How to generate a cohort using python?

• PYTHON

You can create a cohort to do analysis for your business repetitive customers and can make necessary decisions accordingly to improve customer retention for your business.

Example below will generate the cohort which can be seen in attached image. You need to keep the csv file in same folder with python file to avoid any error.

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

import warnings

import seaborn as sns

from operator import attrgetter

import matplotlib.colors as mcolors

df = pd.read_csv('vb_orders.csv',

                   dtype={'user_id': str,

                          'id': str},

                   parse_dates=['created_at'], 

                   infer_datetime_format=True)

n_orders = df.groupby(['user_id'])['id'].nunique()

mult_orders_perc = np.sum(n_orders > 1) / df['user_id'].nunique()

print(f'{100 * mult_orders_perc:.2f}% of customers ordered more than once.')

#Generate Plot/Chart

ax = sns.distplot(n_orders, kde=False, hist=True)

ax.set(title='Distribution of number of orders per customer',

       xlabel='# of orders', 

       ylabel='# of customers')

#Cohort Analysis

df = df[['user_id', 'id', 'created_at']].drop_duplicates()

df['order_month'] = df['created_at'].dt.to_period('M')

df['cohort'] = df.groupby('user_id')['created_at'] \

                 .transform('min') \

                 .dt.to_period('M')

df_cohort = df.groupby(['cohort', 'order_month']) \

              .agg(n_customers=('user_id', 'nunique')) \

              .reset_index(drop=False)

df_cohort['period_number'] = (df_cohort.order_month - df_cohort.cohort).apply(attrgetter('n'))

cohort_pivot = df_cohort.pivot_table(index = 'cohort',

                                     columns = 'period_number',

                                     values = 'n_customers')

cohort_size = cohort_pivot.iloc[:,0]

retention_matrix = cohort_pivot.divide(cohort_size, axis = 0)

with sns.axes_style("white"):

    fig, ax = plt.subplots(1, 2, figsize=(12, 8), sharey=True, gridspec_kw={'width_ratios': [1, 11]})

    # retention matrix

    sns.heatmap(retention_matrix, 

                mask=retention_matrix.isnull(), 

                annot=True, 

                fmt='.0%', 

                cmap='RdYlGn', 

                ax=ax[1])

    ax[1].set_title('Monthly Cohorts: User Retention', fontsize=16)

    ax[1].set(xlabel='# of periods',

              ylabel='')

    # cohort size

    cohort_size_df = pd.DataFrame(cohort_size).rename(columns={0: 'cohort_size'})

    white_cmap = mcolors.ListedColormap(['white'])

    sns.heatmap(cohort_size_df, 

                annot=True, 

                cbar=False, 

                fmt='g', 

                cmap=white_cmap, 

                ax=ax[0])

    fig.tight_layout()

    plt.show()

You need to install required dependencies to generate the cohort, sa below:

pip install pandas
pip install numpy
pip install matplotlib
pip install seaborn 

Let me know if you guys face any issue.