Python: mask a numpy.ndarray with another numpy.ndarray with elegant solution

Question

I have two numpy.ndarray and i found a not elegant solution (using more than 4 lines code) to mask the data2 with data1. I am asking an elegant solution, saving line to do:

example.

data1 = np.array([[1,2,np.nan,4,5],[np.nan,7,np.nan,9,np.nan],[11,12,13,14,np.nan],[np.nan,17,np.nan,19,20]])
data2 = np.ones((6, 4))

print data1
[[  1.   2.  nan   4.   5.]
 [ nan   7.  nan   9.  nan]
 [ 11.  12.  13.  14.  nan]
 [ nan  17.  nan  19.  20.]]
>>> print data2
[[ 1.  1.  1.  1.]
 [ 1.  1.  1.  1.]
 [ 1.  1.  1.  1.]
 [ 1.  1.  1.  1.]
 [ 1.  1.  1.  1.]
 [ 1.  1.  1.  1.]]

the result i wish to have is:

[[  1.   2.  1   4.   5.]
 [ 1   7.  1   9.  1]
 [ 11.  12.  13.  14.  1]
 [ 1  17.  1  19.  20.]]

in other words, where data1 is nan the value of data2

Thanks in advance for help and suggestions. I did this with more than 4 lines of code

ljk07 · Accepted Answer · 2012-10-05 16:59:56Z

2

Assuming you mean to have data1 and data2 as arrays of the same size (which would change your example to read):

data2 = np.ones((4, 5))

A one line approach is:

data1[np.isnan(data1)] = data2[np.isnan(data1)]

answered Oct 5, 2012 at 16:59

ljk07

9625 silver badges14 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

Python: mask a numpy.ndarray with another numpy.ndarray with elegant solution

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related