![]() uniquedogs vetvisits.dropduplicates (subset 'name', 'breed') print (uniquedogs) date name breed weightkg 0. ![]() Since Max and Max are different breeds, we can drop the rows with pairs of names and breeds listed earlier in the dataset. Examples Consider dataset containing ramen rating. In that case, we need to consider more than just name when dropping duplicates. In this dataframe, that applied to row 0 and row 1. DataFrame.dropduplicates Remove duplicate values from DataFrame. Remember: by default, Pandas drop duplicates looks for rows of data where all of the values are the same. Method 1: Remove Duplicates in One Column and Keep Row with Max df.sortvalues('var2', ascendingFalse).dropduplicates('var1').sortindex() Method 2: Remove Duplicates in Multiple Columns and Keep Row with Max df.sortvalues('var3', ascendingFalse).dropduplicates( 'var1', 'var2'). ![]() Series.dropduplicates Remove duplicate values from Series. If order of values in columns is not important convert each column to set for remove duplicates, then to Series and join together by concat: df1 = pd.concat(, axis=1)Ħ54 ms ± 3.16 ms per loop (mean ± std. Series.duplicated Equivalent method on Series.
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