Series.map and ignore_na depends on mapping type · Issue #47527 · pandas-dev/pandas (original) (raw)

It seems this only works if the mapping is a function, not a dictionary. See this test:

import pandas as pd
import numpy as np

mapping = {1: 10, np.nan: 42}

# succeeds as expected (basic simple test)
pd.testing.assert_series_equal(
    pd.Series([1, np.nan, 2]).map(mapping),
    pd.Series([10, 42, np.nan]),
)

# succeeds as expected, note the seemingly unnecessary lambda
pd.testing.assert_series_equal(
    pd.Series([1, np.nan, 2]).map(lambda x: mapping.get(x), na_action="ignore"),
    pd.Series([10, np.nan, np.nan]),
)

# remove the lambda and use the map directly
pd.testing.assert_series_equal(
    pd.Series([1, np.nan, 2]).map(mapping, na_action="ignore"),
    pd.Series([10, np.nan, np.nan]),
)
# Whoops!
# AssertionError: Series are different
# 
# Series values are different (33.33333 %)
# [index]: [0, 1, 2]
# [left]:  [10.0, 42.0, nan]    <-- it did replace the nan even though na_action is ignore
# [right]: [10.0, nan, nan]

So to me it seems the na_action parameter is ignored for dictionaries but works for functions. I don't think it is a good idea to have different behaviour depending on the type of the mapping. So could this either be fixed or corrected in the documentation?