How To Drop Columns In Pandas Code Example

Snippet 1

  # 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 

Snippet 2

  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

Drop columns
>>> df.drop(['B', 'C'], axis=1)
   A   D
0  0   3
1  4   7
2  8  11
>>> df.drop(columns=['B', 'C'])
   A   D
0  0   3
1  4   7
2  8  11 

Snippet 3

  DataFrame.drop(self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise')[source] 

Snippet 4

  >>>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 

Snippet 5

  df = df.drop(df.columns[[0, 1, 3]], axis=1)  # df.columns is zero-based pd.Index  

Snippet 6

  >>> df.drop(['B', 'C'], axis=1)
   A   D
0  0   3
1  4   7
2  8  11
 

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