Novice in python!
A numpy array A of 1000 elements consists of fixed values between -100 to +100. These 201 values are nothing but categories. Another numpy array B has the approximations of the values for each category of A. Both A and B are of same length.
For example A=[-100, -100, -88, 87, 85, 32, 32, 32] and corresponding
B=[-100.3, -100.1, -86.5, 87.3, 85.5, 32.6,32.1,32.5]. I want to get the corresponding approximated data for each category. In the above example
for -100:-100.3, -100.1 for 32:32.1,32.6,32.5
I could not seem to get it working with dictionary and zipping
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Answer
You are on a good truck thinking about dictionaries and zip. What you really want is to iterrate through your A unique values and append values to a dict with keys these values. Using list comprehension it can be almost an one-liner. For example:
A = [-100, -100, -88, 87, 85, 32, 32, 32]
B = [-100.3, -100.1, -86.5, 87.3, 85.5, 32.6, 32.1, 32.5]
values_dict = {i: [] for i in set(A)} # Initialize dictionary with empty lists
[values_dict[pair[0]].append(pair[1]) for pair in zip(A, B)] # Append values to corresponding key.
print(values_dict)
Which prints:
{32: [32.6, 32.1, 32.5], -88: [-86.5], 85: [85.5], 87: [87.3], -100: [-100.3, -100.1]