research/web_routineness/release/01_Basic_Statistics.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from web_tracking.pre_processing.raw_data_processor import RawDataProcessor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-warning\">\n",
    "<b>Warning:</b> Update the data directory path before running. \n",
    "</div>\n",
    "\n",
    "We tested this code using the data available at https://zenodo.org/record/4383164"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_directory = \"../../../../../../data/web_routineness_release_clean/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "users = pd.read_csv(data_directory + '/raw/users.csv', dtype={'panelist_id': int})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Web browsing behavior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "processed = pd.read_csv(data_directory + \"/pre_processed/browsing_with_gap.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "List of users having enough data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_users = pd.read_csv(data_directory + '/pre_processed/selected_users.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Number of individuals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2148"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(users)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1455"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(selected_users)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Number of total website visits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9151243"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(processed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8910779"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_users_visits = selected_users.merge(processed, left_on='user', right_on='panelist_id')\n",
    "len(selected_users_visits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Number of unique domains "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49918"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(processed.top_level_domain.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>prev_id</th>\n",
       "      <th>panelist_id</th>\n",
       "      <th>used_at</th>\n",
       "      <th>left_at</th>\n",
       "      <th>active_seconds</th>\n",
       "      <th>gap_seconds</th>\n",
       "      <th>top_level_domain</th>\n",
       "      <th>category_names_top</th>\n",
       "      <th>sub_level_domain</th>\n",
       "      <th>subdomain</th>\n",
       "      <th>category_names_sub</th>\n",
       "      <th>domain</th>\n",
       "      <th>category_names</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3193009</th>\n",
       "      <td>1010795924</td>\n",
       "      <td>1010795920</td>\n",
       "      <td>754</td>\n",
       "      <td>2018-10-01 08:58:20</td>\n",
       "      <td>2018-10-01 08:58:21</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>kurzurlaub.de</td>\n",
       "      <td>business</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>kurzurlaub.de</td>\n",
       "      <td>business</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id     prev_id  panelist_id              used_at  \\\n",
       "3193009  1010795924  1010795920          754  2018-10-01 08:58:20   \n",
       "\n",
       "                     left_at  active_seconds  gap_seconds top_level_domain  \\\n",
       "3193009  2018-10-01 08:58:21               1            1    kurzurlaub.de   \n",
       "\n",
       "        category_names_top sub_level_domain subdomain category_names_sub  \\\n",
       "3193009           business              NaN       NaN                NaN   \n",
       "\n",
       "                domain category_names  \n",
       "3193009  kurzurlaub.de       business  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "processed.sample()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48721"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(selected_users_visits.top_level_domain.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparing the top domains in our sample with Alexa\n",
    "\n",
    "First, let's analyze our sample. How similar is the top domains in the sample with the top domains given by Alexa? \n",
    "\n",
    "- According to Alexa: \"A website has a Reach score of 5,000, this means that 5,000 people out of a sample of 1 million\"[¹](https://www.klipfolio.com/metrics/marketing/reach-per-million-users), and they calculate it by using `Count Unique(People who saw your content per Day per Million Users)`\n",
    "- So, we computed number of unique visitors per domain to compare our dataset with Alexa.\n",
    "- Section 4 in the article."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_domains = processed.top_level_domain.value_counts(normalize=True).to_frame() \\\n",
    "                    .reset_index().rename(columns={'index': 'domain', 'top_level_domain': 'visits'}) \\\n",
