data-analysis/cohort-analysis.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Some intuition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Randomly generated customer IDs and purchased months\n",
    "df = pd.DataFrame([\n",
    "    {'customer': customer_id, 'month': month}\n",
    "    for month, customer_id in\n",
    "    zip(np.random.randint(1, 13, 100), np.random.randint(1, 31, 100))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cohort = df.sort_values(by='month').groupby('customer')['month'].first()\n",
    "cohort = cohort.to_frame(name='cohort')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
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   },
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cohort</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customer</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "          cohort\n",
       "customer        \n",
       "1              6\n",
       "2              7\n",
       "3             12\n",
       "4              7\n",
       "5              8"
      ]
     },
     "execution_count": 143,
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   ],
   "source": [
    "cohort.head()"
   ]
  },
  {
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   "execution_count": 144,
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   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer</th>\n",
       "      <th>month</th>\n",
       "      <th>cohort</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
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      "text/plain": [
       "    customer  month  cohort\n",
       "0         15     12       3\n",
       "30        15      5       3\n",
       "46        15      3       3\n",
       "48        15     11       3\n",
       "1         22      5       4"
      ]
     },
     "execution_count": 144,
     "metadata": {},
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    }
   ],
   "source": [
    "df_cohort = pd.merge(df, cohort, right_index=True, left_on='customer')\n",
    "df_cohort.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cohort\n",
       "1      7\n",
       "2     36\n",
       "3     11\n",
       "4     16\n",
       "5      2\n",
       "6      9\n",
       "7     14\n",
       "8      4\n",
       "12     1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 145,
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   ],
   "source": [
    "df_cohort.groupby('cohort').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def cohort_generator(df, group_by, customer_column, period_column):\n",
    "    results = []\n",
    "    \n",
    "    for cohort, data in df.groupby(group_by):\n",
    "        cohort_size = data[customer_column].nunique()\n",
    "        unique_periods = sorted(df[period_column].unique())\n",
    "\n",
    "        for period in unique_periods:\n",
    "            unique = data[data[period_column] >= period][customer_column].nunique()\n",
    "            if period >= cohort and unique >= 0:\n",
    "                retention = unique / cohort_size\n",
    "                results.append({'cohort': cohort,\n",
    "                               'period': period,\n",
    "                               'retention': retention})\n",
    "            \n",
    "    c = pd.DataFrame.from_records(results)\n",
    "    return c.pivot(index='period', columns='cohort')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
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       "      <th colspan=\"9\" halign=\"left\">retention</th>\n",
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       "      <th>4</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.750</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.750</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.625</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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      "text/plain": [
       "       retention                                                    \n",
       "cohort        1      2         3    4    5         6    7    8    12\n",
       "period                                                              \n",
       "1            1.0    NaN       NaN  NaN  NaN       NaN  NaN  NaN  NaN\n",
       "2            1.0  1.000       NaN  NaN  NaN       NaN  NaN  NaN  NaN\n",
       "3            1.0  1.000  1.000000  NaN  NaN       NaN  NaN  NaN  NaN\n",
       "4            1.0  1.000  1.000000  1.0  NaN       NaN  NaN  NaN  NaN\n",
       "5            1.0  0.875  1.000000  1.0  1.0       NaN  NaN  NaN  NaN\n",
       "6            1.0  0.875  1.000000  1.0  1.0  1.000000  NaN  NaN  NaN\n",
       "7            1.0  0.875  1.000000  1.0  1.0  0.666667  1.0  NaN  NaN\n",
       "8            1.0  0.750  1.000000  1.0  0.0  0.666667  0.8  1.0  NaN\n",
       "9            1.0  0.750  1.000000  0.6  0.0  0.666667  0.8  0.5  NaN\n",
       "10           0.0  0.750  1.000000  0.4  0.0  0.666667  0.6  0.5  NaN\n",
       "11           0.0  0.750  0.333333  0.2  0.0  0.333333  0.2  0.5  NaN\n",
       "12           0.0  0.625  0.333333  0.2  0.0  0.000000  0.2  0.0  1.0"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohort_generator(df_cohort, 'cohort', 'customer', 'month')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Actual data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "orders = pd.read_csv('orders.csv')[['customer_id', 'created_at']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "orders['created_at'] = pd.to_datetime(orders['created_at'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
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       "      <th>customer_id</th>\n",
       "      <th>created_at</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-04-07 12:00:00</td>\n",
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       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>2013-04-06 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2013-04-08 12:00:00</td>\n",
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       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
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      "text/plain": [
       "   customer_id          created_at\n",
       "0            1 2013-04-07 12:00:00\n",
       "1            2 2013-04-04 12:00:00\n",
       "2            4 2013-04-06 12:00:00\n",
       "3            3 2013-04-08 12:00:00\n",
       "4           10 2013-04-04 12:00:00"
      ]
     },
     "execution_count": 226,
     "metadata": {},
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   ],
   "source": [
    "orders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 27.1 s, sys: 441 ms, total: 27.6 s\n",
      "Wall time: 27.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Extract year and date only\n",
    "orders['created_at_month_year'] = orders['created_at'].map(lambda x: x.strftime('%Y-%m'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
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   "outputs": [
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       "      <th>created_at_month_year</th>\n",
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       "      <th>0</th>\n",
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       "      <td>2013-04-07 12:00:00</td>\n",
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       "      <th>1</th>\n",
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       "      <td>2013-04-04 12:00:00</td>\n",
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       "      <th>2</th>\n",
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       "      <td>2013-04-06 12:00:00</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2013-04-08 12:00:00</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customer_id          created_at created_at_month_year\n",
       "0            1 2013-04-07 12:00:00               2013-04\n",
       "1            2 2013-04-04 12:00:00               2013-04\n",
       "2            4 2013-04-06 12:00:00               2013-04\n",
       "3            3 2013-04-08 12:00:00               2013-04\n",
       "4           10 2013-04-04 12:00:00               2013-04"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.43 s, sys: 213 ms, total: 4.65 s\n",
      "Wall time: 4.66 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Assign a cohort to each \n",
    "cohort = orders.sort_values(by='created_at_month_year').groupby('customer_id')['created_at_month_year'].first()\n",
    "cohort = cohort.to_frame(name='cohort')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th></th>\n",
       "      <th>cohort</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customer_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-04</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-04</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-04</td>\n",
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       "      <th>4</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              cohort\n",
