abtestingprojectbootcampfinal.ipynb

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    "## A/B Testing Project\n",
    "You've received an analytical task from an international online store. Your predecessor failed to complete it: they launched an A/B test and then quit (to start a watermelon farm in Brazil). They left only the technical specifications and the test results.\n",
    "\n",
    "##### Technical description\n",
    "- Test name: recommender_system_test\n",
    "- Groups: А (control), B (new payment funnel)\n",
    "- Launch date: 2020-12-07\n",
    "- Date when they stopped taking up new users: 2020-12-21\n",
    "- End date: 2021-01-01\n",
    "- Audience: 15% of the new users from the EU region\n",
    "- Purpose of the test: testing changes related to the introduction of an improved recommendation system\n",
    "- Expected result: within 14 days of signing up, users will show better conversion into product page views (the product_page event), instances of adding items to the shopping cart (product_cart), and purchases (purchase). At each stage of the funnel product_page → product_cart → purchase, there will be at least a 10% increase.\n",
    "- Expected number of test participants: 6000 \n",
    "\n",
    "##### Description of the data\n",
    "\n",
    "##### Structure of ab_project__marketing_events_us.csv:\n",
    "- name — the name of the marketing event\n",
    "- regions — regions where the ad campaign will be held\n",
    "- start_dt — campaign start date\n",
    "- finish_dt — campaign end date\n",
    "\n",
    "##### Structure of final_ab_new_users_us.csv:\n",
    "- user_id\n",
    "- first_date — sign-up date\n",
    "- region\n",
    "- device — device used to sign up\n",
    "\n",
    "##### Structure of final_ab_events_us.csv:\n",
    "- user_id\n",
    "- event_dt — event date and time\n",
    "- event_name — event type name\n",
    "- details — additional data on the event (for instance, the order total in USD for purchase events)\n",
    "\n",
    "##### Structure of final_ab_participants_us.csv:\n",
    "- user_id\n",
    "- ab_test — test name\n",
    "- group — the test group the user belonged to\n",
    "\n",
    "\n",
    "##### Instructions for completing the task\n",
    "- Describe the goals of the study.\n",
    "- Explore the data:\n",
    "    - Do types need to be converted?\n",
    "    - Are there any missing or duplicate values? If so, how would you characterize them?\n",
    "- Carry out exploratory data analysis:\n",
    "    - Study conversion at different stages of the funnel.\n",
    "    - Is the number of events per user distributed equally among the samples?\n",
    "    - Are there users who are present in both samples?\n",
    "    - How is the number of events distributed among days?\n",
    "    - Think of the possible details in the data that you have to take into account before starting the A/B test?\n",
    "- Evaluate the A/B test results:\n",
    "    - What can you tell about the A/B test results?\n",
    "    - Use a z-test to check the statistical difference between the proportions.\n",
    "- Describe your conclusions regarding the EDA stage and the A/B test results."
   ]
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   "source": [
    "#### Step 1. Data Pre Processing"
   ]
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  {
   "cell_type": "code",
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   "outputs": [],
   "source": [
    "#data preprocessing and upload\n",
    "#import libraries\n",
    "import pandas as pd\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import math as mth\n",
    "from scipy import stats as st"
   ]
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       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>regions</th>\n",
       "      <th>start_dt</th>\n",
       "      <th>finish_dt</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Christmas&amp;New Year Promo</td>\n",
       "      <td>EU, N.America</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2021-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>St. Valentine's Day Giveaway</td>\n",
       "      <td>EU, CIS, APAC, N.America</td>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>2020-02-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>St. Patric's Day Promo</td>\n",
       "      <td>EU, N.America</td>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>2020-03-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Easter Promo</td>\n",
       "      <td>EU, CIS, APAC, N.America</td>\n",
       "      <td>2020-04-12</td>\n",
       "      <td>2020-04-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4th of July Promo</td>\n",
       "      <td>N.America</td>\n",
       "      <td>2020-07-04</td>\n",
       "      <td>2020-07-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Black Friday Ads Campaign</td>\n",
       "      <td>EU, CIS, APAC, N.America</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>2020-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chinese New Year Promo</td>\n",
       "      <td>APAC</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>2020-02-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Labor day (May 1st) Ads Campaign</td>\n",
       "      <td>EU, CIS, APAC</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>2020-05-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>International Women's Day Promo</td>\n",
       "      <td>EU, CIS, APAC</td>\n",
       "      <td>2020-03-08</td>\n",
       "      <td>2020-03-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Victory Day CIS (May 9th) Event</td>\n",
       "      <td>CIS</td>\n",
       "      <td>2020-05-09</td>\n",
       "      <td>2020-05-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>CIS New Year Gift Lottery</td>\n",
       "      <td>CIS</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2021-01-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Dragon Boat Festival Giveaway</td>\n",
       "      <td>APAC</td>\n",
       "      <td>2020-06-25</td>\n",
       "      <td>2020-07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Single's Day Gift Promo</td>\n",
       "      <td>APAC</td>\n",
       "      <td>2020-11-11</td>\n",
       "      <td>2020-11-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Chinese Moon Festival</td>\n",
       "      <td>APAC</td>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>2020-10-07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "                                name                   regions   start_dt  \\\n",
       "0           Christmas&New Year Promo             EU, N.America 2020-12-25   \n",
       "1       St. Valentine's Day Giveaway  EU, CIS, APAC, N.America 2020-02-14   \n",
       "2             St. Patric's Day Promo             EU, N.America 2020-03-17   \n",
       "3                       Easter Promo  EU, CIS, APAC, N.America 2020-04-12   \n",
       "4                  4th of July Promo                 N.America 2020-07-04   \n",
       "5          Black Friday Ads Campaign  EU, CIS, APAC, N.America 2020-11-26   \n",
       "6             Chinese New Year Promo                      APAC 2020-01-25   \n",
       "7   Labor day (May 1st) Ads Campaign             EU, CIS, APAC 2020-05-01   \n",
       "8    International Women's Day Promo             EU, CIS, APAC 2020-03-08   \n",
       "9    Victory Day CIS (May 9th) Event                       CIS 2020-05-09   \n",
       "10         CIS New Year Gift Lottery                       CIS 2020-12-30   \n",
       "11     Dragon Boat Festival Giveaway                      APAC 2020-06-25   \n",
       "12           Single's Day Gift Promo                      APAC 2020-11-11   \n",
       "13             Chinese Moon Festival                      APAC 2020-10-01   \n",
       "\n",
       "    finish_dt  \n",
       "0  2021-01-03  \n",
       "1  2020-02-16  \n",
       "2  2020-03-19  \n",
       "3  2020-04-19  \n",
       "4  2020-07-11  \n",
       "5  2020-12-01  \n",
       "6  2020-02-07  \n",
       "7  2020-05-03  \n",
       "8  2020-03-10  \n",
       "9  2020-05-11  \n",
       "10 2021-01-07  \n",
       "11 2020-07-01  \n",
       "12 2020-11-12  \n",
       "13 2020-10-07  "
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       "                user_id first_date     region   device\n",
       "0      D72A72121175D8BE 2020-12-07         EU       PC\n",
       "1      F1C668619DFE6E65 2020-12-07  N.America  Android\n",
       "2      2E1BF1D4C37EA01F 2020-12-07         EU       PC\n",
       "3      50734A22C0C63768 2020-12-07         EU   iPhone\n",
       "4      E1BDDCE0DAFA2679 2020-12-07  N.America   iPhone\n",
       "...                 ...        ...        ...      ...\n",
       "61728  1DB53B933257165D 2020-12-20         EU  Android\n",
       "61729  538643EB4527ED03 2020-12-20         EU      Mac\n",
       "61730  7ADEE837D5D8CBBD 2020-12-20         EU       PC\n",
       "61731  1C7D23927835213F 2020-12-20         EU   iPhone\n",
       "61732  8F04273BB2860229 2020-12-20         EU  Android\n",
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       "      <td>purchase</td>\n",
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       "                 user_id            event_dt event_name  details\n",
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       "4       1FD7660FDF94CA1F 2020-12-07 10:15:09   purchase     4.99\n",
       "...                  ...                 ...        ...      ...\n",
       "440312  245E85F65C358E08 2020-12-30 19:35:55      login      NaN\n",
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       "      <th>2</th>\n",
       "      <td>DABC14FDDFADD29E</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04988C5DF189632E</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>482F14783456D21B</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18263</th>\n",
       "      <td>1D302F8688B91781</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18264</th>\n",
       "      <td>3DE51B726983B657</td>\n",
       "      <td>A</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18265</th>\n",
       "      <td>F501F79D332BE86C</td>\n",
       "      <td>A</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18266</th>\n",
       "      <td>63FBE257B05F2245</td>\n",
       "      <td>A</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18267</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18268 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                user_id group                  ab_test\n",
       "0      D1ABA3E2887B6A73     A  recommender_system_test\n",
       "1      A7A3664BD6242119     A  recommender_system_test\n",
       "2      DABC14FDDFADD29E     A  recommender_system_test\n",
       "3      04988C5DF189632E     A  recommender_system_test\n",
       "4      482F14783456D21B     B  recommender_system_test\n",
       "...                 ...   ...                      ...\n",
       "18263  1D302F8688B91781     B        interface_eu_test\n",
       "18264  3DE51B726983B657     A        interface_eu_test\n",
       "18265  F501F79D332BE86C     A        interface_eu_test\n",
       "18266  63FBE257B05F2245     A        interface_eu_test\n",
       "18267  79F9ABFB029CF724     B        interface_eu_test\n",
       "\n",
       "[18268 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ab_marketing = pd.read_csv('ab_project_marketing_events_us.csv', sep=',', dtype={'device': 'category'}, parse_dates=['start_dt', 'finish_dt'])\n",
    "ab_newusers = pd.read_csv('final_ab_new_users_us (1).csv', sep=',', parse_dates=['first_date'])\n",
    "ab_events = pd.read_csv('final_ab_events_us (1).csv', sep=',', parse_dates=['event_dt'])\n",
    "ab_participants = pd.read_csv('final_ab_participants_us (1).csv', sep=',')\n",
    "\n",
    "display(ab_marketing)\n",
    "display(ab_newusers)\n",
    "display(ab_events)\n",
    "display(ab_participants)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 14 entries, 0 to 13\n",
      "Data columns (total 4 columns):\n",
      " #   Column     Non-Null Count  Dtype         \n",
      "---  ------     --------------  -----         \n",
      " 0   name       14 non-null     object        \n",
      " 1   regions    14 non-null     object        \n",
      " 2   start_dt   14 non-null     datetime64[ns]\n",
      " 3   finish_dt  14 non-null     datetime64[ns]\n",
      "dtypes: datetime64[ns](2), object(2)\n",
      "memory usage: 576.0+ bytes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 61733 entries, 0 to 61732\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count  Dtype         \n",
      "---  ------      --------------  -----         \n",
      " 0   user_id     61733 non-null  object        \n",
      " 1   first_date  61733 non-null  datetime64[ns]\n",
      " 2   region      61733 non-null  object        \n",
      " 3   device      61733 non-null  object        \n",
      "dtypes: datetime64[ns](1), object(3)\n",
      "memory usage: 1.9+ MB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 440317 entries, 0 to 440316\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count   Dtype         \n",
      "---  ------      --------------   -----         \n",
      " 0   user_id     440317 non-null  object        \n",
      " 1   event_dt    440317 non-null  datetime64[ns]\n",
      " 2   event_name  440317 non-null  object        \n",
      " 3   details     62740 non-null   float64       \n",
      "dtypes: datetime64[ns](1), float64(1), object(2)\n",
      "memory usage: 13.4+ MB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 18268 entries, 0 to 18267\n",
      "Data columns (total 3 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   user_id  18268 non-null  object\n",
      " 1   group    18268 non-null  object\n",
      " 2   ab_test  18268 non-null  object\n",
      "dtypes: object(3)\n",
      "memory usage: 428.3+ KB\n"
     ]
    }
   ],
   "source": [
    "#study the data they contain make sure the data types are correct\n",
    "ab_marketing.info()\n",
    "ab_newusers.info()\n",
    "ab_events.info()\n",
    "ab_participants.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name         0\n",
       "regions      0\n",
       "start_dt     0\n",
       "finish_dt    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for null values in each dataset\n",
    "ab_marketing.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id       0\n",
       "first_date    0\n",
       "region        0\n",
       "device        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_newusers.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id            0\n",
       "event_dt           0\n",
       "event_name         0\n",
       "details       377577\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_events.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ab_events['details'].fillna(0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>details</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>440317.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.402282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>28.495956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>499.990000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             details\n",
       "count  440317.000000\n",
       "mean        3.402282\n",
       "std        28.495956\n",
       "min         0.000000\n",
       "25%         0.000000\n",
       "50%         0.000000\n",
       "75%         0.000000\n",
       "max       499.990000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_events.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id    0\n",
       "group      0\n",
       "ab_test    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_participants.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for duplicates\n",
