numpy sort arrays based on last column values

Question

import numpy as np

a = np.array([[5,9,44],
              [5,12,43],
              [5,33,11]])

b = np.sort(a,axis=0)

print(b) #not well

# [[ 5  9 11]
# [ 5 12 43]
# [ 5 33 44]]

#desired output:

#[[5,33,11],
# [5,12,43],
# [5,9,44]]

what numpy sort does it changes rows completely(ofcourse based on lower to highest), but i would like to keep rows untouched. I would like to sort rows based on last column value, yet rows and values in array must stay untouched. Is there any pythonic way to do this? Thanks

anishtain4 · Accepted Answer · 2018-06-15T16:42:39.627

11

ind=np.argsort(a[:,-1])
b=a[ind]

EDIT When you use axis in the sort, it sorts every column individually, what you want is to get indices of the sorted rows from the selected column (-1 is equivalent to the last column), and then reorder your original array.

edited Jun 15 '18 at 16:42

answered Jun 15 '18 at 16:25

anishtain4

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That was fast,thank you. – filtertips Jun 15 '18 at 16:27
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some further explanation would be great! – leoschet Jun 15 '18 at 16:28

t.. · Answer 2 · 2018-06-15T16:31:31.753

2

a[a[:,-1].argsort()]

may work for you

edited Jun 15 '18 at 16:31

answered Jun 15 '18 at 16:27

t..

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For accessing the last column, it's more robust to use `-1` as opposed to accessing from the front of a list, since the former scales to different shapes. – user3483203 Jun 15 '18 at 16:31

numpy sort arrays based on last column values

2 Answers2