Description
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I have confirmed this bug exists on the latest version of pandas.
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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.
Code Sample, a copy-pastable example
import numpy as np
import pandas as pd
s = pd.Series([1, 2, pd.NA], dtype='category')
Out[3]:
0 1
1 2
2 NaN
dtype: category
Categories (2, int64): [1, 2]
Problem description
pd.NA
is inputted into the Series, but it is changed tonp.nan
.- Since the goal of pd.NA is to
provide a “missing” indicator that can be used consistently across data types
, the CategoricalDtype should support pd.NA
Expected Output
Out[3]:
0 1
1 2
2 <NA>
dtype: category
Categories (2, int64): [1, 2]
Output of pd.show_versions()
pandas : 1.2.0.dev0+482.g4291973e5
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.6.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None