CODEWITHSUNDEEP
pythonnumpy
Benjamin Stewart
Benjamin Stewart

Reputation: 35

Numpy unique with expected unique values

I am trying to process the results of a numpy.unique calculation based on an expected set of unique values - the code below demonstrates what I want. Essentially, I want to have values of 0 when an expected unique value is not found.

import numpy

unqVals = [1,2,3,4,5,6]

x = [1,1,1,2,2,2,3,3,4,4,6,6]
y = [1,1,2,2,3,3,4,4,5,5,6,6]
z = [1,1,2,2,2,3,3,3,3,4,4,5]

for cur in [x,y,z]:
    xx = numpy.unique(cur, return_counts=True)
    print xx[1]

''' Current Results
[3 3 2 2 2]
[2 2 2 2 2 2]
[2 3 4 2 1]

Desired Results - based on the unqVals definition 
[3 3 2 2 0 2]
[2 2 2 2 2 2]
[2 3 4 2 1 0]
'''

Upvotes: 1

Views: 81

Answers (1)

Aritesh
Aritesh

Reputation: 2103

This will work - 

from collections import Counter

unqVals = [1,2,3,4,5,6]

x = [1,1,1,2,2,2,3,3,4,4,6,6]
y = [1,1,2,2,3,3,4,4,5,5,6,6]
z = [1,1,2,2,2,3,3,3,3,4,4,5]

for cur in [x,y,z]:
    xx = dict(Counter(cur))
    print [xx.get(i, 0) for i in unqVals ]

Upvotes: 1

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