    "ab_marketing.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_newusers.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_events.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab_participants.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "\n",
    "no duplicates listed, null events in details are because of information not being complete in the study. removing this information would skew the data so I left it and converted it to 0. converted date values to date time appropriately."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 2. Exploratory Data Analysis\n",
    "    - Study conversion at different stages of the funnel.\n",
    "    - Is the number of events per user distributed equally among the samples?\n",
    "    - Are there users who are present in both samples?\n",
    "    - How is the number of events distributed among days?\n",
    "    - Think of the possible details in the data that you have to take into account before starting the A/B test?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>E1BDDCE0DAFA2679</td>\n",
       "      <td>2020-12-07 20:22:03</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7B6452F081F49504</td>\n",
       "      <td>2020-12-07 09:22:53</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9CD9F34546DF254C</td>\n",
       "      <td>2020-12-07 12:59:29</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-07 04:02:40</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1FD7660FDF94CA1F</td>\n",
       "      <td>2020-12-07 10:15:09</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</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>440312</th>\n",
       "      <td>245E85F65C358E08</td>\n",
       "      <td>2020-12-30 19:35:55</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440313</th>\n",
       "      <td>9385A108F5A0A7A7</td>\n",
       "      <td>2020-12-30 10:54:15</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440314</th>\n",
       "      <td>DB650B7559AC6EAC</td>\n",
       "      <td>2020-12-30 10:59:09</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440315</th>\n",
       "      <td>F80C9BDDEA02E53C</td>\n",
       "      <td>2020-12-30 09:53:39</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440316</th>\n",
       "      <td>7AEC61159B672CC5</td>\n",
       "      <td>2020-12-30 11:36:13</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>440317 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id            event_dt event_name  details session_date  \\\n",
       "0       E1BDDCE0DAFA2679 2020-12-07 20:22:03   purchase    99.99   2020-12-07   \n",
       "1       7B6452F081F49504 2020-12-07 09:22:53   purchase     9.99   2020-12-07   \n",
       "2       9CD9F34546DF254C 2020-12-07 12:59:29   purchase     4.99   2020-12-07   \n",
       "3       96F27A054B191457 2020-12-07 04:02:40   purchase     4.99   2020-12-07   \n",
       "4       1FD7660FDF94CA1F 2020-12-07 10:15:09   purchase     4.99   2020-12-07   \n",
       "...                  ...                 ...        ...      ...          ...   \n",
       "440312  245E85F65C358E08 2020-12-30 19:35:55      login     0.00   2020-12-30   \n",
       "440313  9385A108F5A0A7A7 2020-12-30 10:54:15      login     0.00   2020-12-30   \n",
       "440314  DB650B7559AC6EAC 2020-12-30 10:59:09      login     0.00   2020-12-30   \n",
       "440315  F80C9BDDEA02E53C 2020-12-30 09:53:39      login     0.00   2020-12-30   \n",
       "440316  7AEC61159B672CC5 2020-12-30 11:36:13      login     0.00   2020-12-30   \n",
       "\n",
       "        session_year  session_month  session_week  start_day  \n",
       "0               2020             12            50          7  \n",
       "1               2020             12            50          7  \n",
       "2               2020             12            50          7  \n",
       "3               2020             12            50          7  \n",
       "4               2020             12            50          7  \n",
       "...              ...            ...           ...        ...  \n",
       "440312          2020             12            53         30  \n",
       "440313          2020             12            53         30  \n",
       "440314          2020             12            53         30  \n",
       "440315          2020             12            53         30  \n",
       "440316          2020             12            53         30  \n",
       "\n",
       "[440317 rows x 9 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#number of people who use it daily, weekly, monthly and yearly\n",
    "ab_events['session_date'] = ab_events['event_dt'].dt.date\n",
    "ab_events['session_year']  = ab_events['event_dt'].dt.year\n",
    "ab_events['session_month'] = ab_events['event_dt'].dt.month\n",
    "ab_events['session_week']  = ab_events['event_dt'].dt.week\n",
    "ab_events['start_day'] = ab_events['event_dt'].dt.day\n",
    "display(ab_events)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Users per Day 7904\n",
      "Users per Week 26892\n",
      "Users per Month 58703\n"
     ]
    }
   ],
   "source": [
    "dau_total = ab_events.groupby('session_date').agg({'user_id': 'nunique'}).mean()\n",
    "wau_total = ab_events.groupby(['session_year', 'session_week']).agg({'user_id': 'nunique'}).mean()\n",
    "mau_total = ab_events.groupby(['session_year', 'session_month']).agg({'user_id': 'nunique'}).mean()\n",
    "\n",
    "print('Users per Day', int(dau_total))\n",
    "print('Users per Week', int(wau_total))\n",
    "print('Users per Month',int(mau_total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average sessions daily: 18346\n"
     ]
    }
   ],
   "source": [
    "daily_sessions_total = ab_events.groupby('session_date').agg({'user_id':'count'}).mean()\n",
    "print('Average sessions daily:', int(daily_sessions_total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>E1BDDCE0DAFA2679</td>\n",
       "      <td>2020-12-07 20:22:03</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>N.America</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7B6452F081F49504</td>\n",
       "      <td>2020-12-07 09:22:53</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9CD9F34546DF254C</td>\n",
       "      <td>2020-12-07 12:59:29</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>N.America</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-07 04:02:40</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1FD7660FDF94CA1F</td>\n",
       "      <td>2020-12-07 10:15:09</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</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",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440312</th>\n",
       "      <td>245E85F65C358E08</td>\n",
       "      <td>2020-12-30 19:35:55</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440313</th>\n",
       "      <td>9385A108F5A0A7A7</td>\n",
       "      <td>2020-12-30 10:54:15</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440314</th>\n",
       "      <td>DB650B7559AC6EAC</td>\n",
       "      <td>2020-12-30 10:59:09</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
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       "    <tr>\n",
       "      <th>440315</th>\n",
       "      <td>F80C9BDDEA02E53C</td>\n",
       "      <td>2020-12-30 09:53:39</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440316</th>\n",
       "      <td>7AEC61159B672CC5</td>\n",
       "      <td>2020-12-30 11:36:13</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>440317 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id            event_dt event_name  details session_date  \\\n",
       "0       E1BDDCE0DAFA2679 2020-12-07 20:22:03   purchase    99.99   2020-12-07   \n",
       "1       7B6452F081F49504 2020-12-07 09:22:53   purchase     9.99   2020-12-07   \n",
       "2       9CD9F34546DF254C 2020-12-07 12:59:29   purchase     4.99   2020-12-07   \n",
       "3       96F27A054B191457 2020-12-07 04:02:40   purchase     4.99   2020-12-07   \n",
       "4       1FD7660FDF94CA1F 2020-12-07 10:15:09   purchase     4.99   2020-12-07   \n",
       "...                  ...                 ...        ...      ...          ...   \n",
       "440312  245E85F65C358E08 2020-12-30 19:35:55      login     0.00   2020-12-30   \n",
       "440313  9385A108F5A0A7A7 2020-12-30 10:54:15      login     0.00   2020-12-30   \n",
       "440314  DB650B7559AC6EAC 2020-12-30 10:59:09      login     0.00   2020-12-30   \n",
       "440315  F80C9BDDEA02E53C 2020-12-30 09:53:39      login     0.00   2020-12-30   \n",
       "440316  7AEC61159B672CC5 2020-12-30 11:36:13      login     0.00   2020-12-30   \n",
       "\n",
       "        session_year  session_month  session_week  start_day first_date  \\\n",
       "0               2020             12            50          7 2020-12-07   \n",
       "1               2020             12            50          7 2020-12-07   \n",
       "2               2020             12            50          7 2020-12-07   \n",
       "3               2020             12            50          7 2020-12-07   \n",
       "4               2020             12            50          7 2020-12-07   \n",
       "...              ...            ...           ...        ...        ...   \n",
       "440312          2020             12            53         30 2020-12-07   \n",
       "440313          2020             12            53         30 2020-12-07   \n",
       "440314          2020             12            53         30 2020-12-07   \n",
       "440315          2020             12            53         30 2020-12-07   \n",
       "440316          2020             12            53         30 2020-12-07   \n",
       "\n",
       "           region   device  \n",
       "0       N.America   iPhone  \n",
       "1              EU   iPhone  \n",
       "2       N.America   iPhone  \n",
       "3              EU   iPhone  \n",
       "4              EU  Android  \n",
       "...           ...      ...  \n",
       "440312         EU  Android  \n",
       "440313         EU       PC  \n",
       "440314         EU  Android  \n",
       "440315         EU   iPhone  \n",
       "440316         EU   iPhone  \n",
       "\n",
       "[440317 rows x 12 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#merging events and new users\n",
    "eventandnew = ab_events.merge(ab_newusers, on='user_id', how = 'left')\n",
    "display(eventandnew)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:56</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:29</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:57</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110363</th>\n",
       "      <td>63FBE257B05F2245</td>\n",
       "      <td>A</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-23 13:03:17</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110364</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-14 19:12:49</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110365</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-15 01:50:22</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110366</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-16 19:27:36</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110367</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-20 13:04:31</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110368 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id group                  ab_test            event_dt  \\\n",
       "0       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "1       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:56   \n",
       "2       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:29   \n",
       "3       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:57   \n",
       "4       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "...                  ...   ...                      ...                 ...   \n",
       "110363  63FBE257B05F2245     A        interface_eu_test 2020-12-23 13:03:17   \n",
       "110364  79F9ABFB029CF724     B        interface_eu_test 2020-12-14 19:12:49   \n",
       "110365  79F9ABFB029CF724     B        interface_eu_test 2020-12-15 01:50:22   \n",
       "110366  79F9ABFB029CF724     B        interface_eu_test 2020-12-16 19:27:36   \n",
       "110367  79F9ABFB029CF724     B        interface_eu_test 2020-12-20 13:04:31   \n",
       "\n",
       "          event_name  details session_date  session_year  session_month  \\\n",
       "0           purchase    99.99   2020-12-07        2020.0           12.0   \n",
       "1           purchase     4.99   2020-12-25        2020.0           12.0   \n",
       "2       product_cart     0.00   2020-12-07        2020.0           12.0   \n",
       "3       product_cart     0.00   2020-12-25        2020.0           12.0   \n",
       "4       product_page     0.00   2020-12-07        2020.0           12.0   \n",
       "...              ...      ...          ...           ...            ...   \n",
       "110363         login     0.00   2020-12-23        2020.0           12.0   \n",
       "110364         login     0.00   2020-12-14        2020.0           12.0   \n",
       "110365         login     0.00   2020-12-15        2020.0           12.0   \n",
       "110366         login     0.00   2020-12-16        2020.0           12.0   \n",
       "110367         login     0.00   2020-12-20        2020.0           12.0   \n",
       "\n",
       "        session_week  start_day first_date region   device  \n",
       "0               50.0        7.0 2020-12-07     EU       PC  \n",
       "1               52.0       25.0 2020-12-07     EU       PC  \n",
       "2               50.0        7.0 2020-12-07     EU       PC  \n",
       "3               52.0       25.0 2020-12-07     EU       PC  \n",
       "4               50.0        7.0 2020-12-07     EU       PC  \n",
       "...              ...        ...        ...    ...      ...  \n",
       "110363          52.0       23.0 2020-12-20     EU  Android  \n",
       "110364          51.0       14.0 2020-12-14     EU       PC  \n",
       "110365          51.0       15.0 2020-12-14     EU       PC  \n",
       "110366          51.0       16.0 2020-12-14     EU       PC  \n",
       "110367          51.0       20.0 2020-12-14     EU       PC  \n",
       "\n",
       "[110368 rows x 14 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#merging new users and AB tests\n",
    "eventparticipants = ab_participants.merge(eventandnew, on='user_id', how = 'left')\n",
    "display(eventparticipants)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "reccomenderdata= eventparticipants.query('ab_test == \"recommender_system_test\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Daily Usage: 466\n"
     ]
    }
   ],
   "source": [
    "dau_total = reccomenderdata.groupby('session_date').agg({'user_id': 'nunique'}).mean()\n",
    "print('Average Daily Usage:', int(dau_total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-21-a70e39fb56ca>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  reccomenderdata['date'] = reccomenderdata['event_dt'].dt.date\n",
      "<ipython-input-21-a70e39fb56ca>:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  reccomenderdata['time'] = reccomenderdata['event_dt'].dt.time\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>user_id</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>E1BDDCE0DAFA2679</td>\n",
       "      <td>2020-12-07 20:22:03</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>N.America</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7B6452F081F49504</td>\n",
       "      <td>2020-12-07 09:22:53</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9CD9F34546DF254C</td>\n",
