eda-fe-5months.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SciPy version: 1.5.2\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime as dt\n",
    "import os\n",
    "from constants import (DATASET_5M, USECOLS, EXPORT_DIR,T, DATA_DIR,\n",
    "                       ALL_DATA_PATH, TRAIN_DATA_PATH, VAL_DATA_PATH, TEST_DATA_PATH, VAL_THRESHOLD, TEST_THRESHOLD)\n",
    "import scipy\n",
    "print(f\"SciPy version: {scipy.__version__}\")\n",
    "from collections import OrderedDict\n",
    "import scipy.sparse as sp\n",
    "import time\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "FONT_SIZE = 24\n",
    "plt.rcParams['figure.figsize'] = (20,8)\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.rcParams['font.size'] = FONT_SIZE\n",
    "plt.rcParams['legend.fontsize'] = FONT_SIZE\n",
    "plt.rcParams['xtick.labelsize'] = FONT_SIZE\n",
    "plt.rcParams['ytick.labelsize'] = FONT_SIZE\n",
    "%config InlineBackend.figure_format ='retina'\n",
    "# %matplotlib widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "EVENT_THRESHOLD = 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 4min 28s\n"
     ]
    },
    {
     "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>event_time</th>\n",
       "      <th>event_type</th>\n",
       "      <th>product_id</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-01 00:00:00+00:00</td>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5712790</td>\n",
       "      <td>576802932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-12-01 00:00:00+00:00</td>\n",
       "      <td>view</td>\n",
       "      <td>5764655</td>\n",
       "      <td>412120092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-12-01 00:00:02+00:00</td>\n",
       "      <td>cart</td>\n",
       "      <td>4958</td>\n",
       "      <td>494077766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-12-01 00:00:05+00:00</td>\n",
       "      <td>view</td>\n",
       "      <td>5848413</td>\n",
       "      <td>348405118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-12-01 00:00:07+00:00</td>\n",
       "      <td>view</td>\n",
       "      <td>5824148</td>\n",
       "      <td>576005683</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>4264747</th>\n",
       "      <td>2020-01-31 23:59:52+00:00</td>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5886774</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264748</th>\n",
       "      <td>2020-01-31 23:59:52+00:00</td>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5886774</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264749</th>\n",
       "      <td>2020-01-31 23:59:53+00:00</td>\n",
       "      <td>view</td>\n",
       "      <td>5875432</td>\n",
       "      <td>423651741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264750</th>\n",
       "      <td>2020-01-31 23:59:57+00:00</td>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5820745</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264751</th>\n",
       "      <td>2020-01-31 23:59:58+00:00</td>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5820745</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20692840 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       event_time        event_type  product_id    user_id\n",
       "0       2019-12-01 00:00:00+00:00  remove_from_cart     5712790  576802932\n",
       "1       2019-12-01 00:00:00+00:00              view     5764655  412120092\n",
       "2       2019-12-01 00:00:02+00:00              cart        4958  494077766\n",
       "3       2019-12-01 00:00:05+00:00              view     5848413  348405118\n",
       "4       2019-12-01 00:00:07+00:00              view     5824148  576005683\n",
       "...                           ...               ...         ...        ...\n",
       "4264747 2020-01-31 23:59:52+00:00  remove_from_cart     5886774  607092857\n",
       "4264748 2020-01-31 23:59:52+00:00  remove_from_cart     5886774  607092857\n",
       "4264749 2020-01-31 23:59:53+00:00              view     5875432  423651741\n",
       "4264750 2020-01-31 23:59:57+00:00  remove_from_cart     5820745  607092857\n",
       "4264751 2020-01-31 23:59:58+00:00  remove_from_cart     5820745  607092857\n",
       "\n",
       "[20692840 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "df = pd.concat((pd.read_csv(DATASET_5M+file,engine='c', sep=',',usecols=['event_type','product_id','user_id','event_time']) for file in os.listdir(DATASET_5M)))\n",
