Mastering Matplotlib Scatter Plots: Bubble Charts, Colormaps, and Alpha Blending in Python
@MattMacarty
*matplotlib is the de facto standard for data visualization with Python.* While there are many other graphics libraries available, almost every one of them is a wrapper around the Matplotlib library. Visualization with Matplotlib can be tedious and daunting if you don't know the basics.
This video covers a number of basic settings and capabilities through examples of *scatter plots**—one of the fundamental data analysis tools for discovering relationships between variables. We move beyond the basics by demonstrating techniques to add **dimensionality, colormaps, bubble charts,* and *alpha blending* to visualize *stock correlation* using real financial data.
Introduces how to create effective scatter plots using Matplotlib in Python. You'll learn the basics, including setting themes and adding color maps, demonstrated step-by-step in a Jupyter Notebook. This python tutorial further shows how to customize plots for better data visualization, enhancing your programming skills.
Almost all of the techniques shown can be used in any visualization you make.
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*Video Chapters:*
0:00 Introduction: The Power of Scatter Plots
0:29 Environment Setup & Importing Real Financial Data
1:33 Calculating Instantaneous Rate of Return
2:47 Base Scatter Plot: Google Returns vs. Amazon Returns
3:42 Adding Horizontal/Vertical Guide Lines
5:15 Adding a Third Variable with Color Map (CMAP)
6:21 Applying a Seaborn Style Theme
8:31 Creating a Bubble Chart (Using the 's' Size Parameter)
10:33 Solving Data Overplotting with the Alpha Parameter
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*🔗 Resources & Tutorials:*
Download Jupyter notebook here and see other tutorials: https://alphabench.com/data/python-ma...
You may also be interested in: • Matplotlib Line Plots: Visualize Stock Pri...
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#python #matplotlib #scatterplot #datavisualization #bubblechart #pythonfinance #stockcorrelation #dataanalysis #alphablending
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