Description
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I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas.
(only in current master; dropna=False didn't exist previously) -
(optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
>>> df = pd.DataFrame({'a': [pd.to_datetime('2019-02-12'), pd.to_datetime('2019-02-12'), pd.to_datetime('2019-02-13'), pd.NaT], 'b': [1, 2, 3, 4]})
>>>
>>> dfg = df.groupby(['a'], dropna=False)
>>> len(dfg)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/groupby/groupby.py", line 539, in __len__
return len(self.groups)
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/groupby/groupby.py", line 558, in groups
return self.grouper.groups
File "pandas/_libs/properties.pyx", line 33, in pandas._libs.properties.CachedProperty.__get__
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/groupby/ops.py", line 257, in groups
return self.groupings[0].groups
File "pandas/_libs/properties.pyx", line 33, in pandas._libs.properties.CachedProperty.__get__
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/groupby/grouper.py", line 598, in groups
return self.index.groupby(Categorical.from_codes(self.codes, self.group_index))
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/arrays/categorical.py", line 606, in from_codes
dtype = CategoricalDtype._from_values_or_dtype(
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 365, in _from_values_or_dtype
dtype = CategoricalDtype(categories, ordered)
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 252, in __init__
self._finalize(categories, ordered, fastpath=False)
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 406, in _finalize
categories = self.validate_categories(categories, fastpath=fastpath)
File "./venv/pandas-1/lib64/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 579, in validate_categories
raise ValueError("Categorical categories cannot be null")
ValueError: Categorical categories cannot be nullProblem description
When using groupby with the option of dropna=False, it may happen that a ValueError is being raised when the result of len(groupby(..., dropna=False)) is obtained. This works fine in older version of Pandas (0.25.x) which always dropped na rows by default. Even in the current master version (1.1.0.dev0+2054.gc15f08084) len(...) still works fine when dropna=True is used. The interesting bit (for me at least) is that categoricals are somehow used while there are no categoricals in the dataframe to begin with. Perhaps this is a code path that is not meant to be executed.
Expected Output
No exception being raised (there isn't any categorical after all) and len(...) isn't modifying anything so an exception is totally unexpected.
Output of pd.show_versions()
>>> pd.show_versions()
INSTALLED VERSIONS
------------------
commit : c15f0808428b5cdb4eaea290fb26a71c3534630b
python : 3.8.3.final.0
python-bits : 64
OS : Linux
OS-release : 5.7.7-200.fc32.x86_64
Version : #1 SMP Wed Jul 1 19:53:01 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_AU.UTF-8
LOCALE : en_AU.UTF-8
pandas : 1.1.0.dev0+2054.gc15f08084
numpy : 1.19.0
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1
setuptools : 46.1.3
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None