Numpy:按多个条件过滤行?

Numpy: Filtering rows by multiple conditions?(Numpy:按多个条件过滤行?)

问题描述

我有一个名为 meta 的二维 numpy 数组，它有 3 列.我想要做的是:

I have a two-dimensional numpy array called meta with 3 columns.. what I want to do is :

1. 检查前两列是否为零
2. 检查第三列是否小于 X
3. 只返回符合条件的行

我做到了，但解决方案似乎很做作:

I made it work, but the solution seem very contrived :

meta[ np.logical_and( np.all( meta[:,0:2] == [0,0],axis=1 ) , meta[:,2] < 20) ]

你能想出更清洁的方法吗?似乎很难同时拥有多个条件；(

Could you think of cleaner way ? It seem hard to have multiple conditions at once ;(

谢谢

对不起，我第一次复制了错误的表达方式……已更正.

Sorry first time I copied the wrong expression... corrected.

推荐答案

你可以在一个切片中使用多个过滤器，像这样:

you can use multiple filters in a slice, something like this:

x = np.arange(90.).reshape(30, 3)
#set the first 10 rows of cols 1,2 to be zero
x[0:10, 0:2] = 0.0
x[(x[:,0] == 0.) & (x[:,1] == 0.) & (x[:,2] > 10)]
#should give only a few rows
array([[  0.,   0.,  11.],
       [  0.,   0.,  14.],
       [  0.,   0.,  17.],
       [  0.,   0.,  20.],
       [  0.,   0.,  23.],
       [  0.,   0.,  26.],
       [  0.,   0.,  29.]])

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