xxxxxxxxxx
df.drop_duplicates(['A','B'],keep= 'last')
xxxxxxxxxx
df = df.drop_duplicates(subset=['Column1', 'Column2'], keep='first')
xxxxxxxxxx
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)
xxxxxxxxxx
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)
xxxxxxxxxx
# If same dataset needs to be updated:
df.drop_duplicates(keep=False, inplace=True)
xxxxxxxxxx
# Drop duplicate columns
df2 = df.T.drop_duplicates().T
print(df2)
xxxxxxxxxx
#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'])