Data Analytics using Python Visualizations - Creating Heatmaps

The video tutorial introduces heat maps as a visualization tool to compare the intensity of relationships between attributes, using car sales data as an example. It explains the concept of correlation, highlighting how attributes like engine size and horsepower are related. The tutorial demonstrates how to statistically measure these correlations and visualize them using heat maps, emphasizing the color scheme for positive and negative correlations. Finally, it provides a practical example of generating a heat map from car sales data, encouraging viewers to experiment with different datasets.

What are some of the attributes of cars mentioned in the data file?

How can one interpret a correlation coefficient of -0.72?

What steps are involved in generating a heat map from the car sales data?