Efficient way to count frequency of values in an array while keeping the space if no element value exists

Question

I have this large 1d NumPy array that has the values between [0, 6]. For example, suppose A = [0, 0, 2, 4, 4]

I want to create a array using A: B = [2, 0, 1, 0, 2, 0, 0]

This is because there are 2 0s in the A, 0 1s in A, 1 2s in A, 0 3s in A, 2 4s in A, 0 5s in A, 0 6s in A.

Kindly suggests to me an efficient method is to do this.

Answer 1

Try the np.bincount

In [944]: np.bincount(A, minlength=7)

Out[944]: array([2, 0, 1, 0, 2, 0, 0], dtype=int64)

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