02_Spanish Translation A-B Test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spanish Translation A/B Test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Goal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A/B tests play a huge role in website optimization. Analyzing A/B tests data is a very important data scientist responsibility. Especially, data scientists have to make sure that results are reliable, trustworthy, and conclusions can be drawn.\n",
    "<br>\n",
    "<br>\n",
    "Furthermore, companies often run tens, if not hundreds, of A/B tests at the same time. Manually analyzing all of them would require lot of time and people. Therefore, it is common practice to look at the typical A/B test analysis steps and try to automate as much as possible. This frees up time for the data scientists to work on more high level topics.\n",
    "<br>\n",
    "<br>\n",
    "In this challenge, you will have to analyze results from an A/B test. Also, you will be asked to design an algorithm to automate some steps."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Challenge Description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Company XYZ is a worldwide e-commerce site with localized versions of the site.\n",
    "<br>\n",
    "<br>\n",
    "A data scientist at XYZ noticed that Spain-based users have a much higher conversion rate than any other Spanish-speaking country. She therefore went and talked to the international team in charge of Spain And LatAm to see if they had any ideas about why that was happening.\n",
    "<br>\n",
    "<br>\n",
    "Spain and LatAm country manager suggested that one reason could be translation. All Spanishspeaking countries had the same translation of the site which was written by a Spaniard. They agreed to try a test where each country would have its one translation written by a local. That is, Argentinian users would see a translation written by an Argentinian, Mexican users by a Mexican and so on. Obviously, nothing would change for users from Spain.\n",
    "<br>\n",
    "<br>\n",
    "After they run the test however, they are really surprised cause the test is negative. I.e., it appears that the non-localized translation was doing better!\n",
    "<br>\n",
    "<br>\n",
    "You are asked to:\n",
    "* Confirm that the test is actually negative. That is, it appears that the old version of the site with just one translation across Spain and LatAm performs better\n",
    "* Explain why that might be happening. Are the localized translations really worse?\n",
    "* If you identified what was wrong, design an algorithm that would return FALSE if the same problem is happening in the future and TRUE if everything is good and the results can be trusted."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"test_table\" - general information about the test results.<br>\n",
    "Columns:\n",
    "* **user_id** : the id of the user. Unique by user. Can be joined to user id in the other table. For each user, we just check whether conversion happens the first time they land on the site since the test started.\n",
    "* **date** : when they came to the site for the first time since the test started\n",
    "* **source** : marketing channel: Ads, SEO, Direct . Direct means everything except for ads and SEO. Such as directly typing site URL on the browser, downloading the app w/o coming from SEO or Ads, referral friend, etc.\n",
    "* **device** : device used by the user. It can be mobile or web \n",
    "* **browser_language** : in browser or app settings, the language chosen by the user. It can be EN, ES, Other (Other means any language except for English and Spanish) \n",
    "* **ads_channel** : if marketing channel is ads, this is the site where the ad was displayed. It can be: Google, Facebook, Bing, Yahoo ,Other. If the user didn't come via an ad, this field is NA\n",
    "* **browser** : user browser. It can be: IE, Chrome, Android_App, FireFox, Iphone_App, Safari, Opera\n",
    "* **conversion** : whether the user converted (1) or not (0). This is our label. A test is considered successful if it increases the proportion of users who convert.\n",
    "* **test** : users are randomly split into test (1) and control (0). Test users see the new translation and control the old one. For Spain-based users, this is obviously always 0 since there is no change there."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"user_table\" - some information about the user<br>\n",
    "Columns:\n",
    "* **user_id** : the id of the user. It can be joined to user id in the other table\n",
    "* **sex** : user sex: Male or Female\n",
    "* **age** : user age (self-reported)\n",
    "* **country** : user country based on ip address"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "==================================================================================="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir('F:\\Data_Science\\Product_sense\\DS take home challenges\\Dataset\\Translation_Test')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_table = pd.read_csv('user_table.csv')\n",
    "test_table = pd.read_csv('test_table.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic info "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>765821</td>\n",
       "      <td>M</td>\n",
       "      <td>20</td>\n",
       "      <td>Mexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>343561</td>\n",
       "      <td>F</td>\n",
       "      <td>27</td>\n",
       "      <td>Nicaragua</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>118744</td>\n",
       "      <td>M</td>\n",
       "      <td>23</td>\n",
       "      <td>Colombia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>987753</td>\n",
       "      <td>F</td>\n",
       "      <td>27</td>\n",
       "      <td>Venezuela</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>554597</td>\n",
       "      <td>F</td>\n",
       "      <td>20</td>\n",
       "      <td>Spain</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id sex  age    country\n",
       "0   765821   M   20     Mexico\n",
       "1   343561   F   27  Nicaragua\n",
       "2   118744   M   23   Colombia\n",
       "3   987753   F   27  Venezuela\n",
       "4   554597   F   20      Spain"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(452867, 4)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_table.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>date</th>\n",
       "      <th>source</th>\n",
       "      <th>device</th>\n",
       "      <th>browser_language</th>\n",
       "      <th>ads_channel</th>\n",
       "      <th>browser</th>\n",
       "      <th>conversion</th>\n",
       "      <th>test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>315281</td>\n",
       "      <td>2015-12-03</td>\n",
       "      <td>Direct</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IE</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>497851</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>Google</td>\n",
       "      <td>IE</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>848402</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>290051</td>\n",
       "      <td>2015-12-03</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>Other</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>548435</td>\n",
       "      <td>2015-11-30</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>Google</td>\n",
       "      <td>FireFox</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id        date  source  device browser_language ads_channel  \\\n",
       "0   315281  2015-12-03  Direct     Web               ES         NaN   \n",
       "1   497851  2015-12-04     Ads     Web               ES      Google   \n",
       "2   848402  2015-12-04     Ads     Web               ES    Facebook   \n",
       "3   290051  2015-12-03     Ads  Mobile            Other    Facebook   \n",
       "4   548435  2015-11-30     Ads     Web               ES      Google   \n",
       "\n",
       "       browser  conversion  test  \n",
       "0           IE           1     0  \n",
       "1           IE           0     1  \n",
       "2       Chrome           0     0  \n",
       "3  Android_App           0     1  \n",
       "4      FireFox           0     1  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(453321, 9)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_table.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we have 454 data missing in the user table\n"
     ]
    }
   ],
   "source": [
    "print('we have {} data missing in the user table'.format(test_table.shape[0] - user_table.shape[0])) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>source</th>\n",
       "      <th>device</th>\n",
       "      <th>browser_language</th>\n",
       "      <th>ads_channel</th>\n",
       "      <th>browser</th>\n",
       "      <th>conversion</th>\n",
       "      <th>test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>765821</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>2015-12-02</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>ES</td>\n",
