Ave Coders! In this video, we will look at how you can represent our data graphically. We will cover the most popular plots such as scatter plots, histograms, heatmaps, violin plots, kernel density plots, barplots, and so on. Github: Time-stamps: 0:00 , seaborn 0:28 %matplotlib inline 0:55 working with csv tables (Comma Separated Values) 1:05 dataset repositories: UCI, Center for Machine Learning and Intelligent Systems 2:02 csv-table, read_csv(), head() (first 5 records) 2:33 () - basic stats 3:00 picking records to plot 4:13 () basic plot 5:28 - checking on styles 7:30 colors 9:40 importing table from github 12:33 matplotlib - Matlab-style, OOP-style 13:15 13:35 xlabel, ylabel , title, fontsize 14:16 xticks, yticks(fontsize) 14:30 OOP-style: fig, axes = (nrows = 1, ncons = 1) 16:24 grids Matlab-style 17:20 grid OOP-style 18:00 setting grid style:seaborn 18:25 l
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