如何替换不在列表中的 Pandas Dataframe 中的所有值？
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/34866856/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to replace all values in a Pandas Dataframe not in a list?
提问by banad
I have a list of values. How can I replace all values in a Dataframe column not in the given list of values?
我有一个值列表。如何替换不在给定值列表中的 Dataframe 列中的所有值？
For example,
例如，
>>> df = pd.DataFrame(['D','ND','D','garbage'], columns=['S'])
>>> df
S
0 D
1 ND
2 D
3 garbage
>>> allowed_vals = ['D','ND']
I want to replace all values in the column S of the dataframe which are not in the list allowed_vals with 'None'. How can I do that?
我想将数据框 S 列中所有不在列表 allowed_vals 中的值替换为“无”。我怎样才能做到这一点？
回答by DSM
You can use isinto check membership in allowed_list, ~to negate that, and then .locto modify the series in place:
您可以使用isin来检查 中的成员资格allowed_list，~否定它，然后.loc就地修改系列：
>>> df.loc[~df["S"].isin(allowed_vals), "S"] = "None"
>>> df
S
0 D
1 ND
2 D
3 None
because
因为
>>> df["S"].isin(allowed_vals)
0 True
1 True
2 True
3 False
Name: S, dtype: bool
If you want to modify the entire frame (not just the column S), you can make a frame-sized mask:
如果要修改整个框架（不仅仅是S列），可以制作一个框架大小的遮罩：
>>> df
S T
0 D D
1 ND A
2 D ND
3 garbage A
>>> df[~df.isin(allowed_vals)] = "None"
>>> df
S T
0 D D
1 ND None
2 D ND
3 None None