    "                    .assign(rank = lambda df: range(1, len(df)+1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "alexa_top_5K = pd.read_csv(data_directory + '/raw/alexa_GER_top5000.csv').drop(columns=['X1.nrow.file.Results.Result.Alexa.TopSites.Country.Sites.Site.'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matching the domains "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3484 / 5000'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_domains_5K  = top_domains.merge(alexa_top_5K, left_on='domain', right_on='url')\n",
    "\n",
    "f'{len(top_domains_5K)} / 5000'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pearson correlation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>visits</th>\n",
       "      <th>PageViews.PerMillion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>visits</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.780473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PageViews.PerMillion</th>\n",
       "      <td>0.780473</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        visits  PageViews.PerMillion\n",
       "visits                1.000000              0.780473\n",
       "PageViews.PerMillion  0.780473              1.000000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_domains_5K[['visits', 'PageViews.PerMillion']].corr(method='pearson')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Demographic statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Without filtering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gender distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = users[~users.gender.isna()].gender.apply(lambda x: str(x).title()).value_counts(normalize=True).to_frame().applymap(lambda x: round(x * 100, 2))\n",
    "\n",
    "ax = temp.plot.bar(legend=False, title='Gender Distribution', ylim=(0, 55), xlim=(0, 100))\n",
    "ax.set_ylabel(\"%\")\n",
    "ax.tick_params(axis='x', labelrotation=0)\n",
    "ax.grid(color='lightgrey', linestyle='--', linewidth=.75, alpha=.3)\n",
    "ax.set_axisbelow(True)\n",
    "\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f'{p.get_height():.2f}%', (p.get_x() + p.get_width() / 4., p.get_height() + .5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Age distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 277,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = users[~users.age_recode.isna()].age_recode.apply(str).value_counts(normalize=True).to_frame().applymap(lambda x: x * 100).rename(index={'(24,34]': '[25,34]', '(34,44]': '[35,44]', '(44,54]': '[45,54]', '(54,64]': '[55,64]', '(64,80]': '[65,80]', 'nan': 'n/a'}).sort_index()\n",
    "ax = temp.plot.bar(legend=False, title='Age  Distribution', color='darkturquoise', ylim=(0, 25))\n",
    "ax.set_ylabel(\"%\")\n",
    "ax.set_xlabel(\"Age Groups\")\n",
    "ax.grid(color='lightgrey', linestyle='--', linewidth=.75, alpha=.3)\n",
    "ax.set_axisbelow(True)\n",
    "ax.tick_params(axis='x', labelrotation=0)\n",
    "\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f'{p.get_height():.2f}%', (p.get_x() + p.get_width() / 4., p.get_height() + .5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "users_filtered = users[users.panelist_id.isin(selected_users['user'].values)].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Number of users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1455"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(users_filtered)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gender distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = users_filtered[~users_filtered.gender.isna()].gender.apply(lambda x: str(x).title()).value_counts(normalize=True).to_frame().applymap(lambda x: round(x * 100, 2))\n",
    "ax = temp.plot.bar(legend=False, title='Gender Distribution', ylim=(0, 55), xlim=(0, 100))\n",
    "ax.set_ylabel(\"%\")\n",
    "ax.tick_params(axis='x', labelrotation=0)\n",
    "ax.grid(color='lightgrey', linestyle='--', linewidth=.75, alpha=.3)\n",
    "ax.set_axisbelow(True)\n",
    "\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f'{p.get_height():.2f}%', (p.get_x() + p.get_width() / 4., p.get_height() + .5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Age distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 277,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = users_filtered[~users_filtered.age_recode.isna()].age_recode.apply(str).value_counts(normalize=True).to_frame().applymap(lambda x: x * 100).rename(index={'(24,34]': '[25,34]', '(34,44]': '[35,44]', '(44,54]': '[45,54]', '(54,64]': '[55,64]', '(64,80]': '[65,80]', 'nan': 'n/a'}).sort_index()\n",
    "ax = temp.plot.bar(legend=False, title='Age  Distribution', color='darkturquoise', ylim=(0, 27))\n",
    "ax.set_ylabel(\"%\")\n",
    "ax.set_xlabel(\"Age Groups\")\n",
    "ax.grid(color='lightgrey', linestyle='--', linewidth=.75, alpha=.3)\n",
    "ax.set_axisbelow(True)\n",
    "ax.tick_params(axis='x', labelrotation=0)\n",
    "\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f'{p.get_height():.2f}%', (p.get_x() + p.get_width() / 4., p.get_height() + .5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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