["python","arrays","numpy","unique"]
Find unique rows in numpy.array

I need to find unique rows in a numpy.array. For example: >>> a # I have array([[1, 1, 1, 0, 0, 0], [0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 0, 0], [1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0]]) >>> new_a # I want to get to array([[1, 1, 1, 0, 0, 0], [0, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 0]]) I know that i can create a set and loop over the array, but I am looking for an efficient pure numpy solution. I believe that there is a way to set data type to void and then I could just use numpy.unique, but I couldn't figure out how to make it work.
As of NumPy 1.13, one can simply choose the axis for selection of unique values in any N-dim array. To get unique rows, use np.unique as follows: unique_rows = np.unique(original_array, axis=0)