The shape property is usually used to get the current shape of an array, but may also be used to reshape the array in-place by assigning a tuple of array dimensions to it.

NumPy arrays have an attribute called shape that returns a tuple with each index having the number of corresponding elements. Print the shape of a 2-D array: The example above returns …

Jul 15, 2025 · In this example, two NumPy arrays arr1 and arr2 are created, representing a 2D array and a 3D array, respectively. The shape of each array is printed, revealing their …

May 8, 2025 · Learn how to use NumPy shape in Python to understand and manipulate array dimensions. Examples with real-world data, reshaping techniques, and common solutions.

Nov 30, 2017 · For a 1D array, the shape would be (n,) where n is the number of elements in your array. For a 2D array, the shape would be (n,m) where n is the number of rows and m is the …

Apr 23, 2025 · You can get the number of dimensions, the shape (length of each dimension), and the size (total number of elements) of a NumPy array (numpy.ndarray) using the ndim, shape, …

Feb 13, 2025 · To get the shape of a Python NumPy array use numpy.ndarray.shape property. The array shape can be defined as the number of elements in each dimension and dimension …

Aug 28, 2025 · It returns a tuple of integers, where each integer represents the size of the array along a corresponding dimension. For example, a 2D array's shape would be (rows, columns).

You can access the shape of a NumPy array using the shape attribute. This attribute returns a tuple of integers, each representing the size of the array along a particular dimension.

Mar 4, 2025 · Learn how to determine the shape and size of arrays in Python using NumPy's shape () and size () functions. This article provides clear examples, detailed explanations, and …