Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
i1 = pd.date_range("2022", freq="D", periods=10)
i2 = i1.copy() # COPY
print(i1 is i2) # False
print(id(i1), id(i2)) # 2151608624624 2151619591232
print(i1.freq) # <Day>
print(i2.freq) # <Day>
i1.freq = None
print(i1 is i2) # False
print(id(i1), id(i2)) # 2151608624624 2151619591232
print(i1.freq) # None
print(i2.freq) # None (!!)
Issue Description
See the final line. The frequency of i2 has been changed as well, even though it is a distinct object from i1.
Excuse me if this is expected.
Expected Behavior
The attributes of i2 should not change when they are changed in i1 only.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 91111fd99898d9dcaa6bf6bedb662db4108da6e6
python : 3.8.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : de_DE.cp1252
pandas : 1.5.1
numpy : 1.23.4
pytz : 2022.5
dateutil : 2.8.2
setuptools : 61.2.0
pip : 21.2.2
Cython : None
pytest : 7.1.1
hypothesis : None
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.3.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.1
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.32
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None
Comment From: a-reich
Just chiming in, but the method’s deep param defaults to false. If set to true this behaves as you expected.
Comment From: debnathshoham
as @a-reich rightly pointed out
1 = pd.date_range("2022", freq="D", periods=10)
i2=i1.copy(deep=True)
print(i1 is i2) # False
print(id(i1), id(i2)) # 140340502539808 140340502540240
print(i1.freq) # <Day>
print(i2.freq) # <Day>
i1.freq = None
print(i1 is i2) # False
print(id(i1), id(i2)) # 140340502539808 140340502540240
print(i1.freq) # None
print(i2.freq) # <Day>