scrap pad 2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"></ul></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.notebook.set_autosave_interval(120000)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autosaving every 120 seconds\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 4\n",
    "%autosave 120"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.io import *\n",
    "from fastai.structured import *\n",
    "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
    "from pandas_summary import DataFrameSummary\n",
    "from IPython.display import display\n",
    "from sklearn import metrics\n",
    "import feather"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist_trans = feather.read_dataframe('hist_trans')\n",
    "new_hist_trans = feather.read_dataframe('new_hist_trans')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>counts</th>\n",
       "      <th>uniques</th>\n",
       "      <th>missing</th>\n",
       "      <th>missing_perc</th>\n",
       "      <th>types</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>authorized_flag</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1963031</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>constant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>290001</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>categorical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city_id</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>134.387</td>\n",
       "      <td>101.515</td>\n",
       "      <td>-1</td>\n",
       "      <td>69</td>\n",
       "      <td>110</td>\n",
       "      <td>212</td>\n",
       "      <td>347</td>\n",
       "      <td>1963031</td>\n",
       "      <td>308</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>0.0321421</td>\n",
       "      <td>0.176378</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>0.682964</td>\n",
       "      <td>1.58407</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>1963031</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_3</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>0.57745</td>\n",
       "      <td>0.628879</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1963031</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_category_id</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>430.97</td>\n",
       "      <td>246.339</td>\n",
       "      <td>-1</td>\n",
       "      <td>278</td>\n",
       "      <td>367</td>\n",
       "      <td>683</td>\n",
       "      <td>891</td>\n",
       "      <td>1963031</td>\n",
       "      <td>314</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_id</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>226129</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>categorical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_lag</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>1.47652</td>\n",
       "      <td>0.499448</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>-0.550969</td>\n",
       "      <td>0.694004</td>\n",
       "      <td>-0.746893</td>\n",
       "      <td>-0.716629</td>\n",
       "      <td>-0.674841</td>\n",
       "      <td>-0.581616</td>\n",
       "      <td>263.157</td>\n",
       "      <td>1963031</td>\n",
       "      <td>75190</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>1667025</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>date</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_2</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>2.12965</td>\n",
       "      <td>1.50972</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>1963031</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>10.8807</td>\n",
       "      <td>6.03854</td>\n",
       "      <td>-1</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>15</td>\n",
       "      <td>24</td>\n",
       "      <td>1963031</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subsector_id</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>25.9762</td>\n",
       "      <td>10.1291</td>\n",
       "      <td>-1</td>\n",
       "      <td>19</td>\n",
       "      <td>29</td>\n",
       "      <td>34</td>\n",
       "      <td>41</td>\n",
       "      <td>1963031</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Year</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>2017.85</td>\n",
       "      <td>0.361522</td>\n",
       "      <td>2017</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Month</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>4.13606</td>\n",
       "      <td>2.44582</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>1963031</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Week</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>16.0857</td>\n",
       "      <td>10.6864</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "      <td>52</td>\n",
       "      <td>1963031</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Day</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>15.7556</td>\n",
       "      <td>8.78678</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>16</td>\n",
       "      <td>23</td>\n",
       "      <td>31</td>\n",
       "      <td>1963031</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofweek</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>3.12933</td>\n",
       "      <td>1.92773</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>1963031</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofyear</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>109.884</td>\n",
       "      <td>75.1097</td>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>90</td>\n",
       "      <td>112</td>\n",
       "      <td>365</td>\n",
       "      <td>1963031</td>\n",
       "      <td>365</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_end</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_start</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_end</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_start</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_end</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_start</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Elapsed</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>1.51935e+09</td>\n",
       "      <td>6.6753e+06</td>\n",
       "      <td>1.48834e+09</td>\n",
       "      <td>1.51967e+09</td>\n",
       "      <td>1.52146e+09</td>\n",
       "      <td>1.52322e+09</td>\n",
       "      <td>1.52513e+09</td>\n",
       "      <td>1963031</td>\n",
       "      <td>1667025</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchased_on_weekend</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>0.307438</td>\n",
       "      <td>0.461433</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1963031</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>bool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_diff</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>12.0329</td>\n",
       "      <td>2.53974</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>24</td>\n",
       "      <td>1963031</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date_successive_diff</th>\n",
       "      <td>1.96303e+06</td>\n",
       "      <td>375609</td>\n",
       "      <td>635813</td>\n",
       "      <td>0</td>\n",
       "      <td>6472</td>\n",
       "      <td>99461</td>\n",
       "      <td>438525</td>\n",
       "      <td>5.26258e+06</td>\n",
       "      <td>1963031</td>\n",
       "      <td>747163</td>\n",
       "      <td>0</td>\n",
       "      <td>0%</td>\n",
       "      <td>numeric</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     count         mean         std  \\\n",
       "authorized_flag                1.96303e+06            1           0   \n",
       "card_id                                NaN          NaN         NaN   \n",
       "city_id                        1.96303e+06      134.387     101.515   \n",
       "category_1                     1.96303e+06    0.0321421    0.176378   \n",
       "installments                   1.96303e+06     0.682964     1.58407   \n",
       "category_3                     1.96303e+06      0.57745    0.628879   \n",
       "merchant_category_id           1.96303e+06       430.97     246.339   \n",
       "merchant_id                            NaN          NaN         NaN   \n",
       "month_lag                      1.96303e+06      1.47652    0.499448   \n",
       "purchase_amount                1.96303e+06    -0.550969    0.694004   \n",
       "purchase_date                          NaN          NaN         NaN   \n",
       "category_2                     1.96303e+06      2.12965     1.50972   \n",
       "state_id                       1.96303e+06      10.8807     6.03854   \n",
       "subsector_id                   1.96303e+06      25.9762     10.1291   \n",
       "purchase_Year                  1.96303e+06      2017.85    0.361522   \n",
       "purchase_Month                 1.96303e+06      4.13606     2.44582   \n",
       "purchase_Week                  1.96303e+06      16.0857     10.6864   \n",
       "purchase_Day                   1.96303e+06      15.7556     8.78678   \n",
       "purchase_Dayofweek             1.96303e+06      3.12933     1.92773   \n",
       "purchase_Dayofyear             1.96303e+06      109.884     75.1097   \n",
       "purchase_Is_month_end                  NaN          NaN         NaN   \n",
       "purchase_Is_month_start                NaN          NaN         NaN   \n",
       "purchase_Is_quarter_end                NaN          NaN         NaN   \n",
       "purchase_Is_quarter_start              NaN          NaN         NaN   \n",
       "purchase_Is_year_end                   NaN          NaN         NaN   \n",
       "purchase_Is_year_start                 NaN          NaN         NaN   \n",
       "purchase_Elapsed               1.96303e+06  1.51935e+09  6.6753e+06   \n",
       "purchased_on_weekend           1.96303e+06     0.307438    0.461433   \n",
       "month_diff                     1.96303e+06      12.0329     2.53974   \n",
       "purchase_date_successive_diff  1.96303e+06       375609      635813   \n",
       "\n",
       "                                       min          25%          50%  \\\n",
       "authorized_flag                          1            1            1   \n",
       "card_id                                NaN          NaN          NaN   \n",
       "city_id                                 -1           69          110   \n",
       "category_1                               0            0            0   \n",
       "installments                            -1            0            1   \n",
       "category_3                               0            0            1   \n",
       "merchant_category_id                    -1          278          367   \n",
       "merchant_id                            NaN          NaN          NaN   \n",
       "month_lag                                1            1            1   \n",
       "purchase_amount                  -0.746893    -0.716629    -0.674841   \n",
       "purchase_date                          NaN          NaN          NaN   \n",
       "category_2                               1            1            1   \n",
       "state_id                                -1            9            9   \n",
       "subsector_id                            -1           19           29   \n",
       "purchase_Year                         2017         2018         2018   \n",
       "purchase_Month                           1            3            3   \n",
       "purchase_Week                            1           11           13   \n",
       "purchase_Day                             1            8           16   \n",
       "purchase_Dayofweek                       0            1            3   \n",
       "purchase_Dayofyear                       1           71           90   \n",
       "purchase_Is_month_end                  NaN          NaN          NaN   \n",
       "purchase_Is_month_start                NaN          NaN          NaN   \n",
       "purchase_Is_quarter_end                NaN          NaN          NaN   \n",
       "purchase_Is_quarter_start              NaN          NaN          NaN   \n",
       "purchase_Is_year_end                   NaN          NaN          NaN   \n",
       "purchase_Is_year_start                 NaN          NaN          NaN   \n",
       "purchase_Elapsed               1.48834e+09  1.51967e+09  1.52146e+09   \n",
       "purchased_on_weekend                     0            0            0   \n",
       "month_diff                              10           11           11   \n",
       "purchase_date_successive_diff            0         6472        99461   \n",
       "\n",
       "                                       75%          max   counts  uniques  \\\n",
       "authorized_flag                          1            1  1963031        1   \n",
       "card_id                                NaN          NaN  1963031   290001   \n",
       "city_id                                212          347  1963031      308   \n",
       "category_1                               0            1  1963031        2   \n",
       "installments                             1          999  1963031       15   \n",
       "category_3                               1            2  1963031        3   \n",
       "merchant_category_id                   683          891  1963031      314   \n",
