array ((( 1, 2, 3 ), ( 4, 5, 6 ))) # Define a rank 2 array using a nested tupleį = np. array (( 1, 2, 3 )) # Define a rank 1 array using a tupleĮ = np. array (, ]) # Define a rank 2 array (matrix) using a nested list array (]) # Define a rank 2 array (vector) using a nested listĬ = np. Print ( a, a, a ) # Prints (1, 2, 3)Ī = 5 # Change an element of the arrayī = np. size ) # Prints 3 equivalent to "np.prod(a.shape)" ndim ) # Prints 1 (the rank of the array) equivalent to "len(a.shape)" array () # Define a rank 1 array using a list We can initialize NumPy arrays from (nested) lists and tuples, and access elements using square brackets as array subscripts (similar to lists in Python).The size of an array is the number of elements it contains (which is equivalent to np.prod(.shape), i.e., the product of the array’s dimensions).The shape of an array is a tuple of integers giving the size of the array along each dimension.The rank of an array is the number of dimensions it contains.A NumPy array is a grid of values, all of the same type, and is indexed by a tuple of non-negative integers. ![]()
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