Python: explore, test, automate
Python: explore, test, automate
Projects in experimentation, investment analysis, marketing automation, and time series.
Projects in experimentation, investment analysis, marketing automation, and time series.
Use pandas and the Sharpe ratio to compare investment returns relative to their variability.
Focus: Financial data analysis and risk-adjusted performance.
A guided A/B-test analysis of 90,189 Cookie Cats players, comparing gates at levels 30 and 40.
Methods: pandas, group comparisons, and 500 bootstrap resamples.
Finding: Seven-day retention was 19.02% at level 30 and 18.20% at level 40—a difference of 0.82 percentage points in favor of the earlier gate.
Decision: The notebook supports keeping the gate at level 30 when retention is the goal. Revenue and longer-term outcomes would need separate evaluation.
Learning project · Findings are based on the supplied experiment data.
Generate keyword combinations for a search advertising campaign with Python.
Focus: Repeatable workflows and marketing automation.
Manipulate and visualize Google Trends time series to compare how search interest changes over time.
Focus: Time series preparation and visualization.