       "      <td>Yahoo</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>343561</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Nicaragua</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>Safari</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>118744</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>2015-11-30</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>ES</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>987753</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Venezuela</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IE</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>554597</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Spain</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Direct</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>453316</td>\n",
       "      <td>490883</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>Direct</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>EN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>453317</td>\n",
       "      <td>741971</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-30</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>453318</td>\n",
       "      <td>722387</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-30</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FireFox</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>453319</td>\n",
       "      <td>752632</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>Google</td>\n",
       "      <td>IE</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>453320</td>\n",
       "      <td>443313</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>ES</td>\n",
       "      <td>Google</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>453321 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        user_id  sex   age    country        date  source  device  \\\n",
       "0        765821    M  20.0     Mexico  2015-12-02     Ads  Mobile   \n",
       "1        343561    F  27.0  Nicaragua  2015-12-04     Ads     Web   \n",
       "2        118744    M  23.0   Colombia  2015-11-30     Ads  Mobile   \n",
       "3        987753    F  27.0  Venezuela  2015-12-04     SEO     Web   \n",
       "4        554597    F  20.0      Spain  2015-12-04  Direct     Web   \n",
       "...         ...  ...   ...        ...         ...     ...     ...   \n",
       "453316   490883  NaN   NaN        NaN  2015-12-01  Direct  Mobile   \n",
       "453317   741971  NaN   NaN        NaN  2015-11-30     SEO     Web   \n",
       "453318   722387  NaN   NaN        NaN  2015-11-30     SEO     Web   \n",
       "453319   752632  NaN   NaN        NaN  2015-12-04     Ads     Web   \n",
       "453320   443313  NaN   NaN        NaN  2015-12-04     Ads  Mobile   \n",
       "\n",
       "       browser_language ads_channel      browser  conversion  test  \n",
       "0                    ES       Yahoo  Android_App           0     1  \n",
       "1                    ES    Facebook       Safari           0     0  \n",
       "2                    ES    Facebook  Android_App           0     1  \n",
       "3                    ES         NaN           IE           0     1  \n",
       "4                    ES         NaN       Chrome           0     0  \n",
       "...                 ...         ...          ...         ...   ...  \n",
       "453316               EN         NaN  Android_App           0     1  \n",
       "453317               ES         NaN       Chrome           0     1  \n",
       "453318               ES         NaN      FireFox           0     1  \n",
       "453319               ES      Google           IE           0     1  \n",
       "453320               ES      Google  Android_App           0     0  \n",
       "\n",
       "[453321 rows x 12 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merge two tables\n",
    "data = pd.merge(user_table, test_table, how='right')     # we don't use data in test_table\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 453321 entries, 0 to 453320\n",
      "Data columns (total 12 columns):\n",
      "user_id             453321 non-null int64\n",
      "sex                 452867 non-null object\n",
      "age                 452867 non-null float64\n",
      "country             452867 non-null object\n",
      "date                453321 non-null object\n",
      "source              453321 non-null object\n",
      "device              453321 non-null object\n",
      "browser_language    453321 non-null object\n",
      "ads_channel         181877 non-null object\n",
      "browser             453321 non-null object\n",
      "conversion          453321 non-null int64\n",
      "test                453321 non-null int64\n",
      "dtypes: float64(1), int64(3), object(8)\n",
      "memory usage: 65.0+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>age</th>\n",
       "      <th>conversion</th>\n",
       "      <th>test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>453321.000000</td>\n",
       "      <td>452867.000000</td>\n",
       "      <td>453321.000000</td>\n",
       "      <td>453321.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>499937.514728</td>\n",
       "      <td>27.130740</td>\n",
       "      <td>0.049579</td>\n",
       "      <td>0.476446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>288665.193436</td>\n",
       "      <td>6.776678</td>\n",
       "      <td>0.217073</td>\n",
       "      <td>0.499445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>249816.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>500019.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>749522.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>1000000.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              user_id            age     conversion           test\n",
       "count   453321.000000  452867.000000  453321.000000  453321.000000\n",
       "mean    499937.514728      27.130740       0.049579       0.476446\n",
       "std     288665.193436       6.776678       0.217073       0.499445\n",
       "min          1.000000      18.000000       0.000000       0.000000\n",
       "25%     249816.000000      22.000000       0.000000       0.000000\n",
       "50%     500019.000000      26.000000       0.000000       0.000000\n",
       "75%     749522.000000      31.000000       0.000000       1.000000\n",
       "max    1000000.000000      70.000000       1.000000       1.000000"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A/B Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First check whether Spain converts better than other countries\n",
    "groupby_country = data[data['test'] == 0][['country','conversion']].groupby('country').mean()\n",
    "groupby_country = groupby_country.reset_index()\n",
    "groupby_country = groupby_country.sort_values(by = 'conversion', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18, 6))\n",
    "sns.barplot(x = 'country', y = 'conversion', data = groupby_country, palette='Set2')\n",
    "plt.title('Conversion rate vs Country', fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FuO/Bx7oe76aPHjHCyKTumZQYRVZSJiYrEZKkVp4XJEnqnkmJUWQlReOdiTVJkiRJvWRSYgKpu/nWZVuNMDBNGCbWJEmSJPWSSQlJkiSNiC3oJEkby6SExiUf6iNJUvNsQTd+2KJW0li1SdMBSJIkSZKkycmkhCRJkiRJaoS3b7TwvkhJkqR63XfaS7ouu2bVNsBU1qy6t6vxdjrl9o2ITJLUBJMSLUZyX6QnVkmSJEmSRqbWpEREHAj8CzAF+HxmfqRt+GbABcDuwEPAmzLznoiYA/wYuKsU/e/MfGedsUqSJEka/3wgujS+1JaUiIgpwFnAfkAfcGNELMrMO1uKHQM8nJk7R8QC4HTgTWXYzzJzt7rikwZTZwsYsBWMJGlD3Z4/POf0lj9eJal5dbaU2BNYlpl3A0TExcAhQGtS4hDg1NJ9KfCpiIgaY5LGHStMkiRJkiaqOt++sQNwf8vnvtKvY5nMXAM8Cswsw+ZGxC0R8b2I+ONOXxARx0bEkohYsnLlyt5GL0mSJEmSalVnS4lOLR6yyzK/AHbKzIciYnfgaxHx4sz89QYFM88GzgaYP39++7QlSZJ6ou5Wa5dtNcLAJEka5+pMSvQBO7Z8ng08MECZvoiYCswAVmVmAk8CZOZNEfEz4HeBJcMNwkqEJEmSJEljU1dJiYiYBbwdmNM6TmYePchoNwLzImIusBxYALy5rcwi4EjgOuBQ4MrMzPJ9qzJzbUS8EJgH3N3VHI1h205fB6wp/yVNdt0mP31WyODG2oNp60yGT6b1KknSaBpr9YnJpNuWEl8HrgW+C6ztZoTMXBMRxwGXU70S9NzMXBoRpwFLMnMRcA5wYUQsA1ZRJS4AXgmcFhFryve9MzNXdTtTY9UJL32k6RAmpXXTttjgvzbkAXhicr1KkiRpPOg2KbF5Zr5/uBPPzMXA4rZ+p7R0rwYO6zDeV4GvDvf7pE6emLd/0yFIkqRJqM4EsclhSRNFt0mJb0bEa0qSQZKkYanzlgaf7SNJkjR+dZuUOB74u4h4Cni69MvM3LqesCRJktQEHxIuSRpNXSUlMtPThyRJDfNZIZKk0eR5R6Oh61eCRsTBVA+gBLg6M79ZT0jS+OJbVSRJkiRpZLp9JehHgD2AL5Vex0fE3pl5Um2RNcC3NGgkfKuKJEnS5GHrAam3um0p8Rpgt8xcBxAR5wO3ABMqKeFbGjTemViTJEmSNJ50ffsG8FxgVemeUUMskjaSiTVJmti8ZVDSSI33i1c+hHfi6jYp8U/ALRFxFRBUz5Y4ubaoNO5ZaZIkqfe8ZVDSSHnxSmNVt2/fuCgirqZ6rkQA78/MFXUGpvHNSpMkabIa71cjxxIvckjSxDdoUiIifj8zfxIRLy+9+sr/7SNi+8y8ud7wJEmSxhevRvaOFzkmJpNNkloN1VLifcCxwMc6DEvg1T2PSJIkSRpjbAHTOyabJLUaNCmRmceW/68anXAkjWVe2ZAkTVa2gJGkenT1TImIOAz4dmY+FhF/D7wc+FBm3lJrdJLGFK9sSJIkSeqlTbos94GSkNgbOAA4H/i3+sKSJEmSJEkTXbdJibXl/58Bn8nMrwPT6glJo2HdtC1Yu9nW3hcpSZIkSWpMV7dvAMsj4rPAnwKnR8RmdJ/Q0BjkfZGSJEmSpKZ1m1h4I3A5cGBmPgJsA5xYW1SSpGfYskmSJEkT1ZAtJSJiE+CGzNy1v19m/gL4RZ2BSZIqdbds8q0qkqTJyle9Ss0bMimRmesi4taI2Ckz7xuNoCRJo8e3qjTHyrDGO7fh3hlLCeLJtF69pVlqXrfPlHg+sDQibgCe6O+ZmQfXEpUkSZOAlWGNd27DvTOWEsSuV0mjqdukxAdrjUKSJEmSJE06XSUlMvN7EfECYF5mfjciNgem1BuaJEmSJEmayLp6+0ZEvB24FPhs6bUD8LW6gpIkSZIkSRNft68EfRfwCuDXAJn5U+B5dQUlSZIkSZImvm6fKfFkZj4VEQBExFQga4tKkqQajKWn29dtMs2rJEkav7pNSnwvIv4OeE5E7Af8NfCN+sKSJKn3xtLT7es2meZVkiSNX93evnESsBK4HXgHsBj4+7qCkiRJkiSNH9tOX8fvPMcWehq+bltKHAJckJmfqzMYSZIkSdL4Yws9jVS3LSUOBv4nIi6MiD8rz5SQJEmSJA3A1gPS0LpKSmTmXwE7A/8OvBn4WUR8fqjxIuLAiLgrIpZFxEkdhm8WEZeU4ddHxJy24TtFxOMRcUI3cUqSxr9107Zg7WZbs27aFk2HIknSRjnhpY/wkT1X2YpAGkTXLR4y8+mI+E+qt248h+qWjrcNVD4ipgBnAfsBfcCNEbEoM+9sKXYM8HBm7hwRC4DTgTe1DD8T+M9uY5QkjX9PzNu/6RAkSZI0SrpqKVFaPJwHLAMOBT4PPH+I0fYElmXm3Zn5FHAxVSKj1SHA+aX7UmDfKO8djYjXAXcDS7uJUZIkSZIkjS/dtpQ4iiqp8I7MfLLLcXYA7m/53Af84UBlMnNNRDwKzIyI3wLvp2plMeCtGxFxLHAswE477dRlWJIkSZIkjUz1jBCfFdIrXSUlMnPBCKYdnSbVZZkPAmdm5uOl4cRAcZ0NnA0wf/789mlLkiRJktRTPiOkt7pKSkTEG6ie9/A8qkRCAJmZWw8yWh+wY8vn2cADA5TpK2/0mAGsompRcWhEnAE8F1gXEasz81PdxCtJkiRJksa+bm/fOAN4bWb+eBjTvhGYFxFzgeXAAqo3d7RaBBwJXEf1rIorMzOBP+4vEBGnAo+bkJAkSZIkaWLpNinxy2EmJPqfEXEccDkwBTg3M5dGxGnAksxcBJwDXBgRy6haSIzkNhFJkiRJkjQOdZuUWBIRlwBfA5550GVm/sdgI2XmYmBxW79TWrpXA4cNMY1Tu4xRkiRJkiSNI90mJbYGfgO0vjw+gUGTEpIkSZIkSQPp9u0bf1V3IJIkSZIkaXLZpJtCETE7Ii6LiF9FxC8j4qsRMbvu4CRJkiRJ0sTVVVIC+ALVmzK2B3YAvlH6SZIkSZIkjUi3SYlZmfmFzFxT/s4DZtUYlyRJkiRJw7Zu2has3Wxr1k3boulQ1IVuH3T5YES8FbiofD4ceKiekCRJkiRJGpkn5u0/dCGNGd22lDgaeCOwAvgFcCjgwy8lSZIkSdKIddtS4kPAkZn5MEBEbAP8M1WyQpIkSZIkadi6bSnx0v6EBEBmrgJeVk9IkiRJkiRpMug2KbFJRPyv/g+lpUS3rSwkSZIkSZKepdvEwseAH0bEpUBSPV/iw7VFJUmSJEmSJryukhKZeUFELAFeDQTwhsy8s9bIJEmSJEnShNb1LRglCWEiQpIkSZIk9US3z5SQJEmSJEnqKZMSkiRJkiSpESYlJEmSJElSI0xKSJIkSZKkRpiUkCRJkiRJjTApIUmSJEmSGmFSQpIkSZIkNcKkhCRJkiRJaoRJCUmSJEmS1AiTEpIkSZIkqREmJSRJkiRJUiNMSkiSJEmSpEaYlJAkSZIkSY0wKSFJkiRJkhphUkKSJEmSJDXCpIQkSZIkSWpErUmJiDgwIu6KiGURcVKH4ZtFxCVl+PURMaf03zMiflT+bo2I19cZpyRJkiRJGn21JSUiYgpwFnAQsAtweETs0lbsGODhzNwZOBM4vfS/A5ifmbsBBwKfjYipdcUqSZIkSZJGX50tJfYElmXm3Zn5FHAxcEhbmUOA80v3pcC+ERGZ+ZvMXFP6TweyxjglSZIkSVID6kxK7ADc3/K5r/TrWKYkIR4FZgJExB9GxFLgduCdLUmKZ0TEsRGxJCKWrFy5soZZkCRJkiRJdakzKREd+rW3eBiwTGZen5kvBvYATo6I6c8qmHl2Zs7PzPmzZs3a6IAlSZIkSdLoqTMp0Qfs2PJ5NvDAQGXKMyNmAKtaC2Tmj4EngF1ri1SSJEmSJI26OpMSNwLzImJuREwDFgCL2sosAo4s3YcCV2ZmlnGmAkTEC4DfA+6pMVZJkiRJkjTKanujRWauiYjjgMuBKcC5mbk0Ik4DlmTmIuAc4MKIWEbVQmJBGX1v4KSIeBpYB/x1Zj5YV6ySJEmSJGn01fqazcxcDCxu63dKS/dq4LAO410IXFhnbJIkSZIkqVl13r4hSZIkSZI0IJMSkiRJkiSpESYlJEmSJElSI0xKSJIkSZKkRpiUkCRJkiRJjTApIUmSJEmSGmFSQpIkSZIkNcKkhCRJkiRJaoRJCUmSJEmS1AiTEpIkSZIkqREmJSRJkiRJUiNMSkiSJEmSpEaYlJAkSZIkSY0wKSFJkiRJkhphUkKSJEmSJDXCpIQkSZIkSWqESQlJkiRJktQIkxKSJEmSJKkRJiUkSZIkSVIjTEpIkiRJkqRGmJSQJEmSJEmNMCkhSZIkSZIaYVJCkiRJkiQ1wqSEJEmSJElqhEkJSZIkSZLUiKlNByBJkiRJkoZv4cKFrFixgu22244zzjij6XBGxKSEJEmSJEnj0IoVK1i+fHnTYWwUb9+QJEmSJEmNMCkhSZIkSZIaUWtSIiIOjIi7ImJZRJzUYfhmEXFJGX59RMwp/feLiJsi4vby/9V1xilJkiRJkkZfbUmJiJgCnAUcBOwCHB4Ru7QVOwZ4ODN3Bs4ETi/9HwRem5kvAY4ELqwrTkmSJEmS1Iw6W0rsCSzLzLsz8yngYuCQtjKHAOeX7kuBfSMiMvOWzHyg9F8KTI+IzWqMVZIkSZIkjbI6kxI7APe3fO4r/TqWycw1wKPAzLYyfwHckplPtn9BRBwbEUsiYsnKlSt7FrgkSZIkSapfnUmJ6NAvh1MmIl5MdUvHOzp9QWaenZnzM3P+rFmzRhyoJEmSJEkafXUmJfqAHVs+zwYeGKhMREwFZgCryufZwGXAEZn5sxrjlCRJkiRJDagzKXEjMC8i5kbENGABsKitzCKqB1kCHApcmZkZEc8FvgWcnJk/qDFGSZIkSZLUkNqSEuUZEccBlwM/Br6SmUsj4rSIOLgUOweYGRHLgPcB/a8NPQ7YGfhARPyo/D2vrlglSZIkSdLom1rnxDNzMbC4rd8pLd2rgcM6jPcPwD/UGZskSZIkSWpWnbdvSJIkSZIkDcikhCRJkiRJakStt29IkiQBLFy4kBUrVrDddttxxhlnNB2OJEkaI0xKSJKk2q1YsYLly5c3HYYkSRpjvH1DkiRJkiQ1wqSEJEmSJElqhLdvSJIkSZKkZxmNZ0KZlJAkSZIkSc8yGs+E8vYNSZIkSZLUCJMSkiRJkiSpESYlJEmSJElSI0xKSJIkSZKkRvigS0mSNK6NxpPBJUlSPUxKSJKkEdn9xAu6LrvVg48xBbjvwce6Hu+mjx7RVbnReDK4JEmqh7dvSJIkSZKkRpiUkCRJkiRJjTApIUmSJEmSGmFSQpIkSZIkNcIHXUqSpDHpvtNe0lW5Nau2AaayZtW9XY+z0ym3b0RkkiSpV2wpIUmSJEmSGmFSQpIkSZIkNcLbNyRJkiRJmiS6vdURRucWSVtKSJIkSZKkRthSQpIk1W7dtC02+N9L205fB6wp/yVJ0nhiUkKSJNXuiXn71zbtE176SG3TliSpCbufeEFX5bZ68DGmAPc9+FjX41y21UYEVgNv35AkSZIkSY0wKSFJkiRJkhphUkKSJEmSJDWi1qRERBwYEXdFxLKIOKnD8M0i4pIy/PqImFP6z4yIqyLi8Yj4VJ0xSpIkSZKkZtSWlIiIKcBZwEHALsDhEbFLW7FjgIczc2fgTOD00n818AHghLrikyRJkiRJzaqzpcSewLLMvDsznwIuBg5pK3MIcH7pvhTYNyIiM5/IzO9TJSckSZIkSdIEVGdSYgfg/pbPfaVfxzKZuQZ4FJhZY0ySJEmSJGmMqDMpER365QjKDPwFEcdGxJKIWLJy5cphBSdJkiRJkppVZ1KiD9ix5fNs4IGBykTEVGAGsKrbL8jMszNzfmbOnzVr1kaGK0mSJEmSRlOdSYkbgXkRMTcipgELgEVtZRYBR5buQ4ErM7PrlhKSJEmSJGn8mlrXhDNzTUQcB1wOTAHOzcylEXEasCQzFwHnABdGxDKqFhIL+sePiHuArYFpEfE6YP/MvLOueCVJkiRJ0nrbTl8HrCn/61FbUgIgM4PJhr8AABvcSURBVBcDi9v6ndLSvRo4bIBx59QZmyRJkiRJGtgJL32k9u+o8/YNSZIkSZKkAZmUkCRJkiRJjTApIUmSJEmSGmFSQpIkSZIkNcKkhCRJkiRJaoRJCUmSJEmS1AiTEpIkSZIkqREmJSRJkiRJUiNMSkiSJEmSpEaYlJAkSZIkSY0wKSFJkiRJkhphUkKSJEmSJDXCpIQkSZIkSWqESQlJkiRJktQIkxKSJEmSJKkRJiUkSZIkSVIjTEpIkiRJkqRGmJSQJEmSJEmNMCkhSZIkSZIaYVJCkiRJkiQ1wqSEJEmSJElqhEkJSZIkSZLUCJMSkiRJkiSpESYlJEmSJElSI0xKSJIkSZKkRkxtOgBJkiRJkjR866ZtscH/8cikhCRJkiRJ49AT8/ZvOoSN5u0bkiRJkiSpESYlJEmSJElSI2pNSkTEgRFxV0Qsi4iTOgzfLCIuKcOvj4g5LcNOLv3viogD6oxTkiRJkiSNvtqSEhExBTgLOAjYBTg8InZpK3YM8HBm7gycCZxext0FWAC8GDgQ+HSZniRJkiRJmiDqbCmxJ7AsM+/OzKeAi4FD2socApxfui8F9o2IKP0vzswnM/PnwLIyPUmSJEmSNEHUmZTYAbi/5XNf6dexTGauAR4FZnY5riRJkiRJGsciM+uZcMRhwAGZ+bby+S+BPTPz3S1llpYyfeXzz6haRJwGXJeZXyz9zwEWZ+ZX277jWODY8vH3gLtqmZnBbQs82MD3NsF5nZic14nJeZ2YJtO8wuSaX+d1YnJeJybndWJyXuv3gsyc1d5zao1f2Afs2PJ5NvDAAGX6ImIqMANY1eW4ZObZwNk9jHnYImJJZs5vMobR4rxOTM7rxOS8TkyTaV5hcs2v8zoxOa8Tk/M6MTmvzanz9o0bgXkRMTciplE9uHJRW5lFwJGl+1DgyqyabiwCFpS3c8wF5gE31BirJEmSJEkaZbW1lMjMNRFxHHA5MAU4NzOXRsRpwJLMXAScA1wYEcuoWkgsKOMujYivAHcCa4B3ZebaumKVJEmSJEmjr87bN8jMxcDitn6ntHSvBg4bYNwPAx+uM74eafT2kVHmvE5MzuvE5LxOTJNpXmFyza/zOjE5rxOT8zoxOa8Nqe1Bl5IkSZIkSYOp85kSkiRJkiRJA5rUSYmIyIi4sOXz1IhYGRHfHOH0Do6Ik3oX4bC+OyPiYy2fT4iIU0v3OyPiiCbiqltEbBcRF0fEzyLizohYHBG/O0DZORFxR4++9+qIeNYTa3u5DZTvOKCt33sj4tO9mH4vRcQ9EbFtA9/7/yJiaUTcFhE/iog/HME0Gttv20XE2jIf/X+1xRUR+4z0WLcR39k/f3dExL9HxOaj+f1jRctyuDUibo6I/zNE+WeOXRExPyL+dYjyo3rMj4jXl3PQ74/Cd82JiDe3fB5yeTRpMm3zA5yPjx3oOBMRn4+IXUr3qJ9DIuJ3IuLLEXF3RNwUEddFxOtHOK33jsa6jYjHN2LcrutLQ0zn70YwztURcVc55t0YEbu1DFscEc8d7jS7/N7H2z4fFRGf6tG0z4uIQ3sxrRF+f8f6wiD10z+PiFvKOrgzIt4xxPR7uaxGvN12Of1JcZzt9DsmIk6NiBOaiqmXJnVSAngC2DUinlM+7wcsH+nEMnNRZn6kJ5EN35PAGzqd1DPz3zLzgo2ZeFTG1PYSEQFcBlydmS/KzF2AvwN+p6mYerwNXER5+GuLBaX/pBcRewF/Drw8M18K/Clw/3Cn0/B+2+63mblby99YiYuoXtu8sfrnb1fgKeCdw/j+KT34/rGifzn8AXAy8E/djpiZSzLzPUOU2ehj/jAdDnyfZx+v6lhvc4BnkhLdLI+GTYptfiTn48x8W2beOVoxtirxfg24JjNfmJm7U22/s0c4yfcCY/aHUI/rS8NOShRvKce8TwMf7e+Zma/JzEdGOM1xo0fn0FZd1xciYlOq5we8tqyDlwFX9zienhjhcW/Ex9mJqIZtbVSMqR+ZDflP4M9K9+G0/OCLiC0i4tyS1b0lIg4p/d8XEeeW7peUzNzmrVnFkoG/rGQkb+2/ElbGvaP8vbeH87GG6oDzN+0DWrNoEbFzRHw31l+he1FEbBkR/1U+394yn3Mi4sdRXZm/GdgxIj4TEUuiujr9wZbveE1E/CQivh8R/9p/ZaQ9g1fme07p/lq5OrE0Io4dwTy/Cng6M/+tv0dm/gj4fkR8tHzX7RHxpg7LZHpEfKEMvyUiXlX6H1Xi+kZE/Dwijivr7JaI+O+I2KZlMm+NiB+W79mzZfz+beC1EXF9Gfe7ETHck/+lwJ9HxGZlenOA7cv8nVi2y9v610PL+vpcWaZX9Cfcynr+dlne10a5ohkbZtl/GxF/MsQ6e2tE3FDKf7bTyaMH67VbzwcezMwnATLzwcx8IKorbqeXOG+IiJ1LXB3XR9s6O69svz+M6upZY1dBWkXEHiWmW8s8bRVtVzEi4psRsU/pHmg/PbB/PwXe0NJ/m7Lebivb+UtL/1Mj4uyIuALo9Y/ca4H+ddNxm4mIxyPitIi4HtgrIk4p2/0dJa5oWT63RXWl86OxvlXBsJZRROwbEZe1lN8vIv6jx/Pdbmvg4fJ9EUMfu/Yp87FJ2daf2zJsWVTnntZj/tvLMrs1Ir4aPb6CFBFbAq8AjqEkJUqMV0XEl4HbS78PlG3vOxFxUUt8Ax2bBtoXPwL8cTkG/U20tPgp831uVFcK746I97TEOVrHpcG0bvMdj6UdtvlnWhBE1Srk6oZiH8pA5+NrgS0j4tKy/r/Ust8OdEV3yPNMD7waeKot3nsz85MjOG68h+rcfFVEXFX67V+ORzdHdeV2y9L/noj4xzJsSUS8PCIuj6r1wjtLmY51srZlNGSZNh3XT2ZeO9BxJyKeHxHXxPor0H8cER8BnlP6famUG+6+dR2wQ8u8tG7jR0R1LL81Skvm2Pi6VEcR8YKyDG8r/3cq/Tsee8py+lRUrQy+BTxvgHl4Zj+NtnNoVPW0a8t6e6aVXKdl3Yt5bLEV1csNHgLIzCcz867y3YMu34iYUeZvk/J584i4PyI2jQHOLxExt2zjN0bEh1qmNdC29qxzxkbotm7x4RL3f8f6+uBA9cRTI+L8qOrV90TEGyLijDIP344q6UMMUEcZDVEdT/8xIr4HHB9tLXmitFaJqu7w6bJMvhlVS6X+bXyg7XjPsj/cUv7/Xul/bWzY6ukHUeqPI5KZk/YPeBx4KdWPv+nAj4B9gG+W4f8IvLV0Pxf4H2ALqmTONcDrgSXAK0qZo4BPle5LgPeW7inADGB3qp1tC2BLYCnwsh7Oy9bAPeW7TgBOLcNOBU4o3dcDry/d06ky+1OBrUu/bYFlQFBdkVoH/FHL92zTMk9Xl+U3neoK9dwy7KKWZfjMd5fPdwBz2qb1nNJ/5jDn+T3AmR36/wXwnRLj7wD3Uf2AnQPcUcr8LfCF0v37pcz0sg6XUR3AZwGPAu8s5c5sWadXA58r3a9smW7rNvC/4JmHyb4N+NgI1uu3gENK90lUVxf2p0pABdW2+M0Swxyq5NRupfxXWL/9/hcwr3T/IXBl2/e8lupAvulA6wz438A3gE1L/08DR5Tue4Bte7Feh7FstqTaZ/+nxPInLbH8v9J9RMu22HF9tK2z84B/L8t1F2BZHbEPMk9ryzz1/70JmAbcDexRymxNtc8+E3fp/01gny7203ll2/lKy7L5JPD/le5XAz9q2X9vAp7To/l7vPyfCnwd+L+DbTNAAm9sGX+blu4Lqa769G+j/6d0f4QO+2OXyyiAnwCzyrAv939HTev5J1THmN1L/26OXfu0rLd/Af4q1+/X321Zb/3H/Jkt3/sPwLt7PC9vBc4p3T8EXl5ifIL154T5ZX6fQ3Vs/WlLfB2PTQywL7bOf4flcWqJYTOqc9lDrD9ejcpxqZttnsGPpe3b/D2sP7bOp7rSPWrHpGHM50Dn433KNj67rMvrgL3LsKuB+a3zOdiyGY14y7CjGMZxo8N62paqjrhF+fx+4JSWcv3HvTOB21hf3/hVy7byrDpZh+2pY5kRzO9Ax52/Zf25dAqwVWsMLeMPuW+1rev3Av/Yvo0DLwbu4tl1iRHXpXj2OfU+1p/vvwEcWbqPBr5Wus+j87HnDS3LaXvgEeDQwfZT2s6hVHXu6aV7HrCkdHdc1sOctze1L+u28p8HfkVVR38LsMlgy5cN60ZfB15Vut8EfL50dzy/AItYf0x7F+u324G2tX1oOWeMYH8eSd2iv/5wBvD3QyyLU6laA24K/AHwG+CgMuwy4HWt31e6n6mj9OqPlrpAS79TqX7zXQ18uqX/eZTts20ZHUr1ZsxNgO2oLooMtR1vDUwt3X8KfLV0Hwl8onT/LmV7HunfuGze0UuZeVtUV4EPp+31pVQ//g6O9VeNpwM7ZeaPI+IoqpPJZzPzBx0m/WqqH0Rk5lrg0YjYG7gsM58AiOoK3B8Dt/RoXn4dERdQnXx+2z48IrYCdsjMy0r51aX/psA/RsQrqZIQO7C+Sd+9mfnfLZN5Y8k2TqU6kOxCtWHfnZk/L2UuArrJlr8n1t+/uSPVAfqhbud3EHsDF5Xl/suSNdyDan21lvkkQGb+JCLupdqhAK7KzMeAxyLiUaoTF1QJpdYM4EVl/GsiYut49j2Rs4FLIuL5VD8sf87w9d/C8fXy/2iqpsv7s3672ZJq2d0H/Dyrq1NQnQjnRHWF5v8A/96StN2svyMi5lElO16dmU8PktjdlyqxdmMp8xyqE1y7utbrBjLz8YjYnWofehXVsu5/BsNFLf/PLN3dro+vZeY64M72Kwaj4LeZuVtrj4h4CfCLzLwRqv289B9sOgPtpz/PzJ+W8b/I+v10b6rKApl5ZUTMjIgZZdiizHzW8WSEnhMR/dvntcA5pXugbWYt8NWW8V8VEQupKnbbAEsj4lqqCtwPS5kvU93WM5RnLaNyPriQqhXUF4C9KMfxHntmPUd1G9IFEbEr3R27Wl0CnAJ8ger4cEmHMrtGxD9QJda3BC7v6ZxU585PlO6Ly+dvATe0nBP2Br7evx1FxDfK/0GPTYxsX/xWVq2nnoyIX1Gdy/oYpeNSB522+WMZ+Fjavs1PBDdkZh9UrfOoKtbfH6Bst+eZnoqIs6i206eAswYp2unY2r5//lHp/4MyD9OokjH9FpX/twNbttQ3Vpd6xBN0rpOtaA25izLdGui4cyNwbqkjfq2lbtGu233rSxGxBdUP0pd3GP5q4NLMfBAgM1eV/htTl9rgnFrq7v2tc/ZifYvBC6l+nPbrdOx5JeuX0wMRcWWXMbSeQzcFPlWuLq9lfb2z22U94LwNJTPfVuoTf0r1I3Y/qsRDN8v3EqpkxFVU55r+Z5sNdH55BaVOQbVsTy/dA21rv2bDc8ZwDbdu8RRVshGquvJ+pXuwZfGfpY58O9U2/O3S/3aqYxp0qKOw/jdEL+QQ/TvVAdrtDfx72b5XRGndNYQZwPnl90JSbcdQJe8+EBEnUv0+Oa+LaQ1o0iclikXAP1Nl6ma29A/gL7I0cWozj6p1wvbD+J7RaMbzCapbLb4wjO9/C1WWfveyw91DlYCB6uRYjRwxl+pAtkdmPhwR55Vyg83XGja8TWh6mdY+VAfGvTLzN6WJ0PRnjT24pVQZv3bdLOfByjzZ0r2u5fM6Ntxn2g8O7Z8/CXw8MxeV+T21i7jafQ34eES8nCrTfnNEvAX4p8z8bGvBklxrjX0tVYVuE+CRTievUkH4CvD2zHyg9O64zqiW2fmZefJAwfZovXatnNiuBq4uJ4oj+we1Fiv/u10frctw1JreDSLofCIaaN8aaD9lgOn0f0e7/rJPdBg2Up2SLvsw8DazuqxjImI6VUVofmbeH9WDfEd6/BlsGX2BqhKxmurEvWZks9qdzLyuNJecxfC3t+uAnSNiFvA6qitV7c6juopza6mQ7zPyaDcUETOpfkjsGhFJVVFLqgR/63Yz0HwNeGwqRrIvth8Dp472calNp21+sGPpM9t80boNj1bMIzHQ+Rg6rJNBpjPkeaZHlrL+RxOZ+a6yHy5hZMeNVgF8JzMPH+C7W+sU7fWNqQxeJ+vXTZn2+R1o/XTct