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The second one does not work as expected when the index is not unique, so the user would need to reset_index () then set_index () back. The following tutorials explain how to perform other common functions in pandas: How to Drop Duplicate Rows in a Pandas DataFrame How to Drop Columns in Pandas How to Exclude Columns in Pandas - first: Drop duplicates except for the first occurrence. Pandas Drop Duplicate Rows | Delft Stack Each strategy name is repeated multiple times with the same USD value. How to Count Duplicates in Pandas DataFrame - Data to Fish Pandas drop_duplicates(): How to Drop Duplicated I'm trying to find a way in Python in which to drop rows where duplicates occur within specific columns, but only to drop those duplicates where they are not attributed to the latest date. df = df[(df. Count Duplicates in Pandas DataFrame keep: keep is to control how to consider duplicate value. How to Drop Duplicate Columns in Pandas (With Examples) iloc. Pandas Use boolean masking,groupby() method and assign() method: Duplicate rows can be deleted from a pandas data frame using drop_duplicates () function. Drop columns with missing data. Pandas drop_duplicates () Function Syntax. Created: January-16, 2021 . Replace values in column with a dictionary. import pandas as pd. The default value of keep is ‘first’. You can replace all values or selected values in a column of pandas DataFrame based on condition by using DataFrame.loc[], np.where() and DataFrame.mask() methods. For further detail on drop duplicates one can refer our page on Drop duplicate rows in pandas python drop_duplicates() …