Da Pandas Melt Stack — Free Data Analytics Tutorial
Learn Da Pandas Melt Stack in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Da Pandas Melt Stack 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 Melt Stack in Data Analytics
Data comes in two shapes: Wide (many columns, few rows) and Long (few columns, many rows). Both are valid; choose based on your analysis.
Wide format: Subjects as columns (Maths, Science, English columns). Long format: One column for Subject, one for Score.
melt() converts wide → long. stack() also converts wide → long but is index-based. unstack() does the opposite (long → wide).
When to use: Long format is better for groupBy and analysis. Wide format is better for comparison and pivot tables.
Da Pandas Melt Stack — Syntax
# Melt: wide → long # df_long = df.melt(id_vars=['student'], # value_vars=['Maths', 'Science'], # var_name='subject', # value_name='marks') # Unstack: long → wide (for time series or MultiIndex) # df_wide = df_long.pivot(index='student', #
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