Numpy shape function for single dimension array
Question:
I’ve started to learn NumPy, when I create an array and then invoke the .shape function, I understand how it works for most cases. However, the result does not make sense to me for a single-dimensional array. Can someone please explain the outcome?
array = np.array([4,5,6])
print(array.shape)
The outcome is (3,)
Answers:
Output tulpe of ints in the "np.shape" function gives the lengths of the corresponding array dimension, and this tuple will be (n,m), in which n and m indicate row and columns, respectively. For a single dimension array, this Tuple will be just (n,), in which n indicates the number of array elements.
I’ve started to learn NumPy, when I create an array and then invoke the .shape function, I understand how it works for most cases. However, the result does not make sense to me for a single-dimensional array. Can someone please explain the outcome?
array = np.array([4,5,6])
print(array.shape)
The outcome is (3,)
Output tulpe of ints in the "np.shape" function gives the lengths of the corresponding array dimension, and this tuple will be (n,m), in which n and m indicate row and columns, respectively. For a single dimension array, this Tuple will be just (n,), in which n indicates the number of array elements.