images/catch-user/EDA-01__Sessions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dd65288b-134d-45df-928b-5b9b9e00741c",
   "metadata": {},
   "source": [
    "# Some preliminary work"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5310829b-3c0f-46c2-a5f8-0dbced76e7ca",
   "metadata": {},
   "source": [
    "## Libraries and data loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aa66910c-b12a-40fe-970b-d52c737ef588",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5e9f1c3b-06d4-4fa1-9e44-80c0d571db32",
   "metadata": {},
   "outputs": [],
   "source": [
    "fp = \"data/dataset.json\"\n",
    "\n",
    "sessions = pd.read_json(fp)\n",
    "sessions.index.name = \"session_id\"\n",
    "\n",
    "assert sessions.index.is_unique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a3be4520-a54a-4d06-9864-bf835fdefc38",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>browser</th>\n",
       "      <th>os</th>\n",
       "      <th>locale</th>\n",
       "      <th>user_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>location</th>\n",
       "      <th>sites</th>\n",
       "      <th>time</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>session_id</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>0</th>\n",
       "      <td>Chrome</td>\n",
       "      <td>Windows 8</td>\n",
       "      <td>de-DE</td>\n",
       "      <td>164</td>\n",
       "      <td>m</td>\n",
       "      <td>Canada/Toronto</td>\n",
       "      <td>[{'site': 'lenta.ru', 'length': 296}, {'site':...</td>\n",
       "      <td>03:57:00</td>\n",
       "      <td>2016-08-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chrome</td>\n",
       "      <td>Windows 10</td>\n",
       "      <td>pt-PT</td>\n",
       "      <td>99</td>\n",
       "      <td>f</td>\n",
       "      <td>Netherlands/Amsterdam</td>\n",
       "      <td>[{'site': 'windowsupdate.com', 'length': 56}, ...</td>\n",
       "      <td>13:52:00</td>\n",
       "      <td>2016-05-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chrome</td>\n",
       "      <td>Windows 10</td>\n",
       "      <td>bg-BG</td>\n",
       "      <td>28</td>\n",
       "      <td>m</td>\n",
       "      <td>Brazil/Rio de Janeiro</td>\n",
       "      <td>[{'site': 'slack.com', 'length': 158}, {'site'...</td>\n",
       "      <td>17:40:00</td>\n",
       "      <td>2019-04-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Internet Explorer</td>\n",
       "      <td>Ubuntu</td>\n",
       "      <td>en-US</td>\n",
       "      <td>163</td>\n",
       "      <td>f</td>\n",
       "      <td>New Zealand/Auckland</td>\n",
       "      <td>[{'site': 'amazon.com', 'length': 168}, {'site...</td>\n",
       "      <td>20:23:00</td>\n",
       "      <td>2018-03-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Firefox</td>\n",
       "      <td>Debian</td>\n",
       "      <td>ro-RO</td>\n",
       "      <td>177</td>\n",
       "      <td>f</td>\n",
       "      <td>New Zealand/Auckland</td>\n",
       "      <td>[{'site': 'vk.com', 'length': 43}, {'site': 'm...</td>\n",
       "      <td>01:10:00</td>\n",
       "      <td>2018-09-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159995</th>\n",
       "      <td>Chrome</td>\n",
       "      <td>Windows 8</td>\n",
       "      <td>bg-BG</td>\n",
       "      <td>74</td>\n",
       "      <td>f</td>\n",
       "      <td>China/Shanghai</td>\n",
       "      <td>[{'site': 'amazon.com', 'length': 54}, {'site'...</td>\n",
       "      <td>22:33:00</td>\n",
       "      <td>2018-10-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159996</th>\n",
       "      <td>Internet Explorer</td>\n",
       "      <td>Ubuntu</td>\n",
       "      <td>fr-FR</td>\n",
       "      <td>163</td>\n",
       "      <td>f</td>\n",
       "      <td>New Zealand/Auckland</td>\n",
       "      <td>[{'site': 'microsoft.com', 'length': 278}, {'s...</td>\n",
       "      <td>21:29:00</td>\n",
       "      <td>2016-03-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159997</th>\n",
       "      <td>Chrome</td>\n",
       "      <td>Ubuntu</td>\n",
       "      <td>ja-JP</td>\n",
       "      <td>114</td>\n",
       "      <td>m</td>\n",
       "      <td>Russia/Moscow</td>\n",
       "      <td>[{'site': 'googleapis.com', 'length': 86}, {'s...</td>\n",
       "      <td>19:00:00</td>\n",
       "      <td>2019-03-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159998</th>\n",
       "      <td>Safari</td>\n",
       "      <td>MacOS</td>\n",
       "      <td>it-IT</td>\n",
       "      <td>48</td>\n",
       "      <td>m</td>\n",
       "      <td>Italy/Rome</td>\n",
       "      <td>[{'site': 'live.com', 'length': 145}, {'site':...</td>\n",
       "      <td>16:44:00</td>\n",
       "      <td>2016-12-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159999</th>\n",
       "      <td>Firefox</td>\n",
       "      <td>Windows 8</td>\n",
       "      <td>fr-FR</td>\n",
       "      <td>140</td>\n",
       "      <td>f</td>\n",
       "      <td>Netherlands/Amsterdam</td>\n",
       "      <td>[{'site': 'amazon.com', 'length': 89}, {'site'...</td>\n",
       "      <td>21:18:00</td>\n",
       "      <td>2016-12-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>160000 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      browser          os locale  user_id gender  \\\n",
       "session_id                                                         \n",
