Pandas, Data Wrangling & Data Science
summary
Hands-on Pandas usage with notebooks at https://github.com/xsankar/cautious-octo-waffle shows exact steps: read CSVs, parse timestamps, use groupby to get per-session min/max then duration, use reset_index and merge to attach order totals, apply STR and DT namespaces to extract currency, hour and day features, backfill and impute NA, and a toy classifier (“all males survive”) to reveal label gaps. Uses Titanic, Northwind and Recsys-2015 33M clicks 1M buys datasets to demonstrate what succeeds and what data problems remain.
AI-written summary · about
chapters (7)
- 0:00pandas introduction
- 15:45Basic pandas operations
- 42:21Titanic dataset analysis
- 53:10Northwind orders analysis
- 1:07:21E-commerce recommendation system
- 1:26:03E-commerce feature extraction
- 1:31:04Q&A
