python - mask a 2D numpy array based on values in one column

Question

Suppose I have the following numpy array:

a = [[1, 5, 6],
     [2, 4, 1],
     [3, 1, 5]]

I want to mask all the rows which have 1 in the first column. That is, I want

   [[--, --, --],
     [2, 4, 1],
     [3, 1, 5]]

Is this possible to do using numpy masked array operations? How can one do it?

Thanks.

Answer 1

import numpy as np

a = np.array([[1, 5, 6],
              [2, 4, 1],
              [3, 1, 5]])

np.ma.MaskedArray(a, mask=(np.ones_like(a)*(a[:,0]==1)).T)

# Returns: 
masked_array(data =
 [[-- -- --]
 [2 4 1]
 [3 1 5]],
             mask =
 [[ True  True  True]
 [False False False]
 [False False False]])