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Moreover, 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 dimensions and sizes along each dimension. This aspect of Numpyshape Numpy V23 Manual plays a vital role in practical applications.

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Furthermore, 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 (2, 4), which means that the array has 2 dimensions, where the first dimension has 2 elements and the second has 4. This aspect of Numpyshape Numpy V23 Manual plays a vital role in practical applications.

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Furthermore, the numpy.shape attribute is a fundamental and essential part of working with NumPy arrays. It provides valuable information about the dimensions of an array, which can be used for reshaping, iterating, and performing various operations on the array. This aspect of Numpyshape Numpy V23 Manual plays a vital role in practical applications.

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