8oFl1dS3eJ8YUR8NNueVTPMfestwK1UrdnOouUWwpY4Op2jelGX6kbrdw907BnoHDrYftp6LPwb4JdUV9s3oTrPdLWseyEzbwduL8n3n1MlJbpZvouAf4rqFubdgf6EzHkMfH7ptKwGO45vTF1juHWLp7Nc3mfDY9Jgy6L/VuF1EdE6/jqq88xAdZReeoiqNUerbVifPGldhs9sk+WcM63077bO1Br7h6gu2L6+/Na4GqAs1+8AhwBvZH3Cb0R8pkTlXOC0srO2uhx4d1mZRMTLyv8ZVM1mXwnMjM73nf8XVTNNImJKRGxN1ZzvdVHdj7UF1e0f1/ZyRkpm+StU9/e2D/s10BcRrytxbRbV/V8zqJoNPh3VsxVeMMDkt6ba4B8tmeODSv+fAC8sGypU2dR+91Ay4uWH9dzSfwbwcNmgf5/qysJwXQlsFhFv7+8REXtQNUV6U1nus6jW0w1t415DdYIkqqdP70TVbHA4+u+F2xt4NDMfbRs+g/UPTj2SEcjMx6l2/nNZf/X/cuDoWH+P6g4R8bzOU3hmvf88Ig4r5SMi/qAM/gLVbSyt2+E9dF5n/wUc2v9dUT2HoH1b6cV67UpE/F7J2vbbDbi3dL+p5X//FaqNXh8N+Qmwfdm2iep5ElOp1tNuUd0fuCOwZyk/2H46NyJeVD63Vphb94d9qJ7V8ev6ZmkD3W4z/SfIB8u2fyhAZj5MdZWxf7zWhy3ew/CWESU59wDw92xk1r8bZZ6nUFU2rmHoY9czSqXoMuDjwI8zs9PVya2AX0R1Be4tPQ7/UOCCzHxBZs7JzB2pKkd7t5X7PvDaqJ7lsyXlOU5DHJsG8hjVPA3HqB2XutTNsbTfPVQ/AqDlR/QYNND5+E+GOZ3hLJuNcSUwPSL+b0u//uet3MMwjxtsuF3+N/CKWP88o81jeG+56KZO1m29rV/H9RMRf8IAx52y3H+VmZ+juvLc37rh6XI86Y+j630rM5+mOrb+UUT877bB/0XVEmVmia//GV51nbt/yPrzxVsYuPVOv2uABWU5PZ+qhWa/e+huP51B1fJxHfCXVMd+BlnWPRHVM0j2aenVWl8acvmWuugNVL99vtmSOB3o/PIDNly2/YZ1jttIIznub8y21rGO0ktlPfwiIvaFZ/aRA+m87d7D+m3yENa3bvg+8Bfl+PY7bJhIah2ndTtuXS5HtX3P54F/BW5sad00IraUAEqzwn/pMOhDVC0PbiuJiXuomgWfSXXfzv9ExDFUDze6pm3c44Gzy/C1VPc3XRdVZr1/B/x8Zvbk1o02HwOOG2DYXwKfjYjTgKeBw4AvAd+IiCWsv8/5WUom9BaqjPvdVAcdMvO3EfHXwLcj4kE2PMB8FTgiqmZVN1Ld/w9Vs6d3RsRtVMmA1ltEupKZGVWzrE9E1Wx/NdU6ei9VM7JbqTK1CzNzRUvSBKps5r9FdXV9DXBUZj4Zw3smzcMR8UOqisrRHYafStUseTnV/M3tUKYbFwH/QTnAZ+YV5WR+XYn3car7utcOOIXqpPCZiPh7qgPTxRHxCNVB83cjoj/+tzHAOsvMO8v4V0T1wKOnqe4VvLflezZ6vQ7DlsAno2ruuobqntpjqfbRzaJ6UNwmrP/xfSq9WR91am2CCPDtzDwpqodBfTKqB5f+lir7/wOqH4C3U90reTMMup+ujqrZ8bfKfvp9YNfyPacCXyjr7TeMbtKmq20mMx+JiM9Rze89VNtmv2OAz0XEE1RJvP4E4bCWUYsvUT1Xoq43A7Su56C6r3ltVA/Z3IvBj13tLqFaFkcNMPwDVM8SupdqOQz3B/1gDqe66tnqq1QJ+Z/198jMGyNiEdV83Ut1Nbp/HT3r2FTKDeQ2YE1E3EqVNOrmHDqax6UhdXks7fdB4JyoXsN4/SiGOSyDnI+/NszpDGfZbGy8rwPOjKq59UqqhMP7Gdlx42zgPyPiF5n5qqiuGl8U5UHVVD/E/4fudFMn66re1ja/A9WXrqHzcedI4MSIeJqqntF/K9vZVPXim6nqPsPat0qd8WNUrU6Oaem/NCI+DHwvItZS7dtHUd+5+z1Ut0ycSLX+/2qI8pdRtQy7nWpdfq9lWLf76aeBr5ZE7FWsv7K9D52X9WA61hcGKBvAwoj4LFUd4gnWnzNOpbvlewlVc/19WvoNdH45HvhyRBzPhrejDXSOq+N10iM57p/KCLe1IeoovXQEcFbZhwA+mJk/6/D75XPA1yPiBqqEX/+29lWq2+TuoNqOr2f9+Xig7fgMqts33sf6VjIAZOZNEfFrOrfQH5b+h3lIGyUitszqHv+gapb308w8c6jxpF6Lqhnr/Cz3pWri6z/+lO6TgOdn5vEbMb1PAbdk5jlDFlZXWs4Rm1P9CDo2M29uOi5JkiaTlvPxTKoLya/IzJE8j4aI2J7qYtDvlxZAI2ZLCfXK20tWfRpVdvuzQ5SXpF75s4g4meqcdi8DtxoYUkTcRHVF4W97E5qKsyNiF6omruebkJAkqRHfLK2MpwEf2oiExBHAh4H3bWxCAmwpIUmSJEmSGuKDLiVJkiRJUiNMSvz/7d09i51FGAbg+8aPRgRR0liofSqxEi2MkFoLEUER9AcEEawMFoJ/IFgpmsQQG6MiFqlCFFQwIFHxq7SQWCg2KiSQ9bHYd2ERNtnEdQ8u19Wc4cy8z8x0h+c87wwAAACwEpISAAAAwEpISgAA/xttn1tu8QAA9gAHXQIA/xtXuva37Q0zs7b7qwIArpdKCQBgR7V9uu3Xbb9qe6Lt3W3PLN+daXvXMu5Y28c2PffH8vlQ24/anmr7Q9uTXXcoyZ1JzrY9u/FM25fbfp7kcNv3N8U72Pa9Xd08AHBNblz1AgCAvaPt/iQvJnlgZn5te3uS40nempnjbZ9NciTJo1cJdW+S/UkuJPl0iXek7fNJDmyqlLglyTcz81LbJvm+7b6Z+SXJM0mO7vgmAYAdo1ICANhJDyc5tZE0mJnfktyf5O2l/0SSB7cR59zM/DQzfyX5Msk9W4xbS/LuMtcs8Z9qe9sy7+nr3AcAsAtUSgAAO6lJrnZg1Ub/5Sx/kCxVDjdvGnNpU3stW/9mufiPcySOJvkwycUk78zM5W2uGwBYAZUSAMBOOpPk8bZ3JMny+sZnSZ5Y+p9M8snS/jHJfUv7kSQ3bSP+70lu3apzZi5k/ZWPw0mOXdvSAYDdplICANgxM/Nt21eSfNx2Lcn5JIeSvNn2hSQbZz0kyetJPmh7LuvJjD+3McVrSU63/XlmDmwx5mSSfTPz3b/ZCwDw33MlKACwp7R9Ncn5mXlj1WsBAK5MUgIA2DPafpH1iouDM3PpauMBgNWSlAAAAABWwkGXAAAAwEpISgAAAAArISkBAAAArISkBAAAALASkhIAAADASkhKAAAAACvxNyZNbeE1I+33AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# check conversion rate between test and control groups\n",
    "plt.figure(figsize=(18, 6))\n",
    "sns.barplot(x = 'country', y = 'conversion', hue = 'test', data = data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Basically, the number of test-control groups are 1:1（test/control\n",
    "split is ~50/50）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.043424713982118966 0.04833042316066309\n"
     ]
    }
   ],
   "source": [
    "# A/B test\n",
    "# #nothing changed in Spain, so no point in keeping those users\n",
    "test_data = data[data['country'] != 'Spain']\n",
    "test_val = test_data[test_data['test'] == 1]['conversion'].values   # values：提取出conversion，不带index\n",
    "cont_val = test_data[test_data['test'] == 0]['conversion'].values\n",
    "\n",
    "print(test_val.mean(), cont_val.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the convert rate in control group is 4.8% while the convert rate in test group is 4.3%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-7.393937412134479, pvalue=1.428299475405547e-13)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ttest_ind(test_val, cont_val, equal_var = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the test is accurate, from 4.8% to 4.3% is a 10% drop, which is too dramatic to be true"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most likely reason for weird A/B test results are:\n",
    "1. We didn’t collect **enough data**.\n",
    "2. Some **bias** has been introduced in the experiment so that test/control people are not really\n",
    "random"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To find the bias: Likely, there is for some reason **some segment of users are more likely to end up in test or in control**, this segment had a significantly above/below conversion rate and this affected the overall results\\\n",
    "--------- find out **the relationship between features and test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>source</th>\n",
       "      <th>device</th>\n",
       "      <th>browser_language</th>\n",
       "      <th>ads_channel</th>\n",
       "      <th>browser</th>\n",
       "      <th>conversion</th>\n",
       "      <th>test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>765821</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>2015-12-02</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>ES</td>\n",
       "      <td>Yahoo</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>343561</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Nicaragua</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>Safari</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>118744</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>2015-11-30</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>ES</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>Android_App</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>987753</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Venezuela</td>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Web</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IE</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>62371</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Ecuador</td>\n",
       "      <td>2015-12-02</td>\n",
       "      <td>Direct</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>ES</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Iphone_App</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id sex   age    country        date  source  device browser_language  \\\n",
       "0   765821   M  20.0     Mexico  2015-12-02     Ads  Mobile               ES   \n",
       "1   343561   F  27.0  Nicaragua  2015-12-04     Ads     Web               ES   \n",
       "2   118744   M  23.0   Colombia  2015-11-30     Ads  Mobile               ES   \n",
       "3   987753   F  27.0  Venezuela  2015-12-04     SEO     Web               ES   \n",
       "5    62371   M  29.0    Ecuador  2015-12-02  Direct  Mobile               ES   \n",
       "\n",
       "  ads_channel      browser  conversion  test  \n",
       "0       Yahoo  Android_App           0     1  \n",
       "1    Facebook       Safari           0     0  \n",
       "2    Facebook  Android_App           0     1  \n",
       "3         NaN           IE           0     1  \n",
       "5         NaN   Iphone_App           0     0  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.head()    # spain users removed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visualization(feature):\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=2, figsize = (18, 6))\n",
    "    sns.countplot(x = feature, hue='test', data = test_data, ax = ax[0])\n",
    "    ax[0].set_title('Count of {} in test/control group'.format(feature))\n",
    "\n",
    "    sns.barplot(x = feature, y = 'conversion', hue='test', data = test_data, ax = ax[1])\n",
