Inconsistent python print output

Question

(Python 2.7.12) - I have created an NxN array, when I print it I get the exact following output:

Sample a :

SampleArray=np.random.randint(1,100, size=(5,5))    
    [[49 72 88 56 41]
     [30 73  6 43 53]
     [83 54 65 16 34]
     [25 17 73 10 46]
     [75 77 82 12 91]]

• Nice and clean.

However, when I go to sort this array by the elements in the 4th column using the code:

SampleArray=sorted(SampleArray, key=lambda x: x[4])

I get the following output:

Sample b:

[array([90,  9, 77, 63, 48]), array([43, 97, 47, 74, 53]), array([60, 64, 97,  2, 73]), array([34, 20, 42, 80, 76]), array([86, 61, 95, 21, 82])]

How can I get my output to stay in the format of 'Sample a'. It will make debugging much easier if I can see the numbers in a straight column.

Answer 1

Simply with numpy.argsort() routine:

import numpy as np

a = np.random.randint(1,100, size=(5,5))
print(a)   # initial array
print(a[np.argsort(a[:, -1])])  # sorted array

The output for # initial array :

[[21 99 34 33 55]
 [14 81 92 44 97]
 [68 53 35 46 22]
 [64 33 52 40 75]
 [65 35 35 78 43]]

---

The output for # sorted array :

[[68 53 35 46 22]
 [65 35 35 78 43]
 [21 99 34 33 55]
 [64 33 52 40 75]
 [14 81 92 44 97]]

Answer 2

you just need to convert sample array back to a numpy array by using

SampleArray = np.array(SampleArray)

sample code:-

import numpy as np
SampleArray=np.random.randint(1,100, size=(5,5))    

print (SampleArray)
SampleArray=sorted(SampleArray, key=lambda x: x[4])
print (SampleArray)
SampleArray = np.array(SampleArray)
print (SampleArray)

output:-

[[28 25 33 56 54]
 [77 88 10 68 61]
 [30 83 77 87 82]
 [83 93 70  1  2]
 [27 70 76 28 80]]
[array([83, 93, 70,  1,  2]), array([28, 25, 33, 56, 54]), array([77, 88, 10, 68, 61]), array([27, 70, 76, 28, 80]), array([30, 83, 77, 87, 82])]
[[83 93 70  1  2]
 [28 25 33 56 54]
 [77 88 10 68 61]
 [27 70 76 28 80]
 [30 83 77 87 82]]

Answer 3

This can help:

from pprint import pprint
pprint(SampleArray)

The output is a little bit different from the one for Sample A but it still looks neat and debugging will be easier.

Edit: here's my output

[[92  8 41 64 61]
 [18 67 91 80 35]
 [68 37  4  6 43]
 [26 81 57 26 52]
 [ 6 82 95 15 69]]

[array([18, 67, 91, 80, 35]),
 array([68, 37,  4,  6, 43]),
 array([26, 81, 57, 26, 52]),
 array([92,  8, 41, 64, 61]),
 array([ 6, 82, 95, 15, 69])]