       "merchant_id                            NaN          NaN  1963031   226129   \n",
       "month_lag                                2            2  1963031        2   \n",
       "purchase_amount                  -0.581616      263.157  1963031    75190   \n",
       "purchase_date                          NaN          NaN  1963031  1667025   \n",
       "category_2                               3            5  1963031        5   \n",
       "state_id                                15           24  1963031       25   \n",
       "subsector_id                            34           41  1963031       41   \n",
       "purchase_Year                         2018         2018  1963031        2   \n",
       "purchase_Month                           4           12  1963031       12   \n",
       "purchase_Week                           16           52  1963031       52   \n",
       "purchase_Day                            23           31  1963031       31   \n",
       "purchase_Dayofweek                       5            6  1963031        7   \n",
       "purchase_Dayofyear                     112          365  1963031      365   \n",
       "purchase_Is_month_end                  NaN          NaN  1963031        2   \n",
       "purchase_Is_month_start                NaN          NaN  1963031        2   \n",
       "purchase_Is_quarter_end                NaN          NaN  1963031        2   \n",
       "purchase_Is_quarter_start              NaN          NaN  1963031        2   \n",
       "purchase_Is_year_end                   NaN          NaN  1963031        2   \n",
       "purchase_Is_year_start                 NaN          NaN  1963031        2   \n",
       "purchase_Elapsed               1.52322e+09  1.52513e+09  1963031  1667025   \n",
       "purchased_on_weekend                     1            1  1963031        2   \n",
       "month_diff                              12           24  1963031       15   \n",
       "purchase_date_successive_diff       438525  5.26258e+06  1963031   747163   \n",
       "\n",
       "                              missing missing_perc        types  \n",
       "authorized_flag                     0           0%     constant  \n",
       "card_id                             0           0%  categorical  \n",
       "city_id                             0           0%      numeric  \n",
       "category_1                          0           0%         bool  \n",
       "installments                        0           0%      numeric  \n",
       "category_3                          0           0%      numeric  \n",
       "merchant_category_id                0           0%      numeric  \n",
       "merchant_id                         0           0%  categorical  \n",
       "month_lag                           0           0%         bool  \n",
       "purchase_amount                     0           0%      numeric  \n",
       "purchase_date                       0           0%         date  \n",
       "category_2                          0           0%      numeric  \n",
       "state_id                            0           0%      numeric  \n",
       "subsector_id                        0           0%      numeric  \n",
       "purchase_Year                       0           0%         bool  \n",
       "purchase_Month                      0           0%      numeric  \n",
       "purchase_Week                       0           0%      numeric  \n",
       "purchase_Day                        0           0%      numeric  \n",
       "purchase_Dayofweek                  0           0%      numeric  \n",
       "purchase_Dayofyear                  0           0%      numeric  \n",
       "purchase_Is_month_end               0           0%         bool  \n",
       "purchase_Is_month_start             0           0%         bool  \n",
       "purchase_Is_quarter_end             0           0%         bool  \n",
       "purchase_Is_quarter_start           0           0%         bool  \n",
       "purchase_Is_year_end                0           0%         bool  \n",
       "purchase_Is_year_start              0           0%         bool  \n",
       "purchase_Elapsed                    0           0%      numeric  \n",
       "purchased_on_weekend                0           0%         bool  \n",
       "month_diff                          0           0%      numeric  \n",
       "purchase_date_successive_diff       0           0%      numeric  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DataFrameSummary(new_hist_trans).summary().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp1 = hist_trans.loc[hist_trans['card_id'].isin(['C_ID_05042ebd55'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp2 = hist_trans.loc[hist_trans['card_id'].isin(['C_ID_5c240d6e3c'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = hist_trans.loc[hist_trans['card_id'].isin(['C_ID_05042ebd55', 'C_ID_5c240d6e3c'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "temp1['card_id'] = temp1.card_id.astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "temp1['merchant_id'] = temp1.merchant_id.astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "temp1.sort_values('purchase_date', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "la = temp1.groupby('card_id').rolling('30D', on='purchase_date')['purchase_amount'].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "           card_id       purchase_date  purchase_amount\n",
       "0  C_ID_05042ebd55 2017-10-28 15:16:46        -0.643976\n",
       "1  C_ID_05042ebd55 2017-12-31 16:27:35        -0.716855\n",
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       "5  C_ID_05042ebd55 2018-02-09 15:04:41        -2.829537"
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     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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    "la"
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  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/pandas/core/frame.py:3697: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  errors=errors)\n"
     ]
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   "source": [
    "temp1.drop('month_rolling', axis=1, inplace=True)"
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  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
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       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>-2.103667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>278</td>\n",
       "      <td>M_ID_814793f74b</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.725871</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1518188681</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>-2.829537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   authorized_flag        card_id_x  city_id  category_1  installments  \\\n",
       "0                0  C_ID_05042ebd55       -1           0             0   \n",
       "1                1  C_ID_05042ebd55       -1           0             0   \n",
       "2                1  C_ID_05042ebd55       20           0             0   \n",
       "3                0  C_ID_05042ebd55       -1           0             0   \n",
       "4                1  C_ID_05042ebd55       -1           0             0   \n",
       "5                1  C_ID_05042ebd55       -1           0             0   \n",
       "\n",
       "   category_3  merchant_category_id      merchant_id  month_lag  \\\n",
       "0           0                   437  M_ID_ce1e7a7a85         -4   \n",
       "1           0                   703  M_ID_051eacb2a3         -2   \n",
       "2           0                   422  M_ID_0de7fd2bef         -1   \n",
       "3           0                    80  M_ID_9ecff0beda          0   \n",
       "4           0                    80  M_ID_9ecff0beda          0   \n",
       "5           0                   278  M_ID_814793f74b          0   \n",
       "\n",
       "   purchase_amount_x               ...               purchase_Is_quarter_end  \\\n",
       "0          -0.643976               ...                                 False   \n",
       "1          -0.716855               ...                                  True   \n",
       "2          -0.692948               ...                                 False   \n",
       "3          -0.705134               ...                                 False   \n",
       "4          -0.705585               ...                                 False   \n",
       "5          -0.725871               ...                                 False   \n",
       "\n",
       "   purchase_Is_quarter_start  purchase_Is_year_end  purchase_Is_year_start  \\\n",
       "0                      False                 False                   False   \n",
       "1                      False                  True                   False   \n",
       "2                      False                 False                   False   \n",
       "3                      False                 False                   False   \n",
       "4                      False                 False                   False   \n",
       "5                      False                 False                   False   \n",
       "\n",
       "   purchase_Elapsed  purchased_on_weekend  month_diff  month_cumm  \\\n",
       "0        1509203806                     1          10         NaN   \n",
       "1        1514737655                     1          10         NaN   \n",
       "2        1515964968                     1          11         NaN   \n",
       "3        1518006816                     0          11         NaN   \n",
       "4        1518006846                     0          11         NaN   \n",
       "5        1518188681                     0          11         NaN   \n",
       "\n",
       "   card_id_rolling_amount  purchase_amount_rolling_amount  \n",
       "0         C_ID_05042ebd55                       -0.643976  \n",
       "1         C_ID_05042ebd55                       -0.716855  \n",
       "2         C_ID_05042ebd55                       -1.409802  \n",
       "3         C_ID_05042ebd55                       -1.398082  \n",
       "4         C_ID_05042ebd55                       -2.103667  \n",
       "5         C_ID_05042ebd55                       -2.829537  \n",
       "\n",
       "[6 rows x 32 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(temp1, la, 'inner', on='purchase_date', suffixes=['_x', '_rolling_amount'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "la = temp1.groupby(['card_id', 'month_diff'])['purchase_amount'].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\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>card_id</th>\n",
       "      <th>month_diff</th>\n",
       "      <th>purchase_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>10</td>\n",
       "      <td>-1.360831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>11</td>\n",
       "      <td>-2.829537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           card_id  month_diff  purchase_amount\n",
       "0  C_ID_05042ebd55          10        -1.360831\n",
       "1  C_ID_05042ebd55          11        -2.829537"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "la"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    .dataframe thead tr:last-of-type th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">month_diff</th>\n",
       "      <th colspan=\"3\" halign=\"left\">purchase_amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>mean</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C_ID_05042ebd55</th>\n",
       "      <td>10.5</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>-2.095184</td>\n",
       "      <td>-1.360831</td>\n",
       "      <td>-2.829537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                month_diff         purchase_amount                    \n",
       "                      mean max min            mean       max       min\n",
       "card_id                                                               \n",
       "C_ID_05042ebd55       10.5  11  10       -2.095184 -1.360831 -2.829537"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "la.groupby('card_id').agg(['mean', 'max', 'min'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def monthly_rolling(df, fe1, fe2):\n",
    "    temp_df = df.sort_values('purchase_date')\n",
    "    temp_df2 = temp_df.groupby('card_id').rolling('30D', on='purchase_date')[fe1].sum().reset_index()\n",
    "    temp_df2 = temp_df2[['purchase_date', 'fe1']]\n",
    "    return pd.merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>authorized_flag</th>\n",
       "      <th>card_id</th>\n",
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       "      <th>category_1</th>\n",
       "      <th>installments</th>\n",
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       "      <th>merchant_id</th>\n",
       "      <th>month_lag</th>\n",
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       "      <th>...</th>\n",
       "      <th>purchase_Is_month_end</th>\n",
       "      <th>purchase_Is_month_start</th>\n",
       "      <th>purchase_Is_quarter_end</th>\n",
       "      <th>purchase_Is_quarter_start</th>\n",
       "      <th>purchase_Is_year_end</th>\n",
       "      <th>purchase_Is_year_start</th>\n",
       "      <th>purchase_Elapsed</th>\n",
       "      <th>purchased_on_weekend</th>\n",
