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)

python: remove duplicate in a specific column

df = df.drop_duplicates(subset=['Column1', 'Column2'], keep='first')

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()

remove duplicates based on two columns in dataframe

df.drop_duplicates(['A','B'],keep= 'last')

how to duplicate columns pandas

df = pd.concat([df, df['column']], axis=1)

dataframe delete duplicate rows with same column value

df = df.drop_duplicates(subset=['Column1', 'Column2'], keep='first')

# Exemple
import pandas as pd
df = pd.DataFrame({"A":["foo", "foo", "foo", "bar"], "B":[0,1,1,1], "C":["A","A","B","A"]})
df.drop_duplicates(subset=['A', 'C'], keep=False)

pandas drop duplicates from column

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

dataframe delete duplicate rows with same column value

df = df.drop_duplicates(subset=['Column1', 'Column2'], keep='first')

# Exemple
import pandas as pd
df = pd.DataFrame({"A":["foo", "foo", "foo", "bar"], "B":[0,1,1,1], "C":["A","A","B","A"]})
df.drop_duplicates(subset=['A', 'C'], keep=False)

remove duplicate columns python dataframe

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

pandas merge two dataframes remove duplicates

concat = pd.merge(data_1, data_2, how='inner')

python pandas remove duplicates and make that change to same dataframe

# If same dataset needs to be updated:

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

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)

drop duplicates data frame pandas python

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

pd.merge duplicate columns remove

#Create test data
df1 = pd.DataFrame(np.random.randint(100,size=(1000, 3)),columns=['A','B','C'])
df2 = pd.DataFrame(np.random.randint(100,size=(1000, 3)),columns=['B','C','D'])

pd.merge(df1, df2, how='inner', left_on=['B','C'], right_on=['B','C'])

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()