本文介绍了使用 dict 重新映射 pandas 列中的值，保留 NaN的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着跟版网的小编来一起学习吧！
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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