Heatmaps are powerful tools for visualizing trends and outliers in data. Leveraging Python's Matplotlib library, this project demonstrates how to create a detailed heatmap similar to the one published by the Wall Street Journal to show the impact of vaccines on measles in the United States. The tutorial covers data preparation, handling missing values, creating custom color maps, and plotting the heatmap. Heatmaps are useful for comparing trends, showing temporal developments, and identifying patterns.
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