       "0                      Chrome   Windows 8  de-DE      164      m   \n",
       "1                      Chrome  Windows 10  pt-PT       99      f   \n",
       "2                      Chrome  Windows 10  bg-BG       28      m   \n",
       "3           Internet Explorer      Ubuntu  en-US      163      f   \n",
       "4                     Firefox      Debian  ro-RO      177      f   \n",
       "...                       ...         ...    ...      ...    ...   \n",
       "159995                 Chrome   Windows 8  bg-BG       74      f   \n",
       "159996      Internet Explorer      Ubuntu  fr-FR      163      f   \n",
       "159997                 Chrome      Ubuntu  ja-JP      114      m   \n",
       "159998                 Safari       MacOS  it-IT       48      m   \n",
       "159999                Firefox   Windows 8  fr-FR      140      f   \n",
       "\n",
       "                         location  \\\n",
       "session_id                          \n",
       "0                  Canada/Toronto   \n",
       "1           Netherlands/Amsterdam   \n",
       "2           Brazil/Rio de Janeiro   \n",
       "3            New Zealand/Auckland   \n",
       "4            New Zealand/Auckland   \n",
       "...                           ...   \n",
       "159995             China/Shanghai   \n",
       "159996       New Zealand/Auckland   \n",
       "159997              Russia/Moscow   \n",
       "159998                 Italy/Rome   \n",
       "159999      Netherlands/Amsterdam   \n",
       "\n",
       "                                                        sites      time  \\\n",
       "session_id                                                                \n",
       "0           [{'site': 'lenta.ru', 'length': 296}, {'site':...  03:57:00   \n",
       "1           [{'site': 'windowsupdate.com', 'length': 56}, ...  13:52:00   \n",
       "2           [{'site': 'slack.com', 'length': 158}, {'site'...  17:40:00   \n",
       "3           [{'site': 'amazon.com', 'length': 168}, {'site...  20:23:00   \n",
       "4           [{'site': 'vk.com', 'length': 43}, {'site': 'm...  01:10:00   \n",
       "...                                                       ...       ...   \n",
       "159995      [{'site': 'amazon.com', 'length': 54}, {'site'...  22:33:00   \n",
       "159996      [{'site': 'microsoft.com', 'length': 278}, {'s...  21:29:00   \n",
       "159997      [{'site': 'googleapis.com', 'length': 86}, {'s...  19:00:00   \n",
       "159998      [{'site': 'live.com', 'length': 145}, {'site':...  16:44:00   \n",
       "159999      [{'site': 'amazon.com', 'length': 89}, {'site'...  21:18:00   \n",
       "\n",
       "                 date  \n",
       "session_id             \n",
       "0          2016-08-14  \n",
       "1          2016-05-31  \n",
       "2          2019-04-15  \n",
       "3          2018-03-25  \n",
       "4          2018-09-08  \n",
       "...               ...  \n",
       "159995     2018-10-15  \n",
       "159996     2016-03-23  \n",
       "159997     2019-03-03  \n",
       "159998     2016-12-14  \n",
       "159999     2016-12-04  \n",
       "\n",
       "[160000 rows x 9 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15b96053-1da2-407c-ab93-3528ae2c0c7c",
   "metadata": {},
   "source": [
    "## Extract the site visits to a new dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "78f26c07-fb10-4cd3-ae64-7a81ad1ef709",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1db7d8466e654d4aa0dcba9bd39f8326",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/160000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>session_id</th>\n",
       "      <th>site</th>\n",
       "      <th>visit_duration</th>\n",
       "      <th>is_joe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>lenta.ru</td>\n",
       "      <td>296</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>lenta.ru</td>\n",
       "      <td>69</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>vk.com</td>\n",
       "      <td>94</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>lenta.ru</td>\n",
       "      <td>129</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>wikipedia.org</td>\n",
       "      <td>70</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065868</th>\n",
       "      <td>159999</td>\n",
       "      <td>fisioterapia-online.com</td>\n",
       "      <td>143</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065869</th>\n",
       "      <td>159999</td>\n",
       "      <td>ybassets.com</td>\n",
       "      <td>124</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065870</th>\n",
       "      <td>159999</td>\n",
       "      <td>googleadservices.com</td>\n",
       "      <td>83</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065871</th>\n",
       "      <td>159999</td>\n",
       "      <td>ntvplus.tv</td>\n",
       "      <td>68</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065872</th>\n",
       "      <td>159999</td>\n",
       "      <td>facebook.net</td>\n",
       "      <td>105</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2065873 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         session_id                     site  visit_duration  is_joe\n",
       "0                 0                 lenta.ru             296   False\n",
       "1                 0                 lenta.ru              69   False\n",
       "2                 0                   vk.com              94   False\n",
