[FIXED] Adding value to 2d numpy array based on condition

Issue

Having trouble manipulating a 2D numpy array (below). I'm using np.where to add a value if the given condition is met, but doesn't seem to be working. Is this simply not possible or am I making a simple mistake?

a = ['circle','square']
b=['north','south']
c=['red','blue']
d=['long','short']
x = []
for shape in a:
  for direction in b:
    for color in c:
      for length in d:
        x.append([shape, direction, color, length, 0])
x = np.array(x)

# conditional add - if condition is met, add 1 to numeric index, else assign value of 2
x[:,4] = np.where((x[:,0]=='circle') & (x[:,1]=='south'), x[:,4]+1, 2)

Solution

A solution would be to use indices instead of labels when creating your numpy array; that way it would be a numerical array and your last statement would work:

from itertools import product
import numpy as np

parameters = [
    ['circle', 'square'],
    ['north', 'south'],
    ['red', 'blue'],
    ['long', 'short'],
    ]

x = np.array(list(product(*map(lambda my_list: range(len(my_list)), parameters), [0])))

x[:,4] = np.where((x[:,0]==0) & (x[:,1]==1), x[:,4]+1, 2)

Answered By - Swifty