Description
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I have confirmed this bug exists on the latest version of pandas.
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(optional) I have confirmed this bug exists on the master branch of pandas.
#------ pandas 1.2.* ------
import pandas as pd
df = pd.DataFrame(index = pd.DatetimeIndex([]))
print(df.T.sum().index) # output: Index([], dtype='object')
print(df.sum(axis = 1).index) # output: DatetimeIndex([], dtype='datetime64[ns]', freq=None)Problem description
In pandas versions >= 1.2, if we take the sum of the transpose of an empty DataFrame with DatetimeIndex, it results in an output with normal Index instead of DatetimeIndex.
But if we sum the DataFrame with axis=1, which is an equivalent operation, the DatetimeIndex is preserved.
Expected Output
In pandas versions <= 1.1, the output correctly has a DatetimeIndex in both cases.
#------ pandas 1.1.* ------
import pandas as pd
df = pd.DataFrame(index = pd.DatetimeIndex([]))
print(df.T.sum().index) # output: DatetimeIndex([], dtype='datetime64[ns]', freq=None)
print(df.sum(axis = 1).index) # output: DatetimeIndex([], dtype='datetime64[ns]', freq=None)Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2cb9652
python : 3.7.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.2.4
numpy : 1.19.5
pytz : 2019.3
dateutil : 2.8.1
pip : 21.1.1
setuptools : 56.1.0
Cython : 0.29.16
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.0
IPython : 7.23.1
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.3
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None