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

Question

def stack_plot(data, xtick, col2='project_is_approved', col3='total'):
    ind = np.arange(data.shape[0])

    plt.figure(figsize=(20,5))
    p1 = plt.bar(ind, data[col3].values)
    p2 = plt.bar(ind, data[col2].values)

    plt.ylabel('Projects')
    plt.title('Number of projects aproved vs rejected')
    plt.xticks(ind, list(data[xtick].values))
    plt.legend((p1[0], p2[0]), ('total', 'accepted'))
    plt.show()

def univariate_barplots(data, col1, col2='project_is_approved', top=False):
    # Count number of zeros in dataframe python: https://stackoverflow.com/a/51540521/4084039
    temp = pd.DataFrame(project_data.groupby(col1)[col2].agg(lambda x: x.eq(1).sum())).reset_index()

    # Pandas dataframe grouby count: https://stackoverflow.com/a/19385591/4084039
    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']

    temp.sort_values(by=['total'],inplace=True, ascending=False)

    if top:
        temp = temp[0:top]

    stack_plot(temp, xtick=col1, col2=col2, col3='total')
    print(temp.head(5))
    print("="*50)
    print(temp.tail(5))

univariate_barplots(project_data, 'school_state', 'project_is_approved', False)

Error:

SpecificationError                        Traceback (most recent call last)
<ipython-input-21-2cace8f16608> in <module>()
----> 1 univariate_barplots(project_data, 'school_state', 'project_is_approved', False)

<ipython-input-20-856fcc83737b> in univariate_barplots(data, col1, col2, top)
      4 
      5     # Pandas dataframe grouby count: https://stackoverflow.com/a/19385591/4084039
----> 6     temp['total'] = pd.DataFrame(project_data.groupby(col1)[col2].agg({'total':'count'})).reset_index()['total']
      7     print (temp['total'].head(2))
      8     temp['Avg'] = pd.DataFrame(project_data.groupby(col1)[col2].agg({'Avg':'mean'})).reset_index()['Avg']

~AppDataRoamingPythonPython36site-packagespandascoregroupbygeneric.py in aggregate(self, func, *args, **kwargs)
    251             # but not the class list / tuple itself.
    252             func = _maybe_mangle_lambdas(func)
--> 253             ret = self._aggregate_multiple_funcs(func)
    254             if relabeling:
    255                 ret.columns = columns

~AppDataRoamingPythonPython36site-packagespandascoregroupbygeneric.py in _aggregate_multiple_funcs(self, arg)
    292             # GH 15931
    293             if isinstance(self._selected_obj, Series):
--> 294                 raise SpecificationError("nested renamer is not supported")
    295 
    296             columns = list(arg.keys())

SpecificationError: **nested renamer is not supported**

Answer 1

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