    "    ax[1].set_title('Conversion rate vs {} in test/control group'.format(feature))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QyjfwzJ4tvbVxGm1Gdf1dTnX9/7sSMxuI5Z+pbr04sXxB8i6qD9Z/28fXpU824TXq7bwXAjPKfr5J9WSaxrbQOqovOqZRDeLZRXVrDvTvfdKdnHswIn7RS73DqG5rXg5cBpycmVdvaOeZ+V3gC1S9dDqp2oDQS3uIXtp25ZgXU/0N30TrL5kupEpqraAaePSfNxSn2qd79H5JGjGi6la5gmrA0YfbHc9Aioj3Ug3M9XeDtP8Epmdm52DsX5IkDY2IWEz1yNbFG6xcIxHxAqpEzxYD2OOocf/XUQ0k+uWB3rcGhz01JI1EO1B9s1L7hEZE7BwRr46IzSLi+VTfNl3W7rgkSdKwdx0NY5DUWUS8OSI2j4jtqXqxfGswEhqqJ5MakkaczPxjZp7d7jgGyObAvwOPUt2ucznVLSWSJEk9yszTM/N/2h3HAHk31e1gd1ONIfLe9oaj4cTbTyRJkiRJUi3ZU0OSJEmSJNWSSQ1JkiRJklRLY9sdwHCx44475pQpU9odhiRJw8pNN930QGZObHcco4XtEUmS1tdbe8SkRjFlyhSWLFnS7jAkSRpWIuIP7Y5hNLE9IknS+nprj3j7iSRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFpyTA1JkgbZU089RVdXF2vWrGl3KD0aP348HR0djBs3rt2hSJKkQTBS2yMmNSRJGmRdXV1svfXWTJkyhYhodzjryUwefPBBurq6mDp1arvDkSRJg2Cktke8/USSpEG2Zs0aJkyYMCwbEAARwYQJE4b1NzeSJKl/Rmp7xKSGJElDYLg2ILoN9/gkSVL/Dffr/abEZ1JDkqRh5qGHHuKss87apG0/97nP8fjjjw9wRJIkabSpS3vEpIYkScNMXRoRkiRp5KpLe8SBQiVJGmaOP/547r77bl7ykpew3377sdNOO3HJJZfwxBNP8OY3v5mPf/zjPPbYY7z1rW+lq6uLdevWceKJJ3L//fezfPlyXv/617Pjjjty7bXXtvtUai8iZgOfB8YAX87MU5vWbwFcALwceBB4W2b+PiKmAHcAd5aqP8/M9wxV3JIk9Vdd2iMmNSRJGmZOPfVUfv3rX3PLLbdw1VVXcemll3LDDTeQmRx44IH86Ec/YuXKleyyyy585zvfAeDhhx9m22235bOf/SzXXnstO+64Y5vPov4iYgxwJrAf0AXcGBFXZObtDdWOAlZn5rSImAucBrytrLs7M18ypEFLkjRA6tIe8fYTSZKGsauuuoqrrrqKl770pbzsZS/jN7/5DXfddRcvfOEL+f73v89xxx3Hj3/8Y7bddtt2hzoS7QV0ZuY9mfkksAg4qKnOQcD5Zf5SYN8Y7qOwSZK0kYZze8SeGpIkDWOZyQknnMC73/3u9dbddNNNLF68mBNOOIH999+fk046qQ0Rjmi7AksblruAV/ZUJzPXRsTDwISybmpE3Aw8Anw0M3/c6iARMR+YDzB58uSBi16SBtCxxx7LihUreO5zn8vpp5/e7nA0xIZze8SkhkaUexe8sN0hjBqTT7q13SFII9bWW2/No48+CsCsWbM48cQTefvb385WW23FsmXLGDduHGvXrmWHHXbgHe94B1tttRXnnXfeM7b19pMB0arHRfaxzn3A5Mx8MCJeDnwzIvbIzEfWq5x5DnAOwMyZM5v3P2r5AUoaXlasWMGyZcvaHYaGUF3aIyY1JEkaZiZMmMCrX/1q9txzTw444AAOP/xwXvWqVwGw1VZb8dWvfpXOzk4+/OEPs9lmmzFu3DjOPvtsAObPn88BBxzAzjvv7ECh/dcFTGpY7gCW91CnKyLGAtsCqzIzgScAMvOmiLgb+CtgyaBHPUL4AUqS2qsu7RGTGpIkDUNf//rXn7H8gQ984BnLz3ve85g1a9Z6273//e/n/e9//6DGNorcCEyPiKnAMmAucHhTnSuAecDPgEOAazIzI2IiVXJjXUTsDkwH7hm60CVJ6r86tEdMakiSJLVQxsg4BriS6pGu52bmbRGxAFiSmVcAC4ELI6ITWEWV+AB4LbAgItYC64D3ZOaqoT8LSZJGNpMakiRJPcjMxcDiprKTGubXAIe22O4bwDcGPUBJkkY5H+kqSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUnSKPG9732P5z//+UybNo1TTz213eFIkqRRaKDbIz79RJKkIfbyD18woPu76d+O2GCddevWcfTRR3P11VfT0dHBK17xCg488EBmzJgxoLFo+Bro991g2/qBRxkD3PvAo7WLvS9/kxrd6vaehvr+Tfr32LOR0h4ZtJ4aEXFuRPwxIn7dUPZvEfGbiPhVRFwWEds1rDshIjoj4s6ImNVQPruUdUbE8Q3lUyPi+oi4KyIujojNS/kWZbmzrJ8yWOcoSVJd3HDDDUybNo3dd9+dzTffnLlz53L55Ze3OyxJkjSKDEZ7ZDBvPzkPmN1UdjWwZ2a+CPgtcAJARMwA5gJ7lG3OiogxETEGOBM4AJgBHFbqApwGnJGZ04HVwFGl/ChgdWZOA84o9SRJGtWWLVvGpEmT/rLc0dHBsmXL2hiRJEkabQajPTJoSY3M/BGwqqnsqsxcWxZ/DnSU+YOARZn5RGb+DugE9ipTZ2bek5lPAouAgyIigH2AS8v25wMHN+zr/DJ/KbBvqS9J0qiVmeuVeXmUJElDaTDaI+0cKPRI4LtlfldgacO6rlLWU/kE4KGGBEl3+TP2VdY/XOpLkjRqdXR0sHTp05fUrq4udtlllzZGJEmSRpvBaI+0JakREf8HWAt8rbuoRbXchPLe9tUqjvkRsSQilqxcubL3oCVJqrFXvOIV3HXXXfzud7/jySefZNGiRRx44IHtDkuSJI0ig9EeGfKnn0TEPOCNwL75dN+TLmBSQ7UOYHmZb1X+ALBdRIwtvTEa63fvqysixgLb0nQbTLfMPAc4B2DmzJktEx+SJI0EY8eO5Ytf/CKzZs1i3bp1HHnkkeyxxx7tDkuSJI0ig9EeGdKkRkTMBo4D/i4zH29YdQXw9Yj4LLALMB24garXxfSImAosoxpM9PDMzIi4FjiEapyNecDlDfuaB/ysrL8mW924I0lSm7Tr8XJz5sxhzpw5bTm2JEkaXkZKe2TQkhoRcRHwOmDHiOgCTqZ62skWwNVlMJCfZ+Z7MvO2iLgEuJ3qtpSjM3Nd2c8xwJXAGODczLytHOI4YFFEfBK4GVhYyhcCF0ZEJ1UPjbmDdY6SJEkaHH/e/NnP+ClJUiuDltTIzMNaFC9sUdZd/xTglBbli4HFLcrvoXo6SnP5GuDQjQpWkiRJw8pj0/dvdwiSpBoY8jE1JEmSJEn1Yu8pDVcmNSRJkiRJvbL3lIartjzSVZIkSZIkqb9MakiSJEmSpFoyqSFJ0ihw5JFHstNOO7Hnnnu2OxRJkjRKDUZ7xDE1JEkaYvcueOGA7m/ySbdusM473/lOjjnmGI44oj3PpJckScPLSGmP2FNDkqRR4LWvfS077LBDu8OQJEmj2GC0R0xqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiUHCpUkSZIkaZg49thjWbFiBc997nM5/fTT2x3OsGdPDUmSRoHDDjuMV73qVdx55510dHSwcOHCdockSZJaWLFiBcuWLWPFihXtDmXADUZ7xJ4akiQNsb488mygXXTRRUN+TEn14TfD0ugzUtojJjUkSZKkUa77m2FJqhtvP5EkSZIkSbVkUkOSJEmSJNWSSQ1JkoZAZrY7hF4N9/gkSVL/Dffr/abEZ1JDkqRBNn78eB588MFh25DITB588EHGjx/f7lAkSdIgGantEQcKlSRpkHV0dNDV1cXKlSvbHUqPxo8fT0dHR7vDkCRJg2SktkdMakiSNMjGjRvH1KlT2x2GJEkaxUZqe8SkhiRJkjSA7l3wwnaHsNHWrtoBGMvaVX+oVfyTT7q13SFomKvT+7lbXf8eoT1/k46pIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZYcU2MIvPzDF7Q7hFHjsq3bHYEkSZIkaajYU0OSJEmSJNWSSQ1JkiRJklRLJjUkSZIkSVItOaaGJEmSNMrtOP7PwNryU5Lqw6SGJEmSNMp96EUPtTsESYVJxo1jUkOSJEmSpGHCJOPGcUwNSZIkSZJUSyY1JEmSJElSLZnUkCRJkiRJtWRSQ5IkSZIk1ZJJDUmSJEmSVEsmNSRJkiRJUi2Z1JAkSZIkSbVkUkOSJKkHETE7Iu6MiM6IOL7F+i0i4uKy/vqImNK0fnJE/CkiPjRUMUuSNJqY1JAkSWohIsYAZwIHADOAwyJiRlO1o4DVmTkNOAM4rWn9GcB3BztWSZJGK5MakiRJre0FdGbmPZn5JLAIOKipzkHA+WX+UmDfiAiAiDgYuAe4bYjilSRp1Bm0pEZEnBsRf4yIXzeU7RARV0fEXeXn9qU8IuILpevmryLiZQ3bzCv174qIeQ3lL4+IW8s2X2hoQLQ8hiRJ0kbaFVjasNxVylrWycy1wMPAhIh4NnAc8PENHSQi5kfEkohYsnLlygEJXJKk0WIwe2qcB8xuKjse+EFmTgd+UJah6tY5vUzzgbOhSlAAJwOvpPq25OSGJMXZpW73drM3cAxJkqSNES3Kso91Pg6ckZl/2tBBMvOczJyZmTMnTpy4CWFKkjR6DVpSIzN/BKxqKm7sonk+cHBD+QVZ+TmwXUTsDMwCrs7MVZm5GrgamF3WbZOZP8vMBC5o2lerY0iSJG2MLmBSw3IHsLynOhExFtiWqv3zSuD0iPg98C/ARyLimMEOWJKk0WbsEB/vOZl5H0Bm3hcRO5Xynrp39lbe1aK8t2OsJyLmU/X2YPLkyZt6TpIkaWS6EZgeEVOBZcBc4PCmOlcA84CfAYcA15QvXP62u0JEfAz4U2Z+cSiCliRpNBkuA4X21HVzY8s3it09JUlST8oYGccAVwJ3AJdk5m0RsSAiDizVFlKNodEJfBBve5UkaUgNdU+N+yNi59KDYmfgj6W8p+6dXcDrmsqvK+UdLer3dgxJkqSNkpmLgcVNZSc1zK8BDt3APj42KMFJkqQh76nR3UWT8vPyhvIjylNQ9gYeLreQXAnsHxHblwFC9weuLOsejYi9y1NPjmjaV6tjSJIkSZKkEWTQempExEVUvSx2jIguqqeYnApcEhFHAffy9Dcbi4E5QCfwOPAugMxcFRGfoLqnFWBBZnYPPvpeqiesPAv4bpno5RiSJEmSJGkEGbSkRmYe1sOqfVvUTeDoHvZzLnBui/IlwJ4tyh9sdQxJkiRJkjSyDJeBQiVJkiRJkjaKSQ1JkiRJklRLJjUkSZIkSVItmdSQJEmSJEm1ZFJDkiRJkiTVkkkNSZIkSZJUSyY1JEmSJElSLZnUkCRJkiRJtWRSQ5IkSZIk1ZJJDUmSJEmSVEsmNSRJkiRJUi2Z1JAkSZIkSbVkUkOSJEmSJNWSSQ1JkiRJklRLJjUkSZIkSVItmdSQJEmSJEm1ZFJDkiRJkiTVkkkNSZIkSZJUSyY1JEmSJElSLY1tdwCSpJHp3gUvbHcIo8rkk25tdwiSJElDzp4akiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaolkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaqltiQ1IuJ/R8RtEfHriLgoIsZHxNSIuD4i7oqIiyNi81J3i7LcWdZPadjPCaX8zoiY1VA+u5R1RsTxQ3+GkiRJkiRpsA15UiMidgX+GZiZmXsCY4C5wGnAGZk5HVgNHFU2OQpYnZnTgDNKPSJiRtluD2A2cFZEjImIMcCZwAHADOCwUleSJEmSJI0g7br9ZCzwrIgYC2wJ3AfsA1xa1p8PHFzmDyrLlPX7RkSU8kWZ+URm/g7oBPYqU2dm3pOZTwKLSl1JkiRJkjSCDHlSIzOXAZ8G7qVKZjwM3AQ8lJlrS08AUEYAABqkSURBVLUuYNcyvyuwtGy7ttSf0FjetE1P5euJiPkRsSQilqxcubL/JydJkiRJkoZMO24/2Z6q58RUYBfg2VS3ijTL7k16WLex5esXZp6TmTMzc+bEiRM3FLokSZIkSRpG2nH7yRuA32Xmysx8Cvgv4G+A7crtKAAdwPIy3wVMAijrtwVWNZY3bdNTuSRJkiRJGkHakdS4F9g7IrYsY2PsC9wOXAscUurMAy4v81eUZcr6azIzS/nc8nSUqcB04AbgRmB6eZrK5lSDiV4xBOclSZIkSZKG0NgNVxlYmXl9RFwK/AJYC9wMnAN8B1gUEZ8sZQvLJguBCyOik6qHxtyyn9si4hKqhMha4OjMXAcQEccAV1I9WeXczLxtqM5PkiRJkiQNjSFPagBk5snAyU3F91A9uaS57hrg0B72cwpwSovyxcDi/kcqSZIkSZKGq3Y90lWSJEmSJKlfTGpIkiT1ICJmR8SdEdEZEce3WL9FRFxc1l8fEVNK+V4RcUuZfhkRbx7q2CVJGg3acvuJJLXLyz98QbtDGDUu27rdEUj9ExFjgDOB/aiernZjRFyRmbc3VDsKWJ2Z0yJiLnAa8Dbg18DMzFwbETsDv4yIb2Xm2iE+DUmSRjR7akiSJLW2F9CZmfdk5pPAIuCgpjoHAeeX+UuBfSMiMvPxhgTGeCCHJGJJkkYZkxqSJEmt7QosbVjuKmUt65QkxsPABICIeGVE3AbcCrzHXhqSJA08bz+RJEkjXkRMBP4JmEJD+yczj+xtsxZlzT0ueqyTmdcDe0TEC4DzI+K75aluzbHNB+YDTJ48uZdwJElSM5MakiRpNLgc+DHwfWBdH7fpAiY1LHcAy3uo0xURY4FtgVWNFTLzjoh4DNgTWNJ8kMw8BzgHYObMmd6mIknSRjCpIUmSRoMtM/O4jdzmRmB6REwFlgFzgcOb6lwBzAN+BhwCXJOZWbZZWgYK3Q14PvD7/pyAJElan2NqSJKk0eDbETFnYzYoY2AcA1wJ3AFckpm3RcSCiDiwVFsITIiITuCDQPdjX19D9cSTW4DLgPdl5gMDcSKSJOlp9tSQJEmjwQeAj0TEk8BTpSwzc5veNsrMxcDiprKTGubXAIe22O5C4ML+Bi1JknpnUkOSJI14mbl1u2OQJEkDz6SGJEkaFcotI68ti9dl5rfbGY8kSeo/x9SQJEkjXkScSnULyu1l+kApkyRJNWZPDUmSNBrMAV6SmX8GiIjzgZt5emBPSZJUQ/bUkCRJo8V2DfPbti0KSZI0YOypIUmSRoNPATdHxLVAUI2tcUJ7Q5IkSf1lUkOSJI14mXlRRFwHvIIqqXFcZq5ob1SSJKm/+nT7SUT8oC9lkiRJw0lE/HX5+TJgZ6ALWArsUsokSVKN9dpTIyLGA1sCO0bE9lTfbABsA+wyyLFJkiT11weB+cBnWqxLYJ+hDUeSJA2kDd1+8m7gX6gSGDfxdFLjEeDMQYxLkiSp3zJzfvn5+nbHIkmSBl6vt59k5uczcyrwoczcPTOnlunFmfnFIYpRkiSpXyLi0IjYusx/NCL+KyJe2u64JElS//RpoNDM/H8R8TfAlMZtMvOCQYpLkiRpIJ2Ymf8ZEa8BZgGfBr4EvLK9YUmSpP7oU1IjIi4EngfcAqwrxQmY1JAkSXXQ3X75e+DszLw8Ij7WxngkSdIA6OsjXWcCMzIzBzMYSZKkQbIsIv4deANwWkRsQR+fAidJkoavvl7Mfw08dzADkSRJGkRvBa4EZmfmQ8AOwIfbG5IkSeqvvvbU2BG4PSJuAJ7oLszMAwclKkmSpAESEZsBN2Tmnt1lmXkfcF/7opIkSQOhr0mNjw1mEJIkSYMlM/8cEb+MiMmZeW+745EkSQOnr08/+eFgByJJkjSIdgZuK71OH+sutNepJEn11tennzxK9bQTgM2BccBjmbnNYAUmSZI0gD7e7gAkSdLA62tPja0blyPiYGCvQYlIkiRpgGXmDyNiN2B6Zn4/IrYExrQ7LkmS1D+b9CizzPwmsM8AxyJJkjQoIuKfgEuBfy9FuwLfbF9EkiRpIPT19pO3NCxuBszk6dtRJEmShrujqXqZXg+QmXdFxE7tDUmSJPVXX59+8qaG+bXA74GDBjwaSZKkwfFEZj4ZEQBExFj8gkaSpNrr65ga7xrsQCRJkgbRDyPiI8CzImI/4H3At9ockyRJ6qc+jakRER0RcVlE/DEi7o+Ib0REx2AHJ0mSNECOB1YCtwLvBhYDH21rRJIkqd/6evvJV4CvA4eW5XeUsv0GIyhJkqQBdhBwQWb+R7sDkSRJA6evTz+ZmJlfycy1ZToPmDiIcUmSJA2kA4HfRsSFEfH3ZUwNSZJUc31NajwQEe+IiDFlegfw4GAGJkmSNFDK+GDTgP8EDgfujogvtzcqSZLUX31NahwJvBVYAdwHHAI4eKgkSaqNzHwK+C6wCLgJn+QmSVLt9TWp8QlgXmZOzMydqJIcHxu0qCRJkgZQRMyOiPOATqovZ74M7NzWoCRJUr/1Nanxosxc3b2QmauAl27qQSNiu4i4NCJ+ExF3RMSrImKHiLg6Iu4qP7cvdSMivhARnRHxq4h4WcN+5pX6d0XEvIbyl0fErWWbL0T3Q+klSdJo9U7gm8BfZea8zFycmWvbHJMkSeqnviY1NutOMgBExA70/ckprXwe+F5m/jXwYuAOqket/SAzpwM/KMsABwDTyzQfOLshhpOBVwJ7ASc3xHh2qdu93ex+xCpJkmouM+dm5jcz84l2xyJJkgZOX5ManwF+GhGfiIgFwE+B0zflgBGxDfBaYCFAZj6ZmQ9R3dd6fql2PnBwme9+BFtm5s+B7SJiZ2AWcHVmriq9SK4GZpd122TmzzIzgQsa9iVJkkahiHhL6dn5cEQ8EhGPRsQj7Y5LkiT1T596W2TmBRGxBNgHCOAtmXn7Jh5zd2Al8JWIeDHVQF0fAJ6TmfeV490XETuV+rsCSxu27yplvZV3tSiXJEmj1+nAmzLzjnYHIkmSBk6fbyEpSYxNTWQ0H/NlwPsz8/qI+DxP32rSSqvxMHITytffccR8qttUmDx5cm8xS5KkervfhIYkSSNPX28/GUhdQFdmXl+WL6VKctxfbh2h/PxjQ/1JDdt3AMs3UN7Ronw9mXlOZs7MzJkTJ07s10lJkqRhbUlEXBwRh5VbUd4SEW9pd1CSJKl/hjypkZkrgKUR8fxStC9VD5ArgO4nmMwDLi/zVwBHlKeg7A08XG5TuRLYPyK2LwOE7g9cWdY9GhF7l6eeHNGwL0mSNDptAzxO1V54U5ne2NaIJElSv/XnCSb98X7gaxGxOXAP8C6qBMslEXEUcC9waKm7GJhD9Vz5x0tdMnNVRHwCuLHUW1AeNQvwXuA84FnAd8skSZJGqcx8V7tjkCRJA68tSY3MvAWY2WLVvi3qJnB0D/s5Fzi3RfkSYM9+hilJkkaIiOgA/h/waqqxtn4CfCAzu3rdUJIkDWvtGFNDkiRpqH2F6pbWXaieivatUiZJkmrMpIYkSRoNJmbmVzJzbZnOAxwlXJKkmjOpIUmSRoMHIuIdETGmTO8AHmx3UJIkqX9MakiSpNHgSOCtwArgPuAQyuDjkiSpvtr19BNJkqSh9AlgXmauBoiIHYBPUyU7JElSTdlTQ5IkjQYv6k5oQPVoeOClbYxHkiQNAJMakiRpNNgsIrbvXig9NeyxKklSzXkxlyRJo8FngJ9GxKVAUo2vcUp7Q5IkSf1lUkOSJI14mXlBRCwB9gECeEtm3t7msCRJUj+Z1JAkSaNCSWKYyJAkaQRxTA1JkiRJklRLJjUkSZIkSVItmdSQJEmSJEm1ZFJDkiRJkiTVkkkNSZIkSZJUSyY1JEmSehARsyPizojojIjjW6zfIiIuLuuvj4gppXy/iLgpIm4tP/cZ6tglSRoNTGpIkiS1EBFjgDOBA4AZwGERMaOp2lHA6sycBpwBnFbKHwDelJkvBOYBFw5N1JIkjS4mNSRJklrbC+jMzHsy80lgEXBQU52DgPPL/KXAvhERmXlzZi4v5bcB4yNiiyGJWpKkUcSkhiRJUmu7AksblrtKWcs6mbkWeBiY0FTnfwE3Z+YTrQ4SEfMjYklELFm5cuWABC5J0mhhUkOSJKm1aFGWG1MnIvaguiXl3T0dJDPPycyZmTlz4sSJmxSoJEmjlUkNSZKk1rqASQ3LHcDynupExFhgW2BVWe4ALgOOyMy7Bz1aSZJGIZMakiRJrd0ITI+IqRGxOTAXuKKpzhVUA4ECHAJck5kZEdsB3wFOyMz/HrKIJUkaZUxqSJIktVDGyDgGuBK4A7gkM2+LiAURcWCpthCYEBGdwAeB7se+HgNMA06MiFvKtNMQn4IkSSPe2HYHIEmSNFxl5mJgcVPZSQ3za4BDW2z3SeCTgx6gJEmjnD01JEmSJElSLZnUkCRJkiRJtWRSQ5IkSZIk1ZJJDUmSJEmSVEsmNSRJkiRJUi2