How do I prevent 'NotImplementedError' and 'TypeError' when using numeric aggregate functions in Pandas pivot tables with string columns?

I have tried severally to perform some numeric aggregation methods on numeric data with pandas. However, I have received a NotImplementedError, which then throws a TypeError, whenever I do so. I hypothesize that pandas is refusing to ignore the string columns when performing said numerical tasks. How do I prevent this?

Given a pivot table named matrix_data, and with pandas imported as pan:

  Account Number  Company      Contact Account Manager     Product  Licenses   
0         2123398   Google  Larry Pager    Edward Thorp   Analytics       150  
1         2123398   Google  Larry Pager    Edward Thorp  Prediction       150   
2         2123398   Google  Larry Pager    Edward Thorp    Tracking       300   
3         2192650     BOBO  Larry Pager    Edward Thorp   Analytics       150   
4          420496     IKEA    Elon Tusk    Edward Thorp   Analytics       300   

   Sale Price        Status  
0     2100000     Presented  
1      700000     Presented  
2      350000  Under Review  
3     2450000          Lost  
4     4550000           Won

Trying to aggregate all numerical values by company:

pan.pivot_table(matrix_data, index = "Company", aggfunc="mean");

throws an exception like so:

NotImplementedError                       Traceback (most recent call last)
File ~\AppData\Roaming\Python\Python311\site-packages\pandas\core\groupby\groupby.py:1490, in GroupBy._cython_agg_general..array_func(values)
   1489 try:
-> 1490     result = self.grouper._cython_operation(
   1491         "aggregate",
   1492         values,
   1493         how,
   1494         axis=data.ndim - 1,
   1495         min_count=min_count,
   1496         **kwargs,
   1497     )
   1498 except NotImplementedError:
   1499     # generally if we have numeric_only=False
   1500     # and non-applicable functions
...
   1698             # e.g. "foo"
-> 1699             raise TypeError(f"Could not convert {x} to numeric") from err
   1700 return x

TypeError: Could not convert Larry PagerLarry PagerLarry Pager to numeric

dataframe.groupby(["col_name1"]).mean() will throw an identical error

I'm on windows 10, python 3.11, with pandas version 2.0.1. All this was performed on Jupyter Notebook with VScode

Solution

This has been deprecated in Pandas 2.0. This is the warning pandas 1.5.3 gives:

FutureWarning: pivot_table dropped a column because it failed to aggregate. This behavior is deprecated and will raise in a future version of pandas. Select only the columns that can be aggregated.

You now have to select the specific columns you want to aggregate.

cols = ['Licenses', 'Sale Price']
pd.pivot_table(matrix_data, values=cols, index="Company", aggfunc="mean")