       "      <th>month_diff</th>\n",
       "      <th>month_cumm</th>\n",
       "    </tr>\n",
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       "      <td>0</td>\n",
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       "      <td>422</td>\n",
       "      <td>M_ID_0de7fd2bef</td>\n",
       "      <td>-1</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1515964968</td>\n",
       "      <td>1</td>\n",
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       "      <th>29112047</th>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>1518006816</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1518006846</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>M_ID_814793f74b</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.725871</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>1518188681</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          authorized_flag          card_id  city_id  category_1  installments  \\\n",
       "29112043                0  C_ID_05042ebd55       -1           0             0   \n",
       "29112045                1  C_ID_05042ebd55       -1           0             0   \n",
       "29112044                1  C_ID_05042ebd55       20           0             0   \n",
       "29112047                0  C_ID_05042ebd55       -1           0             0   \n",
       "29112046                1  C_ID_05042ebd55       -1           0             0   \n",
       "29112048                1  C_ID_05042ebd55       -1           0             0   \n",
       "\n",
       "          category_3  merchant_category_id      merchant_id  month_lag  \\\n",
       "29112043           0                   437  M_ID_ce1e7a7a85         -4   \n",
       "29112045           0                   703  M_ID_051eacb2a3         -2   \n",
       "29112044           0                   422  M_ID_0de7fd2bef         -1   \n",
       "29112047           0                    80  M_ID_9ecff0beda          0   \n",
       "29112046           0                    80  M_ID_9ecff0beda          0   \n",
       "29112048           0                   278  M_ID_814793f74b          0   \n",
       "\n",
       "          purchase_amount     ...     purchase_Is_month_end  \\\n",
       "29112043        -0.643976     ...                     False   \n",
       "29112045        -0.716855     ...                      True   \n",
       "29112044        -0.692948     ...                     False   \n",
       "29112047        -0.705134     ...                     False   \n",
       "29112046        -0.705585     ...                     False   \n",
       "29112048        -0.725871     ...                     False   \n",
       "\n",
       "          purchase_Is_month_start  purchase_Is_quarter_end  \\\n",
       "29112043                    False                    False   \n",
       "29112045                    False                     True   \n",
       "29112044                    False                    False   \n",
       "29112047                    False                    False   \n",
       "29112046                    False                    False   \n",
       "29112048                    False                    False   \n",
       "\n",
       "          purchase_Is_quarter_start  purchase_Is_year_end  \\\n",
       "29112043                      False                 False   \n",
       "29112045                      False                  True   \n",
       "29112044                      False                 False   \n",
       "29112047                      False                 False   \n",
       "29112046                      False                 False   \n",
       "29112048                      False                 False   \n",
       "\n",
       "          purchase_Is_year_start  purchase_Elapsed  purchased_on_weekend  \\\n",
       "29112043                   False        1509203806                     1   \n",
       "29112045                   False        1514737655                     1   \n",
       "29112044                   False        1515964968                     1   \n",
       "29112047                   False        1518006816                     0   \n",
       "29112046                   False        1518006846                     0   \n",
       "29112048                   False        1518188681                     0   \n",
       "\n",
       "          month_diff  month_cumm  \n",
       "29112043          10         NaN  \n",
       "29112045          10         NaN  \n",
       "29112044          11         NaN  \n",
       "29112047          11         NaN  \n",
       "29112046          11         NaN  \n",
       "29112048          11         NaN  \n",
       "\n",
       "[6 rows x 30 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "card_id          purchase_date      \n",
       "C_ID_05042ebd55  2017-10-28 15:16:46    0.0\n",
       "                 2017-12-31 16:27:35    0.0\n",
       "                 2018-01-14 21:22:48    0.0\n",
       "                 2018-02-07 12:33:36    0.0\n",
       "                 2018-02-07 12:34:06    0.0\n",
       "                 2018-02-09 15:04:41    0.0\n",
       "Name: installments, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.sort_values('purchase_date').groupby('card_id').rolling('30D', on='purchase_date')['installments'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29112043                NaT\n",
       "29112045   64 days 01:10:49\n",
       "29112044   14 days 04:55:13\n",
       "29112047   23 days 15:10:48\n",
       "29112046    0 days 00:00:30\n",
       "29112048    2 days 02:30:35\n",
       "Name: purchase_date, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.sort_values('purchase_date').groupby('card_id')['purchase_date'].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>29112043</th>\n",
       "      <th>29112045</th>\n",
       "      <th>29112044</th>\n",
       "      <th>29112047</th>\n",
       "      <th>29112046</th>\n",
       "      <th>29112048</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>authorized_flag</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city_id</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>20</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>category_3</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_category_id</th>\n",
       "      <td>437</td>\n",
       "      <td>703</td>\n",
       "      <td>422</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_id</th>\n",
       "      <td>M_ID_ce1e7a7a85</td>\n",
       "      <td>M_ID_051eacb2a3</td>\n",
       "      <td>M_ID_0de7fd2bef</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_814793f74b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_lag</th>\n",
       "      <td>-4</td>\n",
       "      <td>-2</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>-0.716855</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>-0.705134</td>\n",
       "      <td>-0.705585</td>\n",
       "      <td>-0.725871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date</th>\n",
       "      <td>2017-10-28 15:16:46</td>\n",
       "      <td>2017-12-31 16:27:35</td>\n",
       "      <td>2018-01-14 21:22:48</td>\n",
       "      <td>2018-02-07 12:33:36</td>\n",
       "      <td>2018-02-07 12:34:06</td>\n",
       "      <td>2018-02-09 15:04:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>19</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subsector_id</th>\n",
       "      <td>15</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Year</th>\n",
       "      <td>2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Month</th>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Week</th>\n",
       "      <td>43</td>\n",
       "      <td>52</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Day</th>\n",
       "      <td>28</td>\n",
       "      <td>31</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofweek</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofyear</th>\n",
       "      <td>301</td>\n",
       "      <td>365</td>\n",
       "      <td>14</td>\n",
       "      <td>38</td>\n",
       "      <td>38</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Elapsed</th>\n",
       "      <td>1509203806</td>\n",
       "      <td>1514737655</td>\n",
       "      <td>1515964968</td>\n",
       "      <td>1518006816</td>\n",
       "      <td>1518006846</td>\n",
       "      <td>1518188681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchased_on_weekend</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_diff</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                      29112043             29112045  \\\n",
       "authorized_flag                              0                    1   \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                     -1                   -1   \n",
       "category_1                                   0                    0   \n",
       "installments                                 0                    0   \n",
       "category_3                                   0                    0   \n",
       "merchant_category_id                       437                  703   \n",
       "merchant_id                    M_ID_ce1e7a7a85      M_ID_051eacb2a3   \n",
       "month_lag                                   -4                   -2   \n",
       "purchase_amount                      -0.643976            -0.716855   \n",
       "purchase_date              2017-10-28 15:16:46  2017-12-31 16:27:35   \n",
       "category_2                                   1                    1   \n",
       "state_id                                    -1                   -1   \n",
       "subsector_id                                15                   29   \n",
       "purchase_Year                             2017                 2017   \n",
       "purchase_Month                              10                   12   \n",
       "purchase_Week                               43                   52   \n",
       "purchase_Day                                28                   31   \n",
       "purchase_Dayofweek                           5                    6   \n",
       "purchase_Dayofyear                         301                  365   \n",
       "purchase_Is_month_end                    False                 True   \n",
       "purchase_Is_month_start                  False                False   \n",
       "purchase_Is_quarter_end                  False                 True   \n",
       "purchase_Is_quarter_start                False                False   \n",
       "purchase_Is_year_end                     False                 True   \n",
       "purchase_Is_year_start                   False                False   \n",
       "purchase_Elapsed                    1509203806           1514737655   \n",
       "purchased_on_weekend                         1                    1   \n",
       "month_diff                                  10                   10   \n",
       "\n",
       "                                      29112044             29112047  \\\n",
       "authorized_flag                              1                    0   \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                     20                   -1   \n",
       "category_1                                   0                    0   \n",
       "installments                                 0                    0   \n",
       "category_3                                   0                    0   \n",
       "merchant_category_id                       422                   80   \n",
       "merchant_id                    M_ID_0de7fd2bef      M_ID_9ecff0beda   \n",
       "month_lag                                   -1                    0   \n",
       "purchase_amount                      -0.692948            -0.705134   \n",
       "purchase_date              2018-01-14 21:22:48  2018-02-07 12:33:36   \n",
       "category_2                                   3                    1   \n",
       "state_id                                    19                   -1   \n",
       "subsector_id                                27                   37   \n",
       "purchase_Year                             2018                 2018   \n",
       "purchase_Month                               1                    2   \n",
       "purchase_Week                                2                    6   \n",
       "purchase_Day                                14                    7   \n",
       "purchase_Dayofweek                           6                    2   \n",
       "purchase_Dayofyear                          14                   38   \n",
       "purchase_Is_month_end                    False                False   \n",
       "purchase_Is_month_start                  False                False   \n",
       "purchase_Is_quarter_end                  False                False   \n",
       "purchase_Is_quarter_start                False                False   \n",
       "purchase_Is_year_end                     False                False   \n",
       "purchase_Is_year_start                   False                False   \n",
       "purchase_Elapsed                    1515964968           1518006816   \n",
       "purchased_on_weekend                         1                    0   \n",
       "month_diff                                  11                   11   \n",
       "\n",
