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Da Pandas Pivot Tables — Free Data Analytics Tutorial

Learn Da Pandas Pivot Tables in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.

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TL;DR: Learn Da Pandas Pivot Tables in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.

Written & reviewed by the Syllab.in Academic Team (CBSE/NCERT subject experts) · Updated Jul 14, 2026

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Da Pandas Pivot Tables in Data Analytics

A pivot table reorganises data by taking values from columns and placing them into new rows/columns. It automatically aggregates data (sum, mean, count) at intersections.

Use case: You have transaction data with Date, Category, Amount. Pivot table gives you a table with Dates as rows, Categories as columns, and Amount (summed) in cells.

Pandas: df.pivot_table(values='Amount', index='Date', columns='Category', aggfunc='sum'). This is equivalent to manual GroupBy but more intuitive.

Advantages over GroupBy: Visualization, handling of missing values, multiple aggregations simultaneously (sum AND count in one table).

Da Pandas Pivot Tables — Syntax

# Pivot table syntax:
# df.pivot_table(values='sales',
#                 index='city',      # row labels
#                 columns='product', # column labels
#                 aggfunc='sum')     # aggregation function

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