How to Color Scatter Markers Based on a Third Variable in Python?

How to Color Scatter Markers Based on a Third Variable

The scatterplot, a powerful visualization tool in matplotlib, allows you to explore relationships between variables. In some cases, you may want to shade the points in a scatterplot according to a third variable to reveal additional patterns or insights.

To color scatter markers based on a third variable, you can utilize the c parameter of the scatter function. This parameter controls the color of each point, allowing you to map values of the third variable to specific colors.

For instance, consider a scatterplot where you want to shade the points based on their corresponding p values:

plt.scatter(w, M, c=p, marker='s')

Here, w and M are the data points being plotted, and p is the third variable you want to use for coloring. However, this code will color the markers using the default colormap, which may not be suitable if you want to create a grayscale representation.

To specify grayscale colors, you can use either the gray() function or provide a grayscale colormap to the cmap parameter of the scatter function:

# Gray out the colors
plt.scatter(w, M, c=p, marker='s')
plt.gray() 

# Specify a grayscale colormap
plt.scatter(x, y, c=y, s=500, cmap='gray')

The gray() function simply converts the current colors to grayscale, while using a grayscale colormap allows you to choose from a wider range of pre-made grayscale representations. By employing these techniques, you can effectively shade scatter markers based on a third variable, providing additional context and understanding to your data visualization.

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