标准化 pandas 中的数据 [英] Normalize data in pandas

问题描述

假设我有一个熊猫数据框df:

Suppose I have a pandas data frame df:

我想计算数据框的列均值.

I want to calculate the column wise mean of a data frame.

这很简单:

df.apply(average) 

然后是列式范围 max(col) - min(col).这又很简单:

then the column wise range max(col) - min(col). This is easy again:

df.apply(max) - df.apply(min)

现在对于每个元素，我想减去其列的平均值并除以其列的范围.我不知道该怎么做

Now for each element I want to subtract its column's mean and divide by its column's range. I am not sure how to do that

非常感谢任何帮助/指示.

Any help/pointers are much appreciated.

推荐答案

In [92]: df
Out[92]:
           a         b          c         d
A  -0.488816  0.863769   4.325608 -4.721202
B -11.937097  2.993993 -12.916784 -1.086236
C  -5.569493  4.672679  -2.168464 -9.315900
D   8.892368  0.932785   4.535396  0.598124

In [93]: df_norm = (df - df.mean()) / (df.max() - df.min())

In [94]: df_norm
Out[94]:
          a         b         c         d
A  0.085789 -0.394348  0.337016 -0.109935
B -0.463830  0.164926 -0.650963  0.256714
C -0.158129  0.605652 -0.035090 -0.573389
D  0.536170 -0.376229  0.349037  0.426611

In [95]: df_norm.mean()
Out[95]:
a   -2.081668e-17
b    4.857226e-17
c    1.734723e-17
d   -1.040834e-17

In [96]: df_norm.max() - df_norm.min()
Out[96]:
a    1
b    1
c    1
d    1

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