       "3                 0                 lenta.ru             129   False\n",
       "4                 0            wikipedia.org              70   False\n",
       "...             ...                      ...             ...     ...\n",
       "2065868      159999  fisioterapia-online.com             143   False\n",
       "2065869      159999             ybassets.com             124   False\n",
       "2065870      159999     googleadservices.com              83   False\n",
       "2065871      159999               ntvplus.tv              68   False\n",
       "2065872      159999             facebook.net             105   False\n",
       "\n",
       "[2065873 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "site_visits = []\n",
    "\n",
    "for session_id, session in tqdm(sessions.iterrows(), total=len(sessions)):\n",
    "    for site in session[\"sites\"]:\n",
    "        site_visits.append({\n",
    "            \"session_id\": session_id,\n",
    "            \"site\": site[\"site\"],\n",
    "            \"visit_duration\": site[\"length\"],\n",
    "            \"is_joe\": session[\"user_id\"] == 0,\n",
    "        })\n",
    "        \n",
    "site_visits = pd.DataFrame(site_visits)\n",
    "site_visits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "00886080-9c29-408f-b95e-44df61d91059",
   "metadata": {},
   "outputs": [],
   "source": [
    "from os.path import isfile\n",
    "\n",
    "fp = \"results/training.site_visits.csv.gz\"\n",
    "\n",
    "if not isfile(fp):\n",
    "    site_visits.to_csv(fp, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79f24332-7c62-439e-bb4b-7c72a72cc9f9",
   "metadata": {},
   "source": [
    "## Some parsing on the `sessions` dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7024abb6-5aa7-43a0-af07-eba81cfc3786",
   "metadata": {},
   "outputs": [],
   "source": [
    "from operator import itemgetter\n",
    "\n",
    "time_parts = sessions[\"time\"].str.split(\":\")\n",
    "\n",
    "sessions[\"hour\"] = time_parts.map(itemgetter(0)).astype(int)\n",
    "hour_fraction = time_parts.map(itemgetter(1)).astype(int)/60\n",
    "sessions[\"hour_frac\"] = sessions[\"hour\"] + hour_fraction\n",
    "sessions[\"hour_frac\"] = sessions[\"hour\"].round(1)\n",
    "\n",
    "sessions[\"n_sites\"] = sessions[\"sites\"].map(len)\n",
    "\n",
    "sessions[\"year\"] = sessions[\"date\"].dt.year\n",
    "sessions[\"month\"] = sessions[\"date\"].dt.month\n",
    "sessions[\"day\"] = sessions[\"date\"].dt.day\n",
    "sessions[\"weekday\"] = sessions[\"date\"].dt.strftime(\"%A\")\n",
    "\n",
    "total_session_times = site_visits.groupby(\"session_id\")[\"visit_duration\"].sum()\n",
    "sessions[\"duration\"] = sessions.index.map(total_session_times)\n",
    "sessions[\"duration_min\"] = (sessions[\"duration\"]/60).astype(int)\n",
    "\n",
    "sessions[\"is_joe\"] = sessions[\"user_id\"] == 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b26e65c7-d9a9-4d25-8e4f-195059e15fc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "fp = \"results/training.sessions.csv.gz\"\n",
    "\n",
    "sessions.to_csv(fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1416f36f-be43-4bf5-ae85-fea6092459bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "joe_sessions = sessions.query(\"is_joe\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb342f22-0edc-4f0f-8e11-8443a7b2e25f",
   "metadata": {},
   "source": [
    "# Exploratory data analysis on the training dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "537b90d4-401a-4d67-a574-e3f69833d5ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"ticks\")\n",
    "sns.set_context(\"notebook\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bdde2c1-f41a-46e8-bfcf-ef6fe4957924",
   "metadata": {},
   "source": [
    "## OS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "baaee316-940a-4e0d-a40d-052be70a50f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display, HTML\n",
    "\n",
    "def display_comparison(data, varname, x_order=None):\n",
    "    # *data* must have an 'is_joe\" boolean column\n",
    "    joe_data = data.query(\"is_joe\")\n",
    "    \n",
    "\n",
    "    s1 = (100 * data[varname].value_counts(normalize=True)).round(1)\n",
    "    s2 = (100 * joe_data[varname].value_counts(normalize=True)).round(1)\n",
    "\n",
    "    s1.index.name = varname\n",
    "    s2.index.name = varname\n",
    "    s1.name = \"All sessions (%)\"\n",
    "    s2.name = \"Joe sessions (%)\"\n",
    "\n",
    "    comparison = pd.concat([s1, s2], axis=1).fillna(\"\")\n",
    "    if x_order:\n",
    "        comparison = comparison.loc[x_order]\n",
    "    display(comparison)    \n",
    "\n",
    "def make_histograms(data, varname, x_order=None, show_comparison=True):\n",
    "    # *data* must have an 'is_joe\" boolean column\n",
    "    \n",
    "    if show_comparison:\n",
    "        display_comparison(data, varname, x_order)\n",
    "    \n",
    "    fig, ax = plt.subplots(1, 1, figsize=(6, 4))\n",
    "    \n",
    "    common_opts = dict(x=varname, stat=\"percent\", ax=ax)\n",
    "    \n",
    "    if x_order:\n",
    "        new_order = data[varname].map(lambda x: x_order.index(x)).sort_values().index\n",
    "        data = data.loc[new_order]\n",
    "\n",
    "    joe_data = data.query(\"is_joe\")\n",
    "    \n",
    "    sns.histplot(\n",
    "        data=joe_data,\n",
    "        color=\"Orange\",\n",
    "        label=\"Joe\",\n",