       "customer_id         \n",
       "1            2013-04\n",
       "2            2013-04\n",
       "3            2013-04\n",
       "4            2013-04\n",
       "5            2013-04"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohort.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.44 s, sys: 165 ms, total: 1.61 s\n",
      "Wall time: 1.61 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_cohort = pd.merge(orders[['customer_id',\n",
    "                             'created_at_month_year']],\n",
    "                     cohort, right_index=True, left_on='customer_id')\n",
    "assert len(orders) == len(df_cohort)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>created_at_month_year</th>\n",
       "      <th>cohort</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>287846</th>\n",
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       "      <td>2013-10</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1646408</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-03</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1871621</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-04</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2013-04</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         customer_id created_at_month_year   cohort\n",
       "0                  1               2013-04  2013-04\n",
       "287846             1               2013-10  2013-04\n",
       "1646408            1               2015-03  2013-04\n",
       "1871621            1               2015-04  2013-04\n",
       "1                  2               2013-04  2013-04"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cohort.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "collapsed": false
   },
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cohort</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-04</th>\n",
       "      <td>28874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-05</th>\n",
       "      <td>30851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06</th>\n",
       "      <td>29953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07</th>\n",
       "      <td>31013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08</th>\n",
       "      <td>30851</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         customer_id\n",
       "cohort              \n",
       "2013-04        28874\n",
       "2013-05        30851\n",
       "2013-06        29953\n",
       "2013-07        31013\n",
       "2013-08        30851"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of unique customers in each cohort\n",
    "df_cohort.groupby('cohort').agg({'customer_id': pd.Series.nunique}).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 46.3 s, sys: 960 ms, total: 47.2 s\n",
      "Wall time: 47.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "cohort = cohort_generator(df_cohort, 'cohort', 'customer_id', 'created_at_month_year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>period</th>\n",
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       "      <td>1.000000</td>\n",
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       "      <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",
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       "      <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>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
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       "      <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>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06</th>\n",
       "      <td>0.985212</td>\n",
       "      <td>0.984603</td>\n",
       "      <td>1.000000</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>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07</th>\n",
       "      <td>0.983480</td>\n",
       "      <td>0.982821</td>\n",
       "      <td>0.984976</td>\n",
       "      <td>1.000000</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>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08</th>\n",
       "      <td>0.981852</td>\n",
       "      <td>0.980390</td>\n",
       "      <td>0.983107</td>\n",
       "      <td>0.982781</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09</th>\n",
       "      <td>0.979497</td>\n",
       "      <td>0.977829</td>\n",
       "      <td>0.980937</td>\n",
       "      <td>0.980943</td>\n",
       "      <td>0.979450</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10</th>\n",
       "      <td>0.977627</td>\n",
       "      <td>0.975236</td>\n",
       "      <td>0.978299</td>\n",
       "      <td>0.978041</td>\n",
       "      <td>0.976532</td>\n",
       "      <td>0.977918</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11</th>\n",
       "      <td>0.974510</td>\n",
       "      <td>0.972221</td>\n",
       "      <td>0.975628</td>\n",
       "      <td>0.975333</td>\n",
       "      <td>0.973777</td>\n",
       "      <td>0.975208</td>\n",
       "      <td>0.973073</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12</th>\n",
       "      <td>0.971220</td>\n",
       "      <td>0.968785</td>\n",
       "      <td>0.972557</td>\n",
       "      <td>0.972302</td>\n",
       "      <td>0.970017</td>\n",
       "      <td>0.972231</td>\n",
       "      <td>0.969655</td>\n",
       "      <td>0.969568</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01</th>\n",
       "      <td>0.967341</td>\n",
       "      <td>0.964896</td>\n",
       "      <td>0.968718</td>\n",
       "      <td>0.967949</td>\n",
       "      <td>0.966711</td>\n",
       "      <td>0.968617</td>\n",
       "      <td>0.965334</td>\n",
       "      <td>0.966030</td>\n",
       "      <td>0.966098</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-02</th>\n",
       "      <td>0.962769</td>\n",
       "      <td>0.960844</td>\n",
       "      <td>0.964144</td>\n",
       "      <td>0.963435</td>\n",
       "      <td>0.961849</td>\n",
       "      <td>0.964067</td>\n",
       "      <td>0.961045</td>\n",
       "      <td>0.961793</td>\n",
       "      <td>0.962041</td>\n",
       "      <td>0.962968</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03</th>\n",
       "      <td>0.957886</td>\n",
       "      <td>0.955723</td>\n",
       "      <td>0.959370</td>\n",
       "      <td>0.958727</td>\n",
       "      <td>0.957376</td>\n",
       "      <td>0.959684</td>\n",
       "      <td>0.956530</td>\n",
       "      <td>0.956921</td>\n",
       "      <td>0.957437</td>\n",
       "      <td>0.958675</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04</th>\n",
       "      <td>0.952137</td>\n",
       "      <td>0.949596</td>\n",
       "      <td>0.953627</td>\n",
       "      <td>0.952858</td>\n",
       "      <td>0.951314</td>\n",
       "      <td>0.954866</td>\n",
       "      <td>0.950919</td>\n",
       "      <td>0.951782</td>\n",
       "      <td>0.951706</td>\n",
       "      <td>0.953774</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05</th>\n",
       "      <td>0.945903</td>\n",
       "      <td>0.943503</td>\n",
       "      <td>0.947151</td>\n",
       "      <td>0.946603</td>\n",
       "      <td>0.944605</td>\n",
       "      <td>0.948175</td>\n",
       "      <td>0.944212</td>\n",
       "      <td>0.945375</td>\n",
       "      <td>0.945879</td>\n",
       "      <td>0.948552</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06</th>\n",
       "      <td>0.939046</td>\n",
       "      <td>0.936761</td>\n",
       "      <td>0.939205</td>\n",
       "      <td>0.939832</td>\n",
       "      <td>0.937150</td>\n",
       "      <td>0.940781</td>\n",
       "      <td>0.936988</td>\n",
       "      <td>0.939035</td>\n",
       "      <td>0.938506</td>\n",
       "      <td>0.941408</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-07</th>\n",
       "      <td>0.931184</td>\n",
       "      <td>0.929954</td>\n",
       "      <td>0.931459</td>\n",
       "      <td>0.931835</td>\n",
       "      <td>0.929727</td>\n",
       "      <td>0.933655</td>\n",
       "      <td>0.930184</td>\n",
       "      <td>0.931127</td>\n",
       "      <td>0.930232</td>\n",
       "      <td>0.933944</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08</th>\n",
       "      <td>0.921625</td>\n",
       "      <td>0.920586</td>\n",
       "      <td>0.922645</td>\n",
       "      <td>0.923322</td>\n",
       "      <td>0.921721</td>\n",
       "      <td>0.923751</td>\n",
       "      <td>0.920832</td>\n",
       "      <td>0.921750</td>\n",
       "      <td>0.920959</td>\n",
       "      <td>0.924558</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09</th>\n",
       "      <td>0.910646</td>\n",
       "      <td>0.911283</td>\n",
       "      <td>0.913197</td>\n",
       "      <td>0.913714</td>\n",
       "      <td>0.911316</td>\n",
       "      <td>0.914082</td>\n",
       "      <td>0.909965</td>\n",
       "      <td>0.911205</td>\n",
       "      <td>0.911719</td>\n",
