# axis=1 tells Python that we want to apply function on columns instead of rows

# To delete the column permanently from original dataframe df, we can use the option inplace=True

df.drop(['A', 'B', 'C'], axis=1, inplace=True)

df.drop(['column_1', 'Column_2'], axis = 1, inplace = True) 

#To delete the column without having to reassign df

df.drop('column_name', axis=1, inplace=True) 

df.drop('column_name', axis=1, inplace=True)

#no need to reasign df

#axis 1 is columns, 0 is rows

note: df is your dataframe

​

df = df.drop('coloum_name',axis=1)

>>> df.drop(columns=['B', 'C'])

   A   D

0  0   3

1  4   7

2  8  11

​

df = df.drop('column_name', 1)

df = df.drop(['B', 'C'], axis=1)

df.drop(columns=['Unnamed: 0'])

df.drop(['Col_1', 'Col_2'], axis = 1) # to drop full colum more general way can visulize easily

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df.drop(['Col_1', 'Col_2'], axis = 1, inplace = True) # advanced : to generate df without making copies inside memory