数据框列表理解"zip(...)":仅使用列名称字符串列表即可有效地循环浏览选定的df列 [英] Dataframe list comprehension "zip(...)": loop through chosen df columns efficiently with just a list of column name strings

问题描述

这只是一个挑剔的句法问题...

This is just a nitpicking syntactic question...

我有一个数据框，我想使用列表推导来评估使用大量列的函数.

I have a dataframe, and I want to use list comprehension to evaluate a function using lots of columns.

我知道我可以做到

df['result_col'] = [some_func(*var) for var in zip(df['col_1'], df['col_2'],... ,df['col_n'])]

我想做这样的事情

df['result_col'] = [some_func(*var) for var in zip(df[['col_1', 'col_2',... ,'col_n']])]

即不必编写 df n 次.我一生都无法弄清楚语法.

i.e. not having to write df n times. I cannot for the life of me figure out the syntax.

推荐答案

这应该可行，但老实说，OP自己也认为，所以+1 OP:)

this should work, but honestly, OP figured it himself as well, so +1 OP :)

df['result_col'] = [some_func(*var) for var in zip(*[df[col] for col in ['col_1', 'col_2',... ,'col_n']])]

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