pandas 用字典替换熊猫系列中的值
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Replace values in pandas Series with dictionary
提问by joga
I want to replace values in a pandas Seriesusing a dictionary. I'm following @DSM's accepted answerlike so:
我想Series使用字典替换Pandas中的值。我正在关注@DSM接受的答案，如下所示：
s = Series(['abc', 'abe', 'abg'])
d = {'b': 'B'}
s.replace(d)
But this has no affect:
但这没有影响：
0 abc
1 abe
2 abg
dtype: object
The documentationexplains the required format of the dict for DataFrames(i.e. nested dicts with top level keys corresponding to column names) but I can't see anything specific for Series.
该文档解释了所需的 dict 格式DataFrames（即具有与列名对应的顶级键的嵌套 dicts），但我看不到任何特定于Series.
回答by MaxU
You can do it using regex=Trueparameter:
您可以使用regex=True参数来做到这一点：
In [37]: s.replace(d, regex=True)
Out[37]:
0 aBc
1 aBe
2 aBg
dtype: object
As you have already found out yourself- it's a RegEx replacement and it won't work as you expected:
正如您自己已经发现的那样- 它是一个 RegEx 替代品，它不会像您预期的那样工作：
In [36]: s.replace(d)
Out[36]:
0 abc
1 abe
2 abg
dtype: object
this is working as expected:
这是按预期工作的：
In [38]: s.replace({'abc':'ABC'})
Out[38]:
0 ABC
1 abe
2 abg
dtype: object
