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

问题

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']

~\AppData\Roaming\Python\Python36\site-packages\pandas\core\groupby\generic.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

~\AppData\Roaming\Python\Python36\site-packages\pandas\core\groupby\generic.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**

回答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']

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

回答2:

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]: 
   B
A   
1  2

In [196]: group.agg({'B': 'mean', 'non-existing-column': 'mean'})
...
SpecificationError: nested renamer is not supported

回答3:

Do you get the same error if you change

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

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

回答4:

I have got the similar issue as @akshay jindal, but I check the documentation as suggested by @artikay Khanna, the problem solved, some functions has been adjusted, the old is deprecated. Here is the code warning provided per last time execute.

/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: FutureWarning: using a dict on a Series for aggregation
is deprecated and will be removed in a future version. Use                 named aggregation instead.

    >>> grouper.agg(name_1=func_1, name_2=func_2)

  """Entry point for launching an IPython kernel.

Therefore, I will suggest try

grouper.agg(name_1=func_1, name_2=func_2)

Hope this will help

回答5:

I have tried alll the solutions and turned out to be the error with the name. If your column name has some inbuilt keywords such as "in", "is",etc., It is throwing error. In my case, My column name is "Points in Polygon" and I have resolved the issue by renaming the column to "Points"

来源：https://stackoverflow.com/questions/60229375/solution-for-specificationerror-nested-renamer-is-not-supported-while-agg-alo

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python

pandas

aggregate