Z1JAkSZIkSbVkUkOSJEmSJNWSSQ1JkiRJklRLJjUkSZIkSVItmdSQJEmSJEm1ZFJDkiRJkiTVkkkNSZIkSZJUSyY1JEmSJElSLZnUkCRJkiRJtWRSQ5IkSZIk1ZJJDUmSJEmSVEsmNSRJkiRJUi21LakREWMi4uaI+HZZnhoR10fEXRFxcURsXsq3KMudZf2Uhn2cUMrvjIhZDeWzS1lnRBw/1OcmSZIkSZIGXzt7anwAuKNh+TTgjMycDqwGjirlRwGrM3MacEapR0TMAOYCewCzgbNKomQMcCZwADADOKzUlSRJkiRJI0hbkhoR0QH8PfDlshzAPsClpcr5wMFl/qCyTFm/b6l/ELAoM5/IzN8BncBeZerMzHsy80lgUakrSZIkSZJGkHb11PgccCzw57I8AXgoM9eW5S5g1zK/K7AUoKx/uNT/S3nTNj2Vryci5kfEkohYsnLlyv6ekyRJkiRJGkJDntSIiDcCf8zMmxqLW1TNDazb2PL1CzPPycyZmTlz4sSJvUQtSZIkSZKGm7FtOOargQMjYg4wHtiGqufGdhExtvTG6ACWl/pdwCSgKyLGAtsCqxrKuzVu01O5JEmSJEkaIYa8p0ZmnpCZHZk5hWqgz2sy8+3AtcAhpdo84PIyf0VZpqy/JjOzlM8tT0eZCkwHbgBuBKaXp6lsXo5xxRCcmiRJkiRJGkLt6KnRk+OARRHxSeBmYGEpXwhcGBGdVD005gJk5m0RcQlwO7AWODoz1wFExDHAlcAY4NzMvG1Iz0SSJEmSJA26tiY1MvM64Loyfw/Vk0ua66wBDu1h+1OAU1qULwYWD2CokiRJkiRpmGnX008kSZIkSZL6xaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaolkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaolkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIk9SAiZkfEnRHRGRHHt1i/RURcXNZfHxFTSvmEiLg2Iv4UEV8c6rglSRotTGpIkiS1EBFjgDOBA4AZwGERMaOp2lHA6sycBpwBnFbK1wAnAh8aonAlSRqVTGpIkiS1thfQmZn3ZOaTwCLgoKY6BwHnl/lLgX0jIjLzscz8CVVyQ5IkDRKTGpIkSa3tCixtWO4qZS3rZOZa4GFgwsYcJCLmR8SSiFiycuXKfoQrSdLoY1JDkiSptWhRlptQp1eZeU5mzszMmRMnTtyYTSVJGvVMakiSJLXWBUxqWO4AlvdUJyLGAtsCq4YkOkmSZFJDkiSpBzcC0yNiakRsDswFrmiqcwUwr8wfAlyTmRvVU0OSJG26se0OQJIkaTjKzLURcQxwJTAGODczb4uIBcCSzLwCWAhcGBGdVD005nZvHxG/B7YBNo+Ig4H9M/P2oT4PSZJGMpMakiRJPcjMxcDiprKTGubXAIf2sO2UQQ1OkiR5+4kkSZIkSaonkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqaciTGhExKSKujYg7IuK2iPhAKd8hIq6OiLvKz+1LeUTEFyKiMyJ+FREva9jXvFL/roiY11D+8oi4tWzzhYiIoT5PSZIkSZI0uNrRU2Mt8K+Z+QJgb+DoiJgBHA/8IDOnAz8oywAHANPLNB84G6okCHAy8EpgL+Dk7kRIqTO/YbvZQ3BekiRJkiRpCA15UiMz78vMX5T5R4E7gF2Bg4DzS7XzgYPL/EHABVn5ObBdROwMzAKuzsxVmbkauBqYXdZtk5k/y8wELmjYlyRJkiRJGiHaOqZGREwBXgpcDzwnM++DKvEB7FSq7Qosbdisq5T1Vt7VorzV8edHxJKIWLJy5cr+no4kSZIkSRpCbUtqRMRWwDeAf8nMR3qr2qIsN6F8/cLMczJzZmbOnDhx4oZCliRJkiRJw0hbkhoRMY4qofG1zPyvUnx/uXWE8vOPpbwLmNSweQewfAPlHS3KJUmSJEnSCNKOp58EsBC4IzM/27DqCqD7CSbzgMsbyo8oT0HZG3i43J5yJbB/RGxfBgjdH7iyrHs0IvYuxzqiYV+SJEmSJGmEGNuGY74a+Afg1oi4pZR9BDgVuCQijgLuBQ4t6xYDc4BO4HHgXQCZuSoiPgHcWOotyMxVZf69wHnAs4DvlkmSJEmSJI0gQ57UyMyf0HrcC4B9W9RP4Oge9nUucG6L8iXAnv0IU5IkSZIkDXNtffqJJEmSJEnSpjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaolkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaolkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZMakiSJEmSpFoyqSFJkiRJkmrJpIYkSZIkSaolkxqSJEmSJKmWTGpIkiRJkqRaMqkhSZIkSZJqyaSGJEmSJEmqJZMakiRJkiSplkxqSJIkSZKkWjKpIUmSJEmSasmkhiRJkiRJqiWTGpIkSZIkqZZGbFIjImZHxJ0R0RkRx7c7HkmSVD8bak9ExBYRcXFZf31ETGlYd0IpvzMiZg1l3JIkjRYjMqkREWOAM4EDgBnAYRExo71RSZKkOulje+IoYHVmTgPOAE4r284A5gJ7ALOBs8r+JEnSABqRSQ1gL6AzM+/J/9/e/bzacZdhAH8eehWLiwhRxF/ULrqyihBBspFAEcUuAiI0XVVcBETxXxCEUsQsbJcFCxLBIIVCrJZSENwI2gpqjaAUXDTWRUUtqMWa+rrIUYM2eEXvmXvmfD5w4czcmcNzF3N4eO935sy8kuRSkrMLZwIAdsth+sTZJF/dvH40yV1tu9l/aWb+PDO/TPLc5v0AgP+jtQ413pHk+Ru2r272AQAc1mH6xD+OmZlrSV5KcvKQ5wIA/6ODpQMckb7Gvvm3g9rzSc5vNv/Q9udHmoojd1vy5iS/WTrHXvj8a11m8E+uxy07umvytqN64x1wmD5xs2MO1UUSfWSNfP5tkT7Cf+B63LIF+shahxpXk7zrhu13JnnhXw+amYeTPLytUBy9ts/MzAeWzgG4HlmFw/SJvx9zte1BkhNJfnvIc5PoI2vk8w+OD9fj+q319pOnk9zR9va2r8/1B3VdXjgTALBbDtMnLie5b/P6E0m+MzOz2X9u8+0otye5I8kPtpQbAPbGKldqzMy1tp9N8mSSW5I8MjNXFo4FAOyQm/WJtl9I8szMXE7ylSQX2z6X6ys0zm3OvdL2G0l+luRaks/MzKuL/CEAsGK9/s8EWIe25zfLeIGFuR6BfeXzD44P1+P6GWoAAAAAO2mtz9QAAAAAVs5Qg53XdtpevGH7oO2LbR9fMhfsq7avtv3RDT/vXjoTwFHTR+B40Uf2xyofFMre+WOSO9veOjMvJ/lwkl8tnAn22csz8/6lQwBsmT4Cx4s+sies1GAtnkhy9+b1vUm+vmAWAGA/6SMAW2aowVpcSnKu7RuSvC/J9xfOA/vs1huWej62dBiALdJH4PjQR/aE209YhZn5yeY+uXuTfHvZNLD3LPcE9pI+AseKPrInDDVYk8tJLiQ5k+TkslEAgD2ljwBskaEGa/JIkpdm5tm2Z5YOAwDsJX0EYIsMNViNmbma5MGlcwAA+0sfAdiuzszSGQAAAAD+a779BAAAANhJhhoAAADATjLUAAAAAHaSoQYAAACwkww1AAAAgJ1kqAEAAADsJEMNAAAAYCcZagBb1/aNbb/V9sdtf9r2nran2n637Q/bPtn2bW0P2j7d9szmvAfa3r9wfABgBfQRWIeDpQMAe+mjSV6YmbuTpO2JJE8kOTszL7a9J8n9M/Optp9M8mjbz23O++BSoQGAVdFHYAUMNYAlPJvkQtsvJnk8ye+S3JnkqbZJckuSXyfJzFxpezHJN5OcnplXlokMAKyMPgIrYKgBbN3M/KLtqSQfS/JAkqeSXJmZ0zc55b1Jfp/krVuKCACsnD4C6+CZGsDWtX17kj/NzNeSXMj1JZxvaXt68/vXtX3P5vXHk5xM8qEkD7V900KxAYAV0UdgHTozS2cA9kzbjyT5UpK/JvlLkk8nuZbkoSQncn0V2ZeTPJbke0numpnnN/exnpqZ+xYJDgCshj4C62CoAQAAAOwkt58AAAAAO8lQAwAAANhJhhoAAADATjLUAAAAAHaSoQYAAACwkww1AAAAgJ1kqAEAAADsJEMNAAAAYCf9DajFdPOL2TRRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1ee8PpxprZT5qKyYvNKxl5peofjR+huof7SLgBKqsNVTXqC6gGsn6HuB/ShmZ+b9UB9QfUt114idvcPNnAJdF1f3vQw3mX0LVNfTHVCNav0A1yFFf9usp4HDgbKqD8mSqUZK7fY5qwKJnqRId365bxd9TNdCeiYhPlR+qM6i6R3a/TyfSnP8RZ1DzvmTmAqrRoc+nGihqIdW1h1ANuHQ2VU+GpVQHlk+Xed0Nw+UR8T9UdyG5ta4L4ceoGn0PUF17+gmAzLyR6i4e36LK7v8Or3ddXZubqO6osjQinuql3l9RNboeofruXEH1mfcqM+8ty84tsa0ssb/Yy2L9/R5fAXyWqovvHlRdVSVpWOlPm6CPrqS6Fv+mcpzu9hWqHgzXR8RKqsE79+5lPdtQJbJ/Q3WJyY9onERZ53ZEH/0lcGaJ+XReP9vffUnjF4D/LsfzfTLzGqrekXOjukzjl1Q9URrKzBep2ifvZfWeKptSndh4mtfvvPWPPazmw1Tv5Qqq49icmnlzyvKLqe7U8bO6ZS8GppT4v1NOPLwf2I3q/XyK6of/Zgy8rwCHRcTTEXFeuYxmGlVbZAlVm6d7MEqo2jOPlvf1z6l61JKZD1B97x4p+7ED1Y/u2t4uX6L67K6n+k5dDGyYmcupevX8LdV7fBLwx3Xf3YYaff49VF2n72hmvkR1+dWxVAO5fpQqqdJjW6gPbbs/o2rbLqfq0VPfI+g2qvb0U2XfDivvkdpIrH5pjyQNTRHxVeCXmfnVVscykMqZimeAyZn5qyas/1Kqwb4+M9DrliRJg6ecLDssMxudNBvSIuI24GuZ+fUmrPsoqsE79x3odWtg2fNC0nBxN3BNq4MYCBHx/tKleWOqs0338PpAY5IkSY08A5zb6iAGQkT8UURsUy4bmUV1u94ftDoutVZf7wYgSW0tMy9qdQwDaAZVN8ug6sI8M+0mJ0mSepGZ17c6hgH0FqrLXTahulvKYWU8M41gXjYiSZIkSZLampeNSJIkSZKktta05EW5xeHdNY/fRMQnImLLiLghIh4qz1uU+hER50XEwoj4RUTsXrOuWaX+Q+Wap+7yPSLinrLMeRGxttsJSpIkSZKkIWZQLhsp96leTHUro+Op7hl9dkScAmyRmSdHxMFUt845uNT7SmbuHRFbUl3zPRVI4E5gj8x8OiJuBz5Odeuj+cB5mfn93mLZaqutctKkSU3ZT0mShqo777zzqczsaHUcI4FtEUmSGuutPTJYA3buDzycmb+OiBlU98AGuAy4BTiZaoC6OWVQup9FxOYRsW2pe0NmrgCIiBuA6RFxC7BpZt5ayucAhwK9Ji8mTZrEggULBnbvJEka4iLi162OYaSwLSJJUmO9tUcGa8yLmcCV5fWbukeKLc9bl/IJwKKaZbpKWW/lXQ3K1xARsyNiQUQsWLZsWT93RZIkSZIkDaamJy8iYgxwCPAfa6vaoCzXoXzNwsyLMnNqZk7t6LBHrCRJkiRJQ8lg9Lw4CPifzHyiTD9RLgehPD9ZyruA7WuW6wSWrKW8s0G5JEmSJEkaRgZjzIsjeP2SEYB5wCzg7PJ8bU35CRExl2rAzmcz8/GIuA74u+67kgDTgFMzc0VErIyIfYDbgCOBf27+7kiS1NjLL79MV1cXL7zwQqtD6dHYsWPp7Oxk/fXXb3UokiSpCYZre6SpyYuI2Ag4ADiupvhs4KqIOBZ4DDi8lM+nutPIQuB54GiAkqQ4C7ij1Duze/BO4C+AS4ENqQbq7HWwTkmSmqmrq4tx48YxadIk2vHu3ZnJ8uXL6erqYscdd2x1OJIkqQmGa3ukqcmLzHweGF9Xtpzq7iP1dZPqNqqN1nMJcEmD8gXALgMSrCRJ/fTCCy+0bUMBICIYP348Dl4tSdLwNVzbI4N1txFJkkaEdm0odGv3+CRJUv+1+/F+XeIzeSFJUos888wzfPWrX12nZb/85S/z/PPPD3BEkiRpJBlKbRGTF5IktchQajBIkqThZyi1RQbjbiOSJKmBU045hYcffpjddtuNAw44gK233pqrrrqKF198kQ984AN87nOf47nnnuNDH/oQXV1dvPLKK5x22mk88cQTLFmyhHe/+91stdVW3Hzzza3eFUmSNAQNpbaIyQtJklrk7LPP5pe//CV33303119/PVdffTW33347mckhhxzCj3/8Y5YtW8Z2223H9773PQCeffZZNttsM770pS9x8803s9VWW7V4LyRJ0lA1lNoiXjYiSVIbuP7667n++ut5+9vfzu67784DDzzAQw89xK677soPf/hDTj75ZP7rv/6LzTbbrNWhSpKkYajd2yL2vJAkqQ1kJqeeeirHHXfcGvPuvPNO5s+fz6mnnsq0adM4/fTTWxChJLWHk046iaVLl7LNNttwzjnntDocadho97aIyQupzmNn7trqEFYz8fR7Wh2CpCYZN24cK1euBODAAw/ktNNO4yMf+QibbLIJixcvZv3112fVqlVsueWWfPSjH2WTTTbh0ksvXW1ZLxuRNNIsXbqUxYsXtzoMaVgYSm0RkxeSJLXI+PHjeec738kuu+zCQQcdxIc//GHe8Y53ALDJJpvwjW98g4ULF3LiiSey3nrrsf7663PhhRcCMHv2bA466CC23XZbB+yUJEnrZCi1RSIzm76RdjJ16tRcsGBBq8NQG7PnhaR1df/99/PWt7611WGsVaM4I+LOzJzaopBGFNsiUv8ceeSRLF68mAkTJjBnzpxWhyO1neHaHnHATkmSJEmS1NZMXkiSJEmSpLZm8kKSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqayYvJEkaRn7wgx/wlre8hZ122omzzz671eFIkqQRqBntkdEDshZJkrSGPU6cM6Dru/Mfjux1/iuvvMLxxx/PDTfcQGdnJ3vuuSeHHHIIU6ZMGdA4JEnS0DFc2iP2vJAkaZi4/fbb2WmnnXjzm9/MmDFjmDlzJtdee22rw5IkSSNIs9ojJi8kSRomFi9ezPbbb//adGdnJ4sXL25hRJIkaaRpVnvE5IUkScNEZq5RFhEtiESSJI1UzWqPOOaFJEnDRGdnJ4sWLXptuquri+22266FEUmShrqTTjqJpUuXss0223DOOee0OhwNAc1qj5i8kCRpmNhzzz156KGH+NWvfsWECROYO3cuV1xxRavDkqTXDMTAgeOeWsko4LGnVg7I+tY2+OBIt3TpUi9B1BvSrPaIyQtJkoaJ0aNHc/7553PggQfyyiuvcMwxx7Dzzju3OixJkjSCNKs9YvJCkqQmacXZvIMPPpiDDz540Ler9mR3b0nScGmPmLyQJEkapuzuLUkaLrzbiCRJkiRJamsmLyRJ0ogXEdMj4sGIWBgRpzSYv0FEfLPMvy0iJpXySRHxfxFxd3l8bbBjlyRpJPCyEUmSNKJFxCjgAuAAoAu4IyLmZeZ9NdWOBZ7OzJ0iYibwReBPyryHM3O3QQ1akqQRxp4XkiRppNsLWJiZj2TmS8BcYEZdnRnAZeX11cD+ERGDGKMkSSOayQtJkjTSTQAW1Ux3lbKGdTJzFfAsML7M2zEi7oqIH0XEHzbaQETMjogFEbFg2bJlAxu9JEkjgMkLSZKGkWOOOYatt96aXXbZpdWhDCWNelBkH+s8DkzMzLcDnwSuiIhN16iYeVFmTs3MqR0dHf0OWJKkdtaM9ohjXkiS1CSPnbnrgK5v4un3rLXOUUcdxQknnMCRRw7+Pd2HsC5g+5rpTmBJD3W6ImI0sBmwIjMTeBEgM++MiIeB3wUWND1qSZL6YLi0R+x5IUnSMLLffvux5ZZbtjqMoeYOYHJE7BgRY4CZwLy6OvOAWeX1YcBNmZkR0VEG/CQi3gxMBh4ZpLglSWpLzWiP2PNCkiSNaJm5KiJOAK4DRgGXZOa9EXEmsCAz5wEXA5dHxEJgBVWCA2A/4MyIWAW8Avx5Zq4Y/L2QpNXtceKcAVnPuKdWMgp47KmV/V7nnf9gr0CtO5MXkiRpxMvM+cD8urLTa16/ABzeYLlvAd9qeoCSJI1wXjYiSZIkSZLaWlOTFxGxeURcHREPRMT9EfGOiNgyIm6IiIfK8xalbkTEeRGxMCJ+ERG716xnVqn/UETMqinfIyLuKcuc5/3WJUmS1AonnXQSRx55JCeddFKrQxn2Xh2zMa9ssCmvjtm41aFIA8r/I71rds+LrwA/yMzfA34fuB84BbgxMycDN5ZpgIOoBrmaDMwGLgSIiC2BzwJ7A3sBn+1OeJQ6s2uWm97k/ZEkqa0dccQRvOMd7+DBBx+ks7OTiy++uNUhSSPC0qVLWbx4MUuXLm11KMPec5OnsXLnD/Dc5GmtDkUaUMPp/0gz2iNNG/Oi3ON8P+AogMx8CXgpImYA7yrVLgNuAU4GZgBzyi3HflZ6bWxb6t7QPfhVRNwATI+IW4BNM/PWUj4HOBT4frP2SZKkN6IvtxIbaFdeeeWgb1PNMRCD7TnQniRpuLRHmtnz4s3AMuDrEXFXRPxbRGwMvCkzHwcoz1uX+hOARTXLd5Wy3sq7GpRLkiRJkqRhpJnJi9HA7sCFmfl24Dlev0SkkUbjVeQ6lK+54ojZEbEgIhYsW7as96glSZIkSVJbaWbyogvoyszbyvTVVMmMJ8rlIJTnJ2vqb1+zfCewZC3lnQ3K15CZF2Xm1Myc2tHR0a+dkiRJkiRJg6tpyYvMXAosioi3lKL9gfuAeUD3HUNmAdeW1/OAI8tdR/YBni2XlVwHTIuILcpAndOA68q8lRGxT7nLyJE165IkqSWqoZvaV7vHJ0mS+q/dj/frEl/TBuws/gr494gYAzwCHE2VMLkqIo4FHgMOL3XnAwcDC4HnS10yc0VEnAXcUeqd2T14J/AXwKXAhlQDdTpYpySpZcaOHcvy5csZP3487Xj37sxk+fLljB07ttWhSJKkJhmu7ZGmJi8y825gaoNZ+zeom8DxPaznEuCSBuULgF36GaYkSQOis7OTrq4u2nl8pbFjx9LZ2bn2ipIkaUgaru2RZve8kCRpxFh//fXZcccdWx2GJEkawYZre8TkhSRJkka0PU6c0+91jHtqJaOAx55a2e/13fkPR/Y7HmmgvDpm49WepVYxeSFJkiRJaui5ydNaHYIENPdWqZIkSZIkSf1mzwtJkiQNipNOOomlS5eyzTbbcM4557Q6HEnSEGLyQi01ENeYDrRrxrU6AkmShqelS5eyePHiVochSRqCTF5IkiRJUj/Yq0gO/Nt8Ji8kSZIkqR/sVSQ1n8kLSZKkYcpbHEoabuzlMnKZvJAkSRqmvMWhpOHGXi4jl7dKlSRJkiRJbc3khSRJkiRJamteNiJJkiT1UzuOL+LYAJKGE5MXkiRJUj+14/gijg0gaTjxshFJkiRJktTWTF5IkiRJkqS2ZvJCkiRJkiS1NZMXkiRJkiSprTlgpyRJktbqsTN37fc6Vq3YEhjNqhW/HpD1TTz9nn6vQ5I0NNjzQpIkSZIktTV7XkiSJEkasdqtV9Fw7lHUbu81tNf7/eqYjVd7bgcnnXQSS5cuZZtttuGcc85paSwmLyRJkiRJarHnJk9rdQhrWLp0KYsXL251GIDJC0mSJKmtDMTZZLA3gKThxTEvJEmSJElSWzN5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLZm8kKSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqa6NbHYAkSZJGhq3GvgqsKs+S9Mb5f2TkMnkhSZKkQfGptz3T6hBGFH/kaTjy/8jIZfJCkiRJGob8kSdpODF5IUmSJEn9YC8XtZvHztx1QNazasWWwGhWrfh1v9c58fR7+rW8yQtJkiRJ6gd7uUjN591GJEmSJElSW2tq8iIiHo2IeyLi7ohYUMq2jIgbIuKh8rxFKY+IOC8iFkbELyJi95r1zCr1H4qIWTXle5T1LyzLRjP3R5IkSZIkDb7B6Hnx7szcLTOnlulTgBszczJwY5kGOAiYXB6zgQuhSnYAnwX2BvYCPtud8Ch1ZtcsN735uyNJkoabiJgeEQ+WEyKnNJi/QUR8s8y/LSIm1c2fGBG/jYhPDVbMkiSNJK24bGQGcFl5fRlwaE35nKz8DKmNzM8AACAASURBVNg8IrYFDgRuyMwVmfk0cAMwvczbNDNvzcwE5tSsS5IkqU8iYhRwAdWJlCnAERExpa7ascDTmbkTcC7wxbr55wLfb3askiSNVM1OXiRwfUTcGRGzS9mbMvNxgPK8dSmfACyqWbarlPVW3tWgXJIk6Y3YC1iYmY9k5kvAXKqTKrVqT75cDezffblqRBwKPALcO0jxSpI04jT7biPvzMwlEbE1cENEPNBL3UbjVeQ6lK+54ipxMhtg4sSJvUcsSZJGmkYnSvbuqU5mroqIZ4HxEfF/wMnAAYCXjEiS1CRN7XmRmUvK85PANVRnNp4ol3xQnp8s1buA7WsW7wSWrKW8s0F5ozguysypmTm1o6Ojv7slSZKGl76cEOmpzueAczPzt71uIGJ2RCyIiAXLli1bxzAlSRq5mpa8iIiNI2Jc92tgGvBLYB7QfceQWcC15fU84Mhy15F9gGfLZSXXAdMiYosyUOc04Loyb2VE7FO6bR5Zsy5JkqS+6ulEScM6ETEa2AxYQdVD45yIeBT4BPDpiDihfgOeSJEkqX+aednIm4BryuWgo4ErMvMHEXEHcFVEHAs8Bhxe6s8HDgYWAs8DRwNk5oqIOAu4o9Q7MzNXlNd/AVwKbEg1SJYDZUmSpDfqDmByROwILAZmAh+uq9N98uVW4DDgpjJg+B92V4iIM4DfZub5gxG0JEkjSdOSF5n5CPD7DcqXA/s3KE/g+B7WdQlwSYPyBcAu/Q5WkiSNWGUMixOoenuOAi7JzHsj4kxgQWbOAy4GLo+IhVQ9Lma2LmJJkkaeZg/YKUmS1PYycz5VL9DastNrXr/A671Fe1rHGU0JTpIkmbyQJEmSJElr2mrsq8Cq8txaJi8kSZIkSdIaPvW2Z1odwmuaeqtUSZIkSZKk/jJ5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLbmgJ2SNAI8duaurQ5hDRNPv6fVIUiSJGmIsOeFJEmSJElqayYvJEmSJElSWzN5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLZm8kKSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqayYvJEmSJElSWzN5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLZm8kKSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqayYvJEmSJElSWzN5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLZm8kKSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqayYvJEmSJElSWzN5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLY2utUBSNJwtMeJc1odwmquGdfqCCRJkqR11/SeFxExKiLuiojvlukdI+K2iHgoIr4ZEWNK+QZlemGZP6lmHaeW8gcj4sCa8umlbGFEnNLsfZEkSZIkSYNvMC4b+Thwf830F4FzM3My8DRwbCk/Fng6M3cCzi31iIgpwExgZ2A68NWSEBkFXAAcBEwBjih1JUnSCBURHRHx6Yi4KCIu6X60Oi5JktQ/TU1eREQn8D7g38p0AO8Bri5VLgMOLa9nlGnK/P1L/RnA3Mx8MTN/BSwE9iqPhZn5SGa+BMwtdSVJ0sh1LbAZ8EPgezUPSZI0hDV7zIsvAycB3VdbjweeycxVZboLmFBeTwAWAWTmqoh4ttSfAPysZp21yyyqK9+7URARMRuYDTBx4sR+7I4kSWpzG2Xmya0OQpIkDaym9byIiD8GnszMO2uLG1TNtcx7o+VrFmZelJlTM3NqR0dHL1FLkqQh7rsRcXCrg5AkSQOrmT0v3gkcUhoQY4FNqXpibB4Ro0vvi05gSanfBWwPdEXEaKounytqyrvVLtNTuSRJGpk+Dnw6Il4CXi5lmZmbtjAmSZLUT03reZGZp2ZmZ2ZOohpw86bM/AhwM3BYqTaL6tpUgHllmjL/pszMUj6z3I1kR2AycDtwBzC53L1kTNnGvGbtjyRJan+ZOS4z18vMseX1OBMXkiQNfc0e86KRk4G5EfF54C7g4lJ+MXB5RCyk6nExEyAz742Iq4D7gFXA8Zn5CkBEnABcB4wCLsnMewd1TyRJUtuJiEOA/crkLZn53VbGI0mS+m9QkheZeQtwS3n9CNWdQurrvAAc3sPyXwC+0KB8PjB/AEOVJElDWEScDewJ/Hsp+nhE7JuZp7QwLEmS1E+t6HkhSZLULAcDu2XmqwARcRlVT0+TF5IkDWFNG/NCkiSpRTaveb1Zy6KQJEkDxp4XkiRpOPl74K6IuJnqtur7Aae2NiRJktRf9ryQJEnDRmZeCewDfLs83pGZc9e2XERMj4gHI2JhRKxxiUm569k3y/zbImJSKd8rIu4uj59HxAcGdo8kSRL0MXkRETf2pUySJKkVIuL3yvPuwLZAF7AI2K6U9bbsKOAC4CBgCnBEREypq3Ys8HRm7gScC3yxlP8SmJqZuwHTgX+JCHu2SpI0wHo9uEbEWGAjYKuI2IKq+yXApsB2TY5NkiSprz4JzAb+qcG8BN7Ty7J7AQvLHdGIiLnADKrbtHebAZxRXl8NnB8RkZnP19QZW7YlSZIG2NrODBwHfIIqUXEnrycvfkN1hkKSJKnlMnN2eX73Oiw+gaqXRrcuYO+e6mTmqoh4FhgPPBURewOXADsAH8vMVfUbiIjZVMkVJk6cuA4hSpI0svV62UhmfiUzdwQ+lZlvzswdy+P3M/P8QYpRkiSpTyLi8IgYV15/JiK+HRFvX9tiDcrqe1D0WCczb8vMnYE9gVNLz9XVK2ZelJlTM3NqR0fH2ndEkiStpk/XZGbmP0fEHwCTapfJzDlNikuSJGldnJaZ/xER+wIHAv8IfI01e1LU6gK2r5nuBJb0UKerjGmxGbCitkJm3h8RzwG7AAv6tReSJGk1fR2w83Kqg/++VGcV9gSmNjEuSZKkdfFKeX4fcGFmXguMWcsydwCTI2LHiBgDzATm1dWZB8wqrw8DbsrMLMuMBoiIHYC3AI/2fzckSVKtvo6GPRWYkpkOQiVJktrZ4oj4F+C9wBcjYgPWfpnsqog4AbgOGAVckpn3RsSZwILMnAdcDFweEQupelzMLIvvC5wSES8DrwJ/mZlPNWXPJEkawfqavPglsA3weBNjkSRJ6q8PUd2y9B8z85mI2BY4cW0LZeZ8YH5d2ek1r18ADm+w3OXA5f0NWpIk9a6vyYutgPsi4nbgxe7CzDykKVFJkiS9QRGxHnB7Zu7SXZaZj+PJF0mShry+Ji/OaGYQkiRJ/ZWZr0bEzyNiYmY+1up4JEnSwOnr3UZ+1OxAJEmSBsC2wL2lt+hz3YX2FpUkaWjrU/IiIlby+v3OxwDrA89l5qbNCkySJGkdfK7VAUiSpIHX154X42qnI+JQYK+mRCRJkrSOMvNH5ZalkzPzhxGxEdUdRCRJ0hDW663DepKZ3wHeM8CxSJIk9UtE/BlwNfAvpWgC8J3WRSRJkgZCXy8b+WDN5HrAVF6/jESSJKldHE/VO/Q2gMx8KCK2bm1IkiSpv/p6t5H317xeBTwKzBjwaCRJkvrnxcx8KSIAiIjReMJFkqQhr69jXhzd7EAkSZIGwI8i4tPAhhFxAPCXwH+2OCZJktRPfRrzIiI6I+KaiHgyIp6IiG9FRGezg5MkSXqDTgGWAfcAxwHzgc+0NCJJktRvfb1s5OvAFcDhZfqjpeyAZgQlaWR47MxdWx3Caiaefk+rQ9Aw0G7faxhx3+0ZwJzM/NdWByJJkgZOX+820pGZX8/MVeVxKdDRxLgkSZLWxSHA/0bE5RHxvjLmhSRJGuL6ekB/KiI+ClxZpo8AljcnJNXzLJ4kSX2TmUdHxPrAQcCHga9GxA2Z+actDk2SJPVDX3teHAN8CFgKPA4cBjiIpyRJajuZ+TLwfWAucCfeIU2SpCGvr8mLs4BZmdmRmVtTJTPOaFpUkiRJ6yAipkfEpcBCqpMt/wZs29KgJElSv/X1spG3ZebT3ROZuSIi3t6kmCRJktbVUVQ9Lo7LzBdbHIskSRogfU1erBcRW3QnMCJiyzewrCRJ0qDIzJmtjkGSJA28viYg/gn4aURcDSTV+BdfaFpUkiRJ6yAiPgh8EdgaiPLIzNy0pYFJkqR+6VPyIjPnRMQC4D1UjYAPZuZ9TY1MkiTpjTsHeH9m3t/qQCRJ0sDp86UfJVlhwkKSJLWzJ0xcSJI0/DhuhSRJGk4WRMQ3ge8Arw3YmZnfbl1IkiSpv0xeSJKk4WRT4HlgWk1ZAiYvJEkawkxeSJKkYSMzj251DJIkaeCt1+oAJEmSBkpEdEbENRHxZEQ8ERHfiojOVsclSZL6x+SFJEkaTr4OzAO2AyYA/1nKJEnSENa05EVEjI2I2yPi5xFxb0R8rpTvGBG3RcRDEfHNiBhTyjco0wvL/Ek16zq1lD8YEQfWlE8vZQsj4pRm7YskSRoyOjLz65m5qjwuBTpaHZQkSeqfZva8eBF4T2b+PrAbMD0i9gG+CJybmZOBp4FjS/1jgaczcyfg3FKPiJgCzAR2BqYDX42IURExCrgAOAiYAhxR6kqSpJHrqYj4aHdbISI+CixvdVCSJKl/mpa8yMpvy+T65ZHAe4CrS/llwKHl9YwyTZm/f0REKZ+bmS9m5q+AhcBe5bEwMx/JzJeAuaWuJEkauY4BPgQsBR4HDgMcxFOSpCGuqWNelDMedwNPAjcADwPPZOaqUqWL6npUyvMigDL/WWB8bXndMj2VN4pjdkQsiIgFy5YtG4hdkyRJ7eksYFZmdmTm1lTJjDNaG5IkSeqvpiYvMvOVzNwN6KTqKfHWRtXKc/Qw742WN4rjosycmplTOzq87FWSpGHsbZn5dPdEZq4A3t7CeCRJ0gAYlLuNZOYzwC3APsDmETG6zOoElpTXXcD2AGX+ZsCK2vK6ZXoqlyRJI9d6EbFF90REbAmM7qW+JEkaApp5t5GOiNi8vN4QeC9wP3Az1fWnALOAa8vreWWaMv+mzMxSPrPcjWRHYDJwO3AHMLncvWQM1aCe85q1P5IkaUj4J+CnEXFWRJwJ/BQ4p8UxSZKkfmrmmYhtgcvKXUHWA67KzO9GxH3A3Ij4PHAXcHGpfzFweUQspOpxMRMgM++NiKuA+4BVwPGZ+QpARJwAXAeMAi7JzHubuD+SJKnNZeaciFhANUB4AB/MzPtaHJYkSeqnpiUvMvMXNLjGNDMfoRr/or78BeDwHtb1BeALDcrnA/P7HWydPU6cM9Cr7JdrxrU6Ag0H7fa9Br/bGhjt9t32e916JVlhwkKSpGFkUMa8kCRJkiRJWlcmLyRJkiRJUlszeSFJkiRJktqayQtJkiRJktTWTF5IkiRJkqS2ZvJCkiRJkiS1NZMXkiRJkiSprZm8kCRJkiRJbc3khSRJkiRJamsmLyRJkiRJUlszeSFJkiRJktqayQtJkiRJktTWTF5IkiRJkqS2ZvJCkiRJkiS1NZMXkiRpxIuI6RHxYEQsjIhTGszfICK+WebfFhGTSvkBEXFnRNxTnt8z2LFLkjQSmLyQJEkjWkSMAi4ADgKmAEdExJS6ascCT2fmTsC5wBdL+VPA+zNzV2AWcPngRC1J0shi8kKSJI10ewELM/ORzHwJmAvMqKszA7isvL4a2D8iIjPvyswlpfxeYGxEbDAoUUuSNIKYvJAkSSPdBGBRzXRXKWtYJzNXAc8C4+vq/D/grsx8sUlxSpI0Yo1udQCSJEktFg3K8o3UiYidqS4lmdZwAxGzgdkAEydOXLcoJUkawex5IUmSRrouYPua6U5gSU91ImI0sBmwokx3AtcAR2bmw402kJkXZebUzJza0dExwOFLkjT8mbyQJEkj3R3A5IjYMSLGADOBeXV15lENyAlwGHBTZmZEbA58Dzg1M/970CKWJGmEMXkhSZJGtDKGxQnAdcD9wFWZeW9EnBkRh5RqFwPjI2Ih8Emg+3aqJwA7AadFxN3lsfUg74IkScOeY15IkqQRLzPnA/Pryk6vef0CcHiD5T4PfL7pAUqSNMLZ80KSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqayYvJEmSJElSWzN5IUmSJEmS2prJC0mSJEmS1NZMXkiSJEmSpLZm8kKSJEmSJLU1kxeSJEmSJKmtmbyQJEmSJEltzeSFJEmSJElqayYvJEmSJElSWzN5IUmSJEmS2lrTkhcRsX1E3BwR90fEvRHx8VK+ZUTcEBEPlectSnlExHkRsTAifhERu9esa1ap/1BEzKop3yMi7inLnBcR0az9kSRJkiRJrdHMnhergL/NzLcC+wDHR8QU4BTgxsycDNxYpgEOAiaXx2zgQqiSHcBngb2BvYDPdic8Sp3ZNctNb+L+SJIkSZKkFmha8iIzH8/M/ymvVwL3AxOAGcBlpdplwKHl9QxgTlZ+BmweEdsCBwI3ZOaKzHwauAGYXuZtmpm3ZmYCc2rWJUmSJEmSholBGfMiIiYBbwduA96UmY9DleAAti7VJgCLahbrKmW9lXc1KG+0/dkRsSAiFixbtqy/uyNJkiRJkgZR05MXEbEJ8C3gE5n5m96qNijLdShfszDzosycmplTOzo61hayJEmSJElqI01NXkTE+lSJi3/PzG+X4ifKJR+U5ydLeRewfc3incCStZR3NiiXJEmSJEnDSDPvNhLAxcD9mfmlmlnzgO47hswCrq0pP7LcdWQf4NlyWcl1wLSI2KIM1DkNuK7MWxkR+5RtHVmzLkmSJEmSNEyMbuK63wl8DLgnIu4uZZ8GzgauiohjgceAw8u8+cDBwELgeeBogMxcERFnAXeUemdm5ory+i+AS4ENge+XhyRJkiRJGkaalrzIzJ/QeFwKgP0b1E/g+B7WdQlwSYPyBcAu/QhTkiRJkiS1uUG524gkSZIkSdK6MnkhSZIkSZLamskLSZIkSZLU1kxeSJIkSZKktmbyQpIkSZIktTWTF5IkSZIkqa2ZvJAkSZIkSW3N5IUkSZIkSWprJi8kSZIkSVJbM3khSZIkSZLamskLSZIkSZLU1kxeSJIkSZKktmbyQpIkSZIktTWTF5IkSZIkqa2ZvJAkSZIkSW3N5IUkSZIkSWprJi8kSZIkSVJbM3khSZIkSZLamskLSZIkSZLU1kxeSJIkSZKktmbyQpIkSZIktTWTF5IkSZIkqa2ZvJAkSZIkSW3N5IUkSZIkSWprJi8kSZIkSVJbM3khSZIkSZLamskLSZI04kXE9Ih4MCIWRsQpDeZvEBHfLPNvi4hJpXx8RNwcEb+NiPMHO25JkkYKkxeSJGlEi4hRwAXAQcAU4IiImFJX7Vjg6czcCTgX+GIpfwE4DfjUIIUrSdKIZPJCkiSNdHsBCzPzkcx8CZgLzKirMwO4rLy+Gtg/IiIzn8vMn1AlMSRJUpOYvJAkSSPdBGBRzXRXKWtYJzNXAc8C4/u6gYiYHRELImLBsmXL+hmuJEkjj8kLSZI00kWDslyHOj3KzIsyc2pmTu3o6HhDwUmSJJMXkiRJXcD2NdOdwJKe6kTEaGAzYMWgRCdJkkxeSJKkEe8OYHJE7BgRY4CZwLy6OvOAWeX1YcBNmdnnnheSJKl/Rrc6AEmSpFbKzFURcQJwHTAKuCQz742IM4EFmTkPuBi4PCIWUvW4mNm9fEQ8CmwKjImIQ4FpmXnfYO+HJEnDmckLSZI04mXmfGB+XdnpNa9fAA7vYdlJTQ1OkiR52YgkSZIkSWpvJi8kSZIkSVJba1ryIiIuiYgnI+KXNWVbRsQNEfFQed6ilEdEnBcRCyPiFxGxe80ys0r9hyJiVk35HhFxT1nmvIhodAszSZIkSZI0xDWz58WlwPS6slOAGzNzMnBjmQY4CJhcHrOBC6FKdgCfBfYG9gI+253wKHVm1yxXvy1JkiRJkjQMNC15kZk/Zs37n88ALiuvLwMOrSmfk5WfAZtHxLbAgcANmbkiM58GbgCml3mbZuat5TZlc2rWJUmSJEmShpHBHvPiTZn5OEB53rqUTwAW1dTrKmW9lXc1KJckSZIkScNMuwzY2Wi8ilyH8sYrj5gdEQsiYsGyZcvWMURJkiRJktQKg528eKJc8kF5frKUdwHb19TrBJaspbyzQXlDmXlRZk7NzKkdHR393glJkiRJkjR4Bjt5MQ/ovmPILODamvIjy11H9gGeLZeVXAdMi4gtykCd04DryryVEbFPucvIkTXrkiRJkiRJw8joZq04Iq4E3gVsFRFdVHcNORu4KiKOBR4DDi/V5wMHAwuB54GjATJzRUScBdzx/7d3/7GS3WUdx98fuy0hdLFARetSaZVGXQnUWn4EkKgYLY2y27BNShoo2tig4I8/GluyiZhiY6qJGk