       "      <td>2020-12-07 12:59:29</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>N.America</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-07 04:02:40</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1FD7660FDF94CA1F</td>\n",
       "      <td>2020-12-07 10:15:09</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440312</th>\n",
       "      <td>245E85F65C358E08</td>\n",
       "      <td>2020-12-30 19:35:55</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440313</th>\n",
       "      <td>9385A108F5A0A7A7</td>\n",
       "      <td>2020-12-30 10:54:15</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440314</th>\n",
       "      <td>DB650B7559AC6EAC</td>\n",
       "      <td>2020-12-30 10:59:09</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440315</th>\n",
       "      <td>F80C9BDDEA02E53C</td>\n",
       "      <td>2020-12-30 09:53:39</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
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       "    <tr>\n",
       "      <th>440316</th>\n",
       "      <td>7AEC61159B672CC5</td>\n",
       "      <td>2020-12-30 11:36:13</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>30</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>440317 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id            event_dt event_name  details session_date  \\\n",
       "0       E1BDDCE0DAFA2679 2020-12-07 20:22:03   purchase    99.99   2020-12-07   \n",
       "1       7B6452F081F49504 2020-12-07 09:22:53   purchase     9.99   2020-12-07   \n",
       "2       9CD9F34546DF254C 2020-12-07 12:59:29   purchase     4.99   2020-12-07   \n",
       "3       96F27A054B191457 2020-12-07 04:02:40   purchase     4.99   2020-12-07   \n",
       "4       1FD7660FDF94CA1F 2020-12-07 10:15:09   purchase     4.99   2020-12-07   \n",
       "...                  ...                 ...        ...      ...          ...   \n",
       "440312  245E85F65C358E08 2020-12-30 19:35:55      login     0.00   2020-12-30   \n",
       "440313  9385A108F5A0A7A7 2020-12-30 10:54:15      login     0.00   2020-12-30   \n",
       "440314  DB650B7559AC6EAC 2020-12-30 10:59:09      login     0.00   2020-12-30   \n",
       "440315  F80C9BDDEA02E53C 2020-12-30 09:53:39      login     0.00   2020-12-30   \n",
       "440316  7AEC61159B672CC5 2020-12-30 11:36:13      login     0.00   2020-12-30   \n",
       "\n",
       "        session_year  session_month  session_week  start_day first_date  \\\n",
       "0               2020             12            50          7 2020-12-07   \n",
       "1               2020             12            50          7 2020-12-07   \n",
       "2               2020             12            50          7 2020-12-07   \n",
       "3               2020             12            50          7 2020-12-07   \n",
       "4               2020             12            50          7 2020-12-07   \n",
       "...              ...            ...           ...        ...        ...   \n",
       "440312          2020             12            53         30 2020-12-07   \n",
       "440313          2020             12            53         30 2020-12-07   \n",
       "440314          2020             12            53         30 2020-12-07   \n",
       "440315          2020             12            53         30 2020-12-07   \n",
       "440316          2020             12            53         30 2020-12-07   \n",
       "\n",
       "           region   device  \n",
       "0       N.America   iPhone  \n",
       "1              EU   iPhone  \n",
       "2       N.America   iPhone  \n",
       "3              EU   iPhone  \n",
       "4              EU  Android  \n",
       "...           ...      ...  \n",
       "440312         EU  Android  \n",
       "440313         EU       PC  \n",
       "440314         EU  Android  \n",
       "440315         EU   iPhone  \n",
       "440316         EU   iPhone  \n",
       "\n",
       "[440317 rows x 12 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#date column\n",
    "reccomenderdata['date'] = reccomenderdata['event_dt'].dt.date\n",
    "reccomenderdata\n",
    "#time column\n",
    "reccomenderdata['time'] = reccomenderdata['event_dt'].dt.time\n",
    "eventandnew"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>event_name</th>\n",
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       "      <th>003DF44D7589BBD4</th>\n",
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       "    </tr>\n",
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       "      <th>00505E15A9D81546</th>\n",
       "      <td>05:35:34</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "event_name           login product_cart product_page  purchase\n",
       "user_id                                                       \n",
       "001064FEAAB631A1  03:19:15          NaN     03:19:17       NaN\n",
       "0010A1C096941592  04:34:37          NaN     04:34:38  04:34:37\n",
       "00341D8401F0F665  11:14:50          NaN          NaN       NaN\n",
       "003DF44D7589BBD4  00:54:43     00:54:43     00:54:44       NaN\n",
       "00505E15A9D81546  05:35:34          NaN          NaN       NaN"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users = reccomenderdata.pivot_table(\n",
    "    index='user_id', \n",
    "    columns='event_name', \n",
    "    values='time',\n",
    "    aggfunc='min')\n",
    "users.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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_name</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_name</th>\n",
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       "    <tr>\n",
       "      <th>purchase</th>\n",
       "      <td>1</td>\n",
       "      <td>1128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_cart</th>\n",
       "      <td>1</td>\n",
       "      <td>1079</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              event_name  user_id\n",
       "event_name                       \n",
       "login                  1     3675\n",
       "product_page           1     2303\n",
       "purchase               1     1128\n",
       "product_cart           1     1079"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#conversion at different stages of the funnel\n",
    "ExpIdbyDate = reccomenderdata.pivot_table(index='event_name', values='user_id',aggfunc='nunique')\n",
    "ExpIdbyDate.sort_values(by='user_id',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
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       "      <td>00:54:44</td>\n",
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       "      <th>00505E15A9D81546</th>\n",
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       "      <td>NaN</td>\n",
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      ],
      "text/plain": [
       "event_name           login product_cart product_page  purchase\n",
       "user_id                                                       \n",
       "001064FEAAB631A1  03:19:15          NaN     03:19:17       NaN\n",
       "0010A1C096941592  04:34:37          NaN     04:34:38  04:34:37\n",
       "00341D8401F0F665  11:14:50          NaN          NaN       NaN\n",
       "003DF44D7589BBD4  00:54:43     00:54:43     00:54:44       NaN\n",
       "00505E15A9D81546  05:35:34          NaN          NaN       NaN"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users = reccomenderdata.pivot_table(\n",
    "    index='user_id', \n",
    "    columns='event_name', \n",
    "    values='time',\n",
    "    aggfunc='min')\n",
    "users.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Login: 3675 Conv% 0.7262845849802372\n",
      "Viewed Product: 1294 Conv% 0.2557312252964427\n",
      "Had products in Cart: 91 Conv% 0.01798418972332016\n",
      "Paid: 0 Conv% 0.0\n"
     ]
    }
   ],
   "source": [
    "#Study conversion at different stages of the funnel\n",
    "step_1 = ~users['login'].isna()\n",
    "step_2 = step_1 & (users['product_page'] > users['login'])\n",
    "step_3 = step_2 & (users['product_cart'] > users['product_page'])\n",
    "step_4 = step_3 & (users['purchase'] > users['product_cart'])\n",
    "\n",
    "n_login = users[step_1].shape[0]\n",
    "n_productpage = users[step_2].shape[0]\n",
    "n_cart = users[step_3].shape[0]\n",
    "n_payment = users[step_4].shape[0]\n",
    "\n",
    "n_pageview_conv = (n_login/(n_login+n_productpage+n_cart+n_payment))\n",
    "n_productpage_conv = (n_productpage/(n_login+n_productpage+n_cart+n_payment))\n",
    "n_cart_conv = (n_cart/(n_login+n_productpage+n_cart+n_payment))\n",
    "n_payment_conv = (n_payment/(n_login+n_productpage+n_cart+n_payment))\n",
    "\n",
    "print('Login:', n_login, 'Conv%', n_pageview_conv)\n",
    "print('Viewed Product:', n_productpage, 'Conv%', n_productpage_conv)\n",
    "print('Had products in Cart:', n_cart,'Conv%', n_cart_conv)\n",
    "print('Paid:', n_payment, 'Conv%', n_payment_conv)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "- Order actions that take place are login, product page, product cart and purchase. \n",
    "\n",
    "- As we investigate the funnel of users from the reccomender test we see that users who ended up taking steps closer to a purchase that inevitably resulted in no purchases. The users who logged in into the main screen were 3675  (72% of the users) Then the users that viewed products were 1294 (25% of the users), then 91  users added products to the cart (1% of the users), then we ended up getting no users from the test group who actually made a purchase. The promotions ended up resulting in a retention of less than 1%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "      <th>ab_test</th>\n",
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       "      <th>details</th>\n",
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       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "    </tr>\n",
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       "      <th>4</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
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       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
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       "      <td>12.0</td>\n",
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       "      <td>2020-12-15</td>\n",
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       "      <td>12.0</td>\n",
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       "      <td>login</td>\n",
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       "      <td>2020-12-16</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110367</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-20 13:04:31</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110368 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id group                  ab_test            event_dt  \\\n",
       "0       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "1       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:56   \n",
       "2       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:29   \n",
       "3       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:57   \n",
       "4       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "...                  ...   ...                      ...                 ...   \n",
       "110363  63FBE257B05F2245     A        interface_eu_test 2020-12-23 13:03:17   \n",
       "110364  79F9ABFB029CF724     B        interface_eu_test 2020-12-14 19:12:49   \n",
       "110365  79F9ABFB029CF724     B        interface_eu_test 2020-12-15 01:50:22   \n",
       "110366  79F9ABFB029CF724     B        interface_eu_test 2020-12-16 19:27:36   \n",
       "110367  79F9ABFB029CF724     B        interface_eu_test 2020-12-20 13:04:31   \n",
       "\n",
       "          event_name  details session_date  session_year  session_month  \\\n",
       "0           purchase    99.99   2020-12-07        2020.0           12.0   \n",
       "1           purchase     4.99   2020-12-25        2020.0           12.0   \n",
       "2       product_cart     0.00   2020-12-07        2020.0           12.0   \n",
       "3       product_cart     0.00   2020-12-25        2020.0           12.0   \n",
       "4       product_page     0.00   2020-12-07        2020.0           12.0   \n",
       "...              ...      ...          ...           ...            ...   \n",
       "110363         login     0.00   2020-12-23        2020.0           12.0   \n",
       "110364         login     0.00   2020-12-14        2020.0           12.0   \n",
       "110365         login     0.00   2020-12-15        2020.0           12.0   \n",
       "110366         login     0.00   2020-12-16        2020.0           12.0   \n",
       "110367         login     0.00   2020-12-20        2020.0           12.0   \n",
       "\n",
       "        session_week  start_day first_date region   device  \n",
       "0               50.0        7.0 2020-12-07     EU       PC  \n",
       "1               52.0       25.0 2020-12-07     EU       PC  \n",
       "2               50.0        7.0 2020-12-07     EU       PC  \n",
       "3               52.0       25.0 2020-12-07     EU       PC  \n",
       "4               50.0        7.0 2020-12-07     EU       PC  \n",
       "...              ...        ...        ...    ...      ...  \n",
       "110363          52.0       23.0 2020-12-20     EU  Android  \n",
       "110364          51.0       14.0 2020-12-14     EU       PC  \n",
       "110365          51.0       15.0 2020-12-14     EU       PC  \n",
       "110366          51.0       16.0 2020-12-14     EU       PC  \n",
       "110367          51.0       20.0 2020-12-14     EU       PC  \n",
       "\n",
       "[110368 rows x 14 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "display(eventparticipants)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Users in logs: 31517\n"
     ]
    }
   ],
   "source": [
    "# Is the number of events per user distributed equally among the samples?\n",
    "users_average= eventparticipants.groupby(['user_id']).agg({'event_name':'nunique'}).sum()\n",
    "print('Average Users in logs:', int(users_average))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>6B1D0D8C4F8FBBEC</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18569C8DCB0771B6</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9A5549A4A85FCF06</th>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1C3D3C6C3CADDC5</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87A8BCBB07EBDACA</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41FA2525E7869F35</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C8460FF8BEF553A4</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DA7D4CF1CBBADE49</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C7D1A5A6F6BAD476</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B0244412983000C5</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D9C92EC5F9478381</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11285A53EC2B2042</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9CBD8387C8A1DDDF</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0ACD764342811460</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  event_name\n",
       "user_id                     \n",
       "97AD409895906A32          40\n",
       "84DC74ED5E60BA6A          40\n",
       "C165E8C0C5DE19FF          40\n",
       "0082295A41A867B5          40\n",
       "A2DB18F90D9E3362          40\n",
       "2B8FD20CA8A2A616          40\n",
       "6B1D0D8C4F8FBBEC          40\n",
       "18569C8DCB0771B6          40\n",
       "9A5549A4A85FCF06          38\n",
       "A1C3D3C6C3CADDC5          36\n",
       "87A8BCBB07EBDACA          36\n",
       "41FA2525E7869F35          36\n",
