BUG: .fillna({}) doesn't work

[q121212]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the master branch of pandas.

Reproducible Example

import pandas as pd

df = pd.DataFrame([1,2,np.nan, pd.NA], columns=['a'])

# case 1
df.fillna({})

# case 2
df.fillna({np.nan: {}, pd.NA: {}})

Issue Description

.fillna() doesn't work as expected for case then value = {}

as written in pandas.DataFrame.fillna:

DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None)

Fill NA/NaN values using the specified method.

Parameters

value scalar, dict, Series, or DataFrame

Value to use to fill holes (e.g. 0), alternately a dict/Series/DataFrame of values specifying which value to use for each index (for a Series) or column (for a DataFrame). Values not in the dict/Series/DataFrame will not be filled. This value cannot be a list.

Expected Behavior

all values (np.nan and pd.NA) should be changed to {}

Installed Versions

INSTALLED VERSIONS

commit : 73c6825
python : 3.9.6.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.47-linuxkit
Version : #1 SMP Sat Jul 3 21:51:47 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.3
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.24
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.08.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.23
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : 0.54.0

[ShivnarenSrinivasan]

I don't think this will be considered a bug—have you tried inserting an empty set/dictionary into a dataframe?

To your example:

>>> df = pd.DataFrame([1,2,np.nan, pd.NA], columns=['a'])
>>> df
      a
0     1
1     2
2   NaN
3  <NA>

# appending a dict
>>> df.loc[4] = {}
>>> df
      a
0     1
1     2
2   NaN
3  <NA>
4   NaN

The empty dict is considered as NaN.

An empty set, however, is stored as is.

[q121212]

The empty dict is NaN after type casting only. But imho in considered case .fillna({}) should be works without type casting and just replace NaN with the specified value, whatever it is.

I used workaround:

>>> df.loc[df['a'].isnull(), 'a'] = [{}]
>>> df
      a
0     1
1     2
2    {}
3    {}

Also in @ShivnarenSrinivasan example works in the same manner:

>>> df.loc[4] = [{}]
>>> df
      a
0     1
1     2
2    {}
3    {}
4    {}