BUG: Groupby.any(skipna=True) (original) (raw)

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Code Sample, a copy-pastable example

import pandas as pd

def test_groupby_any(): df = pd.DataFrame( { "ids": ["id1", "id1", "id2", "id2"], "A": [True, False, pd.NA, True] } ).astype({"ids": pd.StringDtype(), "A": pd.BooleanDtype()})

result = df.groupby("ids").any(skipna=True)

expected = pd.DataFrame(
    {
        "A": [True, True]
    }, index=pd.Series(["id1", "id2"], name="ids")
)

pd.testing.assert_frame_equal(expected, result)

Problem description

When running df.groupby(field_to_group_on).any(skipna=True) it should be expected that pd.NA values are neglected for the .any() method. However the output is this:

self =
[True, False, , True]
Length: 4, dtype: boolean
dtype = dtype('bool'), copy = True

def astype(self, dtype, copy: bool = True) -> ArrayLike:
    """
    Cast to a NumPy array or ExtensionArray with 'dtype'.

    Parameters
    ----------
    dtype : str or dtype
        Typecode or data-type to which the array is cast.
    copy : bool, default True
        Whether to copy the data, even if not necessary. If False,
        a copy is made only if the old dtype does not match the
        new dtype.

    Returns
    -------
    ndarray or ExtensionArray
        NumPy ndarray, BooleanArray or IntegerArray with 'dtype' for its dtype.

    Raises
    ------
    TypeError
        if incompatible type with an BooleanDtype, equivalent of same_kind
        casting
    """
    from pandas.core.arrays.string_ import StringDtype

    dtype = pandas_dtype(dtype)

    if isinstance(dtype, BooleanDtype):
        values, mask = coerce_to_array(self, copy=copy)
        if not copy:
            return self
        else:
            return BooleanArray(values, mask, copy=False)
    elif isinstance(dtype, StringDtype):
        return dtype.construct_array_type()._from_sequence(self, copy=False)

    if is_bool_dtype(dtype):
        # astype_nansafe converts np.nan to True
        if self._hasna:

         raise ValueError("cannot convert float NaN to bool")

E ValueError: cannot convert float NaN to bool

Expected Output

    expected = pd.DataFrame(
        {
            "A": [True, True]
        }, index=pd.Series(["id1", "id2"], name="ids")
    )

Output of pd.show_versions()

Details

INSTALLED VERSIONS

commit : f2c8480
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.2
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None