Скачать или смотреть Univariate and Bivariate Data Analysis and Visualization: League of Legends Vision Score

In this video, I use a histogram with a KDE (Kernel Density Estimate), swarm plot, box plot, and violin plot to show the univariate analysis of the distribution of the vision score difference in 2000 ranked League of Legends games, and also see how vision score affects the outcome of the game with the latter 3 types of plots.
Data analysis and visualization are crucial parts of supervised machine learning, and the techniques gone over in this video can be carried to other fields.
I used Kaggle.com's League of Legends Diamond Ranked Games (10 min) dataset, which can be found here:
https://www.kaggle.com/bobbyscience/l...

Timestamps:
00:00 Introduction to Dataset
00:38 Reading in the data and printing out 10 samples
00:52 Cutting down the size of the dataset and looking at features
01:40 Creating a new ward_diff feature to analyze vision score difference
02:18 Importing matplotlib.pyplot and seaborn
02:27 Histogram with KDE (Kernel Density Estimate)
04:32 Swarm Plot
07:24 Box Plot
08:30 Violin Plot