"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# code for loading the format for the notebook\n",
"import os\n",
"\n",
"# path : store the current path to convert back to it later\n",
"path = os.getcwd()\n",
"os.chdir(os.path.join('..', '..', 'notebook_format'))\n",
"\n",
"from formats import load_style\n",
"load_style(plot_style = False)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Ethen 2018-09-17 18:37:57 \n",
"\n",
"CPython 3.6.4\n",
"IPython 6.4.0\n",
"\n",
"numpy 1.14.1\n",
"pandas 0.23.0\n",
"seaborn 0.8.1\n",
"matplotlib 2.2.2\n"
]
}
],
"source": [
"os.chdir(path)\n",
"# 1. magic for inline plot\n",
"# 2. magic to print version\n",
"# 3. magic so that the notebook will reload external python modules\n",
"# 4. magic to enable retina (high resolution) plots\n",
"# https://gist.github.com/minrk/3301035\n",
"%matplotlib inline\n",
"%load_ext watermark\n",
"%load_ext autoreload\n",
"%autoreload 2\n",
"%config InlineBackend.figure_format = 'retina'\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"from datetime import datetime\n",
"\n",
"%watermark -a 'Ethen' -d -t -v -p numpy,pandas,seaborn,matplotlib"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Cohort Analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"What is Cohort Analysis? and why is it valuable? To begin with, a cohort is a group of users who share something in common, be it their sign-up date, first purchase month, birth date, acquisition channel, etc. Cohort analysis is the method by which these groups are tracked over time, helping you spot trends, understand repeat behaviors (purchases, engagement, amount spent, etc.) and monitor your customer and revenue retention.\n",
"\n",
"It's common for cohorts to be created based on a customer's first usage of the platform, where \"usage\" is dependent on your business's key metrics. For Uber or Lyft, usage would be booking a trip through one of their apps. For GrubHub, it's ordering some food. For AirBnB, it's booking a stay. With these companies, a purchase is at their core, be it taking a trip or ordering dinner — their revenues are tied to their users' purchase behavior. In others, a purchase is not central to the business model and the business is more interested in \"engagement\" with the platform. Facebook and Twitter are examples of this - are you visiting their sites every day? Are you performing some action on them - maybe a \"like\" on Facebook or a \"favorite\" on a tweet? Thus when building up a cohort analysis, it's important to consider the relationship between the event or interaction you're tracking and its relationship to your business model."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example of Monthly Cohort"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Imagine we have the following dataset that has the standard purchase data with IDs for the order and user, order data and purchase amount. To create our monthly cohort, we'll first have to:\n",
"\n",
"- Convert our date to a monthly-time basis.\n",
"- Determine the user's cohort group based on their first order, which is the year and month in which the user's first purchase occurred."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
"
],
"text/plain": [
" UserId OrderId OrderDate TotalCharges CommonId PupId PickupDate \\\n",
"0 47 262 2009-01-11 50.67 TRQKD 2 1/12/09 \n",
"1 47 278 2009-01-20 26.60 4HH2S 3 1/20/09 \n",
"2 47 294 2009-02-03 38.71 3TRDC 2 2/4/09 \n",
"3 47 301 2009-02-06 53.38 NGAZJ 2 2/9/09 \n",
"4 47 302 2009-02-06 14.28 FFYHD 2 2/9/09 \n",
"\n",
" OrderPeriod CohortGroup \n",
"0 2009-01 2009-01 \n",
"1 2009-01 2009-01 \n",
"2 2009-02 2009-01 \n",
"3 2009-02 2009-01 \n",
"4 2009-02 2009-01 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# convert each user id into their cohort group\n",
"df = df.set_index('UserId')\n",
"df['CohortGroup'] = (df.\n",
" groupby(level = 0)['OrderDate'].min().\n",
" apply(lambda x: x.strftime('%Y-%m')))\n",