       "C8460FF8BEF553A4          36\n",
       "DA7D4CF1CBBADE49          36\n",
       "C7D1A5A6F6BAD476          36\n",
       "B0244412983000C5          36\n",
       "D9C92EC5F9478381          32\n",
       "11285A53EC2B2042          32\n",
       "9CBD8387C8A1DDDF          32\n",
       "0ACD764342811460          32"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#average number of events per user\n",
    "users_per_event = eventparticipants.groupby(['user_id']).agg({'event_name':'count'})\n",
    "users_per_event.sort_values(by='event_name', ascending=False).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_name    6.397756\n",
       "dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TotalEvents_PerUser = eventparticipants.groupby('user_id').agg({'event_name':'count'}).mean()\n",
    "TotalEvents_PerUser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average events per user in logs: event_name    6.397756\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print('Average events per user in logs:', TotalEvents_PerUser)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "      <th>duration_start</th>\n",
       "      <th>duration_end</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:56</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:29</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:57</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>110363</th>\n",
       "      <td>63FBE257B05F2245</td>\n",
       "      <td>A</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-23 13:03:17</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110364</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-14 19:12:49</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110365</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-15 01:50:22</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110366</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-16 19:27:36</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110367</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-20 13:04:31</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110368 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id group                  ab_test            event_dt  \\\n",
       "0       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "1       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:56   \n",
       "2       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:29   \n",
       "3       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:57   \n",
       "4       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "...                  ...   ...                      ...                 ...   \n",
       "110363  63FBE257B05F2245     A        interface_eu_test 2020-12-23 13:03:17   \n",
       "110364  79F9ABFB029CF724     B        interface_eu_test 2020-12-14 19:12:49   \n",
       "110365  79F9ABFB029CF724     B        interface_eu_test 2020-12-15 01:50:22   \n",
       "110366  79F9ABFB029CF724     B        interface_eu_test 2020-12-16 19:27:36   \n",
       "110367  79F9ABFB029CF724     B        interface_eu_test 2020-12-20 13:04:31   \n",
       "\n",
       "          event_name  details session_date  session_year  session_month  \\\n",
       "0           purchase    99.99   2020-12-07        2020.0           12.0   \n",
       "1           purchase     4.99   2020-12-25        2020.0           12.0   \n",
       "2       product_cart     0.00   2020-12-07        2020.0           12.0   \n",
       "3       product_cart     0.00   2020-12-25        2020.0           12.0   \n",
       "4       product_page     0.00   2020-12-07        2020.0           12.0   \n",
       "...              ...      ...          ...           ...            ...   \n",
       "110363         login     0.00   2020-12-23        2020.0           12.0   \n",
       "110364         login     0.00   2020-12-14        2020.0           12.0   \n",
       "110365         login     0.00   2020-12-15        2020.0           12.0   \n",
       "110366         login     0.00   2020-12-16        2020.0           12.0   \n",
       "110367         login     0.00   2020-12-20        2020.0           12.0   \n",
       "\n",
       "        session_week  start_day first_date region   device  \\\n",
       "0               50.0        7.0 2020-12-07     EU       PC   \n",
       "1               52.0       25.0 2020-12-07     EU       PC   \n",
       "2               50.0        7.0 2020-12-07     EU       PC   \n",
       "3               52.0       25.0 2020-12-07     EU       PC   \n",
       "4               50.0        7.0 2020-12-07     EU       PC   \n",
       "...              ...        ...        ...    ...      ...   \n",
       "110363          52.0       23.0 2020-12-20     EU  Android   \n",
       "110364          51.0       14.0 2020-12-14     EU       PC   \n",
       "110365          51.0       15.0 2020-12-14     EU       PC   \n",
       "110366          51.0       16.0 2020-12-14     EU       PC   \n",
       "110367          51.0       20.0 2020-12-14     EU       PC   \n",
       "\n",
       "            duration_start        duration_end  \n",
       "0      2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "1      2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "2      2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "3      2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "4      2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "...                    ...                 ...  \n",
       "110363 2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "110364 2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "110365 2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "110366 2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "110367 2020-12-07 00:02:48 2020-12-30 18:28:55  \n",
       "\n",
       "[110368 rows x 16 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#what period of time does the data cover?\n",
    "eventparticipants['duration_start'] = eventparticipants['event_dt'].min()\n",
    "eventparticipants['duration_end'] = eventparticipants['event_dt'].max()\n",
    "display(eventparticipants)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
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       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
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       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:56</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:29</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:57</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</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",
       "      <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>110363</th>\n",
       "      <td>63FBE257B05F2245</td>\n",
       "      <td>A</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-23 13:03:17</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110364</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-14 19:12:49</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110365</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-15 01:50:22</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110366</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-16 19:27:36</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110367</th>\n",
       "      <td>79F9ABFB029CF724</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "      <td>2020-12-20 13:04:31</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07 00:02:48</td>\n",
       "      <td>2020-12-30 18:28:55</td>\n",
       "      <td>23 days 18:26:07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110368 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id group                  ab_test            event_dt  \\\n",
       "0       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "1       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:56   \n",
       "2       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:29   \n",
       "3       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:57   \n",
       "4       D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "...                  ...   ...                      ...                 ...   \n",
       "110363  63FBE257B05F2245     A        interface_eu_test 2020-12-23 13:03:17   \n",
       "110364  79F9ABFB029CF724     B        interface_eu_test 2020-12-14 19:12:49   \n",
       "110365  79F9ABFB029CF724     B        interface_eu_test 2020-12-15 01:50:22   \n",
       "110366  79F9ABFB029CF724     B        interface_eu_test 2020-12-16 19:27:36   \n",
       "110367  79F9ABFB029CF724     B        interface_eu_test 2020-12-20 13:04:31   \n",
       "\n",
       "          event_name  details session_date  session_year  session_month  \\\n",
       "0           purchase    99.99   2020-12-07        2020.0           12.0   \n",
       "1           purchase     4.99   2020-12-25        2020.0           12.0   \n",
       "2       product_cart     0.00   2020-12-07        2020.0           12.0   \n",
       "3       product_cart     0.00   2020-12-25        2020.0           12.0   \n",
       "4       product_page     0.00   2020-12-07        2020.0           12.0   \n",
       "...              ...      ...          ...           ...            ...   \n",
       "110363         login     0.00   2020-12-23        2020.0           12.0   \n",
       "110364         login     0.00   2020-12-14        2020.0           12.0   \n",
       "110365         login     0.00   2020-12-15        2020.0           12.0   \n",
       "110366         login     0.00   2020-12-16        2020.0           12.0   \n",
       "110367         login     0.00   2020-12-20        2020.0           12.0   \n",
       "\n",
       "        session_week  start_day first_date region   device  \\\n",
       "0               50.0        7.0 2020-12-07     EU       PC   \n",
       "1               52.0       25.0 2020-12-07     EU       PC   \n",
       "2               50.0        7.0 2020-12-07     EU       PC   \n",
       "3               52.0       25.0 2020-12-07     EU       PC   \n",
       "4               50.0        7.0 2020-12-07     EU       PC   \n",
       "...              ...        ...        ...    ...      ...   \n",
       "110363          52.0       23.0 2020-12-20     EU  Android   \n",
       "110364          51.0       14.0 2020-12-14     EU       PC   \n",
       "110365          51.0       15.0 2020-12-14     EU       PC   \n",
       "110366          51.0       16.0 2020-12-14     EU       PC   \n",
       "110367          51.0       20.0 2020-12-14     EU       PC   \n",
       "\n",
       "            duration_start        duration_end session_duration  \n",
       "0      2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "1      2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "2      2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "3      2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "4      2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "...                    ...                 ...              ...  \n",
       "110363 2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "110364 2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "110365 2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "110366 2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "110367 2020-12-07 00:02:48 2020-12-30 18:28:55 23 days 18:26:07  \n",
       "\n",
       "[110368 rows x 17 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eventparticipants['session_duration'] = (eventparticipants['duration_end'] - eventparticipants['duration_start'])\n",
    "eventparticipants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Session Length is: 23 days 18:26:06.999996\n",
      "23 days 18:26:07    1.0\n",
      "Name: session_duration, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import warnings\n",
    "if not sys.warnoptions:\n",
    "       warnings.simplefilter(\"ignore\")\n",
    "\n",
    "print(\"Average Session Length is:\", eventparticipants['session_duration'].mean()) \n",
    "print(eventparticipants['session_duration'].value_counts(normalize=True).head(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>user_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ab_test</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>interface_eu_test</th>\n",
       "      <td>82644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>recommender_system_test</th>\n",
       "      <td>27724</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         user_id\n",
       "ab_test                         \n",
       "interface_eu_test          82644\n",
       "recommender_system_test    27724"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Are there users who are present in both samples?\n",
    "eventusercount = eventparticipants.pivot_table(index='ab_test', values='user_id', aggfunc='count' )\n",
    "eventusercount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique Users in logs: 18268\n"
     ]
    }
   ],
   "source": [
    "uniqueusers= eventparticipants.groupby(['ab_test']).agg({'user_id':'nunique'}).sum()\n",
    "print('Unique Users in logs:', int(uniqueusers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>ab_test</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97AD409895906A32</th>\n",
       "      <td>40</td>\n",
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       "    <tr>\n",
       "      <th>84DC74ED5E60BA6A</th>\n",
       "      <td>40</td>\n",
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       "    <tr>\n",
       "      <th>C165E8C0C5DE19FF</th>\n",
       "      <td>40</td>\n",
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       "      <th>0082295A41A867B5</th>\n",
       "      <td>40</td>\n",
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       "      <th>A2DB18F90D9E3362</th>\n",
       "      <td>40</td>\n",
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       "      <td>40</td>\n",
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       "      <th>6B1D0D8C4F8FBBEC</th>\n",
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       "      <th>18569C8DCB0771B6</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9A5549A4A85FCF06</th>\n",
       "      <td>38</td>\n",
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       "    <tr>\n",
       "      <th>A1C3D3C6C3CADDC5</th>\n",
       "      <td>36</td>\n",
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       "      <th>87A8BCBB07EBDACA</th>\n",
       "      <td>36</td>\n",
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       "      <th>41FA2525E7869F35</th>\n",
       "      <td>36</td>\n",
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       "      <th>C8460FF8BEF553A4</th>\n",
       "      <td>36</td>\n",
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       "      <th>DA7D4CF1CBBADE49</th>\n",
       "      <td>36</td>\n",
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       "    <tr>\n",
       "      <th>C7D1A5A6F6BAD476</th>\n",
       "      <td>36</td>\n",
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       "    <tr>\n",
       "      <th>B0244412983000C5</th>\n",
       "      <td>36</td>\n",
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       "      <th>D9C92EC5F9478381</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11285A53EC2B2042</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9CBD8387C8A1DDDF</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0ACD764342811460</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  ab_test\n",
       "user_id                  \n",
       "97AD409895906A32       40\n",
       "84DC74ED5E60BA6A       40\n",
       "C165E8C0C5DE19FF       40\n",
       "0082295A41A867B5       40\n",
       "A2DB18F90D9E3362       40\n",
