Cohort Analysis in Python: Retention, Cohort Month, Activity Month (Pandas, Matplotlib, And Seaborn) скачать в хорошем качестве

Cohort Analysis in Python: Retention, Cohort Month, Activity Month (Pandas, Matplotlib, And Seaborn)

Learn how to build a complete cohort analysis in Python using Pandas. This video covers every step, including how to create cohort groups, calculate cohort months, extract invoice months, generate activity months, compute retention rates, and build a clean retention matrix for analysis. You will see how to use Python and Pandas to track user behavior over time, measure how cohorts perform across months, and analyze repeat activity using real data. The workflow fits tasks such as customer analytics, product performance tracking, revenue analysis, and user lifecycle evaluation. Dataset: https://drive.google.com/file/d/1B3q9... What the video covers Defining cohort analysis for data analytics Extracting the cohort month from the first transaction Extracting invoice month from date fields Calculating activity month and cohort index Building a retention table in Python Visualizing retention using Pandas and Seaborn Interpreting retention trends for business insights Keywords cohort analysis Python, python cohort tutorial, pandas cohort analysis, retention analysis Python, user cohorts Python, activity month Python, invoice month Python, cohort month explained, python data analysis, customer retention python, cohort table pandas, dataset cohort analysis