For this project, I manipulated user retenetion data using Python's Pandas and Seaborn libraries to calculate retention rates and user count for a mobile application. I first added a seniority column to the main DataFrame to represent the number of days since the user's initial start date. I then grouped the data by country, and lastly generated pivot tables and heatmaps to visually display each country's results. Additionally, I connected each country's DataFrame to a SQL database so that a future analysis could be further explored.
Analysis
- Jupyter Notebook file used to manipulate the data and generate an initial analysis.
- SQL queries used to explore further questions around the data.
Figures
- Heatmap images displaying user count and retention rates per country.
Data
- User retention data I used from a fictitious application.