       "2B8FD20CA8A2A616       40\n",
       "6B1D0D8C4F8FBBEC       40\n",
       "18569C8DCB0771B6       40\n",
       "9A5549A4A85FCF06       38\n",
       "A1C3D3C6C3CADDC5       36\n",
       "87A8BCBB07EBDACA       36\n",
       "41FA2525E7869F35       36\n",
       "C8460FF8BEF553A4       36\n",
       "DA7D4CF1CBBADE49       36\n",
       "C7D1A5A6F6BAD476       36\n",
       "B0244412983000C5       36\n",
       "D9C92EC5F9478381       32\n",
       "11285A53EC2B2042       32\n",
       "9CBD8387C8A1DDDF       32\n",
       "0ACD764342811460       32"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#average number of events per user\n",
    "users_per_event = eventparticipants.groupby(['user_id']).agg({'ab_test':'count'})\n",
    "users_per_event.sort_values(by='ab_test', ascending=False).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>session_date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>purchase</th>\n",
       "      <td>15416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_page</th>\n",
       "      <td>30025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_cart</th>\n",
       "      <td>14849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>login</th>\n",
       "      <td>46335</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              session_date\n",
       "event_name                \n",
       "purchase             15416\n",
       "product_page         30025\n",
       "product_cart         14849\n",
       "login                46335"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How is the number of events distributed among days?\n",
    "users_per_event = eventparticipants.groupby(['event_name']).agg({'session_date':'count'})\n",
    "users_per_event.sort_values(by='event_name', ascending=False).head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### conclusion\n",
    "When we look at the breakdown of the events by days we see that the login action is at the top followed by product page, followed by purchase, followed by product cart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution by time\n",
    "eventparticipants['event_dt'].hist(bins=50)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title(\"Average Session Length\")\n",
    "plt.ylabel(\"Sessions\")\n",
    "plt.xlabel(\"Duration in Seconds\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Think of the possible details in the data that you have to take into account before starting the A/B test?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3. A/B Test Analysis \n",
    "- What can you tell about the A/B test results?\n",
    "- Use a z-test to check the statistical difference between the proportions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14333</th>\n",
       "      <td>FFF28D02B1EACBE1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 15:20:08</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>15:20:08</td>\n",
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       "    <tr>\n",
       "      <th>14326</th>\n",
       "      <td>FFF28D02B1EACBE1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-16 08:24:57</td>\n",
       "      <td>product_cart</td>\n",
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       "      <td>2020-12-16</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
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       "      <td>16.0</td>\n",
       "      <td>2020-12-16</td>\n",
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       "      <td>PC</td>\n",
       "      <td>2020-12-16</td>\n",
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       "    <tr>\n",
       "      <th>14329</th>\n",
       "      <td>FFF28D02B1EACBE1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-16 08:24:57</td>\n",
       "      <td>product_page</td>\n",
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       "      <td>2020-12-16</td>\n",
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       "      <td>FFF28D02B1EACBE1</td>\n",
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       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 15:20:10</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
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       "      <td>15:20:10</td>\n",
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       "      <th>14327</th>\n",
       "      <td>FFF28D02B1EACBE1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 15:20:10</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-16</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>001064FEAAB631A1</td>\n",
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       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-26 15:55:18</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-26</td>\n",
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       "      <th>889</th>\n",
       "      <td>001064FEAAB631A1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-20 14:43:27</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>14:43:27</td>\n",
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       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>001064FEAAB631A1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 03:19:15</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>03:19:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>891</th>\n",
       "      <td>001064FEAAB631A1</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-26 15:55:17</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>15:55:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24080</th>\n",
       "      <td>000ABE35EE11412F</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27724 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                user_id group                  ab_test            event_dt  \\\n",
       "14333  FFF28D02B1EACBE1     B  recommender_system_test 2020-12-21 15:20:08   \n",
       "14326  FFF28D02B1EACBE1     B  recommender_system_test 2020-12-16 08:24:57   \n",
       "14329  FFF28D02B1EACBE1     B  recommender_system_test 2020-12-16 08:24:57   \n",
       "14330  FFF28D02B1EACBE1     B  recommender_system_test 2020-12-21 15:20:10   \n",
       "14327  FFF28D02B1EACBE1     B  recommender_system_test 2020-12-21 15:20:10   \n",
       "...                 ...   ...                      ...                 ...   \n",
       "888    001064FEAAB631A1     B  recommender_system_test 2020-12-26 15:55:18   \n",
       "889    001064FEAAB631A1     B  recommender_system_test 2020-12-20 14:43:27   \n",
       "890    001064FEAAB631A1     B  recommender_system_test 2020-12-21 03:19:15   \n",
       "891    001064FEAAB631A1     B  recommender_system_test 2020-12-26 15:55:17   \n",
       "24080  000ABE35EE11412F     A  recommender_system_test                 NaT   \n",
       "\n",
       "         event_name  details session_date  session_year  session_month  \\\n",
       "14333         login      0.0   2020-12-21        2020.0           12.0   \n",
       "14326  product_cart      0.0   2020-12-16        2020.0           12.0   \n",
       "14329  product_page      0.0   2020-12-16        2020.0           12.0   \n",
       "14330  product_page      0.0   2020-12-21        2020.0           12.0   \n",
       "14327  product_cart      0.0   2020-12-21        2020.0           12.0   \n",
       "...             ...      ...          ...           ...            ...   \n",
       "888    product_page      0.0   2020-12-26        2020.0           12.0   \n",
       "889           login      0.0   2020-12-20        2020.0           12.0   \n",
       "890           login      0.0   2020-12-21        2020.0           12.0   \n",
       "891           login      0.0   2020-12-26        2020.0           12.0   \n",
       "24080           NaN      NaN          NaN           NaN            NaN   \n",
       "\n",
       "       session_week  start_day first_date region   device        date  \\\n",
       "14333          52.0       21.0 2020-12-16     EU       PC  2020-12-21   \n",
       "14326          51.0       16.0 2020-12-16     EU       PC  2020-12-16   \n",
       "14329          51.0       16.0 2020-12-16     EU       PC  2020-12-16   \n",
       "14330          52.0       21.0 2020-12-16     EU       PC  2020-12-21   \n",
       "14327          52.0       21.0 2020-12-16     EU       PC  2020-12-21   \n",
       "...             ...        ...        ...    ...      ...         ...   \n",
       "888            52.0       26.0 2020-12-20     EU  Android  2020-12-26   \n",
       "889            51.0       20.0 2020-12-20     EU  Android  2020-12-20   \n",
       "890            52.0       21.0 2020-12-20     EU  Android  2020-12-21   \n",
       "891            52.0       26.0 2020-12-20     EU  Android  2020-12-26   \n",
       "24080           NaN        NaN        NaT    NaN      NaN         NaT   \n",
       "\n",
       "           time  \n",
       "14333  15:20:08  \n",
       "14326  08:24:57  \n",
       "14329  08:24:57  \n",
       "14330  15:20:10  \n",
       "14327  15:20:10  \n",
       "...         ...  \n",
       "888    15:55:18  \n",
       "889    14:43:27  \n",
       "890    03:19:15  \n",
       "891    15:55:17  \n",
       "24080       NaT  \n",
       "\n",
       "[27724 rows x 16 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#users by event name\n",
    "reccomenderdata.sort_values(by='user_id',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>days_to_order_group</th>\n",
       "      <th>Cart</th>\n",
       "      <th>Logged_In</th>\n",
       "      <th>Looked at Product</th>\n",
       "      <th>Purchase</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_name</th>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th rowspan=\"2\" valign=\"top\">login</th>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>2747</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>B</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">product_cart</th>\n",
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       "      <th>B</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">product_page</th>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1780</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>523</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">purchase</th>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "days_to_order_group  Cart  Logged_In  Looked at Product  Purchase\n",
       "event_name   group                                               \n",
       "login        A          0       2747                  0         0\n",
       "             B          0        928                  0         0\n",
       "product_cart A        824          0                  0         0\n",
       "             B        255          0                  0         0\n",
       "product_page A          0          0               1780         0\n",
       "             B          0          0                523         0\n",
       "purchase     A          0          0                  0       872\n",
       "             B          0          0                  0       256"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# event names\n",
    "def data_by_event_name(event_name):\n",
    "    \"\"\"\n",
    "    Labels users by number of days until first order.\n",
    "    \"\"\"\n",
    "    if event_name == 'login':\n",
    "        return 'Logged_In'\n",
    "    if event_name == 'product_cart':\n",
    "        return 'Cart'\n",
    "    if event_name == 'product_page':\n",
    "        return 'Looked at Product'\n",
    "    else:\n",
    "        return 'Purchase'\n",
    "\n",
    "\n",
    "reccomenderdata['days_to_order_group'] = reccomenderdata['event_name'].apply(data_by_event_name)\n",
    "\n",
    "event_data_pivot = reccomenderdata.pivot_table(index=['event_name', 'group'], columns='days_to_order_group', values='user_id', aggfunc='nunique', fill_value=0)\n",
    "display(event_data_pivot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>days_to_order_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>14:43:27</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:56</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>00:04:56</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>A7A3664BD6242119</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-20 15:46:02</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>15:46:02</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>A7A3664BD6242119</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 00:40:58</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>00:40:58</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>A7A3664BD6242119</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 05:19:45</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>05:19:45</td>\n",
       "      <td>Logged_In</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",
       "      <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>27719</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 10:12:15</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>10:12:15</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27720</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-08 22:51:16</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>22:51:16</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27721</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-09 02:28:03</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>02:28:03</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27722</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-10 22:55:14</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>22:55:14</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27723</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-14 12:40:41</td>\n",
       "      <td>login</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>12:40:41</td>\n",
       "      <td>Logged_In</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11190 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                user_id group                  ab_test            event_dt  \\\n",
       "6      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "7      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:56   \n",
       "11     A7A3664BD6242119     A  recommender_system_test 2020-12-20 15:46:02   \n",
       "12     A7A3664BD6242119     A  recommender_system_test 2020-12-21 00:40:58   \n",
       "13     A7A3664BD6242119     A  recommender_system_test 2020-12-25 05:19:45   \n",
       "...                 ...   ...                      ...                 ...   \n",
       "27719  6715343AFBA285AE     B  recommender_system_test 2020-12-07 10:12:15   \n",
       "27720  6715343AFBA285AE     B  recommender_system_test 2020-12-08 22:51:16   \n",
       "27721  6715343AFBA285AE     B  recommender_system_test 2020-12-09 02:28:03   \n",
       "27722  6715343AFBA285AE     B  recommender_system_test 2020-12-10 22:55:14   \n",
       "27723  6715343AFBA285AE     B  recommender_system_test 2020-12-14 12:40:41   \n",
       "\n",
       "      event_name  details session_date  session_year  session_month  \\\n",
       "6          login      0.0   2020-12-07        2020.0           12.0   \n",
       "7          login      0.0   2020-12-25        2020.0           12.0   \n",
       "11         login      0.0   2020-12-20        2020.0           12.0   \n",
       "12         login      0.0   2020-12-21        2020.0           12.0   \n",
       "13         login      0.0   2020-12-25        2020.0           12.0   \n",
       "...          ...      ...          ...           ...            ...   \n",
       "27719      login      0.0   2020-12-07        2020.0           12.0   \n",
       "27720      login      0.0   2020-12-08        2020.0           12.0   \n",
