如何在无需手动定义每种颜色的情况下拥有较大的matplotlib颜色图？

Question

I have a bunch of data I want to graph. Right now, there are 500 possible values. I want to color the data based on value. To draw a scatterplot now, I use the following for plt.scatter:

c = colormap = np.array(['red', 'lime', 'black'])

Hardcoding 500 colors in that np.array seems impractical.

plt.scatter(pandaframe['WIDTH'], pandaframe['LENGTH'], c=colormap[model.labels_], s=40)

Is there a way I can make it so that I can get 500 different colors without having to hardcode the colormap?

Answer 1

If you don't mind using built-in colormaps, you can find guidance here . To use it, your c should be your 500 possible values which determines corresponding color. Use cmap to specify which colormap you want to use. You can also draw a colorbar to give an idea about the colormap. A simple complete example:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(500)
y = x.copy()
np.random.shuffle(x)

plt.scatter(x, y, c=y, cmap='summer')
plt.colorbar()
plt.show()