NumPy Argsort vs Sort
What are NumPy Argsort and Sort? In 2023, a world of data analysis, NumPy is a powerful library that provides efficient numerical operations in Python. When it comes to sorting arrays, NumPy offers two primary methods: argsort (np.argsort()) and sort (np.sort()). But what exactly are the differences between these two methods, and when should you choose one over the other?
In this informative video, I dive deep into the functionalities of NumPy's argsort and sort methods, explaining their contrasting behaviors and use cases. Firstly, I examine the sort method, which directly modifies the original array, rearranging its elements in ascending order. Next, I explore the argsort method, which returns the indices that would sort an array. This means that instead of sorting the actual array elements, argsort provides the indices in the sorted order. We delve into the syntax and demonstrate how to use them. NumPy Argsort vs Sort (Simply Explained)
Code used in this video:
import numpy as np
Data: Grades
grades = np.array([87, 95, 93, 91, 82])
names = np.array(["Alice", "Charlie", "Grace", "Bob", "Lukas"])
top_2 = names[np.argsort(grades)[::-1]][:2]
print(top_2)
Timestamps:
00:00 - Intro
01:58 - Example
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