You can remove duplicate rows using DataFrame.apply() and lambda function to convert the DataFrame to lower case and then apply a lower string. Remove Duplicate Rows Using DataFrame.apply() and Lambda Function You can set 'keep=False' in the drop_duplicates() function to remove all the duplicate rows. To delete duplicate rows on the basis of multiple columns, specify all column names as a list. Delete Duplicate Rows based on Specific Columns For E.x, df.drop_duplicates(keep=False).Ħ. Remove All Duplicate Rows from Pandas DataFrame For instance, df.drop_duplicates(keep='last').ĥ. If you want to select all the duplicate rows and their last occurrence, you must pass a keep argument as "last". Drop Duplicate Rows and Keep the Last Row Our DataFrame contains column names Courses, Fee, Duration, and Discount. Now, let’s create a DataFrame with a few duplicate rows on columns.
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