2xQShbDVKgsLIgpCWg6R9AZSFLf9AtXaVmN21axdKCjdWWxz/mXB3u3rl3eufeM9859/1KTu6Z7/n1zLPfTJ8+OXOm2++qqlp6COivM/pFk6cDn+oWSZIkSZI0MJvWvKiqN0zY9JoV9i3grRPOcz1w/QrjB4EXzhKjJEmSJElqXysP7JQkSZIkSVqRzQtJkiRJktQ0mxeSJEmSJKlpNi8kSZIkSVLTbF5IkiRJkqSm2byQJEmSJElNs3khSZIkSZKaZvNCkiRJkiQ1zeaFJEmSJElqms0LSZIkSZLUNJsXkiRJkiSpaTYvJEmSJElS02xeSJIkSZKkptm8kCRJkiRJTbN5IUmSJEmSmmbzQpIkSZIkNc3mhSRJkiRJaprNC0mSJEmS1DSbF5IkSZIkqWk2LyRJkiRJUtNsXkiSJEmSpKbZvJAkSZIkSU2zeSFJkiRJkppm80KSJEmSJDXN5oUkSZIkSWqazQtJkiRJktQ0mxeSJEmSJKlpNi8kSZIkSVLTbF5IkiRJkqSm2byQJEmSJElNs3khSZIkSZKaZvNCkiRJkiQ1zeaFJEmSJElqms0LSZIkSZLUNJsXkiRJkiSpaTYvJEmSJElS02xeSJIkSZKkpi188yLJeUnuSXIkyZXzjkeSJC2eteqJJE9L8sFu+21Jzhjb9vZu/J4kv9hn3JIkbRUL3bxIcgJwLfBaYCfwhiQ75xuVJElaJFPWE5cCD1fVC4A/Ba7pjt0JXAT8BHAe8K7ufJIkaQMtdPMCeClwpKr+par+G7gR2DXnmCRJ0mKZpp7YBdzQrd8EvCZJuvEbq+rxqvo6cKQ7nyRJ2kCL3rzYARwde32sG5MkSZrWNPXE/+1TVU8AjwDPmfJYSZI0o23zDmBGWWGsjtspuQy4rHv57ST3bGpUG+z5cCrw7/OO47u8Y6XUD0Nz+TbX/THX/Rpovhc418/f7DAaNk09MWmfLVGLwELP7YVjrvvVXL7Ndb8Gmu8FzvXEemTRmxfHgNPHXj8PuH/5TlX1buDdfQW10ZIcrKpz5x3HVmG++2Ou+2Ou+2OuF9I09cTSPseSbAO+F/iPKY9d+FoEnNt9Mtf9Mt/9Mdf9GWKuF/1rI18EzkpyZpKTGD0w68CcY5IkSYtlmnriAHBJt74H+GxVVTd+UfdrJGcCZwH/1FPckiRtGQt950VVPZHkbcDNwAnA9VV115zDkiRJC2RSPZHkKuBgVR0A3gv8TZIjjO64uKg79q4kHwK+CjwBvLWqnpzLG5EkacAWunkBUFWfBD457zg22ULfZrqAzHd/zHV/zHV/zPUCWqmeqKrfG1v/L+DCCcdeDVy9qQG2wbndH3PdL/PdH3Pdn8HlOqM7HiVJkiRJktq06M+8kCRJkiRJA2fzYh2SnJ7kH5LcneSuJL/djT87yaeT3Nv9fVY3/mNJPp/k8SSXLzvXfUnuSHIoycFVrnl9koeS3Lls/I+THE5ye5L9SU6ZcPyk2C7ujr09yeeSvHjW/GykIeV6bPtLkjyZZM9687JZGsv3hV0M30ky8UnJSd7Z/ZscSnJLkh/sxpPkz5Mc6bafM0tuNlpjuZ71c2TX2L/BwSSvmjU/G2lguZ4Ym7aegc1t65Hjr2k90ka+rUcWZG7HemSlaw6rHqkql6e4AKcB53Tr24GvATuBPwKu7MavBK7p1p8LvITR92EvX3au+4BTp7jmq4FzgDuXjf8CsK1bv2bpmiscPym2VwDP6tZfC9w27/wONdfd6xOAzzL6XvWeeee38Xz/OPCjwD8C565y/DPH1n8LuK5bPx/4FBDg5c7tTf0cOZn//xrii4DD887vgHM9MTaXrbcMbG5bj/SU6+619cj0+bYeWZC5jfVIn7meSz3inRfrUFUPVNWXu/VvAXcDO4BdwA3dbjcAu7t9HqqqLwL/M8M1b2X0dPPl47dU1RPdyy8w+n35lUyK7XNV9fAUx8/FkHLd+U3gI8BD641vMzWW77ur6p4pjn907OUzgKUH+ewC/rpGvgCckuS09ca50RrL9ayfI9+u7r9kfPe/QRMGluuZY9NwDGxuW48cf03rEZrIt/XIgsxt65EVrzmoesTmxYySnAH8JHAb8P1V9QCMJiejjtRaCrglyZeSXDZjOL/KqLO7kmliu3SV4+du0XOdZAdwAXDdjNfuRWP5XlWSq5McBS4Gln4dYAdwdGy3Y91YcxrL9bo+R5JckOQw8PfdOZo0hFxLKxnY3LYemZ71yNqsR6bUWK6tR1Y391zPw8L/VOo8JTmZUdf6d6rq0STrOc0rq+r+JM8FPp3kcNche6qx7GX0+/LvX08QSX6WUbHQ1HfDlgwk138GXFFVT64z/t60lO9pVNVeYG+StwNvA97B6PbM43bdjOvPoqVcz/I5UlX7gf1JXg28E/j5p3qOzTaUXEvLDWluW488pVisR6ZjPTKFlnJtPTKVued6HrzzYp2SnMho0r2/qj7aDT+4dBtY93fNW/Gq6v7u70PAfuClGT3M5VC3vGWKWC4Bfgm4eOlWqSTv645f+s36ibEleRHwHmBXVX1jmvffpwHl+lzgxiT3HI0ZaQAAA8lJREFUAXuAdyXZTWNayveE+Jbne9zfAq/v1o8Bp49tex5w/3quuVlayvWsnyNjsdwK/EiSU9e6Zp+GmGsJhjW3rUesR8a1lO8J8VmPLNPA3B6PxXpk7VgWrh6xebEOSQK8F7i7qv5kbNMB4JJu/RLgY2uc5xlJti+tM3pwyp1VdbSqzu6WVW/pS3IecAXwuqp6bGm8qn6lO/781WJL8kPAR4E3VtXX1nrvfRtSrqvqzKo6o6rOAG4CfqOq/m6NFPSqpXxPsjzfSc4a2/w64PBYzG/KyMuBR5Zue2tBS7negM+RF3Tvh4yeon4S0Mz/eAwp19K4Ic1t6xHrkXEt5XsS65HjzjP3uW09sgXqkWrgyauLtjC6lbGA24FD3XI+8BzgM8C93d9nd/v/AKOu66PAN7v1ZwI/DHylW+4C9q5yzQ8ADzB6KMox4NJu/Aij79EtxXHdhOMnxfYe4OGx4w/OO79DzfWyffbR5tO9W8r3Bd3rx4EHgZsnHP8R4M4u5o8DO7rxANcC/wzcwSpPCDfXM3+OXNFd+xDweeBV887vgHO9YmzzzrHLfJaBzW3rkZ5yvWyffViPrJVv65EFmdtYj/SZ67nUI0s/JSNJkiRJktQkvzYiSZIkSZKaZvNCkiRJkiQ1zeaFJEmSJElqms0LSZIkSZLUNJsXkiRJkiSpaTYvJG2qJL+f5PJVtu9OsrPPmCRJ0tZiPSItPpsXkuZtN2CxIEmS5sl6RGpcqmreMUgamCR7gTcBR4F/A74EPAJcBpwEHAHeCJwNfKLb9gjw+u4U1wLfBzwG/FpVHe4zfkmStPisR6RhsXkhaUMl+SlgH/AyYBvwZeA64H1V9Y1unz8AHqyqv0iyD/hEVd3UbfsM8JaqujfJy4A/rKqf6/+dSJKkRWU9Ig3PtnkHIGlwfhrYX1WPASQ50I2/sCsSTgFOBm5efmCSk4FXAB9OsjT8tE2PWJIkDY31iDQwNi8kbYaVbunaB+yuqq8keTPwMyvs8z3AN6vq7M0LTZIkbRHWI9KA+MBOSRvtVuCCJE9Psh345W58O/BAkhOBi8f2/1a3jap6FPh6kgsBMvLi/kKXJEkDYT0iDYzPvJC04cYekPWvwDHgq8B/Ar/bjd0BbK+qNyd5JfBXwOPAHuA7wF8CpwEnAjdW1VW9vwlJkrTQrEekYbF5IUmSJEmSmubXRiRJkiRJUtNsXkiSJEmSpKbZvJAkSZIkSU2zeSFJkiRJkppm80KSJEmSJDXN5oUkSZIkSWqazQtJkiRJktQ0mxeSJEmSJKlp/wtHr2a5XkB5OwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in ['sex','age','date','source','device','browser_language','ads_channel','browser']:\n",
    "    visualization(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "for the date:\n",
    "    1. Test has constantly been worse than control and there is relatively little variance across days. That probably means that we do have enough data, but there was some bias in the experiment set up.\n",
    "    2. On a side note, we just ran it for 5 days. We should always run the test for at least 1 full week to capture weekly patterns, 2 weeks would be much better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of country\n",
    "groupby_sex = data[['country','test', 'conversion']].groupby('country').mean().reset_index()\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize = (18, 6))\n",
    "sns.countplot(x = 'country', hue='test', data = test_data, ax = ax[0])\n",
    "ax[0].set_title('Count of country in test/control group')\n",
    "ax[0].set_xticklabels(ax[0].get_xticklabels(), rotation=45)   # rotate x labels 45 degree\n",
    "                   \n",
    "sns.barplot(x = 'country', y = 'conversion', hue='test', data = test_data, ax = ax[1])\n",
    "# will automatically compute mean value?\n",
    "ax[1].set_title('Conversion rate vs country in test/control group')\n",
    "ax[1].set_xticklabels(ax[1].get_xticklabels(), rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "People from Argentina and Uruguay are much more likely to be distributed to test groups "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way to check this: build a decision tree where the variables are the user\u0001\n",
    "dimensions and the outcome variable is whether the user is in test or control. If the tree splits, it means\u0001\n",
    "that for given values of that variable you are more likely to end up in test or control. But this should be\u0001\n",
    "impossible! Therefore, if the randomization worked, the tree should not split at all (or at least not be able to\u0001\n",
    "separate the two classes well)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "# with fixed country, let's see whether there is difference between test/control groups\n",
    "# get all the country name that is not null\n",
    "country_list = [i for i in test_data['country'].unique() if i is not np.nan]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Country    Control rate    Test rate       p_value        \n",
      "Mexico     0.049495        0.051186        0.165544       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Nicaragua  0.052647        0.054177        0.780400       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Colombia   0.052089        0.050571        0.423719       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Venezuela  0.050344        0.048978        0.573702       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Ecuador    0.049154        0.048988        0.961512       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Paraguay   0.048493        0.049229        0.883697       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Bolivia    0.049369        0.047901        0.718885       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Argentina  0.015071        0.013725        0.335147       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Peru       0.049914        0.050604        0.771953       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Chile      0.048107        0.051295        0.302848       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Guatemala  0.050643        0.048647        0.572107       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Costa Rica 0.052256        0.054738        0.687876       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Honduras   0.050906        0.047540        0.471463       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "El Salvador 0.053554        0.047947        0.248127       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Panama     0.046796        0.049370        0.705327       \n",
      "Country    Control rate    Test rate       p_value        \n",
      "Uruguay    0.012048        0.012907        0.879764       \n"
     ]
    }
   ],
   "source": [
    "for i in country_list:\n",
    "    cont = test_data[(test_data['country'] == i) & (test_data['test'] == 0)]['conversion'].values\n",
    "    test = test_data[(test_data['country'] == i) & (test_data['test'] == 1)]['conversion'].values\n",
    "    control_mean = cont.mean()\n",
    "    test_mean = test.mean()\n",
    "    p_value = ttest_ind(test,cont, equal_var=False)[1]\n",
    "    print('{0: <10s} {1:<15s} {2:<15s} {3:<15s}'.format('Country', \n",
    "                                                       'Control rate',\n",
    "                                                       'Test rate',\n",
    "                                                       'p_value'))\n",
    "    print('{0:<10s} {1:<15f} {2:<15f} {3:<15f}'.format(i, control_mean, test_mean, p_value))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With fixed country, the p-value changes from 1.428e-13 to values > 0.05, so we fail to reject the null hypothesis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After we control for country, the test clearly appears non significant. Not a great success given that the\n",
    "goal was to improve conversion rate, but at least we know that a localized translation didn’t make things\n",
    "worse!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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