AssertionError when grouping with max/min as aggregation functions (pandas-1.0.0) · Issue #31522 · pandas-dev/pandas (original) (raw)

Code Sample

import pandas as pd import numpy as np

df = pd.DataFrame({'key1' : ['a', 'a', 'b', 'b', 'a'], 'key2' : ['one', 'two', 'one', 'two', 'one'], 'key3' : ['three', 'three', 'three', 'six', 'six'], 'data1' : np.random.randn(5), 'data2' : np.random.randn(5)}) df.groupby('key1').min()

Problem description

Since pandas-1.0.0, an AssertionError is thrown when grouping a DataFrame by a key and using max/min as aggregation functions. It works fine if only 1 key (other than the grouping key) is of the type object in the DataFrame, but it doesn't when the number of keys of type object is bigger than 1 (as shown in the example). This configuration worked fine on previous versions of pandas (e.g., pandas-0.25.3).

Expected Output

Output of pd.show_versions()

commit : None
python : 3.7.6.final.0
python-bits : 64
OS : Darwin
OS-release : 19.2.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

pandas : 1.0.0
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.1.0.post20200127
Cython : 0.29.14
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.11.1
pandas_datareader: None
bs4 : None
bottleneck : 1.3.1
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : None
tabulate : 0.8.3
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : 0.48.0