    "df[\"event_type\"] = df[\"event_type\"].astype(\"category\")\n",
    "df[\"product_id\"] = df[\"product_id\"].astype(\"int32\")\n",
    "df[\"user_id\"] = df[\"user_id\"].astype(\"int32\")\n",
    "df['event_time'] = pd.to_datetime(df['event_time'],infer_datetime_format=True)\n",
    "# df = df.sort_values(by='event_time', kind='mergesort')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20692840, 4)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start_dim = df.shape\n",
    "start_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 20692840 entries, 0 to 4264751\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Dtype              \n",
      "---  ------      -----              \n",
      " 0   event_time  datetime64[ns, UTC]\n",
      " 1   event_type  category           \n",
      " 2   product_id  int32              \n",
      " 3   user_id     int32              \n",
      "dtypes: category(1), datetime64[ns, UTC](1), int32(2)\n",
      "memory usage: 493.4 MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Event types in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "view                9657821\n",
       "cart                5768333\n",
       "remove_from_cart    3979679\n",
       "purchase            1287007\n",
       "Name: event_type, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "event_counts = df.event_type.value_counts()\n",
    "event_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18623728"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "event_counts.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 612,
       "width": 987
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 9), subplot_kw=dict(aspect=\"equal\"))\n",
    "# W - width; P - precision; B - bold; N - normal\n",
    "W = 2\n",
    "P = 2\n",
    "E = 'events'\n",
    "event_counts = df.event_type.value_counts()\n",
    "event_perc = df.event_type.value_counts(normalize=True) * 100\n",
    "event_type_legend = [r\"\\textbf{Viewed the item}\"+f\"\\n{event_perc['view']:{W}.{P}f}\\%\\n{event_counts['view']:,} {E}\",\n",
    "                     r\"\\textbf{Added to cart}\"+f\"\\n{event_perc['cart']:{W}.{P}f}\\%\\n{event_counts['cart']:,} {E}\",\n",
    "                     r\"\\textbf{Removed from cart}\"+f\"\\n{event_perc['remove_from_cart']:{W}.{P}f}\\%\\n{event_counts['remove_from_cart']:,} {E}\",\n",
    "                     r\"\\textbf{Purchased}\"+f\"\\n{event_perc['purchase']:{W}.{P}f}\\%\\n{event_counts['purchase']:,} {E}\"]\n",
    "\n",
    "cmap = plt.get_cmap(\"tab20\")\n",
    "wedges, texts = ax.pie(event_counts, wedgeprops=dict(width=0.382), textprops=dict(color=\"w\"), startangle=-40, colors=cmap([0,5,6,4]))\n",
    "\n",
    "bbox_props = dict(boxstyle=\"square,pad=0.618\", fc=\"w\", ec=\"k\", lw=0.72)\n",
    "kw = dict(arrowprops=dict(arrowstyle=\"-\"),\n",
    "          bbox=bbox_props, zorder=0, va=\"center\")\n",
    "\n",
    "for i, p in enumerate(wedges):\n",
    "    ang = (p.theta2 - p.theta1)/2. + p.theta1\n",
    "    y = np.sin(np.deg2rad(ang))\n",
    "    x = np.cos(np.deg2rad(ang))\n",
    "    horizontalalignment = {-1: \"right\", 1: \"left\"}[int(np.sign(x))]\n",
    "    connectionstyle = \"angle,angleA=0,angleB={}\".format(ang)\n",
    "    kw[\"arrowprops\"].update({\"connectionstyle\": connectionstyle})\n",
    "    ax.annotate(event_type_legend[i], xy=(x, y), xytext=(1.35*np.sign(x), 1.4*y),\n",
    "                horizontalalignment=horizontalalignment, **kw)\n",
    "fig.set_facecolor('w')\n",
    "# ax.set_title(\"Logged user events\")\n",
    "plt.tight_layout()\n",
    "\n",
    "fig.savefig(EXPORT_DIR+'5m-percentage-of-events.png',dpi=300)\n",
    "fig.savefig(EXPORT_DIR+'5m-percentage-of-events.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>event_type</th>\n",
       "      <th>cart</th>\n",
       "      <th>purchase</th>\n",
       "      <th>remove_from_cart</th>\n",
       "      <th>view</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>527021202</th>\n",
       "      <td>4292</td>\n",
       "      <td>0</td>\n",
       "      <td>1968</td>\n",
       "      <td>20492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557616099</th>\n",
       "      <td>217</td>\n",
       "      <td>9</td>\n",
       "      <td>151</td>\n",
       "      <td>9526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583884978</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550388516</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>7539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557956487</th>\n",