    "        **common_opts\n",
    "    )\n",
    "    \n",
    "    sns.histplot(\n",
    "        data=data,\n",
    "        label=\"All users\",\n",
    "        alpha=0.5,\n",
    "        **common_opts\n",
    "    )\n",
    "\n",
    "    ax.set_ylabel(\"Sessions (%)\")\n",
    "    ax.legend()\n",
    "    sns.despine(ax=ax)\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "98bb213c-c981-4931-86d7-cb1554edb37e",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>os</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Windows 10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>49.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Windows 8</th>\n",
       "      <td>27.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MacOS</th>\n",
       "      <td>17.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Windows 7</th>\n",
       "      <td>8.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ubuntu</th>\n",
       "      <td>7.3</td>\n",
       "      <td>50.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debian</th>\n",
       "      <td>5.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            All sessions (%) Joe sessions (%)\n",
       "os                                           \n",
       "Windows 10              34.0             49.6\n",
       "Windows 8               27.5                 \n",
       "MacOS                   17.7                 \n",
       "Windows 7                8.0                 \n",
       "Ubuntu                   7.3             50.4\n",
       "Debian                   5.5                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = make_histograms(sessions, \"os\")\n",
    "_ = plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a05cb6c-5484-44ee-bcd0-7b5700966714",
   "metadata": {},
   "source": [
    "- Joe uses Ubuntu and Win10 only, in equal proportions.\n",
    "- Only ~7% of user sessions are from Ubuntu, so this sets Joes appart in some cases."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a5ed17d-bb56-43a4-ae7a-531a2f92a86a",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Browser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e11694af-64b3-4ae9-90c3-b13c80dc576c",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>browser</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Chrome</th>\n",
       "      <td>52.2</td>\n",
       "      <td>49.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Firefox</th>\n",
       "      <td>21.5</td>\n",
       "      <td>50.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Safari</th>\n",
       "      <td>17.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Internet Explorer</th>\n",
       "      <td>8.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   All sessions (%) Joe sessions (%)\n",
       "browser                                             \n",
       "Chrome                         52.2             49.8\n",
       "Firefox                        21.5             50.2\n",
       "Safari                         17.7                 \n",
       "Internet Explorer               8.5                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = make_histograms(sessions, \"browser\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dad91d02-358b-4a6e-806f-56c27d0f04d0",
   "metadata": {},
   "source": [
    "- Joe uses Firefox and Chrome in equal proportions.\n",
    "- Only 20% of the sessions are in Firefox."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59ae4885-32ce-4557-bce9-9855696a3664",
   "metadata": {},
   "source": [
    "## OS * Browser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "92731c77-d403-41d6-8258-b8902f601a26",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>os_browser</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Win10 + Chrome</th>\n",
       "      <td>22.5</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MacOS + Safari</th>\n",
       "      <td>17.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win8 + Chrome</th>\n",
       "      <td>16.1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win10 + Firefox</th>\n",
       "      <td>8.5</td>\n",
       "      <td>25.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win8 + Firefox</th>\n",
       "      <td>7.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win7 + Chrome</th>\n",
       "      <td>5.3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ubuntu + Chrome</th>\n",
       "      <td>5.2</td>\n",
       "      <td>25.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win8 + IE</th>\n",
       "      <td>3.6</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debian + Chrome</th>\n",
       "      <td>3.1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win10 + IE</th>\n",
       "      <td>3.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win7 + Firefox</th>\n",
       "      <td>2.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ubuntu + Firefox</th>\n",
       "      <td>1.7</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debian + Firefox</th>\n",
       "      <td>1.6</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debian + IE</th>\n",
       "      <td>0.8</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Win7 + IE</th>\n",
       "      <td>0.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ubuntu + IE</th>\n",
       "      <td>0.4</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  All sessions (%) Joe sessions (%)\n",
