Da Pandas Merge Types — Free Data Analytics Tutorial
Learn Da Pandas Merge Types in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Da Pandas 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 Pandas Merge Types in Data Analytics
Merging combines two DataFrames based on a common column (like SQL JOIN). Different merge types preserve different rows.
Inner join: Only rows that match in BOTH tables. Use when you want complete records only.
Left join: All rows from left table + matching rows from right. Use when left table is primary.
Right join: All rows from right table + matching rows from left.
Outer join: All rows from BOTH tables (with NaN where no match). Use when you need everything.
Da Pandas Merge Types — Syntax
# Merge types: # df.merge(other, on='key', how='inner') # only matches # df.merge(other, on='key', how='left') # all left rows # df.merge(other, on='key', how='right') # all right rows # df.merge(other, on='key', how='outer') # all rows, both tables
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