so far in this we've been concerned with rearranging data filteringcleaningand other tranformations are another class of important operations removing duplicates duplicate rows may be found in dataframe for any number of reasons here is an examplein [ ]data dataframe({' '['one' ['two' ' '[ ]}in [ ]data out[ ] one one one two two two two the dataframe method duplicated returns boolean series indicating whether each row is duplicate or notin [ ]data duplicated(out[ ] false true false false true false true relatedlydrop_duplicates returns dataframe where the duplicated array is truein [ ]data drop_duplicates(out[ ] one one two two both of these methods by default consider all of the columnsalternatively you can specify any subset of them to detect duplicates suppose we had an additional column of values and wanted to filter duplicates only based on the ' columnin [ ]data[' 'range( in [ ]data drop_duplicates([' '] data wranglingcleantransformmergereshape www it-ebooks info