numpy sort arrays based on last column values [duplicate]

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 · 2018-06-15 16:42:39Z

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, 2018 at 16:42

answered Jun 15, 2018 at 16:25

anishtain4

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2 Comments

filtertips Over a year ago

That was fast,thank you.

leoschet Over a year ago

some further explanation would be great!

t.. · Accepted Answer · 2018-06-15 16:31:31Z

2

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

may work for you

edited Jun 15, 2018 at 16:31

answered Jun 15, 2018 at 16:27

t..

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1 Comment

user3483203 Over a year ago

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.

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