Numpy where for 2 dimensional array

Question

I have a 2 d numpy array. I need to keep all the rows whose value at a specific column is greater than a certain number. Right now, I have:

f_left = np.where(f_sorted[:,attribute] >= split_point)

And it is failing with: "Index Error: too many indices for array"

How should I do this? I can't figure it out from the numpy website, here

Can you post sample data: This works fine with a simple case where attribute = 0, split_point = 2, and f_sorted = np.arange(20).reshape((2, 10)). — Alex Huszagh
– Alex Huszagh, Commented Feb 19, 2016 at 1:34

Garrett R · Accepted Answer · 2016-02-19 01:42:17Z

4

You actually don't even need where.

    yy = np.array(range(12)).reshape((4,3))


    yy[yy[:,1] > 2]

Output

array([[ 3,  4,  5],
       [ 6,  7,  8],
       [ 9, 10, 11]])

answered Feb 19, 2016 at 1:42

Garrett R

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AGS · Accepted Answer · 2016-02-19 01:36:57Z

3

x = np.array([[2,3,4],[5,6,7],[1,2,3],[8,9,10]])

array([[ 2,  3,  4],
       [ 5,  6,  7],
       [ 1,  2,  3],
       [ 8,  9, 10]])

Find the rows where the second element are >=4

x[np.where(x[:,1] >= 4)]

array([[ 5,  6,  7],
       [ 8,  9, 10]])

answered Feb 19, 2016 at 1:36

AGS

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Awesome, thanks...I would not have gotten there (new to python last semester)