False positive for "nested renamer is not supported" error

[rth]

Code Sample

import pandas as pd

df = pd.DataFrame({'A': [1, 1, 1, 2, 2],  'B': range(5), 'C': range(5)})
df.groupby('A').agg({'B': 'sum', 'G': 'min'})  # aggregate by a non existing column

produces

<ipython-input-5-f5ac34bf856f> in <module>
----> 1 df.groupby('A').agg({'B': 'sum', 'G': 'min'})

~/src/dgr00/.venv3/lib/python3.6/site-packages/pandas/core/groupby/generic.py in aggregate(self, func, *args, **kwargs)
    938         func = _maybe_mangle_lambdas(func)
    939
--> 940         result, how = self._aggregate(func, *args, **kwargs)
    941         if how is None:
    942             return result

~/src/dgr00/.venv3/lib/python3.6/site-packages/pandas/core/base.py in _aggregate(self, arg, *args, **kwargs)
    364                     obj.columns.intersection(keys)
    365                 ) != len(keys):
--> 366                     raise SpecificationError("nested renamer is not supported")
    367
    368             from pandas.core.reshape.concat import concat

SpecificationError: nested renamer is not supported

Problem description

While groupby.agg() with a dictionary when renaming was deprecated in 1.0 (
https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.20.0.html#deprecate-groupby-agg-with-a-dictionary-when-renaming) the corresponding error message can also be obtained when aggregating by an non existing column which can lead to confusion.

Expected Output

Error saying that the column G does not exist.

Output of pd.show_versions()

INSTALLED VERSIONS

python : 3.6.4.final.0
OS : Linux
machine : x86_64
pandas : 1.0.1

[Juan-132]

Confirmed. The incorrect error message threw me off as well.

[luciofaso]

Same problem

[tanglade22]

Same problem here, bug is due to non-existing column

[twang96]

same problem here, anyone has a workaround method? thx

[foxx]

Can confirm, got the same exception due to a non-existing column name.

[benjamin-ny]

It's also inconsistent:

import pandas as pd
df = pd.DataFrame({'A': [1, 1, 1, 2, 2],  'B': range(5), 'C': range(5)})
df.groupby('A').agg({'B': 'sum', 'G': ['min'])  # <- use ['min'] instead of 'min'

raises the correct error: KeyError: "Column 'G' does not exist!"

[KingPegasus]

You wrote G instead of C. 'G' is nothing. 'C' is the column.
import pandas as pd
df = pd.DataFrame({'A': [1, 1, 1, 2, 2], 'B': range(5), 'C': range(5)})
df.groupby('A').agg({'B': 'sum', 'C': 'min'})

Applying multiple aggregation a column
df = pd.DataFrame({'A': [1, 1, 1, 2, 2], 'B': range(5), 'C': range(5)})
df.groupby('A').agg({'B': ['sum','min'], 'C': ['sum','min']})

[thoo]

I think this one is also related.

I tried to rename the column right after groupby by the way it is done in pd.version < 1.0. I do not get the deprecation warnings like I get in pd.version < 1.0.

Here is the example:

df = pd.DataFrame({'A': [1, 1, 1, 2, 2],'B': range(5)})
df.groupby('A').agg({'B': {'foo': 'sum'}})

The error message is:

---------------------------------------------------------------------------
SpecificationError                        Traceback (most recent call last)
<ipython-input-22-440a616816b6> in <module>
      1 df = pd.DataFrame({'A': [1, 1, 1, 2, 2],'B': range(5)})
----> 2 df.groupby('A').agg({'B': {'foo': 'sum'}})

~/anaconda3/lib/python3.7/site-packages/pandas/core/groupby/generic.py in aggregate(self, func, *args, **kwargs)
    926         func = _maybe_mangle_lambdas(func)
    927 
--> 928         result, how = self._aggregate(func, *args, **kwargs)
    929         if how is None:
    930             return result

~/anaconda3/lib/python3.7/site-packages/pandas/core/base.py in _aggregate(self, arg, *args, **kwargs)
    340                     # {'ra' : { 'A' : 'mean' }}
    341                     if isinstance(v, dict):
--> 342                         raise SpecificationError("nested renamer is not supported")
    343                     elif isinstance(obj, ABCSeries):
    344                         raise SpecificationError("nested renamer is not supported")

SpecificationError: nested renamer is not supported

[thoo]

You wrote G instead of C. 'G' is nothing. 'C' is the column.
import pandas as pd
df = pd.DataFrame({'A': [1, 1, 1, 2, 2], 'B': range(5), 'C': range(5)})
df.groupby('A').agg({'B': 'sum', 'C': 'min'})

Applying multiple aggregation a column
df = pd.DataFrame({'A': [1, 1, 1, 2, 2], 'B': range(5), 'C': range(5)})
df.groupby('A').agg({'B': ['sum','min'], 'C': ['sum','min']})

We are expecting the appropriate error message. The current error message is not pointing to the right direction.

[crash5936]

I also ran into this error and as mentioned, it was caused by trying to aggregate a non-existent column. Version 1.0.3

[sibiyes]

got the same error when there are duplicate columns in the dataframe.

[NikkiShah93]

I only get this error when I'm running my code with command or git bash, when I'm running my code in jupyter it works fine, what's the best way to solve it by still using the agg()?