基于列数据生成列描述的优雅方法 [英] Elegant way to produce description of columns based on column data

问题描述

我有一个熊猫数据框：

index    data1    data2
1        30       20
2        20       10  
3        40       90

我想生成一系列描述，每行一个，指示数据是否重要。

I want to produce an array of descriptions, one for each row, indicating whether piece of data was significant.

我将有效值定义为大于25，因此我需要以下数组：

I define significant as having value over 25, so I want the following array:

['data1 was significant', '',  'data1 was significant\ndata2was significant']

我知道我可以遍历每一行并检查每一列并构建一个数组，但是我想知道是否有一种优雅的方法可以使用熊猫来做到这一点。

I know that I can go through each row and check each column and build an array, but I am wondering if there is an elegant way to do this using pandas.

推荐答案

使用 点技巧：

df = pd.DataFrame({
    'data1': [30, 20, 40],
    'data2': [20, 10, 90]
}, index=[1,2,3])

df.gt(25).dot(df.columns + ' was significant\n').str.strip().tolist()
# ['data1 was significant', '', 'data1 was significant\ndata2 was significant']

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