df.drop(['column_1', 'Column_2'], axis = 1, inplace = True)
df.drop(columns=['B', 'C'])
note: df is your dataframe df = df.drop('coloum_name',axis=1)
>>>df = pd.DataFrame(np.arange(12).reshape(3, 4), columns=['A', 'B', 'C', 'D']) >>>df A B C D 0 0 1 2 3 1 4 5 6 7 2 8 9 10 11 >>> df.drop(['B', 'C'], axis=1) A D 0 0 3 1 4 7 2 8 11 OR >>> df.drop(columns=['B', 'C']) A D 0 0 3 1 4 7 2 8 11
df = df.drop('column_name', 1)
df.drop(columns=['Unnamed: 0'])
#To delete the column without having to reassign df df.drop('column_name', axis=1, inplace=True)
#working with "text" syntax for the columns: df.drop(['column_nameA', 'column_nameB'], axis=1, inplace=True)
df = df.drop(df.columns[[0, 1, 3]], axis=1) # df.columns is zero-based pd.Index
>>> df.drop(['B', 'C'], axis=1) A D 0 0 3 1 4 7 2 8 11