Bug: groupby with sort=False creates buggy MultiIndex · Issue #32259 · pandas-dev/pandas (original) (raw)
d = pd.to_datetime(['2020-11-02', '2019-01-02', '2020-01-02', '2020-02-04', '2020-11-03', '2019-11-03', '2019-11-13', '2019-11-13']) a = np.arange(len(d)) b = np.random.rand(len(d)) df = pd.DataFrame({'d': d, 'a': a, 'b': b}) t = df.groupby(['d', 'a'], sort=False).mean()
The index of t
is certainly not sorted, but t.index.is_lexsorted()
returns True.
Another more subtle example is
d = [3,4,10,0,1,2,5,3] a = np.arange(len(d)) b = np.random.rand(len(d)) df = pd.DataFrame({'d': d, 'a': a, 'b': b}) t = df.groupby(['d', 'a'], sort=False).mean()
This time the lexsort flag is correct. However, calling sortlevel will not sort the new MultiIndex correctly, that is, t.index.sortlevel(['d', 'a'])[0]
returns
MultiIndex([( 3, 0),
( 3, 7),
( 4, 1),
(10, 2),
( 0, 3),
( 1, 4),
( 2, 5),
( 5, 6)],
names=['d', 'a'])
Output of pd.show_versions()
[paste the output of pd.show_versions()
here below this line]
INSTALLED VERSIONS
commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-72-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.2.0.post20200210
Cython : 0.29.15
pytest : 5.3.5
hypothesis : 5.5.4
sphinx : 2.4.0
blosc : None
feather : None
xlsxwriter : 1.2.7
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.12.0
pandas_datareader: 0.8.1
bs4 : 4.8.2
bottleneck : 1.3.2
fastparquet : None
gcsfs : None
lxml.etree : 4.5.0
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.13.0
pytables : None
pytest : 5.3.5
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.7
numba : 0.45.1