https://github.com/gakas14/cohort_customer_transaction

Cohort Analysis Using Python, performing time cohorts, working with pandas pivot, and creating a retention table along with visualizing it.
https://github.com/gakas14/cohort_customer_transaction

cohort-analysis cohort-data pandas seaborn-plots

Last synced: 3 months ago
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Cohort Analysis Using Python, performing time cohorts, working with pandas pivot, and creating a retention table along with visualizing it.

• Host: GitHub
• URL: https://github.com/gakas14/cohort_customer_transaction
• Owner: gakas14
• Created: 2021-12-07T06:08:51.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-12-07T06:14:20.000Z (over 3 years ago)
• Last Synced: 2024-12-31T12:34:39.089Z (5 months ago)
• Topics: cohort-analysis, cohort-data, pandas, seaborn-plots
• Language: Jupyter Notebook
• Homepage:
• Size: 2.93 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Cohort_Customer_Transaction

https://www.kaggle.com/archit9406/customer-transaction-dataset

1.Understand what is cohort and cohort analysis

2.Handling missing values

3.Month extraction from date

4.Assign cohort to each transaction

5.Assigning cohort Index to each transaction

6.Calculate the number of unique customers in each group

7.Create cohort table for retention rate

8.Visualize the cohort table using the heatmap

9.Interpret the retention rate