Data manipulation in Python is nearly synonymous with Numpy array manipulation, even newer tools like Pandas are built around the Numpy array. This section will present several examples using Numpy and manipulation to access data and subarrays, and to split, reshape and join arrays.
Let’s start by defining three random arrays: a one-dimensional, two-dimensional, and three dimensional array. We’ll use Numpy’s random number generator, which we will seed with a set value in order to ensure that the same random arrays are generated each time this code is run.

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