Pandas Operations

DataFrames become useful once they are summarized, grouped, joined, reshaped, and transformed. This lesson walks through the operations that show up in almost every pandas script: aggregations (sum, mean, agg), groupby for split-apply-combine, merge and concat for joining tables, pivot tables for reshaping, the apply/map family for custom transforms, the .str and .dt accessors for column-wide string and datetime operations, and rolling windows for time series. It closes with where pandas slows down and how to keep things vectorized.