       "      <td>0.914531</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-10</th>\n",
       "      <td>0.899598</td>\n",
       "      <td>0.899809</td>\n",
       "      <td>0.901679</td>\n",
       "      <td>0.902686</td>\n",
       "      <td>0.901462</td>\n",
       "      <td>0.902305</td>\n",
       "      <td>0.898388</td>\n",
       "      <td>0.900928</td>\n",
       "      <td>0.901900</td>\n",
       "      <td>0.902390</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11</th>\n",
       "      <td>0.886542</td>\n",
       "      <td>0.886551</td>\n",
       "      <td>0.888993</td>\n",
       "      <td>0.889466</td>\n",
       "      <td>0.888723</td>\n",
       "      <td>0.889257</td>\n",
       "      <td>0.884973</td>\n",
       "      <td>0.888147</td>\n",
       "      <td>0.888377</td>\n",
       "      <td>0.889256</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12</th>\n",
       "      <td>0.871788</td>\n",
       "      <td>0.873391</td>\n",
       "      <td>0.874003</td>\n",
       "      <td>0.874085</td>\n",
       "      <td>0.873489</td>\n",
       "      <td>0.874368</td>\n",
       "      <td>0.870622</td>\n",
       "      <td>0.874566</td>\n",
       "      <td>0.873567</td>\n",
       "      <td>0.874487</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01</th>\n",
       "      <td>0.854748</td>\n",
       "      <td>0.857606</td>\n",
       "      <td>0.855874</td>\n",
       "      <td>0.856544</td>\n",
       "      <td>0.856666</td>\n",
       "      <td>0.857372</td>\n",
       "      <td>0.853370</td>\n",
       "      <td>0.857782</td>\n",
       "      <td>0.858789</td>\n",
       "      <td>0.857957</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02</th>\n",
       "      <td>0.835215</td>\n",
       "      <td>0.839033</td>\n",
       "      <td>0.836544</td>\n",
       "      <td>0.837584</td>\n",
       "      <td>0.837023</td>\n",
       "      <td>0.838201</td>\n",
       "      <td>0.834892</td>\n",
       "      <td>0.837193</td>\n",
       "      <td>0.838796</td>\n",
       "      <td>0.838993</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03</th>\n",
       "      <td>0.815717</td>\n",
       "      <td>0.820135</td>\n",
       "      <td>0.818048</td>\n",
       "      <td>0.818721</td>\n",
       "      <td>0.815727</td>\n",
       "      <td>0.819365</td>\n",
       "      <td>0.814995</td>\n",
       "      <td>0.818907</td>\n",
       "      <td>0.820058</td>\n",
       "      <td>0.818907</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04</th>\n",
       "      <td>0.789915</td>\n",
       "      <td>0.794431</td>\n",
       "      <td>0.793744</td>\n",
       "      <td>0.790894</td>\n",
       "      <td>0.789893</td>\n",
       "      <td>0.793971</td>\n",
       "      <td>0.788617</td>\n",
       "      <td>0.795482</td>\n",
       "      <td>0.794623</td>\n",
       "      <td>0.793631</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05</th>\n",
       "      <td>0.761931</td>\n",
       "      <td>0.767593</td>\n",
       "      <td>0.766735</td>\n",
       "      <td>0.763905</td>\n",
       "      <td>0.762925</td>\n",
       "      <td>0.768443</td>\n",
       "      <td>0.762722</td>\n",
       "      <td>0.768353</td>\n",
       "      <td>0.768352</td>\n",
       "      <td>0.768196</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06</th>\n",
       "      <td>0.731662</td>\n",
       "      <td>0.736216</td>\n",
       "      <td>0.736120</td>\n",
       "      <td>0.733434</td>\n",
       "      <td>0.731743</td>\n",
       "      <td>0.737696</td>\n",
       "      <td>0.733634</td>\n",
       "      <td>0.736185</td>\n",
       "      <td>0.739375</td>\n",
       "      <td>0.736770</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-07</th>\n",
       "      <td>0.697583</td>\n",
       "      <td>0.701890</td>\n",
       "      <td>0.702133</td>\n",
       "      <td>0.700932</td>\n",
       "      <td>0.698292</td>\n",
       "      <td>0.704975</td>\n",
       "      <td>0.700322</td>\n",
       "      <td>0.703550</td>\n",
       "      <td>0.703413</td>\n",
       "      <td>0.702749</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08</th>\n",
       "      <td>0.656785</td>\n",
       "      <td>0.664452</td>\n",
       "      <td>0.661570</td>\n",
       "      <td>0.659369</td>\n",
       "      <td>0.658131</td>\n",
       "      <td>0.665763</td>\n",
       "      <td>0.661045</td>\n",
       "      <td>0.664576</td>\n",
       "      <td>0.663587</td>\n",
       "      <td>0.663826</td>\n",
       "      <td>...</td>\n",
       "      <td>0.666011</td>\n",
       "      <td>1.000000</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>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09</th>\n",
       "      <td>0.609891</td>\n",
       "      <td>0.620563</td>\n",
       "      <td>0.615297</td>\n",
       "      <td>0.614903</td>\n",
       "      <td>0.614956</td>\n",
       "      <td>0.619827</td>\n",
       "      <td>0.617285</td>\n",
       "      <td>0.617092</td>\n",
       "      <td>0.619092</td>\n",
       "      <td>0.619394</td>\n",
       "      <td>...</td>\n",
       "      <td>0.621012</td>\n",
       "      <td>0.619802</td>\n",
       "      <td>1.000000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10</th>\n",
       "      <td>0.562721</td>\n",
       "      <td>0.574309</td>\n",
       "      <td>0.565686</td>\n",
       "      <td>0.567439</td>\n",
       "      <td>0.565363</td>\n",
       "      <td>0.568169</td>\n",
       "      <td>0.569526</td>\n",
       "      <td>0.568206</td>\n",
       "      <td>0.572376</td>\n",
       "      <td>0.571790</td>\n",
       "      <td>...</td>\n",
       "      <td>0.572627</td>\n",
       "      <td>0.573840</td>\n",
       "      <td>0.566545</td>\n",
       "      <td>1.000000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11</th>\n",
       "      <td>0.505749</td>\n",
       "      <td>0.517033</td>\n",
       "      <td>0.512102</td>\n",
       "      <td>0.511398</td>\n",
       "      <td>0.509384</td>\n",
       "      <td>0.510857</td>\n",
       "      <td>0.513157</td>\n",
       "      <td>0.508609</td>\n",
       "      <td>0.516388</td>\n",
       "      <td>0.516242</td>\n",
       "      <td>...</td>\n",
       "      <td>0.513564</td>\n",
       "      <td>0.516765</td>\n",
       "      <td>0.511119</td>\n",
       "      <td>0.505937</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12</th>\n",
       "      <td>0.443860</td>\n",
       "      <td>0.456744</td>\n",
       "      <td>0.448536</td>\n",
       "      <td>0.448715</td>\n",
       "      <td>0.447960</td>\n",
       "      <td>0.448526</td>\n",
       "      <td>0.451048</td>\n",
       "      <td>0.448412</td>\n",
       "      <td>0.455634</td>\n",
       "      <td>0.454671</td>\n",
       "      <td>...</td>\n",
       "      <td>0.449695</td>\n",
       "      <td>0.454955</td>\n",
       "      <td>0.448469</td>\n",
       "      <td>0.447879</td>\n",
       "      <td>0.450010</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>0.371580</td>\n",
       "      <td>0.382289</td>\n",
       "      <td>0.377291</td>\n",
       "      <td>0.374424</td>\n",
       "      <td>0.376681</td>\n",
       "      <td>0.376292</td>\n",
       "      <td>0.377556</td>\n",
       "      <td>0.377703</td>\n",
       "      <td>0.381777</td>\n",
       "      <td>0.378524</td>\n",
       "      <td>...</td>\n",
       "      <td>0.377633</td>\n",
       "      <td>0.383000</td>\n",
       "      <td>0.379660</td>\n",
       "      <td>0.374575</td>\n",
       "      <td>0.379730</td>\n",
       "      <td>0.379674</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>0.288460</td>\n",
       "      <td>0.299374</td>\n",
       "      <td>0.296431</td>\n",
       "      <td>0.291878</td>\n",
       "      <td>0.292146</td>\n",
       "      <td>0.294757</td>\n",
       "      <td>0.297581</td>\n",
       "      <td>0.295816</td>\n",
       "      <td>0.296072</td>\n",
       "      <td>0.296771</td>\n",
       "      <td>...</td>\n",
       "      <td>0.292345</td>\n",
       "      <td>0.299095</td>\n",
       "      <td>0.297437</td>\n",
       "      <td>0.292509</td>\n",
       "      <td>0.297504</td>\n",
       "      <td>0.296874</td>\n",
       "      <td>0.288980</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>0.203817</td>\n",
       "      <td>0.211144</td>\n",
       "      <td>0.209061</td>\n",
       "      <td>0.203753</td>\n",
       "      <td>0.207740</td>\n",
       "      <td>0.207300</td>\n",
       "      <td>0.211448</td>\n",
       "      <td>0.208789</td>\n",
       "      <td>0.206439</td>\n",
       "      <td>0.210021</td>\n",
       "      <td>...</td>\n",
       "      <td>0.206413</td>\n",
       "      <td>0.209908</td>\n",
       "      <td>0.209387</td>\n",
       "      <td>0.206368</td>\n",
       "      <td>0.207836</td>\n",
       "      <td>0.209649</td>\n",