"df = df.reset_index()\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since we're looking at monthly cohorts, we need to aggregate users, orders, and amount spent by the CohortGroup within each month (OrderPeriod). After that, we wish to look at how each cohort has behaved in the months following their first purchase, so we'll need to index each cohort with respect to their first purchase month. For example, CohortPeriod = 1 will be the cohort's first month, CohortPeriod = 2 is their second, and so on. This allows us to compare cohorts across various stages of their lifetime."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
"
],
"text/plain": [
" TotalUsers TotalOrders TotalCharges CohortPeriod\n",
"CohortGroup OrderPeriod \n",
"2009-01 2009-01 22 30 1850.26 1\n",
" 2009-02 8 25 1351.07 2\n",
" 2009-03 10 26 1357.36 3\n",
" 2009-04 9 28 1604.50 4\n",
" 2009-05 10 26 1575.63 5"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def cohort_period(df):\n",
" \"\"\"\n",
" Creates a `CohortPeriod` column, \n",
" which is the Nth period based on the user's first purchase.\n",
" \"\"\"\n",
" df['CohortPeriod'] = np.arange(len(df)) + 1\n",
" return df\n",
"\n",
"\n",
"cohorts = cohorts.groupby(level = 'CohortGroup').apply(cohort_period)\n",
"cohorts.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We're now half way done, before we proceed on with the process, we will do some sanity checking to make sure that we did everything right by performing some simple testing. We'll test data points from the original DataFrame with their corresponding values in the new cohorts DataFrame to make sure all our data transformations worked as expected. As long as none of these raise an exception, we're good."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# unit test code chunk\n",
"mask = (df['CohortGroup'] == '2009-01') & (df['OrderPeriod'] == '2009-01')\n",
"x = df[mask]\n",
"y = cohorts.loc[('2009-01', '2009-01')]\n",
"\n",
"assert np.allclose(x['UserId'].nunique(), y['TotalUsers'])\n",
"assert np.allclose(x['TotalCharges'].sum(), y['TotalCharges'])\n",
"assert np.allclose(x['OrderId'].nunique(), y['TotalOrders'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To calculate the user retention by cohort group, We want to look at the percentage change of each `CohortGroup` over time -- not the absolute change. To do this, we'll first need to create a pandas Series containing each `CohortGroup` and its size."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
\n",
"
OrderPeriod
\n",
"
TotalUsers
\n",
"
TotalOrders
\n",
"
TotalCharges
\n",
"
\n",
"
\n",
"
CohortGroup
\n",
"
CohortPeriod
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"
\n",
"
2009-01
\n",
"
1
\n",
"
2009-01
\n",
"
22
\n",
"
30
\n",
"
1850.26
\n",
"
\n",
"
\n",
"
2
\n",
"
2009-02
\n",
"
8
\n",
"
25
\n",
"
1351.07
\n",
"
\n",
"
\n",
"
3
\n",
"
2009-03
\n",
"
10
\n",
"
26
\n",
"
1357.36
\n",
"
\n",
"
\n",
"
4
\n",
"
2009-04
\n",
"
9
\n",
"
28
\n",
"
1604.50
\n",
"
\n",
"
\n",
"
5
\n",
"
2009-05
\n",
"
10
\n",
"
26
\n",
"
1575.63
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" OrderPeriod TotalUsers TotalOrders TotalCharges\n",
"CohortGroup CohortPeriod \n",
"2009-01 1 2009-01 22 30 1850.26\n",
" 2 2009-02 8 25 1351.07\n",
" 3 2009-03 10 26 1357.36\n",
" 4 2009-04 9 28 1604.50\n",
" 5 2009-05 10 26 1575.63"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# convert the CohortPeriod as indices instead of OrderPeriod\n",
"cohorts = cohorts.reset_index()\n",
"cohorts = cohorts.set_index(['CohortGroup', 'CohortPeriod'])\n",
"cohorts.head()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"CohortGroup\n",
"2009-01 22\n",
"2009-02 15\n",
"2009-03 13\n",
"2009-04 39\n",
"2009-05 50\n",
"Name: TotalUsers, dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# create a Series holding the total size of each CohortGroup\n",
"cohorts_size = cohorts['TotalUsers'].groupby(level = 'CohortGroup').first()\n",