       "                                      29112046             29112048  \n",
       "authorized_flag                              1                    1  \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55  \n",
       "city_id                                     -1                   -1  \n",
       "category_1                                   0                    0  \n",
       "installments                                 0                    0  \n",
       "category_3                                   0                    0  \n",
       "merchant_category_id                        80                  278  \n",
       "merchant_id                    M_ID_9ecff0beda      M_ID_814793f74b  \n",
       "month_lag                                    0                    0  \n",
       "purchase_amount                      -0.705585            -0.725871  \n",
       "purchase_date              2018-02-07 12:34:06  2018-02-09 15:04:41  \n",
       "category_2                                   1                    1  \n",
       "state_id                                    -1                   -1  \n",
       "subsector_id                                37                   37  \n",
       "purchase_Year                             2018                 2018  \n",
       "purchase_Month                               2                    2  \n",
       "purchase_Week                                6                    6  \n",
       "purchase_Day                                 7                    9  \n",
       "purchase_Dayofweek                           2                    4  \n",
       "purchase_Dayofyear                          38                   40  \n",
       "purchase_Is_month_end                    False                False  \n",
       "purchase_Is_month_start                  False                False  \n",
       "purchase_Is_quarter_end                  False                False  \n",
       "purchase_Is_quarter_start                False                False  \n",
       "purchase_Is_year_end                     False                False  \n",
       "purchase_Is_year_start                   False                False  \n",
       "purchase_Elapsed                    1518006846           1518188681  \n",
       "purchased_on_weekend                         0                    0  \n",
       "month_diff                                  11                   11  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.sort_values('purchase_date').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "def aggregate_per_month(history):\n",
    "    grouped = history.groupby(['card_id', 'subsector_id'])['purchase_amount']\n",
    "\n",
    "    agg_func = {\n",
    "            'purchase_amount': ['count', 'sum', 'max', 'mean']\n",
    "            }\n",
    "\n",
    "    intermediate_group = grouped.agg(agg_func)\n",
    "    intermediate_group.columns = ['_'.join(col).strip() for col in intermediate_group.columns.values]\n",
    "    intermediate_group.reset_index(inplace=True)\n",
    "\n",
    "    final_group = intermediate_group.groupby('card_id').agg(['mean', 'sum', np.ptp, 'max'])\n",
    "    final_group.columns = ['_'.join(col).strip() for col in final_group.columns.values]\n",
    "    final_group.reset_index(inplace=True)\n",
    "    \n",
    "    return final_group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "                purchase_amount                              \n",
       "                           mean       max       min       sum\n",
       "card_id                                                      \n",
       "C_ID_05042ebd55       -1.516986 -0.643976 -2.829537 -9.101919"
      ]
     },
     "execution_count": 25,
     "metadata": {},
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    }
   ],
   "source": [
    "la.groupby('card_id').agg(['mean', 'max', 'min', 'sum'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_category_id</th>\n",
       "      <td>437</td>\n",
       "      <td>703</td>\n",
       "      <td>422</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_id</th>\n",
       "      <td>M_ID_ce1e7a7a85</td>\n",
       "      <td>M_ID_051eacb2a3</td>\n",
       "      <td>M_ID_0de7fd2bef</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_814793f74b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_lag</th>\n",
       "      <td>-4</td>\n",
       "      <td>-2</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>-0.716855</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>-0.705134</td>\n",
       "      <td>-0.705585</td>\n",
       "      <td>-0.725871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date</th>\n",
       "      <td>2017-10-28 15:16:46</td>\n",
       "      <td>2017-12-31 16:27:35</td>\n",
       "      <td>2018-01-14 21:22:48</td>\n",
       "      <td>2018-02-07 12:33:36</td>\n",
       "      <td>2018-02-07 12:34:06</td>\n",
       "      <td>2018-02-09 15:04:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>19</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subsector_id</th>\n",
       "      <td>15</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Year</th>\n",
       "      <td>2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Month</th>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Week</th>\n",
       "      <td>43</td>\n",
       "      <td>52</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Day</th>\n",
       "      <td>28</td>\n",
       "      <td>31</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofweek</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofyear</th>\n",
       "      <td>301</td>\n",
       "      <td>365</td>\n",
       "      <td>14</td>\n",
       "      <td>38</td>\n",
       "      <td>38</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Elapsed</th>\n",
       "      <td>1509203806</td>\n",
       "      <td>1514737655</td>\n",
       "      <td>1515964968</td>\n",
       "      <td>1518006816</td>\n",
       "      <td>1518006846</td>\n",
       "      <td>1518188681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchased_on_weekend</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_diff</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                                      29112043             29112045  \\\n",
       "authorized_flag                              0                    1   \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                     -1                   -1   \n",
       "category_1                                   0                    0   \n",
       "installments                                 0                    0   \n",
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       "merchant_category_id                       437                  703   \n",
       "merchant_id                    M_ID_ce1e7a7a85      M_ID_051eacb2a3   \n",
       "month_lag                                   -4                   -2   \n",
       "purchase_amount                      -0.643976            -0.716855   \n",
       "purchase_date              2017-10-28 15:16:46  2017-12-31 16:27:35   \n",
       "category_2                                   1                    1   \n",
       "state_id                                    -1                   -1   \n",
       "subsector_id                                15                   29   \n",
       "purchase_Year                             2017                 2017   \n",
       "purchase_Month                              10                   12   \n",
       "purchase_Week                               43                   52   \n",
       "purchase_Day                                28                   31   \n",
       "purchase_Dayofweek                           5                    6   \n",
       "purchase_Dayofyear                         301                  365   \n",
       "purchase_Is_month_end                    False                 True   \n",
       "purchase_Is_month_start                  False                False   \n",
       "purchase_Is_quarter_end                  False                 True   \n",
       "purchase_Is_quarter_start                False                False   \n",
       "purchase_Is_year_end                     False                 True   \n",
       "purchase_Is_year_start                   False                False   \n",
       "purchase_Elapsed                    1509203806           1514737655   \n",
       "purchased_on_weekend                         1                    1   \n",
       "month_diff                                  10                   10   \n",
       "\n",
       "                                      29112044             29112047  \\\n",
       "authorized_flag                              1                    0   \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                     20                   -1   \n",
       "category_1                                   0                    0   \n",
       "installments                                 0                    0   \n",
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       "month_lag                                   -1                    0   \n",
       "purchase_amount                      -0.692948            -0.705134   \n",
       "purchase_date              2018-01-14 21:22:48  2018-02-07 12:33:36   \n",
       "category_2                                   3                    1   \n",
       "state_id                                    19                   -1   \n",
       "subsector_id                                27                   37   \n",
       "purchase_Year                             2018                 2018   \n",
       "purchase_Month                               1                    2   \n",
       "purchase_Week                                2                    6   \n",
       "purchase_Day                                14                    7   \n",
       "purchase_Dayofweek                           6                    2   \n",
       "purchase_Dayofyear                          14                   38   \n",
       "purchase_Is_month_end                    False                False   \n",
       "purchase_Is_month_start                  False                False   \n",
       "purchase_Is_quarter_end                  False                False   \n",
       "purchase_Is_quarter_start                False                False   \n",
       "purchase_Is_year_end                     False                False   \n",
       "purchase_Is_year_start                   False                False   \n",
       "purchase_Elapsed                    1515964968           1518006816   \n",
       "purchased_on_weekend                         1                    0   \n",
       "month_diff                                  11                   11   \n",
       "\n",
       "                                      29112046             29112048  \n",
       "authorized_flag                              1                    1  \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55  \n",
       "city_id                                     -1                   -1  \n",
       "category_1                                   0                    0  \n",
       "installments                                 0                    0  \n",
       "category_3                                   0                    0  \n",
       "merchant_category_id                        80                  278  \n",
       "merchant_id                    M_ID_9ecff0beda      M_ID_814793f74b  \n",
       "month_lag                                    0                    0  \n",
       "purchase_amount                      -0.705585            -0.725871  \n",
       "purchase_date              2018-02-07 12:34:06  2018-02-09 15:04:41  \n",
       "category_2                                   1                    1  \n",
       "state_id                                    -1                   -1  \n",
       "subsector_id                                37                   37  \n",
       "purchase_Year                             2018                 2018  \n",
       "purchase_Month                               2                    2  \n",
       "purchase_Week                                6                    6  \n",
       "purchase_Day                                 7                    9  \n",
       "purchase_Dayofweek                           2                    4  \n",
       "purchase_Dayofyear                          38                   40  \n",
       "purchase_Is_month_end                    False                False  \n",
       "purchase_Is_month_start                  False                False  \n",
       "purchase_Is_quarter_end                  False                False  \n",
       "purchase_Is_quarter_start                False                False  \n",
       "purchase_Is_year_end                     False                False  \n",
       "purchase_Is_year_start                   False                False  \n",
       "purchase_Elapsed                    1518006846           1518188681  \n",
       "purchased_on_weekend                         0                    0  \n",
       "month_diff                                  11                   11  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
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  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
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   "outputs": [
