drop column from dataframe

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

1# Let df be a dataframe
2# Let new_df be a dataframe after dropping a column
3
4new_df = df.drop(labels='column_name', axis=1)
5
6# Or if you don't want to change the name of the dataframe
7df = df.drop(labels='column_name', axis=1)
8
9# Or to remove several columns
10df = df.drop(['list_of_column_names'], axis=1)
11
12# axis=0 for 'rows' and axis=1 for columns

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

1df = pd.DataFrame(np.arange(12).reshape(3, 4),
2...                   columns=['A', 'B', 'C', 'D'])
3>>> df
4   A  B   C   D
50  0  1   2   3
61  4  5   6   7
72  8  9  10  11
8
9Drop columns
10>>> df.drop(['B', 'C'], axis=1)
11   A   D
120  0   3
131  4   7
142  8  11
15>>> df.drop(columns=['B', 'C'])
16   A   D
170  0   3
181  4   7
192  8  11

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

1var = dataframe.drop(['col', 'col'], axis=1)
2var.sum()