       "      <td>298</td>\n",
       "      <td>38</td>\n",
       "      <td>230</td>\n",
       "      <td>7169</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>591525847</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576843109</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450980229</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>597124275</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>575596877</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1639358 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "event_type  cart  purchase  remove_from_cart   view\n",
       "user_id                                            \n",
       "527021202   4292         0              1968  20492\n",
       "557616099    217         9               151   9526\n",
       "583884978      1         0                 1   9418\n",
       "550388516      5         0                12   7539\n",
       "557956487    298        38               230   7169\n",
       "...          ...       ...               ...    ...\n",
       "591525847      9         0                 0      0\n",
       "576843109      1         0                 0      0\n",
       "450980229      1         0                 0      0\n",
       "597124275      3         2                 1      0\n",
       "575596877      2         0                 0      0\n",
       "\n",
       "[1639358 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_events_crosstab=pd.crosstab(df['user_id'],df['event_type'])\n",
    "users_events_crosstab.sort_values(by='view',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "users = df['user_id'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Top 3 most active users (based on the number of views)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_type\n",
       "cart                 4292\n",
       "purchase                0\n",
       "remove_from_cart     1968\n",
       "view                20492\n",
       "Name: 527021202, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_events_crosstab.loc[users.index[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_type\n",
       "cart                 217\n",
       "purchase               9\n",
       "remove_from_cart     151\n",
       "view                9526\n",
       "Name: 557616099, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_events_crosstab.loc[users.index[1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_type\n",
       "cart                   1\n",
       "purchase               0\n",
       "remove_from_cart       1\n",
       "view                9418\n",
       "Name: 583884978, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_events_crosstab.loc[users.index[2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 502,
       "width": 1195
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(users_events_crosstab['view'], users_events_crosstab['purchase'], marker='.',color='k',alpha=0.5,s=10)\n",
    "# plt.title('Number of views and number of purchase actions for the same user.')\n",
    "plt.xlabel('View actions')\n",
    "plt.ylabel('Purchase actions')\n",
    "# plt.savefig(EXPORT_DIR+'view-purchase-per-user.png',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Pearson product-moment correlation coefficient is R=0.3606.\n"
     ]
    }
   ],
   "source": [
    "print(f\"The Pearson product-moment correlation coefficient is R={np.corrcoef(users_events_crosstab['view'], users_events_crosstab['purchase'])[0,1]:.4f}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 502,
       "width": 1195
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(users_events_crosstab['cart'], users_events_crosstab['purchase'], marker='.',color='k',alpha=0.5,s=10)\n",
    "# plt.title('Number of add to cart actions and number of purchase actions for the same user.')\n",
    "plt.xlabel('Add to cart actions')\n",
    "plt.ylabel('Purchase actions')\n",
    "# plt.savefig(EXPORT_DIR+'cart-purchase-per-user.png',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Pearson product-moment correlation coefficient is R=0.6264.\n"
     ]
    }
   ],
   "source": [
    "print(f\"The Pearson product-moment correlation coefficient is R={np.corrcoef(users_events_crosstab['cart'], users_events_crosstab['purchase'])[0,1]:.4f}.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Traffic fluctuation during the observed daterange"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "fluct = df.loc[:,['event_time','user_id']]\n",
