How can I color scatter markers in matplotlib based on a third variable using grayscale shading?

Coloring Scatter Markers Based on a Third Variable

In matplotlib, scatterplots can be used to visualize data points on a coordinate plane. Often, it is useful to differentiate the points based on a third variable. This can be achieved by using the c parameter in the plt.scatter() function, which specifies the color of each marker.

Grayscale Shading

To create a scatterplot where the points are shaded in grayscale according to a third variable, we can use a grayscale colormap. This can be achieved by setting the cmap argument in the plt.scatter() function to a grayscale colormap, such as 'gray' or 'gist_yarg'.

Example

Consider the following data:

w = np.random.random(10)
M = np.random.random(10)
p = np.random.random(10)  # Third variable for shading

To create a scatterplot where the points are shaded according to the values in p, we can use the following code:

import matplotlib.pyplot as plt

plt.scatter(w, M, c=p, s=500, cmap='gray')
plt.show()

This will generate a scatterplot where the markers are shaded according to the values in p, with lighter shades corresponding to smaller values and darker shades corresponding to larger values.

Alternative Colormaps

If desired, other grayscale colormaps can be used by specifying their names as the cmap argument. A list of available colormaps can be found in the matplotlib documentation. By experimenting with different colormaps, you can customize the visualization to best suit your needs.

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