ValueError: 'None' occurs multiple times; use a level number for pivot_table

Programming
,
1

I have a pandas dataframe:

print(df.head())

     Row ID        Order ID  Order Date  ... Quantity Discount    Profit
0       1  CA-2013-152156  09/11/2013  ...        2     0.00   41.9136
1       2  CA-2013-152156  09/11/2013  ...        3     0.00  219.5820
2       3  CA-2013-138688  13/06/2013  ...        2     0.00    6.8714
3       4  US-2012-108966  11/10/2012  ...        5     0.45 -383.0310
4       5  US-2012-108966  11/10/2012  ...        2     0.20    2.5164

When I execute the following command for a pivot table:

ans = pd.pivot_table(data=df, index=['Segment'], columns=['Region'], values=['Sales'], aggfunc={'Sales':['sum', 'mean']}, margins=True, dropna=False)

I get the following error:

Traceback (most recent call last):

  File "<stdin>", line 1, in <module>

  File "/usr/local/lib/python3.6/dist-packages/pandas/core/reshape/pivot.py", line 162, in pivot_table

   fill_value=fill_value,

  File "/usr/local/lib/python3.6/dist-packages/pandas/core/reshape/pivot.py", line 208, in _add_margins

   if margins_name in table.columns.get_level_values(level):

  File "/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/multi.py", line 1598, in 
get_level_values

   level = self._get_level_number(level)

  File "/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/multi.py", line 1292, in 
_get_level_number

   "The name %s occurs multiple times, use a " "level number" % level

ValueError: The name None occurs multiple times, use a level number

I’m getting a ValueError when creating a pivot table from my pandas dataframe. The error message is:

ValueError: The name None occurs multiple times, use a level number
2

The error occurs because the pivot table has multiple levels with no names. To fix this, you can manually assign names to the levels using the names parameter of the MultiIndex object. Here’s the corrected code:

ans = pd.pivot_table(data=df, index=['Segment'], columns=['Region'], values=['Sales'], 
                     aggfunc={'Sales':['sum', 'mean']}, margins=True, dropna=False)
ans.columns = ['_'.join(col).strip() for col in ans.columns.values]
ans = ans.rename_axis(index={'All': 'Total'})