       "      <td>0.207388</td>\n",
       "      <td>0.207600</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>0.099155</td>\n",
       "      <td>0.102622</td>\n",
       "      <td>0.104364</td>\n",
       "      <td>0.100055</td>\n",
       "      <td>0.101780</td>\n",
       "      <td>0.103014</td>\n",
       "      <td>0.104063</td>\n",
       "      <td>0.105779</td>\n",
       "      <td>0.102189</td>\n",
       "      <td>0.104754</td>\n",
       "      <td>...</td>\n",
       "      <td>0.103093</td>\n",
       "      <td>0.104455</td>\n",
       "      <td>0.102264</td>\n",
       "      <td>0.102574</td>\n",
       "      <td>0.103985</td>\n",
       "      <td>0.104243</td>\n",
       "      <td>0.105098</td>\n",
       "      <td>0.103783</td>\n",
       "      <td>0.096181</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        retention                                                              \\\n",
       "cohort    2013-04   2013-05   2013-06   2013-07   2013-08   2013-09   2013-10   \n",
       "period                                                                          \n",
       "2013-04  1.000000       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2013-05  0.986839  1.000000       NaN       NaN       NaN       NaN       NaN   \n",
       "2013-06  0.985212  0.984603  1.000000       NaN       NaN       NaN       NaN   \n",
       "2013-07  0.983480  0.982821  0.984976  1.000000       NaN       NaN       NaN   \n",
       "2013-08  0.981852  0.980390  0.983107  0.982781  1.000000       NaN       NaN   \n",
       "2013-09  0.979497  0.977829  0.980937  0.980943  0.979450  1.000000       NaN   \n",
       "2013-10  0.977627  0.975236  0.978299  0.978041  0.976532  0.977918  1.000000   \n",
       "2013-11  0.974510  0.972221  0.975628  0.975333  0.973777  0.975208  0.973073   \n",
       "2013-12  0.971220  0.968785  0.972557  0.972302  0.970017  0.972231  0.969655   \n",
       "2014-01  0.967341  0.964896  0.968718  0.967949  0.966711  0.968617  0.965334   \n",
       "2014-02  0.962769  0.960844  0.964144  0.963435  0.961849  0.964067  0.961045   \n",
       "2014-03  0.957886  0.955723  0.959370  0.958727  0.957376  0.959684  0.956530   \n",
       "2014-04  0.952137  0.949596  0.953627  0.952858  0.951314  0.954866  0.950919   \n",
       "2014-05  0.945903  0.943503  0.947151  0.946603  0.944605  0.948175  0.944212   \n",
       "2014-06  0.939046  0.936761  0.939205  0.939832  0.937150  0.940781  0.936988   \n",
       "2014-07  0.931184  0.929954  0.931459  0.931835  0.929727  0.933655  0.930184   \n",
       "2014-08  0.921625  0.920586  0.922645  0.923322  0.921721  0.923751  0.920832   \n",
       "2014-09  0.910646  0.911283  0.913197  0.913714  0.911316  0.914082  0.909965   \n",
       "2014-10  0.899598  0.899809  0.901679  0.902686  0.901462  0.902305  0.898388   \n",
       "2014-11  0.886542  0.886551  0.888993  0.889466  0.888723  0.889257  0.884973   \n",
       "2014-12  0.871788  0.873391  0.874003  0.874085  0.873489  0.874368  0.870622   \n",
       "2015-01  0.854748  0.857606  0.855874  0.856544  0.856666  0.857372  0.853370   \n",
       "2015-02  0.835215  0.839033  0.836544  0.837584  0.837023  0.838201  0.834892   \n",
       "2015-03  0.815717  0.820135  0.818048  0.818721  0.815727  0.819365  0.814995   \n",
       "2015-04  0.789915  0.794431  0.793744  0.790894  0.789893  0.793971  0.788617   \n",
       "2015-05  0.761931  0.767593  0.766735  0.763905  0.762925  0.768443  0.762722   \n",
       "2015-06  0.731662  0.736216  0.736120  0.733434  0.731743  0.737696  0.733634   \n",
       "2015-07  0.697583  0.701890  0.702133  0.700932  0.698292  0.704975  0.700322   \n",
       "2015-08  0.656785  0.664452  0.661570  0.659369  0.658131  0.665763  0.661045   \n",
       "2015-09  0.609891  0.620563  0.615297  0.614903  0.614956  0.619827  0.617285   \n",
       "2015-10  0.562721  0.574309  0.565686  0.567439  0.565363  0.568169  0.569526   \n",
       "2015-11  0.505749  0.517033  0.512102  0.511398  0.509384  0.510857  0.513157   \n",
       "2015-12  0.443860  0.456744  0.448536  0.448715  0.447960  0.448526  0.451048   \n",
       "2016-01  0.371580  0.382289  0.377291  0.374424  0.376681  0.376292  0.377556   \n",
       "2016-02  0.288460  0.299374  0.296431  0.291878  0.292146  0.294757  0.297581   \n",
       "2016-03  0.203817  0.211144  0.209061  0.203753  0.207740  0.207300  0.211448   \n",
       "2016-04  0.099155  0.102622  0.104364  0.100055  0.101780  0.103014  0.104063   \n",
       "\n",
       "                                        ...                                  \\\n",
       "cohort    2013-11   2013-12   2014-01   ...     2015-07   2015-08   2015-09   \n",
       "period                                  ...                                   \n",
       "2013-04       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-05       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-06       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-07       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-08       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-09       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-10       NaN       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-11  1.000000       NaN       NaN   ...         NaN       NaN       NaN   \n",
       "2013-12  0.969568  1.000000       NaN   ...         NaN       NaN       NaN   \n",
       "2014-01  0.966030  0.966098  1.000000   ...         NaN       NaN       NaN   \n",
       "2014-02  0.961793  0.962041  0.962968   ...         NaN       NaN       NaN   \n",
       "2014-03  0.956921  0.957437  0.958675   ...         NaN       NaN       NaN   \n",
       "2014-04  0.951782  0.951706  0.953774   ...         NaN       NaN       NaN   \n",
       "2014-05  0.945375  0.945879  0.948552   ...         NaN       NaN       NaN   \n",
       "2014-06  0.939035  0.938506  0.941408   ...         NaN       NaN       NaN   \n",
       "2014-07  0.931127  0.930232  0.933944   ...         NaN       NaN       NaN   \n",
       "2014-08  0.921750  0.920959  0.924558   ...         NaN       NaN       NaN   \n",
       "2014-09  0.911205  0.911719  0.914531   ...         NaN       NaN       NaN   \n",
       "2014-10  0.900928  0.901900  0.902390   ...         NaN       NaN       NaN   \n",
       "2014-11  0.888147  0.888377  0.889256   ...         NaN       NaN       NaN   \n",
       "2014-12  0.874566  0.873567  0.874487   ...         NaN       NaN       NaN   \n",
       "2015-01  0.857782  0.858789  0.857957   ...         NaN       NaN       NaN   \n",
       "2015-02  0.837193  0.838796  0.838993   ...         NaN       NaN       NaN   \n",
       "2015-03  0.818907  0.820058  0.818907   ...         NaN       NaN       NaN   \n",
       "2015-04  0.795482  0.794623  0.793631   ...         NaN       NaN       NaN   \n",
       "2015-05  0.768353  0.768352  0.768196   ...         NaN       NaN       NaN   \n",
       "2015-06  0.736185  0.739375  0.736770   ...         NaN       NaN       NaN   \n",
       "2015-07  0.703550  0.703413  0.702749   ...    1.000000       NaN       NaN   \n",
       "2015-08  0.664576  0.663587  0.663826   ...    0.666011  1.000000       NaN   \n",
       "2015-09  0.617092  0.619092  0.619394   ...    0.621012  0.619802  1.000000   \n",
       "2015-10  0.568206  0.572376  0.571790   ...    0.572627  0.573840  0.566545   \n",
       "2015-11  0.508609  0.516388  0.516242   ...    0.513564  0.516765  0.511119   \n",
       "2015-12  0.448412  0.455634  0.454671   ...    0.449695  0.454955  0.448469   \n",
       "2016-01  0.377703  0.381777  0.378524   ...    0.377633  0.383000  0.379660   \n",
       "2016-02  0.295816  0.296072  0.296771   ...    0.292345  0.299095  0.297437   \n",
       "2016-03  0.208789  0.206439  0.210021   ...    0.206413  0.209908  0.209387   \n",
       "2016-04  0.105779  0.102189  0.104754   ...    0.103093  0.104455  0.102264   \n",
       "\n",
       "                                                                             \n",
       "cohort    2015-10   2015-11   2015-12   2016-01   2016-02   2016-03 2016-04  \n",
       "period                                                                       \n",
       "2013-04       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-05       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-06       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-07       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-08       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-09       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-10       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-11       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2013-12       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-01       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-02       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-03       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-04       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-05       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-06       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-07       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-08       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-09       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-10       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-11       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2014-12       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-01       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-02       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-03       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-04       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-05       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-06       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-07       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-08       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-09       NaN       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-10  1.000000       NaN       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-11  0.505937  1.000000       NaN       NaN       NaN       NaN     NaN  \n",
       "2015-12  0.447879  0.450010  1.000000       NaN       NaN       NaN     NaN  \n",
       "2016-01  0.374575  0.379730  0.379674  1.000000       NaN       NaN     NaN  \n",
       "2016-02  0.292509  0.297504  0.296874  0.288980  1.000000       NaN     NaN  \n",
       "2016-03  0.206368  0.207836  0.209649  0.207388  0.207600  1.000000     NaN  \n",
       "2016-04  0.102574  0.103985  0.104243  0.105098  0.103783  0.096181     1.0  \n",
       "\n",
       "[37 rows x 37 columns]"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohort"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Revenue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>created_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2013-04-07 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>2</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-04-06 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2013-04-08 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  customer_id           created_at\n",
       "0   1            1  2013-04-07 12:00:00\n",
       "1   2            2  2013-04-04 12:00:00\n",
       "2   3            4  2013-04-06 12:00:00\n",
       "3   4            3  2013-04-08 12:00:00\n",
       "4   5           10  2013-04-04 12:00:00"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders = pd.read_csv('orders.csv')[['id', 'customer_id', 'created_at']]\n",
    "orders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <th>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>quantity</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  product_id  quantity\n",
       "0         1           1         1\n",
       "1         2           6         1\n",
       "2         3           2         1\n",
       "3         4           1         1\n",
       "4         5           1         1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items = pd.read_csv('order_items.csv')[['order_id', 'product_id', 'quantity']]\n",
    "items.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2047      1\n",
       "650647    1\n",
       "531881    1\n",
       "529832    1\n",
       "552359    1\n",
       "Name: order_id, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# No order has more than one item\n",
    "items.order_id.value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "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>id</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>8999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>12999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>9999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>7999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  price\n",
       "0   1   8999\n",
       "1   2   4999\n",
       "2   3  12999\n",
       "3   4   9999\n",
       "4   5   7999"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products = pd.read_csv('products.csv')[['id', 'price']]\n",
    "products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "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>order_id</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>8999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>7999</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>8999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>8999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  total\n",
       "0         1   8999\n",
       "1         2   7999\n",
       "2         3   4999\n",
       "3         4   8999\n",
       "4         5   8999"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items_products = pd.merge(items,\n",
    "                          products,\n",
    "                          how='left',\n",
    "                          left_on='product_id',\n",
    "                          right_on='id')[['order_id', 'quantity', 'price']]\n",
    "items_products['total'] = items_products.quantity * items_products.price\n",
    "items_products = items_products[['order_id', 'total']]\n",
    "items_products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "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>customer_id</th>\n",
       "      <th>created_at</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-04-07 12:00:00</td>\n",
       "      <td>8999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
       "      <td>7999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>2013-04-06 12:00:00</td>\n",
       "      <td>4999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2013-04-08 12:00:00</td>\n",
       "      <td>8999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>2013-04-04 12:00:00</td>\n",
       "      <td>8999.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customer_id           created_at   total\n",
       "0            1  2013-04-07 12:00:00  8999.0\n",
       "1            2  2013-04-04 12:00:00  7999.0\n",
       "2            4  2013-04-06 12:00:00  4999.0\n",
       "3            3  2013-04-08 12:00:00  8999.0\n",
       "4           10  2013-04-04 12:00:00  8999.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined = pd.merge(orders, items_products, how='left', left_on='id', right_on='order_id')\n",
    "assert len(orders) == len(combined)\n",
    "combined = combined[['customer_id', 'created_at', 'total']]\n",
    "combined.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 804 ms, sys: 56.1 ms, total: 860 ms\n",
      "Wall time: 857 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "combined['created_at'] = pd.to_datetime(combined['created_at'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 27.6 s, sys: 488 ms, total: 28.1 s\n",
      "Wall time: 28.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Extract year and date only\n",
    "combined['created_at_month_year'] = combined['created_at'].map(lambda x: x.strftime('%Y-%m'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.46 s, sys: 198 ms, total: 4.66 s\n",
      "Wall time: 4.66 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Assign a cohort to each \n",
    "cohort = combined.sort_values(by='created_at_month_year').groupby('customer_id')['created_at_month_year'].first()\n",
    "cohort = cohort.to_frame(name='cohort')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "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",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cohort</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customer_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              cohort\n",
       "customer_id         \n",
       "1            2013-04\n",
       "2            2013-04\n",
       "3            2013-04\n",
       "4            2013-04\n",
       "5            2013-04"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohort.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.5 s, sys: 189 ms, total: 1.69 s\n",
      "Wall time: 1.69 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_cohort = pd.merge(combined[['customer_id',\n",
    "                             'created_at_month_year', 'total']],\n",
    "                     cohort, right_index=True, left_on='customer_id')\n",
    "assert len(orders) == len(df_cohort)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>created_at_month_year</th>\n",
       "      <th>total</th>\n",
       "      <th>cohort</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-04</td>\n",
       "      <td>8999.0</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287846</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-10</td>\n",
       "      <td>9999.0</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1646408</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1871621</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2013-04</td>\n",
       "      <td>7999.0</td>\n",
