Da Merge Types — Free Data Analytics Tutorial
Learn Da Merge Types in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Da Merge Types 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 Merge Types in Data Analytics
Inner merge keeps only matching rows from both DataFrames.
Outer (full) merge keeps all rows from both DataFrames (fills missing with NaN).
Left merge keeps all rows from left DataFrame; matches right rows where available.
Right merge keeps all rows from right DataFrame; matches left rows where available.
Merge key can be column name, index, or a list of columns.
Da Merge Types — Syntax
# Basic merge: pd.merge(df1, df2, on='common_column', how='inner') # Merge on different column names: pd.merge(df1, df2, left_on='col1', right_on='col2')
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