    "fluct['day'] = fluct['event_time'].apply(lambda s: str(s)[0:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-10-01</th>\n",
       "      <td>126245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-02</th>\n",
       "      <td>181132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-03</th>\n",
       "      <td>109820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-04</th>\n",
       "      <td>102356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-05</th>\n",
       "      <td>94707</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             count\n",
       "day               \n",
       "2019-10-01  126245\n",
       "2019-10-02  181132\n",
       "2019-10-03  109820\n",
       "2019-10-04  102356\n",
       "2019-10-05   94707"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_visitors = fluct.drop_duplicates().groupby(['day'])['user_id'].agg(['count']).sort_values(by=['day'], ascending=True)\n",
    "daily_visitors.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.Series(daily_visitors.index.values).apply(lambda s: dt.strptime(s, '%Y-%m-%d').date())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 468,
       "width": 1178
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = daily_visitors.std()[0]\n",
    "y_bar = daily_visitors.mean()[0]\n",
    "ax = plt.subplot()\n",
    "\n",
    "plt.plot(X,daily_visitors['count'],color='k')\n",
    "plt.ylim((0,daily_visitors['count'].max()*1.05))\n",
    "plt.axhline(y = y_bar,linestyle='--', color='k')\n",
    "plt.axhline(y = y_bar+s,linestyle=':', color='k')\n",
    "plt.axhline(y = y_bar-s,linestyle=':', color='k')\n",
    "\n",
    "for label in (ax.get_xticklabels() + ax.get_yticklabels()):\n",
    "    label.set_fontsize(14)\n",
    "\n",
    "plt.legend(['Daily visitor count', r\"$\\bar{y}=$\"+f\"{daily_visitors.mean()[0]:.2f}\"])\n",
    "# plt.savefig(EXPORT_DIR+'daily-visitor-count.png',dpi=300)\n",
    "# plt.savefig(EXPORT_DIR+'daily-visitor-count.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>event_time</th>\n",
       "      <th>product_id</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4264716</th>\n",
       "      <td>2020-01-31 23:58:26+00:00</td>\n",
       "      <td>5867185</td>\n",
       "      <td>604470329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264717</th>\n",
       "      <td>2020-01-31 23:58:26+00:00</td>\n",
       "      <td>5877766</td>\n",
       "      <td>604470329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264718</th>\n",
       "      <td>2020-01-31 23:58:26+00:00</td>\n",
       "      <td>5905704</td>\n",
       "      <td>604470329</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       event_time  product_id    user_id\n",
       "4264716 2020-01-31 23:58:26+00:00     5867185  604470329\n",
       "4264717 2020-01-31 23:58:26+00:00     5877766  604470329\n",
       "4264718 2020-01-31 23:58:26+00:00     5905704  604470329"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "buyers_df = df[df.event_type=='purchase']\n",
    "buyers_df = buyers_df.drop(columns=['event_type'])\n",
    "assert len(buyers_df) == event_counts['purchase'], \"The number of purchase events should stay the same, regardless of the calculation method.\"\n",
    "buyers_df.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of visitors in the observed data-range: 18,190,679\n"
     ]
    }
   ],
   "source": [
    "print(f'Total number of visitors in the observed data-range: {daily_visitors.sum().item():,}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of unique visitors in the observed data-range: 1,639,358\n"
     ]
    }
   ],
   "source": [
    "print(f'Total number of unique visitors in the observed data-range: {len(df.user_id.unique()):,}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of events with missing user_id: 0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Number of events with missing user_id: {len(df[df.user_id.isnull()])}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Steps in the user journey"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "step = pd.Series(dtype='int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pair_id_creator(df,event_type):\n",
    "    pairs=df[df['event_type']==event_type][['user_id','product_id']].drop_duplicates().sort_values('user_id')\n",
    "    pairs['pair_id'] = pairs['user_id'].astype(str)+'-'+pairs['product_id'].astype(str)\n",
    "    return set(pairs['pair_id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "view_pairs = pair_id_creator(df,'view')\n",
