When to reach for them.
WHAT THEY PROVIDE
Tabular data handling, with operations for filtering, grouping, joining and summarising.
WHEN THEY SUIT
Analysis on data larger than a spreadsheet handles Repeated analysis you want reproducible Combining several sources Anything you will run again
WHEN THEY DO NOT
A one-off task a spreadsheet does in minutes Very simple processing, where plain Python is clearer
WHAT THEY REPLACE
Manual loops over rows, which are slow and error-prone.
WHAT TO LEARN FIRST
Loading data Filtering rows and selecting columns Grouping and summarising Joining sources Writing results out
THAT COVERS MOST BUSINESS ANALYSIS
WHAT TO BE CAREFUL WITH
Memory, on large datasets Assuming types were inferred correctly Operations that silently produce copies
WHAT TO VALIDATE
Row counts after any join or filter.
WHAT TO PREFER
Clear steps over compact expressions nobody can read later.
WHAT TO DOCUMENT
What each step does and why.