"cohorts_size.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, we'll need to divide the `TotalUsers` values in cohorts by `cohort_size`. Since DataFrame operations are performed based on the indices of the objects, we'll use `unstack` on our cohorts DataFrame to create a matrix where each column represents a `CohortGroup` and each row is the `CohortPeriod` corresponding to that group."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Stack/Unstack"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In case you're not familiar with what `unstack` and stack does:\n",
"\n",
"Stacking a DataFrame means moving (also rotating or pivoting) the innermost column index to become the innermost row index. The inverse operation is called unstacking. It means moving the innermost row index to become the innermost column index. The following diagram depicts the operations:\n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
CohortGroup
\n",
"
2009-01
\n",
"
2009-02
\n",
"
2009-03
\n",
"
2009-04
\n",
"
2009-05
\n",
"
2009-06
\n",
"
2009-07
\n",
"
2009-08
\n",
"
2009-09
\n",
"
2009-10
\n",
"
2009-11
\n",
"
2009-12
\n",
"
2010-01
\n",
"
2010-02
\n",
"
2010-03
\n",
"
\n",
"
\n",
"
CohortPeriod
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"
\n",
"
1
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.00
\n",
"
1.00000
\n",
"
1.00
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.000000
\n",
"
1.00
\n",
"
1.0
\n",
"
\n",
"
\n",
"
2
\n",
"
0.363636
\n",
"
0.200000
\n",
"
0.307692
\n",
"
0.333333
\n",
"
0.26
\n",
"
0.46875
\n",
"
0.46
\n",
"
0.354839
\n",
"
0.405405
\n",
"
0.314815
\n",
"
0.246154
\n",
"
0.261538
\n",
"
0.526316
\n",
"
0.19
\n",
"
NaN
\n",
"
\n",
"
\n",
"
3
\n",
"
0.454545
\n",
"
0.333333
\n",
"
0.384615
\n",
"
0.256410
\n",
"
0.24
\n",
"
0.28125
\n",
"
0.26
\n",
"
0.290323
\n",
"
0.378378
\n",
"
0.222222
\n",
"
0.200000
\n",
"
0.276923
\n",
"
0.273684
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
"
\n",
"
4
\n",
"
0.409091
\n",
"
0.066667
\n",
"
0.307692
\n",
"
0.333333
\n",
"
0.10
\n",
"
0.18750
\n",
"
0.20
\n",
"
0.225806
\n",
"
0.216216
\n",
"
0.240741
\n",
"
0.223077
\n",
"
0.107692
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
"
\n",
"
5
\n",
"
0.454545
\n",
"
0.266667
\n",
"
0.076923
\n",
"
0.153846
\n",
"
0.08
\n",
"
0.21875
\n",
"
0.22
\n",
"
0.193548
\n",
"
0.351351
\n",
"
0.240741
\n",
"
0.100000
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
"CohortGroup 2009-01 2009-02 2009-03 2009-04 2009-05 2009-06 \\\n",
"CohortPeriod \n",
"1 1.000000 1.000000 1.000000 1.000000 1.00 1.00000 \n",
"2 0.363636 0.200000 0.307692 0.333333 0.26 0.46875 \n",
"3 0.454545 0.333333 0.384615 0.256410 0.24 0.28125 \n",
"4 0.409091 0.066667 0.307692 0.333333 0.10 0.18750 \n",
"5 0.454545 0.266667 0.076923 0.153846 0.08 0.21875 \n",
"\n",
"CohortGroup 2009-07 2009-08 2009-09 2009-10 2009-11 2009-12 \\\n",
"CohortPeriod \n",
"1 1.00 1.000000 1.000000 1.000000 1.000000 1.000000 \n",
"2 0.46 0.354839 0.405405 0.314815 0.246154 0.261538 \n",
"3 0.26 0.290323 0.378378 0.222222 0.200000 0.276923 \n",
"4 0.20 0.225806 0.216216 0.240741 0.223077 0.107692 \n",
"5 0.22 0.193548 0.351351 0.240741 0.100000 NaN \n",
"\n",
"CohortGroup 2010-01 2010-02 2010-03 \n",
"CohortPeriod \n",
"1 1.000000 1.00 1.0 \n",
"2 0.526316 0.19 NaN \n",
"3 0.273684 NaN NaN \n",
"4 NaN NaN NaN \n",
"5 NaN NaN NaN "
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# applying it \n",
"user_retention = (cohorts['TotalUsers'].\n",
" unstack('CohortGroup').\n",
" divide(cohorts_size, axis = 1))\n",
"user_retention.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The resulting DataFrame, `user_retention`, contains the percentage of users from the cohort purchasing within the given period. For instance, 38.4% of users in the 2009-03 cohort purchased again in month 3 (which would be May 2009).\n",
"\n",
"Finally, we can plot the cohorts over time in an effort to spot behavioral differences or similarities. Two common cohort charts are line graphs and heatmaps, both of which are shown below."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"