Description
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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(optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
import pandas
df = pandas.DataFrame({"col1": ["a", "b", "c"]})
df.groupby("col1", level=0) # Fine
df.index = pandas.MultiIndex.from_arrays([["a", "a", "b"], [1, 2, 1]], names=["x", "y"])
df.groupby(["col1", "x"]) # Fine
df.groupby("col1", level=0) # TypeErrorTraceback
Traceback (most recent call last):
File "rofl.py", line 7, in <module>
res = df.groupby("col1", level=0) # TypeError
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/frame.py", line 6727, in groupby
dropna=dropna,
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/groupby/groupby.py", line 568, in __init__
dropna=self.dropna,
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/groupby/grouper.py", line 839, in get_grouper
if not isinstance(gpr, Grouping)
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/groupby/grouper.py", line 485, in __init__
) = index._get_grouper_for_level(self.grouper, level)
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/indexes/multi.py", line 1487, in _get_grouper_for_level
grouper = level_values.map(mapper)
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/indexes/base.py", line 5098, in map
new_values = super()._map_values(mapper, na_action=na_action)
File "/localdisk/dchigare/miniconda3/envs/modin_tests/lib/python3.7/site-packages/pandas/core/base.py", line 937, in _map_values
new_values = map_f(values, mapper)
File "pandas/_libs/lib.pyx", line 2467, in pandas._libs.lib.map_infer
TypeError: 'numpy.ndarray' object is not callable
Problem description
Getting a TypeError when specifying by and level params in .groupby() at the same time. It seems that grouping on column name and index level is supported since there is no error when level name is located in by parameter, so specifying it with level should also be possible.
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.7.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-65-generic
Version : #73-Ubuntu SMP Mon Jan 18 17:25:17 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.19.0
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 47.3.1.post20200622
Cython : None
pytest : 6.0.2
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.5.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : None
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.7.4
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : 0.13.2
pyarrow : 1.0.1
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.1
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
numba : None