       "      <td>2013-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         customer_id created_at_month_year   total   cohort\n",
       "0                  1               2013-04  8999.0  2013-04\n",
       "287846             1               2013-10  9999.0  2013-04\n",
       "1646408            1               2015-03     NaN  2013-04\n",
       "1871621            1               2015-04     NaN  2013-04\n",
       "1                  2               2013-04  7999.0  2013-04"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cohort.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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></th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cohort</th>\n",
       "      <th>created_at_month_year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2013-04</th>\n",
       "      <th>2013-04</th>\n",
       "      <td>216899526.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-05</th>\n",
       "      <td>25514894.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06</th>\n",
       "      <td>26227225.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07</th>\n",
       "      <td>26419512.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08</th>\n",
       "      <td>27238296.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     total\n",
       "cohort  created_at_month_year             \n",
       "2013-04 2013-04                216899526.0\n",
       "        2013-05                 25514894.0\n",
       "        2013-06                 26227225.0\n",
       "        2013-07                 26419512.0\n",
       "        2013-08                 27238296.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "revenue = df_cohort.groupby(['cohort', 'created_at_month_year']).agg({'total': pd.np.sum})\n",
    "revenue.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"21\" halign=\"left\">revenue</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>period</th>\n",
       "      <th>2013-04</th>\n",
       "      <th>2013-05</th>\n",
       "      <th>2013-06</th>\n",
       "      <th>2013-07</th>\n",
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       "      <th>...</th>\n",
       "      <th>2015-07</th>\n",
       "      <th>2015-08</th>\n",
       "      <th>2015-09</th>\n",
       "      <th>2015-10</th>\n",
       "      <th>2015-11</th>\n",
       "      <th>2015-12</th>\n",
       "      <th>2016-01</th>\n",
       "      <th>2016-02</th>\n",
       "      <th>2016-03</th>\n",
       "      <th>2016-04</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cohort</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2013-04</th>\n",
       "      <td>216899526.0</td>\n",
       "      <td>25514894.0</td>\n",
       "      <td>26227225.0</td>\n",
       "      <td>26419512.0</td>\n",
       "      <td>27238296.0</td>\n",
       "      <td>26811655.0</td>\n",
       "      <td>26953020.0</td>\n",
       "      <td>26306898.0</td>\n",
       "      <td>27117914.0</td>\n",
       "      <td>28049071.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>232107922.0</td>\n",
       "      <td>26940399.0</td>\n",
       "      <td>28880927.0</td>\n",
       "      <td>28575980.0</td>\n",
       "      <td>28521738.0</td>\n",
       "      <td>28876224.0</td>\n",
       "      <td>27650180.0</td>\n",
       "      <td>29597311.0</td>\n",
       "      <td>28330289.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>226205043.0</td>\n",
       "      <td>27377372.0</td>\n",
       "      <td>27899470.0</td>\n",
       "      <td>26903092.0</td>\n",
       "      <td>27643548.0</td>\n",
       "      <td>26991132.0</td>\n",
       "      <td>28005795.0</td>\n",
       "      <td>28217347.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>234239087.0</td>\n",
       "      <td>27902357.0</td>\n",
       "      <td>27995429.0</td>\n",
       "      <td>29258999.0</td>\n",
       "      <td>28589001.0</td>\n",
       "      <td>28323543.0</td>\n",
       "      <td>29144705.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>232414240.0</td>\n",
       "      <td>26891138.0</td>\n",
       "      <td>28408414.0</td>\n",
       "      <td>28407545.0</td>\n",
       "      <td>29164234.0</td>\n",
       "      <td>28222726.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>225802212.0</td>\n",
       "      <td>26460161.0</td>\n",
       "      <td>26729968.0</td>\n",
       "      <td>27601337.0</td>\n",
       "      <td>26987381.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10</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>234676292.0</td>\n",
       "      <td>26828754.0</td>\n",
       "      <td>28158126.0</td>\n",
       "      <td>29055815.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11</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>225629435.0</td>\n",
       "      <td>26484060.0</td>\n",
       "      <td>28729198.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12</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>233756503.0</td>\n",
       "      <td>27495206.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01</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>NaN</td>\n",
       "      <td>235037977.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-02</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-07</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-10</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-07</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             revenue                                                      \\\n",
       "period       2013-04      2013-05      2013-06      2013-07      2013-08   \n",
       "cohort                                                                     \n",
       "2013-04  216899526.0   25514894.0   26227225.0   26419512.0   27238296.0   \n",
       "2013-05          NaN  232107922.0   26940399.0   28880927.0   28575980.0   \n",
       "2013-06          NaN          NaN  226205043.0   27377372.0   27899470.0   \n",
       "2013-07          NaN          NaN          NaN  234239087.0   27902357.0   \n",
       "2013-08          NaN          NaN          NaN          NaN  232414240.0   \n",
       "2013-09          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-10          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-11          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-12          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-01          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-02          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-03          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-04          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-05          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-06          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-07          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-08          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-09          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-10          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-11          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-12          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-01          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-02          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-03          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-04          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-05          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-06          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-07          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-08          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-09          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-10          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-11          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-12          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-01          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-02          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-03          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-04          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "                                                                          \\\n",
       "period       2013-09      2013-10      2013-11      2013-12      2014-01   \n",
       "cohort                                                                     \n",
       "2013-04   26811655.0   26953020.0   26306898.0   27117914.0   28049071.0   \n",
       "2013-05   28521738.0   28876224.0   27650180.0   29597311.0   28330289.0   \n",
       "2013-06   26903092.0   27643548.0   26991132.0   28005795.0   28217347.0   \n",
       "2013-07   27995429.0   29258999.0   28589001.0   28323543.0   29144705.0   \n",
       "2013-08   26891138.0   28408414.0   28407545.0   29164234.0   28222726.0   \n",
       "2013-09  225802212.0   26460161.0   26729968.0   27601337.0   26987381.0   \n",
