ENH: pd.cut should be able to return a Series of IntervalDtype #31459
Description
Code Sample, a copy-pastable example if possible
In [1]: import pandas as pd In [2]: import random In [3]: df=pd.DataFrame({'x': [random.randint(0,10) for i in range(100)]}) In [4]: pd.cut(df.x, [2*i for i in range(6)]) Out[4]: 0 (6.0, 8.0] 1 NaN 2 (0.0, 2.0] 3 (2.0, 4.0] 4 (0.0, 2.0] ... 95 (8.0, 10.0] 96 (2.0, 4.0] 97 (8.0, 10.0] 98 (0.0, 2.0] 99 (8.0, 10.0] Name: x, Length: 100, dtype: category Categories (5, interval[int64]): [(0, 2] < (2, 4] < (4, 6] < (6, 8] < (8, 10]] Problem description
By default, the return type of pd.cut is categories, but we know we are creating intervals, so shouldn't it be IntervalDtype ?
Expected Output
In [5]: pd.cut(df.x, [2*i for i in range(6)]).astype('Interval') Out[5]: 0 (6.0, 8.0] 1 NaN 2 (0.0, 2.0] 3 (2.0, 4.0] 4 (0.0, 2.0] ... 95 (8.0, 10.0] 96 (2.0, 4.0] 97 (8.0, 10.0] 98 (0.0, 2.0] 99 (8.0, 10.0] Name: x, Length: 100, dtype: intervalIMHO, I shouldn't need to do the 'astype('Interval')`
Output of pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.7.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.0.0
numpy : 1.17.4
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 42.0.2.post20191203
Cython : None
pytest : 5.3.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.2.6
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.11.1
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.3.2
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : 1.2.6
numba : None