       "os_browser                                         \n",
       "Win10 + Chrome                22.5             24.4\n",
       "MacOS + Safari                17.7                 \n",
       "Win8 + Chrome                 16.1                 \n",
       "Win10 + Firefox                8.5             25.2\n",
       "Win8 + Firefox                 7.7                 \n",
       "Win7 + Chrome                  5.3                 \n",
       "Ubuntu + Chrome                5.2             25.4\n",
       "Win8 + IE                      3.6                 \n",
       "Debian + Chrome                3.1                 \n",
       "Win10 + IE                     3.0                 \n",
       "Win7 + Firefox                 2.0                 \n",
       "Ubuntu + Firefox               1.7             25.0\n",
       "Debian + Firefox               1.6                 \n",
       "Debian + IE                    0.8                 \n",
       "Win7 + IE                      0.7                 \n",
       "Ubuntu + IE                    0.4                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def short_name(name):\n",
    "    return (\n",
    "        name\n",
    "        .replace(\"Windows \", \"Win\")\n",
    "        .replace(\"Internet Explorer\", \"IE\")\n",
    "    )\n",
    "\n",
    "sessions[\"os_browser\"] = \\\n",
    "    (sessions[\"os\"] + \" + \" + sessions[\"browser\"]).map(short_name)\n",
    "\n",
    "ax = make_histograms(sessions.sort_values(by=\"os_browser\"), \"os_browser\")\n",
    "_ = plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "028ca43d-44f8-4ac1-bf70-6ce66c204e3e",
   "metadata": {},
   "source": [
    "- Joe uses both Firefox and Chrome in both Win10 and Ubuntu in almost equal proportions\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e415575-f0b4-41a3-bc3e-615bb70a1b0d",
   "metadata": {},
   "source": [
    "## Locale / location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7cb8780d-8dc4-476a-b88b-b14da0a7d0ea",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>locale</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ru-RU</th>\n",
       "      <td>10.3</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bg-BG</th>\n",
       "      <td>9.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nl-NL</th>\n",
       "      <td>6.8</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de-DE</th>\n",
       "      <td>6.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>en-SG</th>\n",
       "      <td>6.3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ja-JP</th>\n",
       "      <td>6.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ro-RO</th>\n",
       "      <td>5.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>en-CA</th>\n",
       "      <td>5.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fr-FR</th>\n",
       "      <td>5.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>en-NZ</th>\n",
       "      <td>4.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pt-PT</th>\n",
       "      <td>4.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pt-BR</th>\n",
       "      <td>4.6</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>en-GB</th>\n",
       "      <td>4.2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>it-IT</th>\n",
       "      <td>4.2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>es-MX</th>\n",
       "      <td>4.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>en-US</th>\n",
       "      <td>4.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pl-PL</th>\n",
       "      <td>4.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uk-UA</th>\n",
       "      <td>3.2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>en-AU</th>\n",
       "      <td>1.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        All sessions (%) Joe sessions (%)\n",
       "locale                                   \n",
       "ru-RU               10.3            100.0\n",
       "bg-BG                9.0                 \n",
       "nl-NL                6.8                 \n",
       "de-DE                6.5                 \n",
       "en-SG                6.3                 \n",
       "ja-JP                6.0                 \n",
       "ro-RO                5.5                 \n",
       "en-CA                5.5                 \n",
       "fr-FR                5.0                 \n",
       "en-NZ                4.7                 \n",
       "pt-PT                4.7                 \n",
       "pt-BR                4.6                 \n",
       "en-GB                4.2                 \n",
       "it-IT                4.2                 \n",
       "es-MX                4.0                 \n",
       "en-US                4.0                 \n",
       "pl-PL                4.0                 \n",
       "uk-UA                3.2                 \n",
       "en-AU                1.5                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = make_histograms(sessions, \"locale\")\n",
    "_ = plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eb60e4ac-4889-4856-83b8-4966ff60a6b0",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Russia/Moscow</th>\n",
       "      <td>8.9</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA/New York</th>\n",
       "      <td>7.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand/Auckland</th>\n",
       "      <td>7.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore/Singapore</th>\n",
