BUG: Default value for Series(dtype=int) is not pd.NA · Issue #43017 · pandas-dev/pandas (original) (raw)
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Code Sample, a copy-pastable example
pd.Series(index=[0], dtype=int)
Problem description
For other types, the default missing value indicator is set properly:
pd.Series(index=[0], dtype=float)
0 NaN
dtype: float64
pd.Series(index=[0], dtype="datetime64[ns]")
0 NaT
dtype: datetime64[ns]
pd.Series(index=[0], dtype=bool)
0 False
dtype: bool
(This might be tricky, but understandable)
However, for integer types, the default missing value is set to 0 instead of pd.NA, which is dangerous for interpretation.
Expected Output
Either
or
makes sense, given how int64 is converted when having missing values, the latter case may be better.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : c7f7443
python : 3.7.11.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : None.None
pandas : 1.3.1
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.2
setuptools : 52.0.0.post20210125
Cython : 0.29.24
pytest : 6.1.2
hypothesis : 6.14.1
sphinx : 4.0.2
blosc : None
feather : None
xlsxwriter : 1.4.4
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.22.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 2021.07.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : 0.4.2
scipy : 1.6.2
sqlalchemy : 1.4.22
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.19.0
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.0