Creating Arrays (ndarray):
>>> a = np.array([42,56,98,77])
>>> a
array([42, 56, 98, 77])
>>> a = np.array([42,56,98,77], float)
>>> x = np.array(42)
>>> x
array(42)
>>> np.array([1, 1, 2, 3, 5, 8, 13, 21])
array([ 1, 1, 2, 3, 5, 8, 13, 21])
>>> np.array([3.4, 6.9, 99.8, 12.8])
Array([ 3.4, 6.9, 99.8, 12.8])
>>> A = np.array([ [3.4, 8.7, 9.9], [1.1, -7.8, -0.7], [4.1, 12.3, 4.8]])
>>> A
array([[ 3.4, 8.7, 9.9],
[ 1.1, -7.8, -0.7],
[ 4.1, 12.3, 4.8]])
optional
Arrays are the central component of NumPy.
The data object „ndarray“ is an n-dimensional array object in NumPy.
In contrast to Python lists, elements of an narray have to be homogeneous, i.e. all elements are of the same type: float or int.