pandas 取代价值观 [英] Pandas replace values

问题描述

我有以下数据框:

     col
0    pre
1    post
2    a
3    b
4    post
5    pre
6    pre

我想将数据框中不包含"pre"的所有行替换为"nonpre"，因此数据框看起来像:

I want to replace all rows in the dataframe which do not contain 'pre' to become 'nonpre', so dataframe looks like:

     col
0    pre
1    nonpre
2    nonpre
3    nonpre
4    nonpre
5    pre
6    pre

我可以使用字典和熊猫替换来做到这一点，但是我只想选择不是'pre'的元素，然后将它们替换为'nonpre'.有没有一种更好的方法可以在不列出字典中所有可能的col值的情况下做到这一点?

I can do this using a dictionary and pandas replace, however I want to just select the elements which are not 'pre' and replace them with 'nonpre'. is there a better way to do that without listing all possible col values in a dictionary?

推荐答案

只要您对pandas允许的df.loc[condition, column]语法感到满意，这很容易，只需执行df['col'] != 'pre'即可找到所有应进行更改:

As long as you're comfortable with the df.loc[condition, column] syntax that pandas allows, this is very easy, just do df['col'] != 'pre' to find all rows that should be changed:

df['col2'] = df['col']
df.loc[df['col'] != 'pre', 'col2'] = 'nonpre'

df
Out[7]: 
    col    col2
0   pre     pre
1  post  nonpre
2     a  nonpre
3     b  nonpre
4  post  nonpre
5   pre     pre
6   pre     pre

这篇关于 pandas 取代价值观的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！