       "      <td>6.2</td>\n",
       "      <td>15.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA/Miami</th>\n",
       "      <td>6.0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA/Chicago</th>\n",
       "      <td>5.7</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China/Shanghai</th>\n",
       "      <td>5.5</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan/Tokyo</th>\n",
       "      <td>5.3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France/Paris</th>\n",
       "      <td>5.3</td>\n",
       "      <td>39.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy/Rome</th>\n",
       "      <td>4.9</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malaysia/Kuala Lumpur</th>\n",
       "      <td>4.8</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands/Amsterdam</th>\n",
       "      <td>4.6</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain/Madrid</th>\n",
       "      <td>4.2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UK/London</th>\n",
       "      <td>4.1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany/Berlin</th>\n",
       "      <td>3.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India/Delhi</th>\n",
       "      <td>3.7</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA/San Francisco</th>\n",
       "      <td>3.6</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada/Toronto</th>\n",
       "      <td>3.5</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil/Rio de Janeiro</th>\n",
       "      <td>2.3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia/Sydney</th>\n",
       "      <td>1.8</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada/Vancouver</th>\n",
       "      <td>1.6</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       All sessions (%) Joe sessions (%)\n",
       "location                                                \n",
       "Russia/Moscow                       8.9                 \n",
       "USA/New York                        7.5                 \n",
       "New Zealand/Auckland                7.0                 \n",
       "Singapore/Singapore                 6.2             15.1\n",
       "USA/Miami                           6.0                 \n",
       "USA/Chicago                         5.7             23.0\n",
       "China/Shanghai                      5.5                 \n",
       "Japan/Tokyo                         5.3                 \n",
       "France/Paris                        5.3             39.6\n",
       "Italy/Rome                          4.9                 \n",
       "Malaysia/Kuala Lumpur               4.8                 \n",
       "Netherlands/Amsterdam               4.6                 \n",
       "Spain/Madrid                        4.2                 \n",
       "UK/London                           4.1                 \n",
       "Germany/Berlin                      3.7                 \n",
       "India/Delhi                         3.7                 \n",
       "USA/San Francisco                   3.6                 \n",
       "Canada/Toronto                      3.5             22.2\n",
       "Brazil/Rio de Janeiro               2.3                 \n",
       "Australia/Sydney                    1.8                 \n",
       "Canada/Vancouver                    1.6                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = make_histograms(sessions, \"location\")\n",
    "_ = plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a538c5ff-1dcd-4ba4-b3ad-fbd68a05d98f",
   "metadata": {},
   "source": [
    "- Users might have multiple locales. Joe always uses the most common one: `ru-RU`\n",
    "- Joe browses from Paris 40% of the time, but also from Chicago, Toronto and Singapore."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "116a4745-3995-4ce9-a145-25a6506ef1b9",
   "metadata": {},
   "source": [
    "## Gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f2f72eb7-0d1b-4e99-b01c-2f138f7ea998",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "m    64.0\n",
       "f    36.0\n",
       "Name: gender, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "100 * sessions[\"gender\"].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d9473b21-bcec-4d12-a965-170bd23e4257",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "m    800\n",
       "Name: gender, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joe_sessions[\"gender\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "731cf674-79d1-4ae0-a9fa-025ca43627f7",
   "metadata": {},
   "source": [
    "- Most users are male, like Joe."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fab39e1e-02f3-48a9-b9a0-f23ee265d07e",
   "metadata": {},
   "source": [
    "## Session dates (year, month, day, weekday)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cd0f44b5-76b3-46e7-8e00-1f7d3fceeed2",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_cat</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>29.4</td>\n",
       "      <td>30.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>30.5</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>30.5</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>9.7</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          All sessions (%)  Joe sessions (%)\n",
       "year_cat                                    \n",
       "2016                  29.4              30.1\n",
       "2017                  30.5              30.0\n",
       "2018                  30.5              30.0\n",
