Python 计算二维数组中跨维度的平均值
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Calculate mean across dimension in a 2D array
提问by otmezger
I have an array alike this:
我有一个a这样的数组：
a = [[40, 10], [50, 11]]
I need to calculate the mean for each dimension separately, the result should be this:
我需要分别计算每个维度的平均值，结果应该是这样的：
[45, 10.5]
45being the mean of a[*][0]and 10.5the mean of a[*][1].
45是 的均值a[*][0]和10.5的均值a[*][1]。
What is the most elegant way of solving this without using a loop?
在不使用循环的情况下解决这个问题的最优雅的方法是什么？
回答by askewchan
a.mean()takes an axisargument:
a.mean()接受一个axis论点：
In [1]: import numpy as np
In [2]: a = np.array([[40, 10], [50, 11]])
In [3]: a.mean(axis=1) # to take the mean of each row
Out[3]: array([ 25. , 30.5])
In [4]: a.mean(axis=0) # to take the mean of each col
Out[4]: array([ 45. , 10.5])
Or, as a standalone function:
或者，作为一个独立的函数：
In [5]: np.mean(a, axis=1)
Out[5]: array([ 25. , 30.5])
The reason your slicing wasn't working is because this is the syntax for slicing:
您的切片不起作用的原因是因为这是切片的语法：
In [6]: a[:,0].mean() # first column
Out[6]: 45.0
In [7]: a[:,1].mean() # second column
Out[7]: 10.5
回答by NPE
回答by Andrew Clark
Here is a non-numpy solution:
这是一个非numpy的解决方案：
>>> a = [[40, 10], [50, 11]]
>>> [float(sum(l))/len(l) for l in zip(*a)]
[45.0, 10.5]