    "cart_pairs = pair_id_creator(df,'cart')\n",
    "remove_pairs = pair_id_creator(df,'remove_from_cart')\n",
    "purchase_pairs = pair_id_creator(df,'purchase')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "view_cart          1526194\n",
       "cart_remove        2104855\n",
       "cart_purchase      1129944\n",
       "view_purchase       486204\n",
       "remove_purchase     174408\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "step['view_cart'] = len(view_pairs.intersection(cart_pairs))\n",
    "step['cart_remove'] = len(cart_pairs.intersection(remove_pairs))\n",
    "step['cart_purchase'] = len(cart_pairs.intersection(purchase_pairs))\n",
    "step['view_purchase'] = len(view_pairs.intersection(purchase_pairs))\n",
    "step['remove_purchase'] = len(remove_pairs.intersection(purchase_pairs))\n",
    "step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance for a viewed item to be added to cart: 0.15803\n"
     ]
    }
   ],
   "source": [
    "print(f\"Chance for a viewed item to be added to cart: {step['view_cart']/event_counts['view']:.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance for an item in cart to be removed from it: 0.36490\n"
     ]
    }
   ],
   "source": [
    "print(f\"Chance for an item in cart to be removed from it: {step['cart_remove']/event_counts['cart']:.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance for an item in cart to be purchased: 0.19589\n"
     ]
    }
   ],
   "source": [
    "print(f\"Chance for an item in cart to be purchased: {step['cart_purchase']/event_counts['cart']:.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance for an item in cart be abandoned: 0.43921\n"
     ]
    }
   ],
   "source": [
    "print(f\"Chance for an item in cart be abandoned: {1-(step['cart_purchase']/event_counts['cart']+step['cart_remove']/event_counts['cart']):.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance for a viewed item to be purchased: 0.05034\n"
     ]
    }
   ],
   "source": [
    "print(f\"Chance for a viewed item to be purchased: {step['view_purchase']/event_counts['view']:.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance for an item removed from cart to be purchased: 0.04382\n"
     ]
    }
   ],
   "source": [
    "print(f\"Chance for an item removed from cart to be purchased: {step['remove_purchase']/event_counts['remove_from_cart']:.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "ux_constants = pd.Series(dtype='int64')\n",
    "\n",
    "ux_constants['view_to_purchase'] = step['view_purchase']/event_counts['view']\n",
    "ux_constants['cart_to_purchase'] = step['cart_purchase']/event_counts['cart']\n",
    "ux_constants['remove_to_purchase'] = step['remove_purchase']/event_counts['remove_from_cart']\n",
    "ux_constants['purchase_to_purchase'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "view_to_purchase        0.050343\n",
       "cart_to_purchase        0.195887\n",
       "remove_to_purchase      0.043825\n",
       "purchase_to_purchase    1.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ux_constants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "ux_constants.to_csv(DATA_DIR+'ux-constants-5m.csv', index = True, header=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data reduction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "ux_constants = pd.Series(pd.read_csv(DATA_DIR+'ux-constants-5m.csv', index_col=0, squeeze=True, header=None), dtype='float32')\n",
    "VIEW     = ux_constants['view_to_purchase']\n",
    "CART     = ux_constants['cart_to_purchase']\n",
    "REMOVE   = ux_constants['remove_to_purchase']\n",
    "PURCHASE = ux_constants['purchase_to_purchase']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "view_to_purchase        0.050343\n",
      "cart_to_purchase        0.195887\n",
      "remove_to_purchase      0.043825\n",
      "purchase_to_purchase    1.000000\n",
      "Name: 1, dtype: float32\n"
     ]
    }
   ],
   "source": [
    "print(ux_constants)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def event_to_ux(event):\n",
    "    event_weights = {\n",
    "        'view': VIEW,\n",
    "        'cart': CART,\n",
    "        'remove_from_cart': REMOVE,\n",
    "        'purchase': PURCHASE,   \n",
    "    }\n",
    "    return event_weights.get(event, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 11.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df = pd.concat((pd.read_csv(DATASET_5M+file,engine='c', sep=',',\n",
    "                            usecols=[\"event_type\",\"product_id\",\"user_id\"],\n",
