How to delete columns in numpy.array

bgbg_17523 0
Viewed 251805

I would like to delete selected columns in a numpy.array . This is what I do:

n [397]: a = array([[ NaN,   2.,   3., NaN],
   .....:        [  1.,   2.,   3., 9]])

In [398]: print a
[[ NaN   2.   3.  NaN]
 [  1.   2.   3.   9.]]

In [399]: z = any(isnan(a), axis=0)

In [400]: print z
[ True False False  True]

In [401]: delete(a, z, axis = 1)
Out[401]:
 array([[  3.,  NaN],
       [  3.,   9.]])

In this example my goal is to delete all the columns that contain NaN's. I expect the last command to result in:

array([[2., 3.],
       [2., 3.]])

How can I do that?

scipy numpy python
8 Answers

Given its name, I think the standard way should be delete:

import numpy as np

A = np.delete(A, 1, 0)  # delete second row of A
B = np.delete(B, 2, 0)  # delete third row of B
C = np.delete(C, 1, 1)  # delete second column of C

According to numpy's documentation page, the parameters for numpy.delete are as follow:

numpy.delete(arr, obj, axis=None)

  • arr refers to the input array,
  • obj refers to which sub-arrays (e.g. column/row no. or slice of the array) and
  • axis refers to either column wise (axis = 1) or row-wise (axis = 0) delete operation.
user_2083390

From Numpy Documentation

np.delete(arr, obj, axis=None) Return a new array with sub-arrays along an axis deleted.

>>> arr
array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12]])
>>> np.delete(arr, 1, 0)
array([[ 1,  2,  3,  4],
       [ 9, 10, 11, 12]])

>>> np.delete(arr, np.s_[::2], 1)
array([[ 2,  4],
       [ 6,  8],
       [10, 12]])
>>> np.delete(arr, [1,3,5], None)
array([ 1,  3,  5,  7,  8,  9, 10, 11, 12])
user_9979380
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