testing_make_dataframe_from_summary.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1b2e9e65",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variant_id</th>\n",
       "      <th>exposure_period</th>\n",
       "      <th>exposures</th>\n",
       "      <th>conversions</th>\n",
       "      <th>revenue</th>\n",
       "      <th>cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>'2022-01-01'</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>'2022-01-02'</td>\n",
       "      <td>200</td>\n",
       "      <td>20</td>\n",
       "      <td>200.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>'2022-01-03'</td>\n",
       "      <td>100</td>\n",
       "      <td>12</td>\n",
       "      <td>120.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B</td>\n",
       "      <td>'2022-01-01'</td>\n",
       "      <td>100</td>\n",
       "      <td>12</td>\n",
       "      <td>120.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>'2022-01-02'</td>\n",
       "      <td>110</td>\n",
       "      <td>15</td>\n",
       "      <td>180.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>B</td>\n",
       "      <td>'2022-01-03'</td>\n",
       "      <td>200</td>\n",
       "      <td>30</td>\n",
       "      <td>350.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  variant_id exposure_period  exposures  conversions  revenue  cost\n",
       "0          A    '2022-01-01'        100           10    100.0  20.0\n",
       "1          A    '2022-01-02'        200           20    200.0  40.0\n",
       "2          A    '2022-01-03'        100           12    120.0  24.0\n",
       "3          B    '2022-01-01'        100           12    120.0  24.0\n",
       "4          B    '2022-01-02'        110           15    180.0  36.0\n",
       "5          B    '2022-01-03'        200           30    350.0  70.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from janus.utils.make_dataframe_multivariate import create_per_user_dataframe_multivariate\n",
    "\n",
    "df = pd.read_csv('tests/dataset_summary.csv')\n",
    "for col in ['revenue', 'cost']:\n",
    "    df[col] = df[col].astype('float64')\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "24a499d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6 entries, 0 to 5\n",
      "Data columns (total 6 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   variant_id       6 non-null      object \n",
      " 1   exposure_period  6 non-null      object \n",
      " 2   exposures        6 non-null      int64  \n",
      " 3   conversions      6 non-null      int64  \n",
      " 4   revenue          6 non-null      float64\n",
      " 5   cost             6 non-null      float64\n",
      "dtypes: float64(2), int64(2), object(2)\n",
      "memory usage: 416.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "867fc964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\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>variant_id</th>\n",
       "      <th>user_id</th>\n",
       "      <th>exposure_period</th>\n",
       "      <th>converted</th>\n",
       "      <th>revenue</th>\n",
       "      <th>cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>3</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>4</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A</td>\n",
       "      <td>5</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>B</td>\n",
       "      <td>806</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>B</td>\n",
       "      <td>807</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>B</td>\n",
       "      <td>808</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>B</td>\n",
       "      <td>809</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>B</td>\n",
       "      <td>810</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>810 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    variant_id user_id exposure_period converted  revenue  cost\n",
       "0            A       1      2022-01-01         1     10.0   2.0\n",
       "1            A       2      2022-01-01         1     10.0   2.0\n",
       "2            A       3      2022-01-01         1     10.0   2.0\n",
       "3            A       4      2022-01-01         1     10.0   2.0\n",
       "4            A       5      2022-01-01         1     10.0   2.0\n",
       "..         ...     ...             ...       ...      ...   ...\n",
       "165          B     806      2022-01-03         0      0.0   0.0\n",
       "166          B     807      2022-01-03         0      0.0   0.0\n",
       "167          B     808      2022-01-03         0      0.0   0.0\n",
       "168          B     809      2022-01-03         0      0.0   0.0\n",
       "169          B     810      2022-01-03         0      0.0   0.0\n",
       "\n",
       "[810 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conversion_value_cols=['revenue', 'cost']\n",
    "df2 = create_per_user_dataframe_multivariate(df, conversion_value_cols)\n",
    "\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "12c81181",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\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>variant_id</th>\n",
       "      <th>exposure_period</th>\n",
       "      <th>exposures</th>\n",
       "      <th>conversions</th>\n",
       "      <th>revenue</th>\n",
       "      <th>cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>2022-01-02</td>\n",
       "      <td>200</td>\n",
       "      <td>20</td>\n",
       "      <td>200.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>100</td>\n",
       "      <td>12</td>\n",
       "      <td>120.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>100</td>\n",
       "      <td>12</td>\n",
       "      <td>120.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>2022-01-02</td>\n",
       "      <td>110</td>\n",
       "      <td>15</td>\n",
       "      <td>180.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>B</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>200</td>\n",
       "      <td>30</td>\n",
       "      <td>350.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  variant_id exposure_period  exposures  conversions  revenue  cost\n",
       "0          A      2022-01-01        100           10    100.0  20.0\n",
       "1          A      2022-01-02        200           20    200.0  40.0\n",
       "2          A      2022-01-03        100           12    120.0  24.0\n",
       "3          B      2022-01-01        100           12    120.0  24.0\n",
       "4          B      2022-01-02        110           15    180.0  36.0\n",
       "5          B      2022-01-03        200           30    350.0  70.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_dict = {\n",
    "        'user_id': 'count',\n",
    "        'converted': 'sum',\n",
    "    }\n",
    "agg_dict.update({c: 'sum' for c in conversion_value_cols})\n",
    "\n",
    "\n",
    "df3 = (\n",
    "    df2\n",
    "    .groupby(['variant_id', 'exposure_period'])\n",
    "    .agg(agg_dict)\n",
    "    .reset_index()\n",
    "    .rename(columns={\n",
    "        'user_id': 'exposures',\n",
    "        'converted': 'conversions',\n",
    "    })\n",
    ")\n",
    "for col in conversion_value_cols:\n",
    "    df3[col] = df3[col].astype('float64')\n",
    "df3['conversions'] = df3['conversions'].astype(\"int64\")\n",
    "\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc485b04",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "04ccbec5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe thead th {\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>variant_id</th>\n",
       "      <th>exposure_period</th>\n",
       "      <th>exposures</th>\n",
       "      <th>conversions</th>\n",
       "      <th>revenue</th>\n",
       "      <th>cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>2022-01-02</td>\n",
       "      <td>200</td>\n",
       "      <td>20</td>\n",
       "      <td>200.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>100</td>\n",
       "      <td>12</td>\n",
       "      <td>120.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>100</td>\n",
       "      <td>12</td>\n",
       "      <td>120.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>2022-01-02</td>\n",
       "      <td>110</td>\n",
       "      <td>15</td>\n",
       "      <td>180.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>B</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>200</td>\n",
       "      <td>30</td>\n",
       "      <td>350.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  variant_id exposure_period  exposures  conversions  revenue  cost\n",
       "0          A      2022-01-01        100           10    100.0  20.0\n",
       "1          A      2022-01-02        200           20    200.0  40.0\n",
       "2          A      2022-01-03        100           12    120.0  24.0\n",
       "3          B      2022-01-01        100           12    120.0  24.0\n",
       "4          B      2022-01-02        110           15    180.0  36.0\n",
       "5          B      2022-01-03        200           30    350.0  70.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "de59bfd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df['conversions'] - df3['conversions']).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "afb75e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: []"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = [\n",
    "    'variant_id', \n",
    "    'exposure_period', \n",
    "    'exposures',\n",
    "    'conversions'\n",
    "]\n",
    "pd.DataFrame.compare(df[cols], df3[cols])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6895b578",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.equals(df3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25a9b7d6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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