    "                           dtype={'product_id': np.int64, 'user_id': np.int64, 'event_type': 'category'}\n",
    "                           ) for file in os.listdir(DATASET_5M)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>event_type</th>\n",
       "      <th>product_id</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5712790</td>\n",
       "      <td>576802932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>view</td>\n",
       "      <td>5764655</td>\n",
       "      <td>412120092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>cart</td>\n",
       "      <td>4958</td>\n",
       "      <td>494077766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>view</td>\n",
       "      <td>5848413</td>\n",
       "      <td>348405118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>view</td>\n",
       "      <td>5824148</td>\n",
       "      <td>576005683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264747</th>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5886774</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264748</th>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5886774</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264749</th>\n",
       "      <td>view</td>\n",
       "      <td>5875432</td>\n",
       "      <td>423651741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264750</th>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5820745</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4264751</th>\n",
       "      <td>remove_from_cart</td>\n",
       "      <td>5820745</td>\n",
       "      <td>607092857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20692840 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               event_type  product_id    user_id\n",
       "0        remove_from_cart     5712790  576802932\n",
       "1                    view     5764655  412120092\n",
       "2                    cart        4958  494077766\n",
       "3                    view     5848413  348405118\n",
       "4                    view     5824148  576005683\n",
       "...                   ...         ...        ...\n",
       "4264747  remove_from_cart     5886774  607092857\n",
       "4264748  remove_from_cart     5886774  607092857\n",
       "4264749              view     5875432  423651741\n",
       "4264750  remove_from_cart     5820745  607092857\n",
       "4264751  remove_from_cart     5820745  607092857\n",
       "\n",
       "[20692840 rows x 3 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20692840, 3)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start_dim = df.shape\n",
    "start_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We start with 1,639,358 unique users.\n"
     ]
    }
   ],
   "source": [
    "print(f\"We start with {len(df.user_id.unique()):,} unique users.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will \u001b[91mdrop 1,243,312 (75.84%) users,\u001b[0m for not meeting the minimum \u001b[91m5\u001b[0m event requirement.\n"
     ]
    }
   ],
   "source": [
    "drop_visitors = set(df.user_id.value_counts()[df.user_id.value_counts()<EVENT_THRESHOLD].index)\n",
    "print(f\"We will {T.R}drop {len(drop_visitors):,} ({len(drop_visitors)*100/len(df.user_id.unique()):.2f}%) users,{T.E} \"+\n",
    "      f\"for not meeting the minimum {T.R}{EVENT_THRESHOLD}{T.E} event requirement.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[~df.user_id.isin(drop_visitors)]\n",
    "df.reset_index(inplace=True,drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This way we have reduced the number of total events by \u001b[92m10.00%\u001b[0m.\n"
     ]
    }
   ],
   "source": [
    "print(f\"This way we have reduced the number of total events by {T.G}{100-len(df)*100/start_dim[0]:.2f}%{T.E}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18623728, 3)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will have \u001b[94m396,046 unique users.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "new_user_id = pd.DataFrame()\n",
    "new_user_id['user_id']=df.user_id.unique()\n",
    "print(f\"We will have {T.B}{len(new_user_id):,} unique users.{T.E}\")\n",
    "new_user_id.to_csv(DATA_DIR+'new-user-id-5m.csv', index = True, header=True)\n",
    "uid_lookup = pd.Series(index=new_user_id.user_id,data=new_user_id.index)\n",
    "uid_lookup = uid_lookup.to_dict(OrderedDict)\n",
    "del new_user_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will have \u001b[94m53,619 unique features\u001b[0m (products for e-commerce).\n"
