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You can operate with + and * over an Interval and the operation is applied to each of its bounds, so the result depends on the type of the bound elements
However , we can apply the + operation manually on each bounds:
Code Sample, a copy-pastable example if possible
Problem description
From the pd.Interval documentation:
However , we can apply the + operation manually on each bounds:
Expected Output
The same as the manual operation on each bounds:
Output of
pd.show_versions()
pandas 1.0.1
INSTALLED VERSIONS
commit : None
python : 3.7.6.final.0
python-bits : 64
OS : Linux
OS-release : 4.4.0-146-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : fr_FR.UTF-8
LOCALE : fr_FR.UTF-8
pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.5.0
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 : 1.3.10
tables : None
tabulate : None
xarray : 0.15.0
xlrd : None
xlwt : None
xlsxwriter : None
numba : 0.46.0
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