熊猫使用布尔值选择DataFrame列

问题描述：

我想使用布尔值从具有超过1,000列的数据框comb中选择具有4000多个条目的列.该表达式为我提供了布尔(真/假)结果:

I want to use a boolean to select the columns with more than 4000 entries from a dataframe comb which has over 1,000 columns. This expression gives me a Boolean (True/False) result:

criteria = comb.ix[:,'c_0327':].count()>4000

我想用它仅选择新数据框的True列.
以下只是给我提供了不可调布尔系列键":

I want to use it to select only the True columns to a new Dataframe.
The following just gives me "Unalignable boolean Series key provided":

comb.loc[criteria,]

我也尝试过:

comb.ix[:, comb.ix[:,'c_0327':].count()>4000]

类似于此问题的答案沿着列而不是行的数据框布尔选择但这给了我同样的错误:提供了不可对齐的布尔系列键"

Similar to this question answer dataframe boolean selection along columns instead of row but that gives me the same error: "Unalignable boolean Series key provided"

comb.ix[:,'c_0327':].count()>4000

产量:

c_0327    False
c_0328    False
c_0329    False
c_0330    False
c_0331    False
c_0332    False
c_0333    False
c_0334    False
c_0335    False
c_0336    False
c_0337     True
c_0338    False
.....

答

返回的是一个以列名作为索引，布尔值作为行值的Series.

What is returned is a Series with the column names as the index and the boolean values as the row values.

我想您实际上是想要的:

I think actually you want:

这现在应该可以工作:

comb[criteria.index[criteria]]

基本上，这会使用条件中的索引值和布尔值来屏蔽它们，这将返回一个列名数组，我们可以使用它从orig df中选择感兴趣的列.

Basically this uses the index values from criteria and the boolean values to mask them, this will return an array of column names, we can use this to select the columns of interest from the orig df.

熊猫使用布尔值选择DataFrame列

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