       "2019                   9.7               9.9"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sessions[\"year_cat\"] = sessions[\"year\"].astype(str)\n",
    "\n",
    "ax = make_histograms(\n",
    "    sessions,\n",
    "    \"year_cat\",\n",
    "    x_order=[\"2016\", \"2017\", \"2018\", \"2019\"]\n",
    ")\n",
    "\n",
    "_ = ax.set_xlabel(\"Year\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "760a0005-ec12-43bf-931f-feb6f5bd4096",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_cat</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.4</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.3</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.4</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.1</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.5</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7.8</td>\n",
       "      <td>7.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7.7</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7.5</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7.8</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>7.5</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>7.7</td>\n",
       "      <td>7.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           All sessions (%)  Joe sessions (%)\n",
       "month_cat                                    \n",
       "1                       9.2               9.1\n",
       "2                       9.4               8.9\n",
       "3                      10.3              10.6\n",
       "4                       9.4               9.1\n",
       "5                       8.1               7.9\n",
       "6                       7.5               7.6\n",
       "7                       7.8               7.8\n",
       "8                       7.7               8.1\n",
       "9                       7.5               7.5\n",
       "10                      7.8               8.0\n",
       "11                      7.5               7.6\n",
       "12                      7.7               7.8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sessions[\"month_cat\"] = sessions[\"month\"].astype(str)\n",
    "\n",
    "ax = make_histograms(\n",
    "    sessions,\n",
    "    \"month_cat\",\n",
    "    x_order=[str(m) for m in np.arange(1, 13)]\n",
    ")\n",
    "_ = ax.set_xlabel(\"Month\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "91fc5428-4ffb-48bb-9a8e-1d8cacc7268e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sessions[\"day_cat\"] = sessions[\"day\"].astype(str)\n",
    "\n",
    "ax = make_histograms(\n",
    "    sessions,\n",
    "    \"day_cat\",\n",
    "    x_order=[str(d) for d in np.arange(1, 32)],\n",
    "    show_comparison=False,\n",
    ")\n",
    "\n",
    "ax.set_xlabel(\"Day of the month\", labelpad=10)\n",
    "_ = plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ff4d89e2-8624-4e2c-b19e-92a2e60875cf",
   "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>All sessions (%)</th>\n",
       "      <th>Joe sessions (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weekday</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Monday</th>\n",
       "      <td>14.3</td>\n",
       "      <td>14.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tuesday</th>\n",
       "      <td>14.3</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wednesday</th>\n",
       "      <td>14.2</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thursday</th>\n",
       "      <td>14.3</td>\n",
       "      <td>14.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Friday</th>\n",
       "      <td>14.3</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saturday</th>\n",
       "      <td>14.3</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sunday</th>\n",
       "      <td>14.3</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           All sessions (%)  Joe sessions (%)\n",
       "weekday                                      \n",
       "Monday                 14.3              14.9\n",
       "Tuesday                14.3              15.0\n",
       "Wednesday              14.2              13.8\n",
       "Thursday               14.3              14.8\n",
       "Friday                 14.3              13.4\n",
       "Saturday               14.3              14.5\n",
       "Sunday                 14.3              13.8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import calendar\n",
    "\n",
    "ax = make_histograms(\n",
    "    sessions,\n",
    "    \"weekday\",\n",
    "    x_order=list(calendar.day_name)\n",
    ")\n",
    "_ = plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e0ae782-56fa-48c4-b75a-a563302299a5",
   "metadata": {},
   "source": [
    "- Session years, months, days and weekdays look the same for Joe as for other users."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00712b9d-28f3-4a58-97c7-1ae3869a1e25",
   "metadata": {},
   "source": [
    "## Session hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fca59e38-8066-45a1-bb8e-de7867cd4366",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"ticks\")\n",
    "\n",
    "bins = np.arange(0, 25)\n",
    "\n",
    "ax = sns.histplot(\n",
    "    data=sessions,\n",
    "    x=\"hour\",\n",
    "    stat=\"percent\",\n",
    "    label=\"All users\",\n",
    "    bins=bins,\n",
    ")\n",
    "\n",
    "sns.histplot(\n",
    "    data=joe_sessions,\n",
    "    x=\"hour\",\n",