    {
     "name": "stderr",
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     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/ipykernel_launcher.py:9: FutureWarning: using a dict on a Series for aggregation\n",
      "is deprecated and will be removed in a future version\n",
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       "                                          0\n",
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  {
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      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/ipykernel_launcher.py:9: FutureWarning: using a dict on a Series for aggregation\n",
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      "  if __name__ == '__main__':\n"
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    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_5c240d6e3c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_count_mean</th>\n",
       "      <td>1.2</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_count_sum</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_count_ptp</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_count_max</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_sum_mean</th>\n",
       "      <td>-0.838074</td>\n",
       "      <td>0.623645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_sum_sum</th>\n",
       "      <td>-4.19037</td>\n",
       "      <td>1.24729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_sum_ptp</th>\n",
       "      <td>0.766743</td>\n",
       "      <td>2.56277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments_sum_max</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>1.90503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_count_mean</th>\n",
       "      <td>1.2</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_count_sum</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_count_ptp</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_count_max</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_sum_mean</th>\n",
       "      <td>-0.838074</td>\n",
       "      <td>0.623645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_sum_sum</th>\n",
       "      <td>-4.19037</td>\n",
       "      <td>1.24729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_sum_ptp</th>\n",
       "      <td>0.766743</td>\n",
       "      <td>2.56277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_sum_max</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>1.90503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_mean</th>\n",
       "      <td>-0.696957</td>\n",
       "      <td>0.238336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_sum</th>\n",
       "      <td>-3.48478</td>\n",
       "      <td>0.476671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_ptp</th>\n",
       "      <td>0.0818945</td>\n",
       "      <td>1.79215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_max</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>1.13441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_min_mean</th>\n",
       "      <td>-0.697047</td>\n",
       "      <td>0.0564396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_min_sum</th>\n",
       "      <td>-3.48523</td>\n",
       "      <td>0.112879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_min_ptp</th>\n",
       "      <td>0.0818945</td>\n",
       "      <td>1.42836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_min_max</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>0.77062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_mean</th>\n",
       "      <td>-0.697002</td>\n",
       "      <td>0.147388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_sum</th>\n",
       "      <td>-3.48501</td>\n",
       "      <td>0.294775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_ptp</th>\n",
       "      <td>0.0818945</td>\n",
       "      <td>1.61026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_max</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>0.952516</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          0                1\n",
       "card_id                     C_ID_05042ebd55  C_ID_5c240d6e3c\n",
       "installments_count_mean                 1.2              1.5\n",
       "installments_count_sum                    6                3\n",
       "installments_count_ptp                    1                1\n",
       "installments_count_max                    2                2\n",
       "installments_sum_mean             -0.838074         0.623645\n",
       "installments_sum_sum               -4.19037          1.24729\n",
       "installments_sum_ptp               0.766743          2.56277\n",
       "installments_sum_max              -0.643976          1.90503\n",
       "purchase_amount_count_mean              1.2              1.5\n",
       "purchase_amount_count_sum                 6                3\n",
       "purchase_amount_count_ptp                 1                1\n",
       "purchase_amount_count_max                 2                2\n",
       "purchase_amount_sum_mean          -0.838074         0.623645\n",
       "purchase_amount_sum_sum            -4.19037          1.24729\n",
       "purchase_amount_sum_ptp            0.766743          2.56277\n",
       "purchase_amount_sum_max           -0.643976          1.90503\n",
       "purchase_amount_max_mean          -0.696957         0.238336\n",
       "purchase_amount_max_sum            -3.48478         0.476671\n",
       "purchase_amount_max_ptp           0.0818945          1.79215\n",
       "purchase_amount_max_max           -0.643976          1.13441\n",
       "purchase_amount_min_mean          -0.697047        0.0564396\n",
       "purchase_amount_min_sum            -3.48523         0.112879\n",
       "purchase_amount_min_ptp           0.0818945          1.42836\n",
       "purchase_amount_min_max           -0.643976          0.77062\n",
       "purchase_amount_mean_mean         -0.697002         0.147388\n",
       "purchase_amount_mean_sum           -3.48501         0.294775\n",
       "purchase_amount_mean_ptp          0.0818945          1.61026\n",
       "purchase_amount_mean_max          -0.643976         0.952516"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregate_per_month(temp).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def successive_aggregates(df, field1, field2):\n",
    "    t = df.groupby(['card_id', field1])[field2].mean()\n",
    "    u = pd.DataFrame(t).reset_index().groupby('card_id')[field2].agg(['mean', 'min', 'max', 'std'])\n",
    "    u.columns = [field1 + '_' + field2 + '_' + col for col in u.columns.values]\n",
    "    u.reset_index(inplace=True)\n",
    "    return u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_5c240d6e3c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>authorized_flag_purchase_amount_mean</th>\n",
       "      <td>-0.692435</td>\n",
       "      <td>0.415764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>authorized_flag_purchase_amount_min</th>\n",
       "      <td>-0.710314</td>\n",
       "      <td>0.415764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>authorized_flag_purchase_amount_max</th>\n",
       "      <td>-0.674555</td>\n",
       "      <td>0.415764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>authorized_flag_purchase_amount_std</th>\n",
       "      <td>0.0252857</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    0                1\n",
       "card_id                               C_ID_05042ebd55  C_ID_5c240d6e3c\n",
       "authorized_flag_purchase_amount_mean        -0.692435         0.415764\n",
       "authorized_flag_purchase_amount_min         -0.710314         0.415764\n",
       "authorized_flag_purchase_amount_max         -0.674555         0.415764\n",
       "authorized_flag_purchase_amount_std         0.0252857              NaN"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "successive_aggregates(temp, 'authorized_flag', 'purchase_amount').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_5c240d6e3c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1_purchase_amount_mean</th>\n",
       "      <td>-0.698395</td>\n",
       "      <td>0.415764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1_purchase_amount_min</th>\n",
       "      <td>-0.698395</td>\n",
       "      <td>0.415764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1_purchase_amount_max</th>\n",
       "      <td>-0.698395</td>\n",
       "      <td>0.415764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1_purchase_amount_std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "                                               0                1\n",
       "card_id                          C_ID_05042ebd55  C_ID_5c240d6e3c\n",
       "category_1_purchase_amount_mean        -0.698395         0.415764\n",
       "category_1_purchase_amount_min         -0.698395         0.415764\n",
       "category_1_purchase_amount_max         -0.698395         0.415764\n",
       "category_1_purchase_amount_std               NaN              NaN"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "successive_aggregates(temp, 'category_1', 'purchase_amount').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_cat_agg(df):\n",
    "    agg_df = agg_on_cat(df, 'category_1', 'purchase_amount')\n",
    "    agg_df = pd.merge(agg_df, agg_on_cat(df, 'category_2', 'purchase_amount'), on='card_id', how='left')\n",
    "    agg_df = pd.merge(agg_df, agg_on_cat(df, 'category_3', 'purchase_amount'), on='card_id', how='left')\n",
    "    agg_df = pd.merge(agg_df, agg_on_cat(df, 'authorized_flag', 'purchase_amount'), on='card_id', how='left')\n",
    "    return agg_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def agg_on_cat(df, category, feature):\n",
    "    temp_df = df.pivot_table(index='card_id', columns=category, aggfunc={feature: ['sum', 'mean']})\n",
    "    cols = [category + '_{0[2]}_{0[0]}_{0[1]}'.format(col) for col in temp_df.columns.tolist()]\n",
    "    temp_df.columns = cols\n",
    "    return temp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>category_1_0_purchase_amount_mean</th>\n",
       "      <th>category_1_0_purchase_amount_sum</th>\n",
       "      <th>category_2_1.0_purchase_amount_mean</th>\n",
       "      <th>category_2_3.0_purchase_amount_mean</th>\n",
       "      <th>category_2_1.0_purchase_amount_sum</th>\n",
       "      <th>category_2_3.0_purchase_amount_sum</th>\n",
       "      <th>category_3_0_purchase_amount_mean</th>\n",
       "      <th>category_3_0_purchase_amount_sum</th>\n",
       "      <th>authorized_flag_0_purchase_amount_mean</th>\n",
       "      <th>authorized_flag_1_purchase_amount_mean</th>\n",
       "      <th>authorized_flag_0_purchase_amount_sum</th>\n",
       "      <th>authorized_flag_1_purchase_amount_sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>C_ID_05042ebd55</th>\n",
       "      <td>-0.698395</td>\n",
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       "      <td>-0.699484</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>-3.497421</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>-0.698395</td>\n",
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       "      <td>-0.674555</td>\n",
       "      <td>-0.710314</td>\n",
       "      <td>-1.34911</td>\n",
       "      <td>-2.841258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C_ID_5c240d6e3c</th>\n",
       "      <td>0.415764</td>\n",
       "      <td>1.247291</td>\n",
       "      <td>0.415764</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.247291</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.415764</td>\n",
       "      <td>1.247291</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.415764</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.247291</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 category_1_0_purchase_amount_mean  \\\n",
       "card_id                                              \n",
       "C_ID_05042ebd55                          -0.698395   \n",
       "C_ID_5c240d6e3c                           0.415764   \n",
       "\n",
       "                 category_1_0_purchase_amount_sum  \\\n",
       "card_id                                             \n",
       "C_ID_05042ebd55                         -4.190368   \n",
       "C_ID_5c240d6e3c                          1.247291   \n",
       "\n",
       "                 category_2_1.0_purchase_amount_mean  \\\n",
       "card_id                                                \n",
       "C_ID_05042ebd55                            -0.699484   \n",
       "C_ID_5c240d6e3c                             0.415764   \n",
       "\n",
       "                 category_2_3.0_purchase_amount_mean  \\\n",
       "card_id                                                \n",
       "C_ID_05042ebd55                            -0.692948   \n",
       "C_ID_5c240d6e3c                                  NaN   \n",
       "\n",
       "                 category_2_1.0_purchase_amount_sum  \\\n",
       "card_id                                               \n",
       "C_ID_05042ebd55                           -3.497421   \n",
       "C_ID_5c240d6e3c                            1.247291   \n",
       "\n",
       "                 category_2_3.0_purchase_amount_sum  \\\n",
       "card_id                                               \n",
       "C_ID_05042ebd55                           -0.692948   \n",
