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Reproducible Example

import pandas as pd

d = {'UserId': {0: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  1: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  2: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  3: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  4: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  5: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  6: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  7: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  8: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net',
  9: '092202ce-ac51-433b-9827-2c1264b6783f@tunnel.msging.net'},
 'BotId': {0: 'claroresidentialsales@msging.net',
  1: 'claroresidentialsales@msging.net',
  2: 'claroresidentialsales@msging.net',
  3: 'claroresidentialsales@msging.net',
  4: 'claroresidentialsales@msging.net',
  5: 'claroresidentialsales@msging.net',
  6: 'claroresidentialsales@msging.net',
  7: 'claroresidentialsales@msging.net',
  8: 'claroresidentialsales@msging.net',
  9: 'claroresidentialsales@msging.net'}}

df = pd.DataFrame(d,dtype='category')
print(df.groupby('BotId',observed=True)['UserId'].unique().values.shape)

Issue Description

If you take a closer look at the given result you will notice the given array result, comes with a shape of one dimension with only one value, when in reality the expected result is to be an array of shape 10.

Expected Behavior

The shape of the ndarray should be 10.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 91111fd99898d9dcaa6bf6bedb662db4108da6e6 python : 3.9.15.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19044 machine : AMD64 processor : AMD64 Family 25 Model 80 Stepping 0, AuthenticAMD byteorder : little LC_ALL : None LANG : None LOCALE : pt_BR.cp1252 pandas : 1.5.1 numpy : 1.23.4 pytz : 2022.1 dateutil : 2.8.2 setuptools : 65.5.0 pip : 22.2.2 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.6.0 pandas_datareader: None bs4 : 4.11.1 bottleneck : 1.3.5 brotli : fastparquet : None fsspec : None gcsfs : None matplotlib : 3.5.3 numba : None numexpr : 2.8.4 odfpy : None openpyxl : 3.0.9 pandas_gbq : None pyarrow : 8.0.0 pyreadstat : None pyxlsb : None s3fs : None scipy : 1.9.3 snappy : None sqlalchemy : None tables : None tabulate : 0.9.0 xarray : 2022.12.0 xlrd : None xlwt : None zstandard : None tzdata : None

Comment From: Sirmadeira

Just noticed that in the given sample, the groupby only afflicts a single value