    "    stat=\"percent\",\n",
    "    label=\"Joe\",\n",
    "    color=\"Orange\",\n",
    "    alpha=0.5,\n",
    "    bins=bins,\n",
    ")\n",
    "\n",
    "ax.legend(loc=\"upper right\")\n",
    "\n",
    "ax.set_xticks(np.arange(24) + 0.5)\n",
    "ax.set_xticklabels(np.arange(24))\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "for hour in [0, 6, 12, 18]:\n",
    "    ax.axvline(hour, color=\"k\")\n",
    "    \n",
    "offset = 0.5\n",
    "ax.text(0 + offset, 1, \"night\", ha=\"left\")\n",
    "ax.text(6 + offset, 1, \"morning\", ha=\"left\")\n",
    "ax.text(12 + offset, 1, \"afternoon\", ha=\"left\")\n",
    "ax.text(18 + offset, 1, \"evening\", ha=\"left\")\n",
    "\n",
    "sns.despine(left=True)\n",
    "_ = ax.set_xlabel(\"Session hour\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8522efb3-3823-4a91-9aa7-3bf17ae8f327",
   "metadata": {},
   "source": [
    "- Joe might start a session at any moment of the day: night/morning/afternoon/evening\n",
    "- Joe never starts a session at some particular hours: 6 to 9, 12, 15, 21 to 0. This could be informative."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0505c71a-26f3-4a42-953f-6dee71cd2fc5",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Session duration in minutes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5e84ce0e-dfcd-4a83-905f-432fd032bbc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "min     0\n",
       "max    64\n",
       "Name: duration_min, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions[\"duration_min\"].agg([min, max])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "94b717f0-98ca-43e2-b60b-9b7965ea63e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(1, 70, step=2.5)\n",
    "\n",
    "ax = sns.histplot(\n",
    "    data=sessions,\n",
    "    x=\"duration_min\",\n",
    "    stat=\"percent\",\n",
    "    label=\"All users\",\n",
    "    bins=bins,\n",
    ")\n",
    "\n",
    "sns.histplot(\n",
    "    data=joe_sessions,\n",
    "    x=\"duration_min\",\n",
    "    stat=\"percent\",\n",
    "    label=\"Joe\",\n",
    "    color=\"Orange\",\n",
    "    alpha=0.5,\n",
    "    bins=bins,\n",
    ")\n",
    "\n",
    "ax.legend()\n",
    "ax.set_xticks(np.arange(0, 70, step=10))\n",
    "sns.despine(ax=ax)\n",
    "\n",
    "_ = ax.set_xlabel(\"Session duration (min)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "734aa20e-37a1-40fa-896a-323ea85211b7",
   "metadata": {},
   "source": [
    "- Joe sessions' duration are distributed like other users: sessions last around 30 minutes with some variation, almost always between 10 and 50 minutes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e6db385-afbe-4e2f-ac1f-c92eef62d27f",
   "metadata": {},
   "source": [
    "## Number of sites visited in a session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6060a2be-66c6-4d5a-bdcd-e6c2a0e180fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "min     1\n",
       "max    15\n",
       "Name: n_sites, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions[\"n_sites\"].agg([min, max])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ad61c0f8-5acd-4dcd-8c26-a86744b5b7f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"ticks\")\n",
    "\n",
    "bins = np.arange(1, 16)\n",
    "\n",
    "ax = sns.histplot(\n",
    "    data=sessions,\n",
    "    x=\"n_sites\",\n",
    "    stat=\"percent\",\n",
    "    label=\"All users\",\n",
    "    bins=bins,\n",
    ")\n",
    "\n",
    "sns.histplot(\n",
    "    data=joe_sessions,\n",
    "    x=\"n_sites\",\n",
    "    stat=\"percent\",\n",
    "    label=\"Joe\",\n",
    "    color=\"Orange\",\n",
    "    alpha=0.5,\n",
    "    bins=bins,\n",
    ")\n",
    "\n",
    "ax.set_xticks(np.arange(1, 16) - 0.5)\n",
    "ax.set_xticklabels(np.arange(1, 16))\n",
    "ax.legend()\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "\n",
    "_ = ax.set_xlabel(\"Number of sites visited\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5fd1494-e5c6-4b51-87d3-6158c7564f5a",
   "metadata": {},
   "source": [
    "- Joe has the same distribution of number of sites visited than the average user."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dbed1a6-ec37-49ca-a106-c9c3680ab343",
   "metadata": {},
   "source": [
    "## Users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "89eea92e-b5ea-4024-98c6-7311846da1e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 200 unique users\n"
     ]
    }
   ],
   "source": [
    "n_users = len(sessions[\"user_id\"].unique())\n",
    "print(f\"There are {n_users} unique users\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f54f95b-e202-4506-aea4-7c04687d2f2c",
   "metadata": {},
   "source": [
    "All users have 800 sessions recorded:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cdcd2033-1440-4f41-a643-067a7e39b2b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      800\n",
       "1      800\n",
       "2      800\n",
       "3      800\n",
       "4      800\n",
       "      ... \n",
       "195    800\n",
       "196    800\n",
       "197    800\n",
       "198    800\n",
       "199    800\n",
       "Name: user_id, Length: 200, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions[\"user_id\"].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "81b4a4aa-4905-4250-97ce-75177144c097",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(sessions[\"user_id\"].value_counts() == 800).all()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}