Generate larger synthetic dataset based on a smaller dataset in Python
So what T[i] is giving it is an array with shape (102, ).
What the function expects is an array with shape (1, 102).
You can get this by calling reshape on it:
nn = neigh.kneighbors(T[i].reshape(1, -1), return_distance=False)
In case you're not familiar with np.reshape, The 1 says that the first dimension should be size 1, and the -1 says that the second dimension should be what ever size numpy can broadcast it to; in this case the original 102.