Closed
Description
Code Sample, a copy-pastable example if possible
In [87]: df2 = pd.DataFrame([['a', 1], ['b', pd.NA]])
In [108]: df2
Out[108]:
0 1
0 a 1
1 b <NA>
In [109]: df2.replace({0: 'a'}, np.nan)
/home/torstein/anaconda3/lib/python3.7/site-packages/pandas/core/missing.py:47: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
mask = arr == x
Out[111]:
0 1
0 a 1
1 b <NA>
In [112]: df2.dtypes
Out[112]:
0 object
1 object
dtype: object
# This works:
In [121]: df2[0].replace('a', np.nan)
Out[121]:
0 NaN
1 b
Name: 0, dtype: object
# This also works:
In [126]: pd.DataFrame([['a', 1], ['b', np.nan]]).replace({0: 'a'}, 'b')
Out[126]:
0 1
0 b 1.0
1 b NaN
Problem description
There are multiple similar issues, but in this case, there are no NaNs in the column specified by the replacement-dictionary. If the dataframe is created without additional column 1 with a pd.NA, even though no replacement is performed on that column, then replace works.
Expected Output
'a' to be replaced with nan
Output of pd.show_versions()
pandas : 1.0.2
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 41.6.0.post20191030
Cython : 0.29.13
pytest : 5.2.2
hypothesis : None
sphinx : 2.2.1
blosc : None
feather : None
xlsxwriter : 1.2.2
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.8.1
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 2.2.3
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pytest : 5.2.2
pyxlsb : None
s3fs : None
scipy : 1.3.1
sqlalchemy : 1.3.10
tables : 3.5.2
tabulate : 0.8.5
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.2
numba : 0.46.0