find duplicated rows with respect to multiple columns pandas
df = df[df.duplicated(subset=['val1','val2'], keep=False)]
print (df)
id val1 val2
0 1 1.1 2.2
1 1 1.1 2.2
3 3 8.8 6.2
4 4 1.1 2.2
5 5 8.8 6.2
find duplicated rows with respect to multiple columns pandas
df = df[df.duplicated(subset=['val1','val2'], keep=False)]
print (df)
id val1 val2
0 1 1.1 2.2
1 1 1.1 2.2
3 3 8.8 6.2
4 4 1.1 2.2
5 5 8.8 6.2
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'])
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