       "C_ID_5c240d6e3c                                 NaN   \n",
       "\n",
       "                 category_3_0_purchase_amount_mean  \\\n",
       "card_id                                              \n",
       "C_ID_05042ebd55                          -0.698395   \n",
       "C_ID_5c240d6e3c                           0.415764   \n",
       "\n",
       "                 category_3_0_purchase_amount_sum  \\\n",
       "card_id                                             \n",
       "C_ID_05042ebd55                         -4.190368   \n",
       "C_ID_5c240d6e3c                          1.247291   \n",
       "\n",
       "                 authorized_flag_0_purchase_amount_mean  \\\n",
       "card_id                                                   \n",
       "C_ID_05042ebd55                               -0.674555   \n",
       "C_ID_5c240d6e3c                                     NaN   \n",
       "\n",
       "                 authorized_flag_1_purchase_amount_mean  \\\n",
       "card_id                                                   \n",
       "C_ID_05042ebd55                               -0.710314   \n",
       "C_ID_5c240d6e3c                                0.415764   \n",
       "\n",
       "                 authorized_flag_0_purchase_amount_sum  \\\n",
       "card_id                                                  \n",
       "C_ID_05042ebd55                               -1.34911   \n",
       "C_ID_5c240d6e3c                                    NaN   \n",
       "\n",
       "                 authorized_flag_1_purchase_amount_sum  \n",
       "card_id                                                 \n",
       "C_ID_05042ebd55                              -2.841258  \n",
       "C_ID_5c240d6e3c                               1.247291  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_cat_agg(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "def successive_aggregates(df, field1, field2):\n",
    "    t = df.groupby(['card_id', field1])[field2].mean()\n",
    "    u = pd.DataFrame(t).reset_index().groupby('card_id')[field2].agg(['mean', 'max', np.ptp, 'sum'])\n",
    "    u.columns = [field1 + '_' + field2 + '_' + col for col in u.columns.values]\n",
    "    u.reset_index(inplace=True)\n",
    "    return u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>card_id</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id_purchase_amount_mean</th>\n",
       "      <td>-0.696216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id_purchase_amount_max</th>\n",
       "      <td>-0.692948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id_purchase_amount_ptp</th>\n",
       "      <td>0.00653653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id_purchase_amount_sum</th>\n",
       "      <td>-1.39243</td>\n",
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       "</table>\n",
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      "text/plain": [
       "                                             0\n",
       "card_id                        C_ID_05042ebd55\n",
       "state_id_purchase_amount_mean        -0.696216\n",
       "state_id_purchase_amount_max         -0.692948\n",
       "state_id_purchase_amount_ptp        0.00653653\n",
       "state_id_purchase_amount_sum          -1.39243"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "successive_aggregates(temp1, 'state_id', 'purchase_amount').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>-0.691494</td>\n",
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       "      <td>0.0728786</td>\n",
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       "      <th>subsector_id_purchase_amount_sum</th>\n",
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      ],
      "text/plain": [
       "                                                 0\n",
       "card_id                            C_ID_05042ebd55\n",
       "subsector_id_purchase_amount_mean        -0.691494\n",
       "subsector_id_purchase_amount_max         -0.643976\n",
       "subsector_id_purchase_amount_ptp         0.0728786\n",
       "subsector_id_purchase_amount_sum          -2.76598"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "successive_aggregates(temp1, 'subsector_id', 'purchase_amount').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/ipykernel_launcher.py:8: FutureWarning: using a dict on a Series for aggregation\n",
      "is deprecated and will be removed in a future version\n",
      "  \n"
     ]
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    {
     "data": {
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       "      <th>card_id</th>\n",
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       "      <th>subsector_id_mean</th>\n",
       "      <td>27</td>\n",
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       "      <th>subsector_id_sum</th>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
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       "      <th>subsector_id_ptp</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subsector_id_max</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_count_mean</th>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_count_sum</th>\n",
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       "      <th>purchase_amount_count_ptp</th>\n",
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       "    <tr>\n",
       "      <th>purchase_amount_sum_sum</th>\n",
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       "    <tr>\n",
       "      <th>purchase_amount_max_mean</th>\n",
       "      <td>-0.689728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_sum</th>\n",
       "      <td>-2.75891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_ptp</th>\n",
       "      <td>0.0728786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_max_max</th>\n",
       "      <td>-0.643976</td>\n",
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       "    <tr>\n",
       "      <th>purchase_amount_mean_mean</th>\n",
       "      <td>-0.691494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_sum</th>\n",
       "      <td>-2.76598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_ptp</th>\n",
       "      <td>0.0728786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount_mean_max</th>\n",
       "      <td>-0.643976</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          0\n",
       "card_id                     C_ID_05042ebd55\n",
       "subsector_id_mean                        27\n",
       "subsector_id_sum                        108\n",
       "subsector_id_ptp                         22\n",
       "subsector_id_max                         37\n",
       "purchase_amount_count_mean              1.5\n",
       "purchase_amount_count_sum                 6\n",
       "purchase_amount_count_ptp                 2\n",
       "purchase_amount_count_max                 3\n",
       "purchase_amount_sum_mean           -1.04759\n",
       "purchase_amount_sum_sum            -4.19037\n",
       "purchase_amount_sum_ptp             1.49261\n",
       "purchase_amount_sum_max           -0.643976\n",
       "purchase_amount_max_mean          -0.689728\n",
       "purchase_amount_max_sum            -2.75891\n",
       "purchase_amount_max_ptp           0.0728786\n",
       "purchase_amount_max_max           -0.643976\n",
       "purchase_amount_mean_mean         -0.691494\n",
       "purchase_amount_mean_sum           -2.76598\n",
       "purchase_amount_mean_ptp          0.0728786\n",
       "purchase_amount_mean_max          -0.643976"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregate_per_month(temp1).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>authorized_flag</th>\n",
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       "      <td>C_ID_05042ebd55</td>\n",
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       "      <th>category_1</th>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>installments</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>merchant_category_id</th>\n",
       "      <td>437</td>\n",
       "      <td>703</td>\n",
       "      <td>422</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_id</th>\n",
       "      <td>M_ID_ce1e7a7a85</td>\n",
       "      <td>M_ID_051eacb2a3</td>\n",
       "      <td>M_ID_0de7fd2bef</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_814793f74b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_lag</th>\n",
       "      <td>-4</td>\n",
       "      <td>-2</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>-0.716855</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>-0.705134</td>\n",
       "      <td>-0.705585</td>\n",
       "      <td>-0.725871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date</th>\n",
       "      <td>2017-10-28 15:16:46</td>\n",
       "      <td>2017-12-31 16:27:35</td>\n",
       "      <td>2018-01-14 21:22:48</td>\n",
       "      <td>2018-02-07 12:33:36</td>\n",
       "      <td>2018-02-07 12:34:06</td>\n",
       "      <td>2018-02-09 15:04:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>19</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subsector_id</th>\n",
       "      <td>15</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Year</th>\n",
       "      <td>2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Month</th>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Week</th>\n",
       "      <td>43</td>\n",
       "      <td>52</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Day</th>\n",
       "      <td>28</td>\n",
       "      <td>31</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofweek</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofyear</th>\n",
       "      <td>301</td>\n",
       "      <td>365</td>\n",
       "      <td>14</td>\n",
       "      <td>38</td>\n",
       "      <td>38</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_end</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Elapsed</th>\n",
       "      <td>1509203806</td>\n",
       "      <td>1514737655</td>\n",
       "      <td>1515964968</td>\n",
       "      <td>1518006816</td>\n",
       "      <td>1518006846</td>\n",
       "      <td>1518188681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchased_on_weekend</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_diff</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      29112043             29112045  \\\n",
       "authorized_flag                              0                    1   \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                     -1                   -1   \n",
       "category_1                                   0                    0   \n",
       "installments                                 0                    0   \n",
       "category_3                                   0                    0   \n",
       "merchant_category_id                       437                  703   \n",
       "merchant_id                    M_ID_ce1e7a7a85      M_ID_051eacb2a3   \n",
       "month_lag                                   -4                   -2   \n",
       "purchase_amount                      -0.643976            -0.716855   \n",
       "purchase_date              2017-10-28 15:16:46  2017-12-31 16:27:35   \n",
       "category_2                                   1                    1   \n",
       "state_id                                    -1                   -1   \n",
       "subsector_id                                15                   29   \n",
       "purchase_Year                             2017                 2017   \n",
       "purchase_Month                              10                   12   \n",
       "purchase_Week                               43                   52   \n",
       "purchase_Day                                28                   31   \n",
       "purchase_Dayofweek                           5                    6   \n",
       "purchase_Dayofyear                         301                  365   \n",
       "purchase_Is_month_end                    False                 True   \n",
       "purchase_Is_month_start                  False                False   \n",
       "purchase_Is_quarter_end                  False                 True   \n",
       "purchase_Is_quarter_start                False                False   \n",
       "purchase_Is_year_end                     False                 True   \n",
       "purchase_Is_year_start                   False                False   \n",
       "purchase_Elapsed                    1509203806           1514737655   \n",
       "purchased_on_weekend                         1                    1   \n",
       "month_diff                                  10                   10   \n",
       "\n",
       "                                      29112044             29112047  \\\n",
       "authorized_flag                              1                    0   \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                     20                   -1   \n",
       "category_1                                   0                    0   \n",
       "installments                                 0                    0   \n",
       "category_3                                   0                    0   \n",
       "merchant_category_id                       422                   80   \n",
       "merchant_id                    M_ID_0de7fd2bef      M_ID_9ecff0beda   \n",
