Description
Pandas version checks
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I have checked that this issue has not already been reported.
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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
import numpy as np
from collections import defaultdict
s = pd.Series([1,2, np.nan])
s2 = pd.Series(['a', 'b', np.nan])
d = defaultdict(lambda: "missing", {1:'a', 2:'b', np.nan: 'c'})
d2 = defaultdict(lambda: -1, {'a': 1, 'b': 2, np.nan: 3})
s.map(d)
s2.map(d2)Issue Description
In the first case the np.nan is not replaced with 'c' but is instead mapped to the default value.
>>> s.map(d)
0 a
1 b
2 missing
dtype: objectin the second case, np.nan is correctly replaced with 3 and not -1
>>> s2.map(d2)
0 1
1 2
2 3
dtype: int64Expected Behavior
the first case to output
>>> s.map(d)
0 a
1 b
2 c
dtype: objectI know I can use .fillna as a workaround - but this seems to be explicitly tested in the case of regular dicts here -
pandas/pandas/tests/apply/test_series_apply.py
Lines 592 to 598 in 49d4c07
but seems to be untested for defaultdicts / objects that implement __missing__
Installed Versions
INSTALLED VERSIONS
commit : b3552c5
python : 3.8.13.final.0
python-bits : 64
OS : Linux
OS-release : 4.19.128-microsoft-standard
Version : #1 SMP Tue Jun 23 12:58:10 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.5.0.dev0+1579.gb3552c54be
numpy : 1.23.3
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.4.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.3
hypothesis : 6.54.6
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.5.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.3
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.3.2
numba : 0.53.1
numexpr : 2.8.0
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.15.0
pyarrow : 2.0.0
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.9.1
snappy :
sqlalchemy : 1.4.41
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : 0.18.0
tzdata : None