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Reproducible Example

import numpy as np
import pandas as pd

df = pd.DataFrame({
    'a':np.random.randn(150),
    'b':np.repeat( [25,50,75,100,np.nan], 30),
    'c':np.random.choice( ['panda','python','shark'], 150),
})

df['b'] = df['b'].astype("Int64")
df = df.set_index(['b', 'c'])

groups = df.groupby(axis='rows', level='b', dropna=False)

# Crashes here with something like "index 91 is out of bounds for axis 0 with size 4"
groups.ngroups

Issue Description

Attempting to run df.groupby() with an Int64Dtype column (nullable integers) no longer works as of Pandas 1.5.0. Seems to be caused by #46601, and I'm unsure if the patch at #48702 fixes this issue.

Traceback (most recent call last):
  File "pandas15_groupby_bug.py", line 17, in <module>
    groups.ngroups
  File "venv\lib\site-packages\pandas\core\groupby\groupby.py", line 992, in __getattribute__
    return super().__getattribute__(attr)
  File "venv\lib\site-packages\pandas\core\groupby\groupby.py", line 671, in ngroups
    return self.grouper.ngroups
  File "pandas\_libs\properties.pyx", line 36, in pandas._libs.properties.CachedProperty.__get__
  File "venv\lib\site-packages\pandas\core\groupby\ops.py", line 983, in ngroups
    return len(self.result_index)
  File "pandas\_libs\properties.pyx", line 36, in pandas._libs.properties.CachedProperty.__get__
  File "venv\lib\site-packages\pandas\core\groupby\ops.py", line 994, in result_index
    return self.groupings[0].result_index.rename(self.names[0])
  File "pandas\_libs\properties.pyx", line 36, in pandas._libs.properties.CachedProperty.__get__
  File "venv\lib\site-packages\pandas\core\groupby\grouper.py", line 648, in result_index
    return self.group_index
  File "pandas\_libs\properties.pyx", line 36, in pandas._libs.properties.CachedProperty.__get__
  File "venv\lib\site-packages\pandas\core\groupby\grouper.py", line 656, in group_index
    uniques = self._codes_and_uniques[1]
  File "pandas\_libs\properties.pyx", line 36, in pandas._libs.properties.CachedProperty.__get__
  File "venv\lib\site-packages\pandas\core\groupby\grouper.py", line 693, in _codes_and_uniques
    codes, uniques = algorithms.factorize(  # type: ignore[assignment]
  File "venv\lib\site-packages\pandas\core\algorithms.py", line 792, in factorize
    codes, uniques = values.factorize(  # type: ignore[call-arg]
  File "venv\lib\site-packages\pandas\core\arrays\masked.py", line 918, in factorize
    uniques = np.insert(uniques, na_code, 0)
  File "<__array_function__ internals>", line 180, in insert
  File "venv\lib\site-packages\numpy\lib\function_base.py", line 5332, in insert
    raise IndexError(f"index {obj} is out of bounds for axis {axis} "
IndexError: index 91 is out of bounds for axis 0 with size 4

Expected Behavior

Groupby shouldn't throw, and behave the same as on Pandas 1.4.

Installed Versions

commit : 87cfe4e38bafe7300a6003a1d18bd80f3f77c763 python : 3.8.10.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19042 machine : AMD64 processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : French_Canada.1252 pandas : 1.5.0 numpy : 1.23.3 pytz : 2022.2.1 dateutil : 2.8.2 setuptools : 60.2.0 pip : 21.3.1 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : 3.0.3 lxml.etree : None html5lib : None pymysql : None psycopg2 : 2.9.3 jinja2 : 3.1.2 IPython : None pandas_datareader: None bs4 : None bottleneck : None brotli : None fastparquet : None fsspec : 2022.8.2 gcsfs : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 9.0.0 pyreadstat : None pyxlsb : None s3fs : None scipy : None snappy : None sqlalchemy : 1.3.24 tables : None tabulate : 0.8.10 xarray : None xlrd : None xlwt : None zstandard : None tzdata : None

Comment From: phofl

cc @rhshadrach 

commit 56a71845decdc308d4210d74c7a59e42f0762c31
Author: Richard Shadrach <45562402+rhshadrach@users.noreply.github.com>
Date:   Thu Aug 18 12:09:09 2022 -0400

    BUG: algorithms.factorize moves null values when sort=False (#46601)

Comment From: rhshadrach

Thanks for the report! The PR identified above added computing the code using argmax and should have used max. These coincide when all values prior to the first NA value are distinct, which was the case in the tests added. Will put up a PR to fix.

Comment From: MarcoGorelli

Hey @sm-Fifteen

Thanks for having reported this - there's now a release candidate for pandas 2.0.0, which you can install with

mamba install -c conda-forge/label/pandas_rc pandas==2.0.0rc0

or

python -m pip install --upgrade --pre pandas==2.0.0rc0

If you try it out and report bugs, then we can fix them before the final 2.0.0 release

Comment From: rhshadrach

Just for clarity, this should have also been fixed in 1.5.1.