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Pivot table

A pivot table is a tabular summary that groups and aggregates source data across selected row and column dimensions.

How 2 Manning books explain it

Pandas Workout: 200 exercises to make you a stronger data analyst

A pivot table is a tabular summary that organizes values by categories in rows and columns and aggregates values at their intersections.

How it is used
Summarizes large data frames into grids for comparing categories across many row-column combinations.
How deep it goes
Explains row, column, and value choices through examples, then extends aggregation and multi-index variations.
Examples
Uses quarterly product sales, Olympic athlete and medal records, developer salaries, and wine scores.
What you can do after
Apply it via pandas `pivot_table` to compare grouped measures, counts, maxima, and means.

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The Well-Grounded Data Analyst

A pivot table is a summarized tabular view that groups and aggregates records across selected row and column dimensions.

How it is used
Reshapes grouped records into a comparison-ready table for plotting trends across years, distributors, or categorical variables.
How deep it goes
Demonstrates grouping, summing, unstacking, category cleanup, and filtering, but does not develop pivot-table internals.
Examples
Uses distributor market share by year and categorical-variable cross-tabulation as concrete analytical examples.
What you can do after
Apply it via pandas to aggregate records, reshape dimensions, expose category problems, and prepare comparisons for visualization.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.