Data Preparation

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NumPy is short for Numerical Python. It is a fundamental open-source library in Python for data analysis and scientific computing. It provides powerful n-dimensional arrays, fast numerical processing,…

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An ndarray is the core n-dimensional array data structure of NumPy. It is often simply called an array. Its elements are of the same data type and are stored contiguously in memory, which makes proces…

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NumPy arrays are faster because their elements are stored in contiguous memory locations and all elements have the same data type. Python lists are heterogeneous and are not stored contiguously, so th…

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A Python list is a core Python data structure and can store different data types. A NumPy array is part of the NumPy library and stores only one data type in all elements. Arrays are faster and more m…

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Zero based indexing means the first element of an array is accessed using index 0, the second using index 1, and so on. This is the standard indexing convention used in NumPy arrays.

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ndarray.ndim gives the number of dimensions of the array. A 1-D array has one dimension, a 2-D array has two dimensions, and so on.

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ndarray.shape gives the sequence of integers showing the size of the array in each dimension. For example, a 2-D array may have shape like (3, 2), meaning 3 rows and 2 columns.

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ndarray.size gives the total number of elements in the array. It is equal to the product of the values in shape.