       "month_lag                                   -1                    0   \n",
       "purchase_amount                      -0.692948            -0.705134   \n",
       "purchase_date              2018-01-14 21:22:48  2018-02-07 12:33:36   \n",
       "category_2                                   3                    1   \n",
       "state_id                                    19                   -1   \n",
       "subsector_id                                27                   37   \n",
       "purchase_Year                             2018                 2018   \n",
       "purchase_Month                               1                    2   \n",
       "purchase_Week                                2                    6   \n",
       "purchase_Day                                14                    7   \n",
       "purchase_Dayofweek                           6                    2   \n",
       "purchase_Dayofyear                          14                   38   \n",
       "purchase_Is_month_end                    False                False   \n",
       "purchase_Is_month_start                  False                False   \n",
       "purchase_Is_quarter_end                  False                False   \n",
       "purchase_Is_quarter_start                False                False   \n",
       "purchase_Is_year_end                     False                False   \n",
       "purchase_Is_year_start                   False                False   \n",
       "purchase_Elapsed                    1515964968           1518006816   \n",
       "purchased_on_weekend                         1                    0   \n",
       "month_diff                                  11                   11   \n",
       "\n",
       "                                      29112046             29112048  \n",
       "authorized_flag                              1                    1  \n",
       "card_id                        C_ID_05042ebd55      C_ID_05042ebd55  \n",
       "city_id                                     -1                   -1  \n",
       "category_1                                   0                    0  \n",
       "installments                                 0                    0  \n",
       "category_3                                   0                    0  \n",
       "merchant_category_id                        80                  278  \n",
       "merchant_id                    M_ID_9ecff0beda      M_ID_814793f74b  \n",
       "month_lag                                    0                    0  \n",
       "purchase_amount                      -0.705585            -0.725871  \n",
       "purchase_date              2018-02-07 12:34:06  2018-02-09 15:04:41  \n",
       "category_2                                   1                    1  \n",
       "state_id                                    -1                   -1  \n",
       "subsector_id                                37                   37  \n",
       "purchase_Year                             2018                 2018  \n",
       "purchase_Month                               2                    2  \n",
       "purchase_Week                                6                    6  \n",
       "purchase_Day                                 7                    9  \n",
       "purchase_Dayofweek                           2                    4  \n",
       "purchase_Dayofyear                          38                   40  \n",
       "purchase_Is_month_end                    False                False  \n",
       "purchase_Is_month_start                  False                False  \n",
       "purchase_Is_quarter_end                  False                False  \n",
       "purchase_Is_quarter_start                False                False  \n",
       "purchase_Is_year_end                     False                False  \n",
       "purchase_Is_year_start                   False                False  \n",
       "purchase_Elapsed                    1518006846           1518188681  \n",
       "purchased_on_weekend                         0                    0  \n",
       "month_diff                                  11                   11  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def percentile(n):\n",
    "    def percentile_(x):\n",
    "        return x.quantile(0.5)\n",
    "    percentile_.__name__ = 'percentile_{:2.0f}'.format(n*100)\n",
    "    return percentile_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def aggregate_new_trans(df):\n",
    "\n",
    "    aggs = {}\n",
    "#     aggs['purchase_amount'] = ['sum','max','min','mean','median', percentile(80), percentile(20), percentile(75), percentile(25)]\n",
    "    aggs['purchase_amount'] = [('sum', 'sum'), ('pct_75', lambda x: np.percentile(x, q = 75)), \n",
    "                               ('pct_25', lambda x: np.percentile(x, q = 25)), ('mean', 'mean'), \n",
    "                               ('median', 'median'), ('max', 'max'), ('min', 'min'), ('var', 'var'), \n",
    "                               ('skew', 'skew')]\n",
    "    \n",
    "    new_df = df.groupby(['card_id']).agg(aggs)\n",
    "\n",
    "    new_df.columns = ['_'.join(col).strip() for col in new_df.columns.values]\n",
    "    new_df.reset_index(inplace=True)\n",
    "    other_df = (df.groupby('card_id')\n",
    "          .size()\n",
    "          .reset_index(name='transactions_count'))\n",
    "    \n",
    "    new_df = pd.merge(other_df, new_df, on='card_id', how='left')\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>card_id</th>\n",
       "      <th>transactions_count</th>\n",
       "      <th>purchase_amount_sum</th>\n",
       "      <th>purchase_amount_pct_75</th>\n",
       "      <th>purchase_amount_pct_25</th>\n",
       "      <th>purchase_amount_mean</th>\n",
       "      <th>purchase_amount_median</th>\n",
       "      <th>purchase_amount_max</th>\n",
       "      <th>purchase_amount_min</th>\n",
       "      <th>purchase_amount_var</th>\n",
       "      <th>purchase_amount_skew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>6</td>\n",
       "      <td>-4.190368</td>\n",
       "      <td>-0.695994</td>\n",
       "      <td>-0.714037</td>\n",
       "      <td>-0.698395</td>\n",
       "      <td>-0.705359</td>\n",
       "      <td>-0.643976</td>\n",
       "      <td>-0.725871</td>\n",
       "      <td>0.000837</td>\n",
       "      <td>1.655883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           card_id  transactions_count  purchase_amount_sum  \\\n",
       "0  C_ID_05042ebd55                   6            -4.190368   \n",
       "\n",
       "   purchase_amount_pct_75  purchase_amount_pct_25  purchase_amount_mean  \\\n",
       "0               -0.695994               -0.714037             -0.698395   \n",
       "\n",
       "   purchase_amount_median  purchase_amount_max  purchase_amount_min  \\\n",
       "0               -0.705359            -0.643976            -0.725871   \n",
       "\n",
       "   purchase_amount_var  purchase_amount_skew  \n",
       "0             0.000837              1.655883  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregate_new_trans(temp1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    6.000000\n",
       "mean    -0.698395\n",
       "std      0.028927\n",
       "min     -0.725871\n",
       "25%     -0.714037\n",
       "50%     -0.705359\n",
       "75%     -0.695994\n",
       "max     -0.643976\n",
       "Name: purchase_amount, dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1['purchase_amount'].describe( percentiles = [ 0.25, 0.75 ] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>29112043</th>\n",
       "      <th>29112044</th>\n",
       "      <th>29112045</th>\n",
       "      <th>29112046</th>\n",
       "      <th>29112047</th>\n",
       "      <th>29112048</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>authorized_flag</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>card_id</th>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "      <td>C_ID_05042ebd55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city_id</th>\n",
       "      <td>-1</td>\n",
       "      <td>20</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installments</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_category_id</th>\n",
       "      <td>437</td>\n",
       "      <td>422</td>\n",
       "      <td>703</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_id</th>\n",
       "      <td>M_ID_ce1e7a7a85</td>\n",
       "      <td>M_ID_0de7fd2bef</td>\n",
       "      <td>M_ID_051eacb2a3</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_9ecff0beda</td>\n",
       "      <td>M_ID_814793f74b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_lag</th>\n",
       "      <td>-4</td>\n",
       "      <td>-1</td>\n",
       "      <td>-2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_amount</th>\n",
       "      <td>-0.643976</td>\n",
       "      <td>-0.692948</td>\n",
       "      <td>-0.716855</td>\n",
       "      <td>-0.705585</td>\n",
       "      <td>-0.705134</td>\n",
       "      <td>-0.725871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date</th>\n",
       "      <td>2017-10-28 15:16:46</td>\n",
       "      <td>2018-01-14 21:22:48</td>\n",
       "      <td>2017-12-31 16:27:35</td>\n",
       "      <td>2018-02-07 12:34:06</td>\n",
       "      <td>2018-02-07 12:33:36</td>\n",
       "      <td>2018-02-09 15:04:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category_2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_id</th>\n",
       "      <td>-1</td>\n",
       "      <td>19</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subsector_id</th>\n",
       "      <td>15</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Year</th>\n",
       "      <td>2017</td>\n",
       "      <td>2018</td>\n",
       "      <td>2017</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Month</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Week</th>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>52</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Day</th>\n",
       "      <td>28</td>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofweek</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Dayofyear</th>\n",
       "      <td>301</td>\n",
       "      <td>14</td>\n",
       "      <td>365</td>\n",
       "      <td>38</td>\n",
       "      <td>38</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_end</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_month_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_end</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_quarter_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_end</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Is_year_start</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_Elapsed</th>\n",
       "      <td>1509203806</td>\n",
       "      <td>1515964968</td>\n",
       "      <td>1514737655</td>\n",
       "      <td>1518006846</td>\n",
       "      <td>1518006816</td>\n",
       "      <td>1518188681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchased_on_weekend</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month_diff</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purchase_date_successive_diff</th>\n",
       "      <td>0</td>\n",
       "      <td>1.22731e+06</td>\n",
       "      <td>5.53385e+06</td>\n",
       "      <td>30</td>\n",
       "      <td>2.04185e+06</td>\n",
       "      <td>181835</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          29112043             29112044  \\\n",
       "authorized_flag                                  0                    1   \n",
       "card_id                            C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                         -1                   20   \n",
       "category_1                                       0                    0   \n",
       "installments                                     0                    0   \n",
       "category_3                                       0                    0   \n",
       "merchant_category_id                           437                  422   \n",
       "merchant_id                        M_ID_ce1e7a7a85      M_ID_0de7fd2bef   \n",
       "month_lag                                       -4                   -1   \n",
       "purchase_amount                          -0.643976            -0.692948   \n",
       "purchase_date                  2017-10-28 15:16:46  2018-01-14 21:22:48   \n",
       "category_2                                       1                    3   \n",
       "state_id                                        -1                   19   \n",
       "subsector_id                                    15                   27   \n",
       "purchase_Year                                 2017                 2018   \n",
       "purchase_Month                                  10                    1   \n",
       "purchase_Week                                   43                    2   \n",
       "purchase_Day                                    28                   14   \n",
       "purchase_Dayofweek                               5                    6   \n",
       "purchase_Dayofyear                             301                   14   \n",
       "purchase_Is_month_end                        False                False   \n",
       "purchase_Is_month_start                      False                False   \n",