     ]
    }
   ],
   "source": [
    "new_product_id = pd.DataFrame()\n",
    "new_product_id['product_id']=df.product_id.unique()\n",
    "print(f\"We will have {T.B}{len(new_product_id):,} unique features{T.E} (products for e-commerce).\")\n",
    "new_product_id.to_csv(DATA_DIR+'new-product-id-5m.csv', index = True, header=True)\n",
    "pid_lookup = pd.Series(index=new_product_id.product_id,data=new_product_id.index)\n",
    "pid_lookup = pid_lookup.to_dict(OrderedDict)\n",
    "del new_product_id"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time = time.time()\n",
    "number_of_users = df['user_id'].unique().shape[0]\n",
    "number_of_features = df['product_id'].unique().shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "def user_experience_matrix(df):\n",
    "    last_index = df.shape[0]-1      \n",
    "    # Use np.float32 for torch.cuda.FloatTensor.or np.float16 for torch.cuda.HalfTensor (float64 not recommended)\n",
    "    uxm = sp.dok_matrix((number_of_users, number_of_features), dtype=np.float32)   \n",
    "    print(f\"   Event |   User | Product | Event | Previous |   {T.b}New UX{T.E}\")\n",
    "    \n",
    "    for row in df.itertuples():        \n",
    "        uid = uid_lookup[row.user_id]\n",
    "        pid = pid_lookup[row.product_id]        \n",
    "        prev_ux = uxm[uid,pid]\n",
    "        ux = np.tanh(prev_ux+event_to_ux(row.event_type))   \n",
    "#       ux = prev_ux + 1 # test case calculating the number of events between the user-product pair\n",
    "        uxm[uid,pid] = ux        \n",
    "        if (row.Index % 500000 == 0) or (row.Index == last_index):\n",
    "            print(f\"{row.Index:8} | \"+\n",
    "                  f\"{uid:6} | \"+\n",
    "                  f\"{pid:7} |  \"+\n",
    "                  f\"{row.event_type[:4]} | \"+\n",
    "                  f\"{prev_ux:8.5f} | \"+\n",
    "                  f\"{T.b}{ux:8.5f}{T.E}\")       \n",
    "    return uxm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Event |   User | Product | Event | Previous |   \u001b[1mNew UX\u001b[0m\n",
      "       0 |      0 |       0 |  remo |  0.00000 | \u001b[1m 0.04380\u001b[0m\n",
      "  500000 |  30551 |      27 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      " 1000000 |  52259 |    8585 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      " 1500000 |  69639 |     198 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      " 2000000 |  27028 |    1020 |  cart |  0.60991 | \u001b[1m 0.66727\u001b[0m\n",
      " 2500000 |  88038 |     783 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      " 3000000 | 118871 |    3650 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      " 3500000 |  46808 |    3194 |  remo |  0.19342 | \u001b[1m 0.23289\u001b[0m\n",
      " 4000000 | 148903 |   15473 |  remo |  0.10031 | \u001b[1m 0.14314\u001b[0m\n",
      " 4500000 | 144370 |   26734 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      " 5000000 |  28150 |   39026 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      " 5500000 | 181196 |    3098 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      " 6000000 |  25948 |    2814 |  remo |  0.00000 | \u001b[1m 0.04380\u001b[0m\n",
      " 6500000 |   7498 |    7657 |  remo |  0.39236 | \u001b[1m 0.41048\u001b[0m\n",
      " 7000000 |  27219 |    9803 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      " 7500000 | 145332 |    1127 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      " 8000000 | 217890 |   17834 |  remo |  0.23905 | \u001b[1m 0.27556\u001b[0m\n",
      " 8500000 |  53899 |   18389 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      " 9000000 | 109026 |    9040 |  cart |  0.05030 | \u001b[1m 0.24133\u001b[0m\n",
      " 9500000 | 249325 |    1247 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      "10000000 | 256596 |    3513 |  purc |  0.39236 | \u001b[1m 0.88369\u001b[0m\n",
      "10500000 | 135622 |   17401 |  cart |  0.09385 | \u001b[1m 0.28189\u001b[0m\n",
      "11000000 | 124986 |    9148 |  remo |  0.74315 | \u001b[1m 0.65669\u001b[0m\n",
      "11500000 | 284544 |    6878 |  remo |  0.19342 | \u001b[1m 0.23289\u001b[0m\n",
      "12000000 | 104971 |     377 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      "12500000 | 308450 |    2316 |  cart |  0.00000 | \u001b[1m 0.19342\u001b[0m\n",
      "13000000 | 229845 |   10535 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      "13500000 |  38585 |   23475 |  view |  0.10031 | \u001b[1m 0.14952\u001b[0m\n",