       "2013-10          NaN  234676292.0   26828754.0   28158126.0   29055815.0   \n",
       "2013-11          NaN          NaN  225629435.0   26484060.0   28729198.0   \n",
       "2013-12          NaN          NaN          NaN  233756503.0   27495206.0   \n",
       "2014-01          NaN          NaN          NaN          NaN  235037977.0   \n",
       "2014-02          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-03          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-04          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-05          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-06          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-07          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-08          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-09          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-10          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-11          NaN          NaN          NaN          NaN          NaN   \n",
       "2014-12          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-01          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-02          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-03          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-04          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-05          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-06          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-07          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-08          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-09          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-10          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-11          NaN          NaN          NaN          NaN          NaN   \n",
       "2015-12          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-01          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-02          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-03          NaN          NaN          NaN          NaN          NaN   \n",
       "2016-04          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "          ...                                                            \\\n",
       "period    ...   2015-07 2015-08 2015-09 2015-10 2015-11 2015-12 2016-01   \n",
       "cohort    ...                                                             \n",
       "2013-04   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-05   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-06   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-07   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-08   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-09   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-10   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-11   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2013-12   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-01   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-02   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-03   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-04   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-05   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-06   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-07   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-08   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-09   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-10   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-11   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2014-12   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-01   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-02   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-03   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-04   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-05   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-06   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-07   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-08   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-09   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-10   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-11   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2015-12   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2016-01   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2016-02   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2016-03   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2016-04   ...       NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "\n",
       "                                 \n",
       "period  2016-02 2016-03 2016-04  \n",
       "cohort                           \n",
       "2013-04     NaN     NaN     NaN  \n",
       "2013-05     NaN     NaN     NaN  \n",
       "2013-06     NaN     NaN     NaN  \n",
       "2013-07     NaN     NaN     NaN  \n",
       "2013-08     NaN     NaN     NaN  \n",
       "2013-09     NaN     NaN     NaN  \n",
       "2013-10     NaN     NaN     NaN  \n",
       "2013-11     NaN     NaN     NaN  \n",
       "2013-12     NaN     NaN     NaN  \n",
       "2014-01     NaN     NaN     NaN  \n",
       "2014-02     NaN     NaN     NaN  \n",
       "2014-03     NaN     NaN     NaN  \n",
       "2014-04     NaN     NaN     NaN  \n",
       "2014-05     NaN     NaN     NaN  \n",
       "2014-06     NaN     NaN     NaN  \n",
       "2014-07     NaN     NaN     NaN  \n",
       "2014-08     NaN     NaN     NaN  \n",
       "2014-09     NaN     NaN     NaN  \n",
       "2014-10     NaN     NaN     NaN  \n",
       "2014-11     NaN     NaN     NaN  \n",
       "2014-12     NaN     NaN     NaN  \n",
       "2015-01     NaN     NaN     NaN  \n",
       "2015-02     NaN     NaN     NaN  \n",
       "2015-03     NaN     NaN     NaN  \n",
       "2015-04     NaN     NaN     NaN  \n",
       "2015-05     NaN     NaN     NaN  \n",
       "2015-06     NaN     NaN     NaN  \n",
       "2015-07     NaN     NaN     NaN  \n",
       "2015-08     NaN     NaN     NaN  \n",
       "2015-09     NaN     NaN     NaN  \n",
       "2015-10     NaN     NaN     NaN  \n",
       "2015-11     NaN     NaN     NaN  \n",
       "2015-12     NaN     NaN     NaN  \n",
       "2016-01     NaN     NaN     NaN  \n",
       "2016-02     NaN     NaN     NaN  \n",
       "2016-03     NaN     NaN     NaN  \n",
       "2016-04     NaN     NaN     NaN  \n",
       "\n",
       "[37 rows x 37 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "revenue.reset_index().rename(columns={\n",
    "    'created_at_month_year': 'period',\n",
    "    'total': 'revenue'\n",
    "}).pivot(index='cohort', columns='period')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Total revenue over the upcoming periods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def cohort_revenue_generator(df):\n",
    "    results = []\n",
    "    \n",
    "    for cohort, data in df.groupby('cohort'):\n",
    "        cohort_size = data['customer_id'].nunique()\n",
    "        unique_periods = sorted(df['created_at_month_year'].unique())\n",
    "\n",
    "        for period in unique_periods:\n",
    "            revenue = data[data['created_at_month_year'] >= period].total.sum()\n",
    "            if period >= cohort and revenue >= 0:\n",
    "                results.append({'cohort': cohort,\n",
    "                               'period': period,\n",
    "                               'revenue': revenue})\n",
    "            \n",
    "    c = pd.DataFrame.from_records(results)\n",
    "    return c.pivot(index='period', columns='cohort')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <th>cohort</th>\n",
       "      <th>2013-04</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>2014-02</th>\n",
       "      <td>70553190.0</td>\n",
       "      <td>76889377.0</td>\n",
       "      <td>75150373.0</td>\n",
       "      <td>75912777.0</td>\n",
       "      <td>77832468.0</td>\n",
       "      <td>73394170.0</td>\n",
       "      <td>76232266.0</td>\n",
       "      <td>74780660.0</td>\n",
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       "      <td>19959468.0</td>\n",
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       "      <td>20161145.0</td>\n",
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       "      <td>18578224.0</td>\n",
       "      <td>21601313.0</td>\n",
       "      <td>187361476.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "             revenue                                                      \\\n",
       "cohort       2013-04      2013-05      2013-06      2013-07      2013-08   \n",
       "period                                                                     \n",
       "2013-04  528091201.0          NaN          NaN          NaN          NaN   \n",
       "2013-05  311191675.0  536370347.0          NaN          NaN          NaN   \n",
       "2013-06  285676781.0  304262425.0  494393172.0          NaN          NaN   \n",
