PYTHON

python: remove duplicate in a specific column

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

remove duplicates based on two columns in dataframe

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

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)

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()]

pd.merge remove duplicate columns

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)

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

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

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