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Essentials of NumPy arrays

Essentials of NumPy arrays - Python Tutorial

From the course: More Python Tips, Tricks, and Techniques for Data Science

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Essentials of NumPy arrays

- [Instructor] In this video, we're going to talk about some very important and basic operations of NumPy. Now, NumPy is short for Numerical Python, which provides an efficient interface to store and operate on dense data buffers. Now, starting from the basics, we'll see how to create NumPy arrays, use their attributes to learn about ndarray object, then we'll look at indexing and slicing to access sub-arrays. So, first off, we'll import the NumPy package as np, as per the convention. Then it's very important and very basic to create NumPy arrays. So, in some ways, NumPy arrays are like Python's built-in list type, but NumPy arrays provide much more efficient storage and data operations as the array grows larger in size. So let's say if... The first method is very simple, so we can use the Python list to create NumPy arrays. So let's say I create a list with elements three, comma, four, comma, five, and then I can…

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