Da Duplicate Detection — Free Data Analytics Tutorial
Learn Da Duplicate Detection in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Da Duplicate Detection 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 Duplicate Detection in Data Analytics
Duplicates are exact or near-exact copies of rows. They waste storage, skew analysis, and violate database integrity.
Types: Exact duplicates (all columns same), Key duplicates (same ID/name but different other columns), Fuzzy duplicates (very similar but not identical).
Detection: df.duplicated() flags duplicate rows. Can check subsets of columns: df.duplicated(subset=['name', 'email'])
Removal: df.drop_duplicates(). Options: keep='first', keep='last', keep=False.
Da Duplicate Detection — Syntax
# Find duplicates: df.duplicated() # Find duplicate columns: df.duplicated(subset=['col1', 'col2']) # Remove: df.drop_duplicates() # Mark all duplicates: df.duplicated(keep=False)
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