如何通过ith字段的值对numpy数组进行切片? [英] How can I slice a numpy array by the value of the ith field?

问题描述

我有一个具有4列和很多行的2D numpy数组(> 10000，此数字是固定的).

I have a 2D numpy array with 4 columns and a lot of rows (>10000, this number is not fixed).

我需要通过其中一列的值创建 n 个子数组；我发现的最接近的问题是如何按列值分割Numpy数组；但是，我不知道该字段中的确切值(它们是浮点型的，它们在我需要的每个文件中都会更改)，但是我知道它们最多不超过20个.

I need to create n subarrays by the value of one of the columns; the closest question I found was How slice Numpy array by column value; nevertheless, I dont know the exact values in the field (they're floats and they change in every file I need), but I know they are no more than 20.

我想我可以逐行阅读，记录不同的值然后进行拆分，但是我认为有一种更有效的方法.

I guess I could read line by line, record the different values and then make the split, but I figure there is a more efficient way to do this.

谢谢.

推荐答案

您可以方便地使用多维切片:

You can use multidimensional slicing conveniently:

import numpy as np

# just creating a random 2d array.
a = (np.random.random((10, 5)) * 100).astype(int)
print a
print

# select by the values of the 3rd column, selecting out more than 50.
b = a[a[:, 2] > 50]

# showing the rows for which the 3rd column value is > 50.
print b

另一个例子，更接近您在评论(?)中的要求:

Another example, closer to what you are asking in the comment (?):

import numpy as np

# just creating a random 2d array.
a = np.random.random((10000, 5)) * 100
print a
print

# select by the values of the 3rd column, selecting out more than 50.
b = a[a[:, 2] > 50.0]
b = b[b[:, 2] <= 50.2]

# showing the rows for which the 3rd column value is > 50.
print b

这将选择第三列值为(50，50.2]的行.

This selects out rows for which the 3rd column values are (50, 50.2].

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