drop multiple columns pandas

yourdf.drop(['columnheading1', 'columnheading2'], axis=1, inplace=True)

# Let df be a dataframe
# Let new_df be a dataframe after dropping a column

new_df = df.drop(labels='column_name', axis=1)

# Or if you don't want to change the name of the dataframe
df = df.drop(labels='column_name', axis=1)

# Or to remove several columns
df = df.drop(['list_of_column_names'], axis=1)

# axis=0 for 'rows' and axis=1 for columns

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