       "27721      login      0.0   2020-12-09        2020.0           12.0   \n",
       "27722      login      0.0   2020-12-10        2020.0           12.0   \n",
       "27723      login      0.0   2020-12-14        2020.0           12.0   \n",
       "\n",
       "       session_week  start_day first_date region   device        date  \\\n",
       "6              50.0        7.0 2020-12-07     EU       PC  2020-12-07   \n",
       "7              52.0       25.0 2020-12-07     EU       PC  2020-12-25   \n",
       "11             51.0       20.0 2020-12-20     EU   iPhone  2020-12-20   \n",
       "12             52.0       21.0 2020-12-20     EU   iPhone  2020-12-21   \n",
       "13             52.0       25.0 2020-12-20     EU   iPhone  2020-12-25   \n",
       "...             ...        ...        ...    ...      ...         ...   \n",
       "27719          50.0        7.0 2020-12-07    CIS  Android  2020-12-07   \n",
       "27720          50.0        8.0 2020-12-07    CIS  Android  2020-12-08   \n",
       "27721          50.0        9.0 2020-12-07    CIS  Android  2020-12-09   \n",
       "27722          50.0       10.0 2020-12-07    CIS  Android  2020-12-10   \n",
       "27723          51.0       14.0 2020-12-07    CIS  Android  2020-12-14   \n",
       "\n",
       "           time days_to_order_group  \n",
       "6      14:43:27           Logged_In  \n",
       "7      00:04:56           Logged_In  \n",
       "11     15:46:02           Logged_In  \n",
       "12     00:40:58           Logged_In  \n",
       "13     05:19:45           Logged_In  \n",
       "...         ...                 ...  \n",
       "27719  10:12:15           Logged_In  \n",
       "27720  22:51:16           Logged_In  \n",
       "27721  02:28:03           Logged_In  \n",
       "27722  22:55:14           Logged_In  \n",
       "27723  12:40:41           Logged_In  \n",
       "\n",
       "[11190 rows x 17 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of users who performed event name #login\n",
    "userswhoperformedloginscreen =  reccomenderdata.query('event_name == \"login\"')\n",
    "userswhoperformedloginscreen "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>ab_test</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>11190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   ab_test  user_id\n",
       "0  recommender_system_test    11190"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userswhoperformedloginscreen.pivot_table(index='ab_test',values='user_id',aggfunc='count').sort_values(by='user_id', ascending=True).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Conclusion\n",
    "Users who performed the \"login\" action between the tests were 11190 in the reccomender system test group out of 27724 total tested and (40%) "
   ]
  },
  {
   "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>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>days_to_order_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>14:43:27</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:57</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>00:04:57</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>A7A3664BD6242119</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-20 15:46:06</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>15:46:06</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>A7A3664BD6242119</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 00:40:59</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>00:40:59</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>A7A3664BD6242119</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 05:19:45</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>05:19:45</td>\n",
       "      <td>Looked at Product</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",
       "      <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>27714</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 10:12:16</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>10:12:16</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27715</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-08 22:51:16</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>22:51:16</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27716</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-09 02:28:04</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>02:28:04</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27717</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-10 22:55:14</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>22:55:14</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27718</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-14 12:40:42</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>12:40:42</td>\n",
       "      <td>Looked at Product</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6930 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                user_id group                  ab_test            event_dt  \\\n",
       "4      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "5      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:57   \n",
       "8      A7A3664BD6242119     A  recommender_system_test 2020-12-20 15:46:06   \n",
       "9      A7A3664BD6242119     A  recommender_system_test 2020-12-21 00:40:59   \n",
       "10     A7A3664BD6242119     A  recommender_system_test 2020-12-25 05:19:45   \n",
       "...                 ...   ...                      ...                 ...   \n",
       "27714  6715343AFBA285AE     B  recommender_system_test 2020-12-07 10:12:16   \n",
       "27715  6715343AFBA285AE     B  recommender_system_test 2020-12-08 22:51:16   \n",
       "27716  6715343AFBA285AE     B  recommender_system_test 2020-12-09 02:28:04   \n",
       "27717  6715343AFBA285AE     B  recommender_system_test 2020-12-10 22:55:14   \n",
       "27718  6715343AFBA285AE     B  recommender_system_test 2020-12-14 12:40:42   \n",
       "\n",
       "         event_name  details session_date  session_year  session_month  \\\n",
       "4      product_page      0.0   2020-12-07        2020.0           12.0   \n",
       "5      product_page      0.0   2020-12-25        2020.0           12.0   \n",
       "8      product_page      0.0   2020-12-20        2020.0           12.0   \n",
       "9      product_page      0.0   2020-12-21        2020.0           12.0   \n",
       "10     product_page      0.0   2020-12-25        2020.0           12.0   \n",
       "...             ...      ...          ...           ...            ...   \n",
       "27714  product_page      0.0   2020-12-07        2020.0           12.0   \n",
       "27715  product_page      0.0   2020-12-08        2020.0           12.0   \n",
       "27716  product_page      0.0   2020-12-09        2020.0           12.0   \n",
       "27717  product_page      0.0   2020-12-10        2020.0           12.0   \n",
       "27718  product_page      0.0   2020-12-14        2020.0           12.0   \n",
       "\n",
       "       session_week  start_day first_date region   device        date  \\\n",
       "4              50.0        7.0 2020-12-07     EU       PC  2020-12-07   \n",
       "5              52.0       25.0 2020-12-07     EU       PC  2020-12-25   \n",
       "8              51.0       20.0 2020-12-20     EU   iPhone  2020-12-20   \n",
       "9              52.0       21.0 2020-12-20     EU   iPhone  2020-12-21   \n",
       "10             52.0       25.0 2020-12-20     EU   iPhone  2020-12-25   \n",
       "...             ...        ...        ...    ...      ...         ...   \n",
       "27714          50.0        7.0 2020-12-07    CIS  Android  2020-12-07   \n",
       "27715          50.0        8.0 2020-12-07    CIS  Android  2020-12-08   \n",
       "27716          50.0        9.0 2020-12-07    CIS  Android  2020-12-09   \n",
       "27717          50.0       10.0 2020-12-07    CIS  Android  2020-12-10   \n",
       "27718          51.0       14.0 2020-12-07    CIS  Android  2020-12-14   \n",
       "\n",
       "           time days_to_order_group  \n",
       "4      14:43:27   Looked at Product  \n",
       "5      00:04:57   Looked at Product  \n",
       "8      15:46:06   Looked at Product  \n",
       "9      00:40:59   Looked at Product  \n",
       "10     05:19:45   Looked at Product  \n",
       "...         ...                 ...  \n",
       "27714  10:12:16   Looked at Product  \n",
       "27715  22:51:16   Looked at Product  \n",
       "27716  02:28:04   Looked at Product  \n",
       "27717  22:55:14   Looked at Product  \n",
       "27718  12:40:42   Looked at Product  \n",
       "\n",
       "[6930 rows x 17 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of users who performed event name #product\n",
    "userswhoperformedproductscreen =  reccomenderdata.query('event_name == \"product_page\"')\n",
    "userswhoperformedproductscreen "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>ab_test</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>6930</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   ab_test  user_id\n",
       "0  recommender_system_test     6930"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userswhoperformedproductscreen.pivot_table(index='ab_test',values='user_id',aggfunc='count').sort_values(by='user_id', ascending=True).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Conclusion\n",
    "Users who performed the \"Product screen\" action between the tests were 6930 in the reccomender system test out of 27724 total tested (25%) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>days_to_order_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:29</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>14:43:29</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:57</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>00:04:57</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>4FF2998A348C484F</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-20 19:06:22</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Mac</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>19:06:22</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>4FF2998A348C484F</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-26 14:39:50</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Mac</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>14:39:50</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>4FF2998A348C484F</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-28 20:00:24</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>EU</td>\n",
       "      <td>Mac</td>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>20:00:24</td>\n",
       "      <td>Cart</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",
       "      <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>27709</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 10:12:15</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>10:12:15</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27710</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-08 22:51:16</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>22:51:16</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27711</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-09 02:28:05</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>02:28:05</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27712</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-10 22:55:14</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>22:55:14</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27713</th>\n",
       "      <td>6715343AFBA285AE</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-14 12:40:43</td>\n",
       "      <td>product_cart</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>CIS</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>12:40:43</td>\n",
       "      <td>Cart</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3247 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                user_id group                  ab_test            event_dt  \\\n",
       "2      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:29   \n",
       "3      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:57   \n",
       "36     4FF2998A348C484F     A  recommender_system_test 2020-12-20 19:06:22   \n",
       "37     4FF2998A348C484F     A  recommender_system_test 2020-12-26 14:39:50   \n",
       "38     4FF2998A348C484F     A  recommender_system_test 2020-12-28 20:00:24   \n",
       "...                 ...   ...                      ...                 ...   \n",
       "27709  6715343AFBA285AE     B  recommender_system_test 2020-12-07 10:12:15   \n",
       "27710  6715343AFBA285AE     B  recommender_system_test 2020-12-08 22:51:16   \n",
       "27711  6715343AFBA285AE     B  recommender_system_test 2020-12-09 02:28:05   \n",
       "27712  6715343AFBA285AE     B  recommender_system_test 2020-12-10 22:55:14   \n",
       "27713  6715343AFBA285AE     B  recommender_system_test 2020-12-14 12:40:43   \n",
       "\n",
       "         event_name  details session_date  session_year  session_month  \\\n",
       "2      product_cart      0.0   2020-12-07        2020.0           12.0   \n",
       "3      product_cart      0.0   2020-12-25        2020.0           12.0   \n",
       "36     product_cart      0.0   2020-12-20        2020.0           12.0   \n",
       "37     product_cart      0.0   2020-12-26        2020.0           12.0   \n",
       "38     product_cart      0.0   2020-12-28        2020.0           12.0   \n",
       "...             ...      ...          ...           ...            ...   \n",
       "27709  product_cart      0.0   2020-12-07        2020.0           12.0   \n",
       "27710  product_cart      0.0   2020-12-08        2020.0           12.0   \n",
       "27711  product_cart      0.0   2020-12-09        2020.0           12.0   \n",
       "27712  product_cart      0.0   2020-12-10        2020.0           12.0   \n",
       "27713  product_cart      0.0   2020-12-14        2020.0           12.0   \n",
       "\n",
       "       session_week  start_day first_date region   device        date  \\\n",
       "2              50.0        7.0 2020-12-07     EU       PC  2020-12-07   \n",
       "3              52.0       25.0 2020-12-07     EU       PC  2020-12-25   \n",
       "36             51.0       20.0 2020-12-20     EU      Mac  2020-12-20   \n",
       "37             52.0       26.0 2020-12-20     EU      Mac  2020-12-26   \n",
       "38             53.0       28.0 2020-12-20     EU      Mac  2020-12-28   \n",
       "...             ...        ...        ...    ...      ...         ...   \n",
       "27709          50.0        7.0 2020-12-07    CIS  Android  2020-12-07   \n",
       "27710          50.0        8.0 2020-12-07    CIS  Android  2020-12-08   \n",
       "27711          50.0        9.0 2020-12-07    CIS  Android  2020-12-09   \n",
       "27712          50.0       10.0 2020-12-07    CIS  Android  2020-12-10   \n",
       "27713          51.0       14.0 2020-12-07    CIS  Android  2020-12-14   \n",
       "\n",
       "           time days_to_order_group  \n",
       "2      14:43:29                Cart  \n",
       "3      00:04:57                Cart  \n",
       "36     19:06:22                Cart  \n",
       "37     14:39:50                Cart  \n",
       "38     20:00:24                Cart  \n",
       "...         ...                 ...  \n",
       "27709  10:12:15                Cart  \n",
       "27710  22:51:16                Cart  \n",
       "27711  02:28:05                Cart  \n",
       "27712  22:55:14                Cart  \n",
       "27713  12:40:43                Cart  \n",
       "\n",
       "[3247 rows x 17 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of users who performed event name #product cart\n",
