How to Manipulate Arrays Using NumPy's Reshape Function

This tutorial teaches you how to use the NumPy np.reshape() method. Learn NumPy reshape() by following our step-by-step code and examples.

NumPy is the most popular Python library for numerical and scientific computing.

NumPy's most important capability is the ability to use NumPy arrays, which is its built-in data structure for dealing with ordered data sets.

The np.reshape function is an import function that allows you to give a NumPy array a new shape without changing the data it contains. In this tutorial, I will teach you how to use the NumPy reshape function to manipulate arrays in NumPy.

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Learn numpy features to see why you should use numpy - high performance, multidimensional container, broadcasting functions, working with varied databases

Learn the uses of numpy - Alternate for lists in python, multi dimensional array, mathematical operations. See numpy applications with python libraries.

Learn NumPy Copy and View - Deep Copy, shallow copy and No copy in NumPy, NumPy view creation and types with examples, NumPy View vs Copy

Python is an open-source object-oriented language. It has many features of which one is the wide range of external packages. There are a lot of packages for installation and use for expanding functionalities. These packages are a repository of functions in python script. NumPy is one such package to ease array computations.

Learn about NumPy Array, NumPy Array creation, various array functions, array indexing & Slicing, array operations, methods and dimensions,It also includes array splitting, reshaping, and joining of arrays. Even the other external libraries in Python relate to NumPy arrays.