how to search for unique elements by the first column of a multidimensional array

Question

I am trying to find a way how to create a new array from a multidimensional array by taking only elements that are unique in the first column, for example if I have an array

Answer 1

main = [[1, 2, 3], [1, 3, 4], [2, 4, 5], [3, 6, 5]]
used = []
new = [[sub, used.append(sub[0])][0] for sub in main if sub[0] not in used]
print(new)
# Output: [[1, 2, 3], [2, 3, 4], [3, 6, 5]]

Answer 2

Since you are looking to keep the first row of first column uniqueness, you can just use np.unique with its optional return_index argument which will give you the first occurring index (thus fulfils the first row criteria) among the uniqueness on A[:,0] elements, where A is the input array. Thus, we would have a vectorized solution, like so -

_,idx = np.unique(A[:,0],return_index=True)
out = A[idx]

Sample run -

In [16]: A
Out[16]: 
array([[1, 2, 3],
       [5, 2, 3],
       [1, 4, 3]])

In [17]: _,idx = np.unique(A[:,0],return_index=True)
    ...: out = A[idx]
    ...: 

In [18]: out
Out[18]: 
array([[1, 2, 3],
       [5, 2, 3]])