       "2013-07  259449556.0  277322026.0  268188129.0  481365898.0          NaN   \n",
       "2013-08  233030044.0  248441099.0  240810757.0  247126811.0  451340765.0   \n",
       "2013-09  205791748.0  219865119.0  212911287.0  219224454.0  218926525.0   \n",
       "2013-10  178980093.0  191343381.0  186008195.0  191229025.0  192035387.0   \n",
       "2013-11  152027073.0  162467157.0  158364647.0  161970026.0  163626973.0   \n",
       "2013-12  125720175.0  134816977.0  131373515.0  133381025.0  135219428.0   \n",
       "2014-01   98602261.0  105219666.0  103367720.0  105057482.0  106055194.0   \n",
       "2014-02   70553190.0   76889377.0   75150373.0   75912777.0   77832468.0   \n",
       "2014-03   46638266.0   51224884.0   49225624.0   49913547.0   51173281.0   \n",
       "2014-04   19427875.0   21207372.0   20234417.0   20360186.0   20877614.0   \n",
       "\n",
       "                                                                          \\\n",
       "cohort       2013-09      2013-10      2013-11      2013-12      2014-01   \n",
       "period                                                                     \n",
       "2013-04          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-05          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-06          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-07          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-08          NaN          NaN          NaN          NaN          NaN   \n",
       "2013-09  406975229.0          NaN          NaN          NaN          NaN   \n",
       "2013-10  181173017.0  394951253.0          NaN          NaN          NaN   \n",
       "2013-11  154712856.0  160274961.0  355623353.0          NaN          NaN   \n",
       "2013-12  127982888.0  133446207.0  129993918.0  338833037.0          NaN   \n",
       "2014-01  100381551.0  105288081.0  103509858.0  105076534.0  310986455.0   \n",
       "2014-02   73394170.0   76232266.0   74780660.0   77581328.0   75948478.0   \n",
       "2014-03   48320699.0   50535412.0   49003398.0   52034914.0   50848134.0   \n",
       "2014-04   19959468.0   20889916.0   20161145.0   21404055.0   20888291.0   \n",
       "\n",
       "                                                \n",
       "cohort       2014-02      2014-03      2014-04  \n",
       "period                                          \n",
       "2013-04          NaN          NaN          NaN  \n",
       "2013-05          NaN          NaN          NaN  \n",
       "2013-06          NaN          NaN          NaN  \n",
       "2013-07          NaN          NaN          NaN  \n",
       "2013-08          NaN          NaN          NaN  \n",
       "2013-09          NaN          NaN          NaN  \n",
       "2013-10          NaN          NaN          NaN  \n",
       "2013-11          NaN          NaN          NaN  \n",
       "2013-12          NaN          NaN          NaN  \n",
       "2014-01          NaN          NaN          NaN  \n",
       "2014-02  251515540.0          NaN          NaN  \n",
       "2014-03   43451855.0  265138004.0          NaN  \n",
       "2014-04   18578224.0   21601313.0  187361476.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohort_revenue_generator(df_cohort)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Further investigation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>customer_id</th>\n",
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       "      <td>2016-04-28 21:15:27</td>\n",
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      "text/plain": [
       "   id  customer_id                mc_cid           created_at  \\\n",
       "0   1            1  aadf87qef-2013-04-01  2013-04-07 12:00:00   \n",
       "\n",
       "            updated_at  \n",
       "0  2016-04-28 21:15:27  "
      ]
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     "execution_count": 36,
     "metadata": {},
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   ],
   "source": [
    "orders = pd.read_csv('/Users/amir.ziai/Downloads/data/orders.csv')\n",
    "orders[orders.id == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   id  order_id  product_id  quantity           created_at  \\\n",
       "0   1         1           1         1  2015-04-02 12:00:00   \n",
       "\n",
       "            updated_at  \n",
       "0  2016-04-24 19:04:05  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
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   ],
   "source": [
    "items = pd.read_csv('/Users/amir.ziai/Downloads/data/order_items.csv')\n",
    "items[items.order_id == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Exotic Meats Crate</td>\n",
       "      <td>food</td>\n",
       "      <td>8999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sriracha Crate</td>\n",
       "      <td>food</td>\n",
       "      <td>4999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Zombie Annihilation Crate</td>\n",
       "      <td>outdoors</td>\n",
       "      <td>12999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Personalized Whiskey Crate</td>\n",
       "      <td>glassware</td>\n",
       "      <td>9999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>NFL Barware Crate</td>\n",
       "      <td>glassware</td>\n",
       "      <td>7999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Retro Gamer Crate</td>\n",
       "      <td>gaming</td>\n",
       "      <td>7999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Grill Master Crate</td>\n",
       "      <td>grilling</td>\n",
       "      <td>1099</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Personalized Growler Crate</td>\n",
       "      <td>glassware</td>\n",
       "      <td>10999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Hot Sauce Making Kit</td>\n",
       "      <td>food</td>\n",
       "      <td>5999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Saloon Nuts Crate</td>\n",
       "      <td>food</td>\n",
       "      <td>3999</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "      <td>2016-04-24 19:04:05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "   id                        name   category  price           created_at  \\\n",
       "0   1          Exotic Meats Crate       food   8999  2016-04-24 19:04:05   \n",
       "1   2              Sriracha Crate       food   4999  2016-04-24 19:04:05   \n",
       "2   3   Zombie Annihilation Crate   outdoors  12999  2016-04-24 19:04:05   \n",
       "3   4  Personalized Whiskey Crate  glassware   9999  2016-04-24 19:04:05   \n",
       "4   5           NFL Barware Crate  glassware   7999  2016-04-24 19:04:05   \n",
       "5   6           Retro Gamer Crate     gaming   7999  2016-04-24 19:04:05   \n",
       "6   7          Grill Master Crate   grilling   1099  2016-04-24 19:04:05   \n",
       "7   8  Personalized Growler Crate  glassware  10999  2016-04-24 19:04:05   \n",
       "8   9        Hot Sauce Making Kit       food   5999  2016-04-24 19:04:05   \n",
       "9  10           Saloon Nuts Crate       food   3999  2016-04-24 19:04:05   \n",
       "\n",
       "            updated_at  \n",
       "0  2016-04-24 19:04:05  \n",
       "1  2016-04-24 19:04:05  \n",
       "2  2016-04-24 19:04:05  \n",
       "3  2016-04-24 19:04:05  \n",
       "4  2016-04-24 19:04:05  \n",
       "5  2016-04-24 19:04:05  \n",
       "6  2016-04-24 19:04:05  \n",
       "7  2016-04-24 19:04:05  \n",
       "8  2016-04-24 19:04:05  \n",
       "9  2016-04-24 19:04:05  "
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       "   id  order_id  product_id  quantity           created_at  \\\n",
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       "1   2         2           6         1  2015-04-08 12:00:00   \n",
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       "   id  first_name    last_name                                email  \\\n",
       "0   1       Nigel       Larson                 stan_crona@paucek.co   \n",
       "1   2       Jessy        Lynch                  jonas_roob@davis.io   \n",
       "2   3        Ocie        Davis          laurel@maggioswaniawski.org   \n",
       "3   4      Lemuel        Hayes       simone.armstrong@hodkiewicz.io   \n",
       "4   5  Christophe          Orn                   elvis@dietrich.biz   \n",
       "5   6     Cathryn   Cartwright   thalia.fisher@langworthgibson.name   \n",
       "6   7       Abner       Little               bart.kuphal@hirthe.org   \n",
       "7   8        Jett     Cummings  rhoda_prosacco@cormierbergstrom.com   \n",
       "8   9      Keaton  Schamberger                     lilla@raynor.com   \n",
       "9  10         Iva   Morissette                     michale@olson.co   \n",
       "\n",
       "   orders_count           created_at           updated_at  \n",
       "0           NaN  2015-04-02 12:00:00  2016-04-24 19:04:05  \n",
       "1           NaN  2015-04-08 12:00:00  2016-04-24 19:04:05  \n",
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