Python 基于列数据生成列描述的优雅方法

我有一个数据框：

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

我想生成一个描述数组，每行一个，指示数据块是否重要

我将“重要”定义为值大于25，因此需要以下数组：

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

我知道我可以遍历每一行、检查每一列并构建一个数组，但我想知道是否有一种优雅的方法可以使用pandas来实现这一点

使用：

---

或者，使用

np.where

[''.join(x) for x in np.where(df > 25, df.columns + ' was significant\n', '')] 
['data1 was significant\n',
 '',
 'data1 was significant\ndata2 was significant\n']

---

或者，使用

apply

In [323]: (df.gt(25).apply(lambda x: '\n'.join(
                       ['%s was significant' % c for c, v in x.iteritems() if v]), axis=1)
             .tolist())
Out[323]: ['data1 was significant', '', 'data1 was significant\ndata2 was significant']

---

@我通常很节俭。。。今天他们已经走了，还有9个小时，我整晚都没睡。而且。。。你知道/耸耸肩

In [323]: (df.gt(25).apply(lambda x: '\n'.join(
                       ['%s was significant' % c for c, v in x.iteritems() if v]), axis=1)
             .tolist())
Out[323]: ['data1 was significant', '', 'data1 was significant\ndata2 was significant']