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.
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
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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