How to delete specific rows from a numpy array using a condition?

Question

This is the code

a = np.array([[ 0,  1],
              [ 3, 11],
               [4,2]])

This is what I tried

a= a[a[0]>0,:]

It works fine when I only have two elements, but anything more it throws an error.What I am trying to do is that in the first column if there's a value less than one than I need to delete that entire row.

so the expected output is

     ([ 3, 11],
     [4,2]])

I was hoping for a solution which I could generalize even if there were more than 2 elements per item such as

    ([2,3,4,5],
     [8,2,4,6],
     [2,4,9,1],
     [5,3,2,0],)

then the application of the code will give a result such as

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

Any suggestions.

Padraic Cunningham · Accepted Answer · 2016-02-01 20:26:03Z

6

For just the first column use a[:,0] > 0 which will pull all the values from the first column and check which are > 0 or whatever condition you want:

 In [50]: a = np.array([[ 0,  1],
              [ 3, 11],
               [4,2]])

In [51]: a[a[:,0] > 0]
Out[51]: 
array([[ 3, 11],
       [ 4,  2]])

You can use all if you want to check all values in each row:

In [43]: a = np.array([[ 0,  1],
              [ 3, 11],
               [4,2]])

In [44]: a[(a >= 0).all(axis=1)]
Out[44]: 
array([[ 3, 11],
       [ 4,  2]])

In [45]: a = np.array ([[2,3,4,5],
                       [8,2,4,6],
                       [2,4,9,1],
                        [5,3,2,0]])

In [46]: a[(a > 0).all(axis=1)]
Out[46]: 
array([[2, 3, 4, 5],
       [8, 2, 4, 6],
       [2, 4, 9, 1]])

edited Feb 1, 2016 at 20:26

answered Feb 1, 2016 at 20:19

Padraic Cunningham

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1 Comment

Amit Singh Parihar Over a year ago

Thank you! That's exactly what I was looking for. I like the explanation for the first part as well.

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