numpy:按多种条件过滤行吗? [英] Numpy: Filtering rows by multiple conditions?
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问题描述
我有一个名为meta
的二维NumPy数组,具有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 :
- 检查前两列是否为零
- 检查第三列是否小于X
- 仅返回符合条件的行
我成功了,但是解决方案似乎非常人为:
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) ]
您能想到更清洁的方式吗?似乎很难同时具有多个条件;(
Could you think of cleaner way ? It seem hard to have multiple conditions at once ;(
谢谢
对不起,我第一次复制错误的表达式...已更正.
Sorry first time I copied the wrong expression... corrected.
推荐答案
您可以在一个切片中使用多个过滤器,如下所示:
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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