https://pandas.pydata.org › ... › stable › reference › api › pandas.DataFrame.drop_duplicates.html

DataFrame.drop_duplicates(subset=None, *, keep='first', inplace=False, ignore_index=False) [source] #. Return DataFrame with duplicate rows removed. Considering certain columns is optional. Indexes, including time indexes are ignored. Parameters:

https://stackoverflow.com › questions › 50885093

Removing duplicates from Pandas rows, replace them with NaNs, shift NaNs to end of rows

https://www.statology.org › pandas-drop-duplicates

The easiest way to drop duplicate rows in a pandas DataFrame is by using the drop_duplicates() function, which uses the following syntax: df.drop_duplicates(subset=None, keep=’first’, inplace=False)

https://note.nkmk.me › en › python-pandas-duplicated-drop-duplicates

In pandas, the duplicated() method is used to find, extract, and count duplicate rows in a DataFrame, while drop_duplicates() is used to remove these duplicates. This article also briefly explains the groupby() method, which aggregates values based on duplicates.

https://pandas.pydata.org › ... › 1.2.4 › reference › api › pandas.DataFrame.drop_duplicates.html

pandas.DataFrame.drop_duplicates. ¶. DataFrame.drop_duplicates(subset=None, keep='first', inplace=False, ignore_index=False) [source] ¶. Return DataFrame with duplicate rows removed. Considering certain columns is optional. Indexes, including time indexes are ignored. Parameters.

https://www.slingacademy.com › article › pandas-removing-duplicate-rows-from-a-dataframe

Removing Duplicate Rows. Once you’ve identified duplicates, removing them is straightforward with the drop_duplicates() method. By default, this method keeps the first occurrence of the duplicate row and removes subsequent duplicates.

https://www.programiz.com › python-programming › pandas › methods › drop_duplicates

The drop_duplicates() method in Pandas returns a new DataFrame with duplicate rows removed. Example1: Remove Duplicate Rows Across all Columns. import pandas as pd. # create a sample DataFrame with duplicate data . data = { 'Student_ID': [1, 2, 3, 2, 4, 1, 5], 'Name': ['Alice', 'Bob', 'Charlie', 'Bob', 'David', 'Alice', 'Eve'],

https://www.w3schools.com › python › pandas › ref_df_drop_duplicates.asp

The drop_duplicates() method removes duplicate rows. Use the subset parameter if only some specified columns should be considered when looking for duplicates.