使用 dict 重新映射 pandas 列中的值,保留 NaN
问题描述
I have a dictionary which looks like this: di = {1: "A", 2: "B"}
I would like to apply it to the col1
column of a dataframe similar to:
col1 col2
0 w a
1 1 2
2 2 NaN
to get:
col1 col2
0 w a
1 A 2
2 B NaN
How can I best do this? For some reason googling terms relating to this only shows me links about how to make columns from dicts and vice-versa :-/
解决方案You can use .replace
. For example:
>>> df = pd.DataFrame({'col2': {0: 'a', 1: 2, 2: np.nan}, 'col1': {0: 'w', 1: 1, 2: 2}})
>>> di = {1: "A", 2: "B"}
>>> df
col1 col2
0 w a
1 1 2
2 2 NaN
>>> df.replace({"col1": di})
col1 col2
0 w a
1 A 2
2 B NaN
or directly on the Series
, i.e. df["col1"].replace(di, inplace=True)
.
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