在 pandas 列上执行条件操作 [英] Perform a conditional operation on a pandas column

问题描述

我知道这应该很简单，但是我想从熊猫中摘取专栏 数据框，并且仅对于满足某些条件(例如小于1)的条目， 乘以标量(例如2).

I know that this should be simple, but I want to take a column from a pandas dataframe, and for only the entries which meet some condition (say less than 1), multiply by a scalar (say 2).

例如，在此数据框中，

df = pd.DataFrame(randn(5,4),index='A B C D E'.split(),columns='W X Y Z'.split())

          W         X       Y        Z  

A    2.706850 0.628133 0.907969 0.503826 
B    0.651118 -0.319318 -0.848077 0.605965 
C    -2.018168 0.740122 0.528813 -0.589001 
D    0.188695 -0.758872 -0.933237 0.955057 
E    0.190794 1.978757 2.605967 0.683509 

如果我有兴趣在列W上执行此操作，则结果应为

if I'm interested in carrying out this operation on column W, the result should be

          W         X       Y        Z  

A    2.706850 0.628133 0.907969 0.503826 
B    1.302236 -0.319318 -0.848077 0.605965 
C    -4.036336 0.740122 0.528813 -0.589001 
D    0.37739 -0.758872 -0.933237 0.955057 
E    0.381588 1.978757 2.605967 0.683509

我有以下内容用于绝对作业:

I have the below for an absolute assignment:

df.loc[df['W'] < 1, 'W'] = 4

但是我不确定如何使用W中的实际值.

but I'm not sure how to use the actual values from W.

提前谢谢！

推荐答案

在您的情况下，只需使用*=运算符就可以进行乘法运算:

In your case, just use the *= operator to make your multiplication in place:

如果您的原始数据框如下所示:

If your Original dataframe looks like:

>>> df
          W         X         Y         Z
0  2.706850  0.628133  0.907969  0.503826
1  0.651118 -0.319318 -0.848077  0.605965
2 -2.018168  0.740122  0.528813 -0.589001
3  0.188695 -0.758872 -0.933237  0.955057
4  0.190794  1.978757  2.605967  0.683509

您可以使用:

df.loc[df['W'] < 1, 'W'] *= 2

导致的结果:

>>> df
          W         X         Y         Z
0  2.706850  0.628133  0.907969  0.503826
1  1.302236 -0.319318 -0.848077  0.605965
2 -4.036336  0.740122  0.528813 -0.589001
3  0.377390 -0.758872 -0.933237  0.955057
4  0.381588  1.978757  2.605967  0.683509

这等效于以下内容:

df.loc[df['W'] < 1, 'W'] = df.loc[df['W'] < 1, 'W'] * 2

这篇关于在 pandas 列上执行条件操作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！