}\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> We are interested in points that have high y-values, relative to their x-neighbours. Controlling for the number of deaths, these points represent the diseases which depart the most from the overall pattern. To find these unusual points, we fit a robust linear model and plot the residuals, Figure 3. The plot shows an empty region around a residual of 1.5. So somewhat arbitrarily, we’ll select those diseases with a residual greater than 1.5."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Note that the HuberRegressor is not the exact\n",
+    "# same method as in the paper but close.\n",
+    "X = np.log(devi['n']).values[:, np.newaxis]\n",
+    "y = np.log(devi['dist']).values\n",
+    "rlm = HuberRegressor()\n",
+    "rlm.fit(X, y)\n",
+    "devi['residuals'] = y - rlm.predict(X)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot the threshold for \"unusual\" deaths, set arbitrarily at 1.5."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_, ax = plt.subplots(figsize=(4, 4))\n",
+    "ax.set_xscale('log')\n",
+    "ax.set_xlim(50, 200000)\n",
+    "ax.set_ylim(-1, 3)\n",
+    "sns.regplot(\n",
+    "    'n', 'residuals', data=devi, ax=ax, fit_reg=False, scatter_kws={'s': 1}\n",
+    ")\n",
+    "ax.hlines(1.5, 0, 200000);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> Finally, we plot the temporal course for each unusual cause, Figure 4. We split the diseases into two plots because of differences in variability. The top plot shows diseases with over 350 deaths and the bottom with under 350. The causes of death fall into three main groups: murder, drowning, and transportation related. Murder is more common at night, drowning in the afternoon, and transportation related deaths during commute times. The pale gray line in the background shows the temporal course across all diseases."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x864 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x864 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get all temporarily \"unusual\" deaths.\n",
+    "unusual = (\n",
+    "    devi.loc[(devi['residuals'] > 1.5), ['disease', 'n']]\n",
+    "    .sort_values('disease')\n",
+    ")\n",
+    "# Helper dataset for easy indexing / value retrieval.\n",
+    "plot_data = counts[['cod', 'hod', 'prop', 'prop_all']].set_index('cod')\n",
+    "# Divide the plots in two big categories.\n",
+    "for header, cond, ylim in [\n",
+    "    ('> 350 Deaths / Year', (unusual['n'] > 350), 0.125),\n",
+    "    ('< 350 Deaths / Year', (unusual['n'] <= 350), 0.3),\n",
+    "]:\n",
+    "    nrows = math.ceil(len(unusual[cond]) / 3)\n",
+    "    fig = plt.figure(figsize=(16, 12), )\n",
+    "    for i, (cod, (disease, _)) in enumerate(unusual[cond].iterrows(), 1):\n",
+    "        ax = fig.add_subplot(nrows, 3, i)\n",
+    "        ax.set_title('\\n'.join(textwrap.wrap(disease, 40)))\n",
+    "        ax.set_xlim(0, 24)\n",
+    "        ax.set_ylim(0, ylim)\n",
+    "        ax.plot(plot_data.loc[cod, 'hod'], plot_data.loc[cod, 'prop'])\n",
+    "        ax.plot(plot_data.loc[cod, 'hod'], plot_data.loc[cod, 'prop_all'])\n",
+    "        # Show only lower and left axes.\n",
+    "        if i not in (3 * nrows - 2, 3 * nrows - 1, 3 * nrows):\n",
+    "            plt.setp(ax.get_xticklabels(), visible=False)\n",
+    "        if i % 3 != 1:\n",
+    "            plt.setp(ax.get_yticklabels(), visible=False)\n",
+    "    fig.suptitle(header, fontsize=20)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Pipfile b/Pipfile
index 63ded14..e0fd7c0 100644
--- a/Pipfile
+++ b/Pipfile
@@ -8,6 +8,10 @@ pandas = "*"
 jupyter = "*"
 watermark = "*"
 savreaderwriter = "*"
+"rpy2" = "==2.8.*"
+matplotlib = "*"
+seaborn = "*"
+sklearn = "*"
 
 [dev-packages]
 black = "*"
diff --git a/Pipfile.lock b/Pipfile.lock
index d61f5d8..a47851f 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "17887e5d226dc191a6888602758b72facfac8eeb873597b5bcbce9ade25c1e66"
+            "sha256": "9fc4c60d75aac99be98f4bd18fa6b1bf507d093c96a4c639901a1d0746a83ace"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -37,6 +37,13 @@
             ],
             "version": "==2.1.4"
         },
+        "cycler": {
+            "hashes": [
+                "sha256:1d8a5ae1ff6c5cf9b93e8811e581232ad8920aeec647c37316ceac982b08cb2d",
+                "sha256:cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"
+            ],
+            "version": "==0.10.0"
+        },
         "decorator": {
             "hashes": [
                 "sha256:2c51dff8ef3c447388fe5e4453d24a2bf128d3a4c32af3fabef1f01c6851ab82",
@@ -140,12 +147,73 @@
             ],
             "version": "==4.4.0"
         },
+        "kiwisolver": {
+            "hashes": [
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@@ -290,6 +358,13 @@
             ],
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@@ -348,6 +423,13 @@
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@@ -355,6 +437,81 @@
             "index": "pypi",
             "version": "==3.4.2"
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+            "version": "==1.1.0"
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@@ -375,6 +532,13 @@
             ],
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