    "userswhoperformedcartscreen =  reccomenderdata.query('event_name == \"product_cart\"')\n",
    "userswhoperformedcartscreen "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ab_test</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>3247</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   ab_test  user_id\n",
       "0  recommender_system_test     3247"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userswhoperformedcartscreen.pivot_table(index='ab_test',values='user_id',aggfunc='count').sort_values(by='user_id', ascending=True).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Conclusion\n",
    "Users who performed the \"Cart screen\" action between the tests were 3247 in the reccomender system test group out of 27724 total tested(12%)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>first_date</th>\n",
       "      <th>region</th>\n",
       "      <th>device</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>days_to_order_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-07 14:43:27</td>\n",
       "      <td>purchase</td>\n",
       "      <td>99.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>14:43:27</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D1ABA3E2887B6A73</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:04:56</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>EU</td>\n",
       "      <td>PC</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>00:04:56</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>04988C5DF189632E</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-14 18:51:34</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>18:51:34</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>04988C5DF189632E</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-15 02:39:20</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>02:39:20</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>04988C5DF189632E</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-18 04:33:43</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>EU</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>04:33:43</td>\n",
       "      <td>Purchase</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",
       "      <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>27644</th>\n",
       "      <td>15E18335C5DB30C9</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-21 21:22:10</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>N.America</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>21:22:10</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27687</th>\n",
       "      <td>053FB26D6D49EDDC</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-10 04:03:07</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>N.America</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>04:03:07</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27688</th>\n",
       "      <td>053FB26D6D49EDDC</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-11 14:11:37</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-11</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>N.America</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-11</td>\n",
       "      <td>14:11:37</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27689</th>\n",
       "      <td>053FB26D6D49EDDC</td>\n",
       "      <td>A</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-25 00:27:11</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>N.America</td>\n",
       "      <td>Android</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>00:27:11</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27696</th>\n",
       "      <td>9D263B8EF15CF188</td>\n",
       "      <td>B</td>\n",
       "      <td>recommender_system_test</td>\n",
       "      <td>2020-12-16 15:17:29</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>N.America</td>\n",
       "      <td>Mac</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>15:17:29</td>\n",
       "      <td>Purchase</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3331 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                user_id group                  ab_test            event_dt  \\\n",
       "0      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-07 14:43:27   \n",
       "1      D1ABA3E2887B6A73     A  recommender_system_test 2020-12-25 00:04:56   \n",
       "17     04988C5DF189632E     A  recommender_system_test 2020-12-14 18:51:34   \n",
       "18     04988C5DF189632E     A  recommender_system_test 2020-12-15 02:39:20   \n",
       "19     04988C5DF189632E     A  recommender_system_test 2020-12-18 04:33:43   \n",
       "...                 ...   ...                      ...                 ...   \n",
       "27644  15E18335C5DB30C9     A  recommender_system_test 2020-12-21 21:22:10   \n",
       "27687  053FB26D6D49EDDC     A  recommender_system_test 2020-12-10 04:03:07   \n",
       "27688  053FB26D6D49EDDC     A  recommender_system_test 2020-12-11 14:11:37   \n",
       "27689  053FB26D6D49EDDC     A  recommender_system_test 2020-12-25 00:27:11   \n",
       "27696  9D263B8EF15CF188     B  recommender_system_test 2020-12-16 15:17:29   \n",
       "\n",
       "      event_name  details session_date  session_year  session_month  \\\n",
       "0       purchase    99.99   2020-12-07        2020.0           12.0   \n",
       "1       purchase     4.99   2020-12-25        2020.0           12.0   \n",
       "17      purchase     4.99   2020-12-14        2020.0           12.0   \n",
       "18      purchase     4.99   2020-12-15        2020.0           12.0   \n",
       "19      purchase     9.99   2020-12-18        2020.0           12.0   \n",
       "...          ...      ...          ...           ...            ...   \n",
       "27644   purchase     4.99   2020-12-21        2020.0           12.0   \n",
       "27687   purchase     9.99   2020-12-10        2020.0           12.0   \n",
       "27688   purchase     4.99   2020-12-11        2020.0           12.0   \n",
       "27689   purchase     4.99   2020-12-25        2020.0           12.0   \n",
       "27696   purchase     4.99   2020-12-16        2020.0           12.0   \n",
       "\n",
       "       session_week  start_day first_date     region   device        date  \\\n",
       "0              50.0        7.0 2020-12-07         EU       PC  2020-12-07   \n",
       "1              52.0       25.0 2020-12-07         EU       PC  2020-12-25   \n",
       "17             51.0       14.0 2020-12-14         EU   iPhone  2020-12-14   \n",
       "18             51.0       15.0 2020-12-14         EU   iPhone  2020-12-15   \n",
       "19             51.0       18.0 2020-12-14         EU   iPhone  2020-12-18   \n",
       "...             ...        ...        ...        ...      ...         ...   \n",
       "27644          52.0       21.0 2020-12-15  N.America   iPhone  2020-12-21   \n",
       "27687          50.0       10.0 2020-12-10  N.America  Android  2020-12-10   \n",
       "27688          50.0       11.0 2020-12-10  N.America  Android  2020-12-11   \n",
       "27689          52.0       25.0 2020-12-10  N.America  Android  2020-12-25   \n",
       "27696          51.0       16.0 2020-12-16  N.America      Mac  2020-12-16   \n",
       "\n",
       "           time days_to_order_group  \n",
       "0      14:43:27            Purchase  \n",
       "1      00:04:56            Purchase  \n",
       "17     18:51:34            Purchase  \n",
       "18     02:39:20            Purchase  \n",
       "19     04:33:43            Purchase  \n",
       "...         ...                 ...  \n",
       "27644  21:22:10            Purchase  \n",
       "27687  04:03:07            Purchase  \n",
       "27688  14:11:37            Purchase  \n",
       "27689  00:27:11            Purchase  \n",
       "27696  15:17:29            Purchase  \n",
       "\n",
       "[3331 rows x 17 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of users who performed event name #checkout\n",
    "userswhoperformedpurchasescreen =  reccomenderdata.query('event_name == \"purchase\"')\n",
    "userswhoperformedpurchasescreen "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
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       "      <th>user_id</th>\n",
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      "text/plain": [
       "                   ab_test  user_id\n",
       "0  recommender_system_test     3331"
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     "execution_count": 48,
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   ],
   "source": [
    "userswhoperformedpurchasescreen.pivot_table(index='ab_test',values='user_id',aggfunc='count').sort_values(by='user_id', ascending=True).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Conclusion\n",
    "Users who performed the \"Product screen\" action between the tests were 3331 in the reccomender system test group out of 27724 (12%) total tested "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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_name</th>\n",
       "      <th>group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>login</td>\n",
       "      <td>11190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>product_cart</td>\n",
       "      <td>3247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>product_page</td>\n",
       "      <td>6930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>purchase</td>\n",
       "      <td>3331</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     event_name  group\n",
       "0         login  11190\n",
       "1  product_cart   3247\n",
       "2  product_page   6930\n",
       "3      purchase   3331"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#what is the most popular event among reccomender system test\n",
    "pop_event = reccomenderdata.drop(['date'], axis=1).groupby('event_name', as_index=False).agg({'group' : 'count'})\n",
    "display(pop_event)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "Login is the most popular event"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "userswhoperformedloginscreen=  reccomenderdata.query('event_name == \"login\"')\n",
    "userswhoperformedproductscreen =  reccomenderdata.query('event_name == \"product_page\"') \n",
    "userswhoperformedcartscreen =  reccomenderdata.query('event_name == \"product_cart\"')\n",
    "userswhoperformedpurchasescreen =  reccomenderdata.query('event_name == \"purchase\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    20381\n",
       "B     7343\n",
       "Name: group, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reccomenderdata.group.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>days_to_order_group</th>\n",
       "      <th>Cart</th>\n",
       "      <th>Logged_In</th>\n",
       "      <th>Looked at Product</th>\n",
       "      <th>Purchase</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_name</th>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">login</th>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>2747</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0</td>\n",
       "      <td>928</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">product_cart</th>\n",
       "      <th>A</th>\n",
       "      <td>824</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">product_page</th>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1780</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>523</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">purchase</th>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "days_to_order_group  Cart  Logged_In  Looked at Product  Purchase\n",
       "event_name   group                                               \n",
       "login        A          0       2747                  0         0\n",
       "             B          0        928                  0         0\n",
       "product_cart A        824          0                  0         0\n",
       "             B        255          0                  0         0\n",
       "product_page A          0          0               1780         0\n",
       "             B          0          0                523         0\n",
       "purchase     A          0          0                  0       872\n",
       "             B          0          0                  0       256"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(event_data_pivot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>group</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>1</td>\n",
       "      <td>3824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>1</td>\n",
       "      <td>2877</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       group  user_id\n",
       "group                \n",
       "A          1     3824\n",
       "B          1     2877"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usersamples = reccomenderdata.pivot_table(index='group', values='user_id',aggfunc='nunique')\n",
    "usersamples.sort_values(by='user_id',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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_name</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>login</th>\n",
       "      <td>1</td>\n",
       "      <td>3675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_page</th>\n",
       "      <td>1</td>\n",
       "      <td>2303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase</th>\n",
       "      <td>1</td>\n",
       "      <td>1128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_cart</th>\n",
       "      <td>1</td>\n",
       "      <td>1079</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              event_name  user_id\n",
       "event_name                       \n",
       "login                  1     3675\n",
       "product_page           1     2303\n",
       "purchase               1     1128\n",
       "product_cart           1     1079"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eventsamples = reccomenderdata.pivot_table(index='event_name', values='user_id',aggfunc='nunique')\n",
    "eventsamples.sort_values(by='user_id',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>user_id</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
       "      <th>session_week</th>\n",
       "      <th>start_day</th>\n",
       "      <th>group</th>\n",
       "      <th>ab_test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-07 04:02:40</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-08 09:43:14</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-09 00:44:10</td>\n",
       "      <td>purchase</td>\n",
       "      <td>4.99</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>9</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-26 00:33:57</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>26</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-07 04:02:41</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106620</th>\n",
       "      <td>40076B77CFC12421</td>\n",
       "      <td>2020-12-24 04:21:53</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>24</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106621</th>\n",
       "      <td>40076B77CFC12421</td>\n",
       "      <td>2020-12-25 15:37:05</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>25</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106622</th>\n",
       "      <td>40076B77CFC12421</td>\n",
       "      <td>2020-12-26 03:50:17</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>26</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106623</th>\n",
       "      <td>301C602AF78BABAD</td>\n",
       "      <td>2020-12-23 10:39:25</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>23</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106624</th>\n",