       "purchase_Is_quarter_end                      False                False   \n",
       "purchase_Is_quarter_start                    False                False   \n",
       "purchase_Is_year_end                         False                False   \n",
       "purchase_Is_year_start                       False                False   \n",
       "purchase_Elapsed                        1509203806           1515964968   \n",
       "purchased_on_weekend                             1                    1   \n",
       "month_diff                                      10                   11   \n",
       "purchase_date_successive_diff                    0          1.22731e+06   \n",
       "\n",
       "                                          29112045             29112046  \\\n",
       "authorized_flag                                  1                    1   \n",
       "card_id                            C_ID_05042ebd55      C_ID_05042ebd55   \n",
       "city_id                                         -1                   -1   \n",
       "category_1                                       0                    0   \n",
       "installments                                     0                    0   \n",
       "category_3                                       0                    0   \n",
       "merchant_category_id                           703                   80   \n",
       "merchant_id                        M_ID_051eacb2a3      M_ID_9ecff0beda   \n",
       "month_lag                                       -2                    0   \n",
       "purchase_amount                          -0.716855            -0.705585   \n",
       "purchase_date                  2017-12-31 16:27:35  2018-02-07 12:34:06   \n",
       "category_2                                       1                    1   \n",
       "state_id                                        -1                   -1   \n",
       "subsector_id                                    29                   37   \n",
       "purchase_Year                                 2017                 2018   \n",
       "purchase_Month                                  12                    2   \n",
       "purchase_Week                                   52                    6   \n",
       "purchase_Day                                    31                    7   \n",
       "purchase_Dayofweek                               6                    2   \n",
       "purchase_Dayofyear                             365                   38   \n",
       "purchase_Is_month_end                         True                False   \n",
       "purchase_Is_month_start                      False                False   \n",
       "purchase_Is_quarter_end                       True                False   \n",
       "purchase_Is_quarter_start                    False                False   \n",
       "purchase_Is_year_end                          True                False   \n",
       "purchase_Is_year_start                       False                False   \n",
       "purchase_Elapsed                        1514737655           1518006846   \n",
       "purchased_on_weekend                             1                    0   \n",
       "month_diff                                      10                   11   \n",
       "purchase_date_successive_diff          5.53385e+06                   30   \n",
       "\n",
       "                                          29112047             29112048  \n",
       "authorized_flag                                  0                    1  \n",
       "card_id                            C_ID_05042ebd55      C_ID_05042ebd55  \n",
       "city_id                                         -1                   -1  \n",
       "category_1                                       0                    0  \n",
       "installments                                     0                    0  \n",
       "category_3                                       0                    0  \n",
       "merchant_category_id                            80                  278  \n",
       "merchant_id                        M_ID_9ecff0beda      M_ID_814793f74b  \n",
       "month_lag                                        0                    0  \n",
       "purchase_amount                          -0.705134            -0.725871  \n",
       "purchase_date                  2018-02-07 12:33:36  2018-02-09 15:04:41  \n",
       "category_2                                       1                    1  \n",
       "state_id                                        -1                   -1  \n",
       "subsector_id                                    37                   37  \n",
       "purchase_Year                                 2018                 2018  \n",
       "purchase_Month                                   2                    2  \n",
       "purchase_Week                                    6                    6  \n",
       "purchase_Day                                     7                    9  \n",
       "purchase_Dayofweek                               2                    4  \n",
       "purchase_Dayofyear                              38                   40  \n",
       "purchase_Is_month_end                        False                False  \n",
       "purchase_Is_month_start                      False                False  \n",
       "purchase_Is_quarter_end                      False                False  \n",
       "purchase_Is_quarter_start                    False                False  \n",
       "purchase_Is_year_end                         False                False  \n",
       "purchase_Is_year_start                       False                False  \n",
       "purchase_Elapsed                        1518006816           1518188681  \n",
       "purchased_on_weekend                             0                    0  \n",
       "month_diff                                      11                   11  \n",
       "purchase_date_successive_diff          2.04185e+06               181835  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "card_id\n",
       "C_ID_05042ebd55   -0.716855\n",
       "Name: purchase_amount, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.groupby(['card_id'])['purchase_amount'].quantile(.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>purchase_Is_year_end</th>\n",
       "      <th>purchase_Is_year_start</th>\n",
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       "      <td>1514313471</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2780376.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29112359</th>\n",
       "      <td>1</td>\n",
       "      <td>C_ID_5c240d6e3c</td>\n",
       "      <td>331</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>514</td>\n",
       "      <td>M_ID_1a75f94f92</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.770620</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
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       "      <td>1511533095</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2506115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29112360</th>\n",
       "      <td>1</td>\n",
       "      <td>C_ID_5c240d6e3c</td>\n",
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       "      <td>0</td>\n",
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       "      <td>M_ID_1a75f94f92</td>\n",
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       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          authorized_flag          card_id  city_id  category_1  installments  \\\n",
       "29112043                0  C_ID_05042ebd55       -1           0             0   \n",
       "29112044                1  C_ID_05042ebd55       20           0             0   \n",
       "29112045                1  C_ID_05042ebd55       -1           0             0   \n",
       "29112046                1  C_ID_05042ebd55       -1           0             0   \n",
       "29112047                0  C_ID_05042ebd55       -1           0             0   \n",
       "29112048                1  C_ID_05042ebd55       -1           0             0   \n",
       "29112358                1  C_ID_5c240d6e3c        3           0             0   \n",
       "29112359                1  C_ID_5c240d6e3c      331           0             0   \n",
       "29112360                1  C_ID_5c240d6e3c      331           0             0   \n",
       "\n",
       "          category_3  merchant_category_id      merchant_id  month_lag  \\\n",
       "29112043           0                   437  M_ID_ce1e7a7a85         -4   \n",
       "29112044           0                   422  M_ID_0de7fd2bef         -1   \n",
       "29112045           0                   703  M_ID_051eacb2a3         -2   \n",
       "29112046           0                    80  M_ID_9ecff0beda          0   \n",
       "29112047           0                    80  M_ID_9ecff0beda          0   \n",
       "29112048           0                   278  M_ID_814793f74b          0   \n",
       "29112358           0                   278  M_ID_9cdcfe8673          0   \n",
       "29112359           0                   514  M_ID_1a75f94f92         -1   \n",
       "29112360           0                   514  M_ID_1a75f94f92         -2   \n",
       "\n",
       "          purchase_amount              ...                \\\n",
       "29112043        -0.643976              ...                 \n",
       "29112044        -0.692948              ...                 \n",
       "29112045        -0.716855              ...                 \n",
       "29112046        -0.705585              ...                 \n",
       "29112047        -0.705134              ...                 \n",
       "29112048        -0.725871              ...                 \n",
       "29112358        -0.657740              ...                 \n",
       "29112359         0.770620              ...                 \n",
       "29112360         1.134411              ...                 \n",
       "\n",
       "         purchase_Is_month_end  purchase_Is_month_start  \\\n",
       "29112043                 False                    False   \n",
       "29112044                 False                    False   \n",
       "29112045                  True                    False   \n",
       "29112046                 False                    False   \n",
       "29112047                 False                    False   \n",
       "29112048                 False                    False   \n",
       "29112358                 False                    False   \n",
       "29112359                 False                    False   \n",
       "29112360                 False                    False   \n",
       "\n",
       "          purchase_Is_quarter_end  purchase_Is_quarter_start  \\\n",
       "29112043                    False                      False   \n",
       "29112044                    False                      False   \n",
       "29112045                     True                      False   \n",
       "29112046                    False                      False   \n",
       "29112047                    False                      False   \n",
       "29112048                    False                      False   \n",
       "29112358                    False                      False   \n",
       "29112359                    False                      False   \n",
       "29112360                    False                      False   \n",
       "\n",
       "          purchase_Is_year_end  purchase_Is_year_start  purchase_Elapsed  \\\n",
       "29112043                 False                   False        1509203806   \n",
       "29112044                 False                   False        1515964968   \n",
       "29112045                  True                   False        1514737655   \n",
       "29112046                 False                   False        1518006846   \n",
       "29112047                 False                   False        1518006816   \n",
       "29112048                 False                   False        1518188681   \n",
       "29112358                 False                   False        1514313471   \n",
       "29112359                 False                   False        1511533095   \n",
       "29112360                 False                   False        1509026980   \n",
       "\n",
       "          purchased_on_weekend  month_diff  purchase_date_successive_diff  \n",
       "29112043                     1          10                            0.0  \n",
       "29112044                     1          11                      1227313.0  \n",
       "29112045                     1          10                      5533849.0  \n",
       "29112046                     0          11                           30.0  \n",
       "29112047                     0          11                      2041848.0  \n",
       "29112048                     0          11                       181835.0  \n",
       "29112358                     0          13                      2780376.0  \n",
       "29112359                     0          13                      2506115.0  \n",
       "29112360                     0          13                            0.0  \n",
       "\n",
       "[9 rows x 30 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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