Solution for SpecificationError: nested renamer is not supported while agg() along with groupby()

change

temp['total'] = pd.DataFrame(project_data.groupby(col1)[col2].agg({'total':'count'})).reset_index()['total']temp['Avg'] = pd.DataFrame(project_data.groupby(col1)[col2].agg({'Avg':'mean'})).reset_index()['Avg']

to

temp['total'] = pd.DataFrame(project_data.groupby(col1)[col2].agg(total='count')).reset_index()['total']temp['Avg'] = pd.DataFrame(project_data.groupby(col1)[col2].agg(Avg='mean')).reset_index()['Avg']

reason: in new pandas version named aggregation is the recommended replacement for the deprecated “dict-of-dicts” approach to naming the output of column-specific aggregations (Deprecate groupby.agg() with a dictionary when renaming).

source: https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.25.0.html

This error also happens if a column specified in the aggregation function dict does not exist in the dataframe:

In [190]: group = pd.DataFrame([[1, 2]], columns=['A', 'B']).groupby('A')In [195]: group.agg({'B': 'mean'})Out[195]:    BA   1  2In [196]: group.agg({'B': 'mean', 'non-existing-column': 'mean'})...SpecificationError: nested renamer is not supported

Do you get the same error if you change

temp['total'] = pd.DataFrame(project_data.groupby(col1)[col2].agg({'total':'count'})).reset_index()['total']

to

temp['total'] = project_data.groupby(col1)[col2].agg(total=('total','count')).reset_index()['total']