       "      <td>85500F5DD194ADBA</td>\n",
       "      <td>2020-12-23 09:33:24</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>23</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>106625 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 user_id            event_dt    event_name  details  \\\n",
       "0       96F27A054B191457 2020-12-07 04:02:40      purchase     4.99   \n",
       "1       96F27A054B191457 2020-12-08 09:43:14      purchase     4.99   \n",
       "2       96F27A054B191457 2020-12-09 00:44:10      purchase     4.99   \n",
       "3       96F27A054B191457 2020-12-26 00:33:57      purchase     9.99   \n",
       "4       96F27A054B191457 2020-12-07 04:02:41  product_page     0.00   \n",
       "...                  ...                 ...           ...      ...   \n",
       "106620  40076B77CFC12421 2020-12-24 04:21:53         login     0.00   \n",
       "106621  40076B77CFC12421 2020-12-25 15:37:05         login     0.00   \n",
       "106622  40076B77CFC12421 2020-12-26 03:50:17         login     0.00   \n",
       "106623  301C602AF78BABAD 2020-12-23 10:39:25         login     0.00   \n",
       "106624  85500F5DD194ADBA 2020-12-23 09:33:24         login     0.00   \n",
       "\n",
       "       session_date  session_year  session_month  session_week  start_day  \\\n",
       "0        2020-12-07          2020             12            50          7   \n",
       "1        2020-12-08          2020             12            50          8   \n",
       "2        2020-12-09          2020             12            50          9   \n",
       "3        2020-12-26          2020             12            52         26   \n",
       "4        2020-12-07          2020             12            50          7   \n",
       "...             ...           ...            ...           ...        ...   \n",
       "106620   2020-12-24          2020             12            52         24   \n",
       "106621   2020-12-25          2020             12            52         25   \n",
       "106622   2020-12-26          2020             12            52         26   \n",
       "106623   2020-12-23          2020             12            52         23   \n",
       "106624   2020-12-23          2020             12            52         23   \n",
       "\n",
       "       group            ab_test  \n",
       "0          B  interface_eu_test  \n",
       "1          B  interface_eu_test  \n",
       "2          B  interface_eu_test  \n",
       "3          B  interface_eu_test  \n",
       "4          B  interface_eu_test  \n",
       "...      ...                ...  \n",
       "106620     B  interface_eu_test  \n",
       "106621     B  interface_eu_test  \n",
       "106622     B  interface_eu_test  \n",
       "106623     B  interface_eu_test  \n",
       "106624     B  interface_eu_test  \n",
       "\n",
       "[106625 rows x 11 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eventsparticipants = ab_events.merge(ab_participants, on='user_id', how='inner')\n",
    "eventsparticipants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>event_dt</th>\n",
       "      <th>event_name</th>\n",
       "      <th>details</th>\n",
       "      <th>session_date</th>\n",
       "      <th>session_year</th>\n",
       "      <th>session_month</th>\n",
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       "      <th>0</th>\n",
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       "      <td>2020-12-09 00:44:10</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-26 00:33:57</td>\n",
       "      <td>purchase</td>\n",
       "      <td>9.99</td>\n",
       "      <td>2020-12-26</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
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       "      <td>interface_eu_test</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>96F27A054B191457</td>\n",
       "      <td>2020-12-07 04:02:41</td>\n",
       "      <td>product_page</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
       "      <th>106620</th>\n",
       "      <td>40076B77CFC12421</td>\n",
       "      <td>2020-12-24 04:21:53</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>24</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
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       "    <tr>\n",
       "      <th>106621</th>\n",
       "      <td>40076B77CFC12421</td>\n",
       "      <td>2020-12-25 15:37:05</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52</td>\n",
       "      <td>25</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
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       "    <tr>\n",
       "      <th>106622</th>\n",
       "      <td>40076B77CFC12421</td>\n",
       "      <td>2020-12-26 03:50:17</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-26</td>\n",
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       "      <td>52</td>\n",
       "      <td>26</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
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       "      <th>106623</th>\n",
       "      <td>301C602AF78BABAD</td>\n",
       "      <td>2020-12-23 10:39:25</td>\n",
       "      <td>login</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>2020</td>\n",
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       "      <td>23</td>\n",
       "      <td>B</td>\n",
       "      <td>interface_eu_test</td>\n",
       "    </tr>\n",
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       "<p>45751 rows × 11 columns</p>\n",
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      ],
      "text/plain": [
       "                 user_id            event_dt    event_name  details  \\\n",
       "0       96F27A054B191457 2020-12-07 04:02:40      purchase     4.99   \n",
       "1       96F27A054B191457 2020-12-08 09:43:14      purchase     4.99   \n",
       "2       96F27A054B191457 2020-12-09 00:44:10      purchase     4.99   \n",
       "3       96F27A054B191457 2020-12-26 00:33:57      purchase     9.99   \n",
       "4       96F27A054B191457 2020-12-07 04:02:41  product_page     0.00   \n",
       "...                  ...                 ...           ...      ...   \n",
       "106620  40076B77CFC12421 2020-12-24 04:21:53         login     0.00   \n",
       "106621  40076B77CFC12421 2020-12-25 15:37:05         login     0.00   \n",
       "106622  40076B77CFC12421 2020-12-26 03:50:17         login     0.00   \n",
       "106623  301C602AF78BABAD 2020-12-23 10:39:25         login     0.00   \n",
       "106624  85500F5DD194ADBA 2020-12-23 09:33:24         login     0.00   \n",
       "\n",
       "       session_date  session_year  session_month  session_week  start_day  \\\n",
       "0        2020-12-07          2020             12            50          7   \n",
       "1        2020-12-08          2020             12            50          8   \n",
       "2        2020-12-09          2020             12            50          9   \n",
       "3        2020-12-26          2020             12            52         26   \n",
       "4        2020-12-07          2020             12            50          7   \n",
       "...             ...           ...            ...           ...        ...   \n",
       "106620   2020-12-24          2020             12            52         24   \n",
       "106621   2020-12-25          2020             12            52         25   \n",
       "106622   2020-12-26          2020             12            52         26   \n",
       "106623   2020-12-23          2020             12            52         23   \n",
       "106624   2020-12-23          2020             12            52         23   \n",
       "\n",
       "       group            ab_test  \n",
       "0          B  interface_eu_test  \n",
       "1          B  interface_eu_test  \n",
       "2          B  interface_eu_test  \n",
       "3          B  interface_eu_test  \n",
       "4          B  interface_eu_test  \n",
       "...      ...                ...  \n",
       "106620     B  interface_eu_test  \n",
       "106621     B  interface_eu_test  \n",
       "106622     B  interface_eu_test  \n",
       "106623     B  interface_eu_test  \n",
       "106624     B  interface_eu_test  \n",
       "\n",
       "[45751 rows x 11 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_A = eventsparticipants[eventsparticipants['group']=='A']\n",
    "sample_A\n",
    "sample_B = eventsparticipants[eventsparticipants['group']=='B']\n",
    "sample_B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users in both samples: 441\n",
      "13638\n",
      "13638\n"
     ]
    }
   ],
   "source": [
    "users_in_both_samples = sample_A[sample_A['user_id'].isin(sample_B['user_id'])]\n",
    "print('Number of users in both samples:', users_in_both_samples['user_id'].nunique())\n",
    "print(eventsparticipants['user_id'].nunique())\n",
    "eda=(eventsparticipants[~eventsparticipants['user_id'].isin(users_in_both_samples['user_id'])])\n",
    "print(eventsparticipants['user_id'].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of users in the control group: 2747\n",
      "Total number of users in the test group: 928\n"
     ]
    }
   ],
   "source": [
    "control= sample_A[sample_A['ab_test']=='recommender_system_test']\n",
    "print('Total number of users in the control group:', control['user_id'].nunique())\n",
    "test= sample_B[sample_B['ab_test']=='recommender_system_test']\n",
    "print('Total number of users in the test group:', test['user_id'].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "def function(e):\n",
    "    group_A = sample_A[(sample_A['event_name']==e) & (sample_A['ab_test']=='recommender_system_test')]\n",
    "    group_B = sample_B[(sample_B['event_name']==e) & (sample_B['ab_test']=='recommender_system_test')]\n",
    "    convert_A = group_A['user_id'].nunique()\n",
    "    convert_B = group_B['user_id'].nunique()\n",
    "    users_A = control['user_id'].nunique()\n",
    "    users_B = test['user_id'].nunique()\n",
    "    print('Number of users in group A performed this action:', convert_A)\n",
    "    print('Number of users in group B performed this action:', convert_B)\n",
    "    print()\n",
    "    sample= np.array([users_A, users_B])\n",
    "    convert= np.array([convert_A, convert_B])\n",
    "    p1= convert[0]/sample[0]\n",
    "    p2= convert[1]/sample[1]\n",
    "    alpha= .05\n",
    "    p_combined = (convert[0]+ convert[1])/(sample[0]+ sample[1])\n",
    "    difference = p1-p2\n",
    "    z_value = difference/mth.sqrt(p_combined * (1-p_combined) * (1/sample[0] + 1/sample[1]))\n",
    "    distr = st.norm(0,1)\n",
    "    p_value= (1-distr.cdf(abs(z_value))) *2\n",
    "    print('p_value:', p_value)\n",
    "    if(p_value < alpha):\n",
    "        print('Rejecting the null hypothesis: there is a significant difference between the proportions')\n",
    "    else:\n",
    "        print('Failed to reject the null hypothesis: there is no reason to consider the proportions different')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users in group A performed this action: 1780\n",
      "Number of users in group B performed this action: 523\n",
      "\n",
      "p_value: 4.310980554755872e-06\n",
      "Rejecting the null hypothesis: there is a significant difference between the proportions\n"
     ]
    }
   ],
   "source": [
    "function('product_page')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users in group A performed this action: 872\n",
      "Number of users in group B performed this action: 256\n",
      "\n",
      "p_value: 0.017592402663314743\n",
      "Rejecting the null hypothesis: there is a significant difference between the proportions\n"
     ]
    }
   ],
   "source": [
    "function('purchase')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users in group A performed this action: 2747\n",
      "Number of users in group B performed this action: 928\n",
      "\n",
      "p_value: nan\n",
      "Failed to reject the null hypothesis: there is no reason to consider the proportions different\n"
     ]
    }
   ],
   "source": [
    "function('login')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users in group A performed this action: 824\n",
      "Number of users in group B performed this action: 255\n",
      "\n",
      "p_value: 0.14534814557238196\n",
      "Failed to reject the null hypothesis: there is no reason to consider the proportions different\n"
     ]
    }
   ],
   "source": [
    "function('product_cart')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "Based on the values of the login screen, product page, the values on the cart, and purchase page we see that all of the valuess demonstrate a significant difference between the a and b proportions with the data set specific to the recommender_system_test."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 4. Ending Observations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "- Order actions that take place are login, product page, product cart and purchase. \n",
    "- As we investigate the funnel we see that users who ended up taking steps closer to a purchase that inevitably resulted in purchases. The users who logged in into the main screen were 58697 (71% of the users) Then the users that viewed products were 22212(27% of the users), then 1336 users added products to the cart (2% of the users), then we ended up getting one user who actually made a purchase. The promotions ended up resulting in a retention of less than 1%\n",
    "- Although we see an average of 6 events per user it doesnt really add much value when it comes to the test subjects\n",
    "- The number of unique users in the samples are only 18268 which could mean that users are partipating in both tests or continually accessing the accounts looking for new promotions, although it doesnt neccessarily result in purchase activity the review of the events distributed by date correlates with this information because we see login spanning many more days then, views for products much higher than purchase days and product cart days\n",
    "- Most of the events occured the week of christmas\n",
    "\n",
    "###### Out of the test groups we found the following distributions\n",
    "- Users who performed the \"login\" action between the tests were 11190 in the reccomender system test group out of 27724 total tested and (40%) and 35145 out of the interface eu test group total 82644 (43%)\n",
    "- Users who performed the \"Product screen\" action between the tests were 6930 in the reccomender system test out of 27724 total tested (25%) and 23095 out of the interface eu test total 82644 (28%)\n",
    "- Users who performed the \"Cart screen\" action between the tests were 3247 in the reccomender system test group out of 27724 total tested(12%) and 11602 out of the interface eu test  group total 82644 (14%)\n",
    "- Users who performed the \"Product screen\" action between the tests were 3331 in the reccomender system test group out of 27724 (12%) total tested and 12085 out of the interface eu test group total 82644 (15%)\n",
    "\n",
    "- Based on the values of the login screen, product page, the values on the cart, and purchase page we see that all of the valuess demonstrate a significant difference between the a and b proportions with the data set specific to the recommender_system_test.\n",
    "\n",
    "- Based on this information it looks like the ab testing groups demonstrate completely different distributions when we look at the reccomender data set. The test group that has the most valuable information is the interface_eu_test because there were more subjects and more data to demonstrate user behavior.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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