测试pandas DataFrame的任何列是否满足条件 [英] Test if any column of a pandas DataFrame satisfies a condition

问题描述

我有一个包含很多列的DataFrame.现在，我有一个条件来测试其中某些列，如果该列集中的任何一个都不为零.

I got a DataFrame with lots of columns. Now I have a condition that tests some of those columns if any of that column-set is different to zero.

是否有更优雅的方法将该条件应用于一列列?我当前的代码是:

Is there any more elegant way to apply that condition to a subset of columns? My current code is:

df['indicator'] = (
    (df['col_1'] != 0) | 
    (df['col_2'] != 0) | 
    (df['col_3'] != 0) | 
    (df['col_4'] != 0) | 
    (df['col_5'] != 0)
)

我正在寻找类似这样的伪代码:

I was looking for something like this pseudo code:

columns = ['col_1', 'col_1', 'col_2', 'col_3', 'col_4', 'col_5']
df['indicator'] = df.any(columns, lambda value: value != 0)

推荐答案

ne是!=的方法形式.我用它来使流水线any看起来更好.我使用any(axis=1)来连续查找是否为真.

ne is the method form of !=. I use that so that pipelining any looks nicer. I use any(axis=1) to find if any are true in a row.

df['indicator'] = df[columns].ne(0).any(axis=1)

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