pandas 如何根据布尔标准拆分数据帧？
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/14957116/
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 split a dataframe according to a boolean criterion?
提问by kjo
Suppose that dfis a pandasdataframe. I want to split it into two dataframes according to some criterion. The best way I've found for doing this is something like
假设这df是一个pandas数据框。我想根据某种标准将它分成两个数据帧。我发现这样做的最好方法是
df0, df1 = [v for _, v in df.groupby(df['class'] != 'special')]
In the above example, the criterion is the argument to the groupbymethod. The resulting df0consists of the sub-dataframe where the classfield hasvalue 'special', and df1is basically the complement of df0. (Unfortunately, with this construct, the sub-dataframe consisting of the items that failthe criterion are returned first, which is not intuitive.)
在上面的例子中，标准是groupby方法的参数。结果df0由class字段具有value的子数据帧组成'special'，并且df1基本上是 的补充df0。（不幸的是，使用此构造，首先返回由不符合标准的项目组成的子数据框，这不直观。）
The above construct has the drawback that it is not particularly readable, certainly not as readable as, for instance, some hypothetical splitbymethod like
上述构造的缺点是它不是特别可读，当然不如某些假设splitby方法如
df0, df1 = df.splitby(df['class'] == 'special')
Since splitting a dataframe like this is something I often need to do, I figure that there may be a built-in function, or maybe an established idiom, for doing this. If so, please let me know.
由于像这样拆分数据帧是我经常需要做的事情，我认为可能有一个内置函数，或者可能是一个既定的习惯用法，用于执行此操作。如果是这样，请告诉我。
回答by Andy Hayden
I think the most readable way is to do this is:
我认为最易读的方法是：
m = df['class'] != 'special'
a, b = df[m], df[~m]
I haven't come across a special method for this...
我还没有遇到过一种特殊的方法...