      "14000000 | 335812 |    2976 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      "14500000 | 333769 |   41101 |  view |  0.32213 | \u001b[1m 0.35615\u001b[0m\n",
      "15000000 |  34266 |   31021 |  remo |  0.23905 | \u001b[1m 0.27556\u001b[0m\n",
      "15500000 | 358749 |   10244 |  purc |  0.41134 | \u001b[1m 0.88778\u001b[0m\n",
      "16000000 |  89417 |     735 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      "16500000 |  53947 |   16554 |  view |  0.00000 | \u001b[1m 0.05030\u001b[0m\n",
      "17000000 |   2912 |     575 |  cart |  0.61732 | \u001b[1m 0.67136\u001b[0m\n",
      "17500000 |  40903 |   23547 |  cart |  0.19342 | \u001b[1m 0.37076\u001b[0m\n",
      "18000000 | 309765 |    8565 |  view |  0.50265 | \u001b[1m 0.50276\u001b[0m\n",
      "18500000 | 283320 |    7869 |  remo |  0.23289 | \u001b[1m 0.26986\u001b[0m\n",
      "18623727 | 269072 |    1655 |  remo |  0.27767 | \u001b[1m 0.31086\u001b[0m\n",
      "Wall time: 7min 48s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "uxm = user_experience_matrix(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time: 469.37 seconds\n"
     ]
    }
   ],
   "source": [
    "print(f\"Elapsed time: {time.time()-start_time:.2f} seconds\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Datasplit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_to_npz(X,path):\n",
    "    X = X.tocoo()\n",
    "    sp.save_npz(path,X)\n",
    "    print(f\"{T.G}Sparse matrix saved to: {path}{T.E}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: 70.00% \n",
      "Validation: 15.00% \n",
      "Test: 15.00%\n"
     ]
    }
   ],
   "source": [
    "print(f\"Train: {VAL_THRESHOLD*100:.2f}% \\nValidation: {(1-TEST_THRESHOLD)*100:.2f}% \\nTest: {(1-TEST_THRESHOLD)*100:.2f}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of stored values: 8,543,328\n"
     ]
    }
   ],
   "source": [
    "NNZ = uxm.nnz\n",
    "print(f\"Number of stored values: {NNZ:,}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(396046, 53619)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uxm.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1min 12s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "uxm_train = sp.dok_matrix.copy(uxm)\n",
    "uxm_val = sp.dok_matrix((number_of_users, number_of_features), dtype=np.float32) \n",
    "uxm_test = sp.dok_matrix((number_of_users, number_of_features), dtype=np.float32) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1min 29s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rows,cols = uxm_train.nonzero()\n",
    "for row,col in zip(rows,cols):\n",
    "    rnd = random.random()\n",
    "    if rnd > TEST_THRESHOLD:\n",
    "        uxm_test[row,col] = uxm_train[row,col]\n",
    "        uxm_train[row,col] = 0\n",
    "    elif rnd > VAL_THRESHOLD:\n",
    "        uxm_val[row,col] = uxm_train[row,col]\n",
    "        uxm_train[row,col] = 0   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of train data values: 5,980,369 (70.00%)\n",
      "Number of validation data values: 1,280,614 (14.99%)\n",
      "Number of test data values: 1,282,345 (15.01%)\n"
     ]
    }
   ],
   "source": [
    "print(f\"Number of train data values: {uxm_train.nnz:,} ({uxm_train.nnz*100/NNZ:.2f}%)\")\n",
    "print(f\"Number of validation data values: {uxm_val.nnz:,} ({uxm_val.nnz*100/NNZ:.2f}%)\")\n",
    "print(f\"Number of test data values: {uxm_test.nnz:,} ({uxm_test.nnz*100/NNZ:.2f}%)\")\n",
    "errormessage = '''All datapoints should be in either the train, the test of the validation datasets. \n",
    "The reason might be a change in how .nnz of a DOK matrix (scipy.sparse.dok_matrix) is calculated. \n",
    "In version 1.5.2 SciPy setting the value to zero explicitly (X[i,j]=0) is not counted by .nnz'''\n",
    "assert NNZ - uxm_train.nnz - uxm_val.nnz - uxm_test.nnz == 0, errormessage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92mSparse matrix saved to: ./data/uxm-5m.npz\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "save_to_npz(uxm,DATA_DIR+r'uxm-5m.npz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92mSparse matrix saved to: ./data/uxm_train-5m.npz\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "save_to_npz(uxm_train,DATA_DIR+r'uxm_train-5m.npz')\n",
    "# save_to_npz(uxm_val,VAL_DATA_PATH)\n",
    "# save_to_npz(uxm_test,TEST_DATA_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.5"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}