PYTHON

Remove duplicates with pandas

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)

drop duplicates pandas first column

import pandas as pd 
  
# making data frame from csv file 
data = pd.read_csv("employees.csv") 
  
# sorting by first name 
data.sort_values("First Name", inplace = True) 
  
# dropping ALL duplicte values 
data.drop_duplicates(subset ="First Name",keep = False, inplace = True) 
  
# displaying data 
print(data)

remove duplicate row in df

df = df.drop_duplicates()

pandas drop duplicates from column

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

remove duplicate columns python dataframe

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

remove duplicates in dataframe by index python

# Remove by index
df = df[df.index.duplicated(keep='first')]

# Other methods to remove duplicates
import pandas as pd

df = df.drop_duplicates()

df = df.drop_duplicates(subset = "column")

df = df.drop_duplicates(subset = ["column", "column2"])

pd df drop duplicates

df.drop_duplicates(subset=['brand', 'style'], keep='last')

how to drop duplicate columns in pandas that dont have the same name?

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

df index drop duplicates

df3 = df3[~df3.index.duplicated(keep='first')]

drop duplicates data frame pandas python

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

drop duplicates columns pandas

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

pandas remove duplicates columns

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

# https://stackoverflow.com/questions/14984119/python-pandas-remove-duplicate-columns

pandas remove duplicates

df.drop_duplicates()