In this video, we go through several real-world examples of using the Matplotlib & Pandas libraries to visualize data from CSV files. This is a follow-up to my introductory matplotlib video ( Timeline for what we cover can be found in the comments.
We start by creating line graphs of global gas price data over time. We review how to add a title, x & y axis labels, and scale our graph. We review how to customize the style and size of our charts. Next, we look at the FIFA 19 player data to create a histogram, a couple pie charts, and a box and whisker plot.
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Link to Source Code & Datasets!
Matplotlib Style Options:
Kaggle Data Link:
0:00 – Intro & Video Overview
2:22 – Load Necessary Libraries & Download Data
3:48 – Line Graph Example (Plotting Data from CSV file)
21:52 – Histogram Example (FIFA Overall Skill Distribution)
29:25 – Pie Chart #1 (Counting data in CSV) – Visualizing Soccer Foot Preferences
36:41 – Pie Chart #2 (More advance Pandas Example) – Weight Distribution of FIFA Players
47:49 – Box & Whisker Plot (Comparing FIFA teams to one another)
1:00:37 – Final Comments
Equipment I use to film my videos (I get a small commission on purchases made through these links?)
– Sony a6500 Camera:
– Rokinon 12mm Lens:
– Rode Videomicro Microphone:
– Blue Snowball Microphone (alternate mic):
– Andycine Camera Monitor:
– Snagit for screen recording
– Adobe Premiere Pro for video editing
– Adobe Photoshop for thumbnails