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How can I make a scatter plot colored by density in Matplotlib?
We can create a dict for color and a value. If the same value comes up, we can use a scatter method and if the closer values have the same set of colors, that could make the plot color denser.
Create a new figure, or activate an existing figure.
Add an ~.axes.Axes to the figure as part of a subplot arrangement.
Get the x and y values using np.random.normal() method. Draw random samples from a normal (Gaussian) distribution.
Make a color list with red and blue colors.
To make it denser, we can store the same color with the same value.
Plot scatter point, a scatter plot of *y* vs. *x* with varying marker size and/or color.
Set the x-view limit.
Set the y-view limit.
To show the figure, use the plt.show() method.
import random import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(1, 1, 1) x = np.random.normal(0.5, 0.3, 10000) y = np.random.normal(0.5, 0.3, 10000) colors = ['red', 'blue'] color = dict() for i in x: if i not in color: color[i] = colors[random.randint(1, 10) % len(colors)] ax.scatter(x, y, c=[color.get(i) for i in x]) ax.set_xlim(-0.5, 1.5) ax.set_ylim(-0.5, 1.5) plt.show()
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