Melt, Stack, and Unstack Operations — Free Data Analytics Tutorial

Learn Melt, Stack, and Unstack Operations in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.

Melt, Stack, and Unstack Operations — Free Data Analytics Tutorial

Learn Melt, Stack, and Unstack Operations 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 Melt, Stack, and Unstack Operations in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syll…

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Melt, Stack, and Unstack Operations in Data Analytics

Melt converts wide data to long format: one column becomes index, rest become (variable, value) pairs.

Stack converts columns to rows (wide → long); unstack converts index to columns (long → wide).

Useful for preparing data for analysis or reshaping for visualization.

Melt with id_vars specifies which columns to keep as identifiers.

Unstack with level controls which index level to pivot.

Melt, Stack, and Unstack Operations — Syntax

# Melt: df.melt(id_vars=['id'], value_vars=['col1', 'col2'], var_name='variable', value_name='value')
# Stack: df.stack() converts columns to index level
# Unstack: df.unstack() converts index to columns

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