Answered by : elisabeth-engering

import pandas as pd
# Drop all duplicates in the DataFrame
df = df.drop_duplicates()
# Drop all duplicates in a specific column of the DataFrame
df = df.drop_duplicates(subset = "column")
# Drop all duplicate pairs in DataFrame
df = df.drop_duplicates(subset = ["column", "column2"])
# Display DataFrame
print(df)

Source : https://www.datacamp.com/cheat-sheet/pandas-cheat-sheet-for-data-science-in-python | Last Update : Fri, 06 May 22

Answered by : clean-chimpanzee-x9xh2muu92w1

data = data.drop_duplicates(subset=['City'], keep='first')

Source : https://duckduckgo.com/?q=pandas+drop+duplicates+from+column&t=brave&ia=web | Last Update : Sun, 22 May 22

Answered by : happy-hawk

df = df.loc[:,~df.columns.duplicated()]

Source : https://stackoverflow.com/questions/14984119/python-pandas-remove-duplicate-columns | Last Update : Thu, 04 Jun 20

Answered by : jose-santiago-bordas

# Drop duplicate columns
df2 = df.T.drop_duplicates().T
print(df2)

Source : https://sparkbyexamples.com/pandas/pandas-remove-duplicate-columns-from-dataframe/ | Last Update : Fri, 22 Jul 22

Answered by : athul-mathew

df.drop_duplicates(keep=False, inplace=True)

Source : https://stackoverflow.com/questions/23667369/drop-all-duplicate-rows-across-multiple-columns-in-python-pandas | Last Update : Tue, 02 Aug 22

Answered by : or-berger

df.loc[:,~df.columns.duplicated()]

Source : | Last Update : Wed, 08 Jun 22

Answered by : perfect-penguin-a1nt3r09ybl6

df = df.loc[:,~df.columns.duplicated()].copy()
# https://stackoverflow.com/questions/14984119/python-pandas-remove-duplicate-columns

Source : | Last Update : Mon, 10 Oct 22

Answered by : lazy-lark-jenyffc7wa94

df.drop_duplicates()

Source : | Last Update : Mon, 30 May 22