Create legend for scatter plot using the label of the samples in matplotlib

Question

I am using scatter plot in matplotlib to plot some points. I have two 1D arrays each storing the x and y coordinate of the samples. Also there is another 1D array that stores the label(to decide in which colour the point should be plotted). I programmed thus far:

import matplotlib.pyplot as plt
X = [1,2,3,4,5,6,7]
Y = [1,2,3,4,5,6,7]
label = [0,1,4,2,3,1,1]
plt.scatter(X, Y, c= label, s=50)
plt.show()

Now I want to be able to see which color corresponds to which label? I looked up the implementation of legends in matplotlib like the one here: how to add legend for scatter()? However they are suggesting to create a plot for each label of sample. However all my labels are in the same 1D array(label). How can I achieve this?

Answer 1

You could do it with a colormap. Some examples of how to do it are here.

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.colors as colors
X = [1,2,3,4,5,6,7]
Y = [1,2,3,4,5,6,7]
label = [0,1,4,2,3,1,1]

# Define a colormap with the right number of colors
cmap = plt.cm.get_cmap('jet',max(label)-min(label)+1)

bounds = range(min(label),max(label)+2)
norm = colors.BoundaryNorm(bounds, cmap.N)

plt.scatter(X, Y, c= label, s=50, cmap=cmap, norm=norm)

# Add a colorbar. Move the ticks up by 0.5, so they are centred on the colour.
cb=plt.colorbar(ticks=np.array(label)+0.5)
cb.set_ticklabels(label)

plt.show()

You might need to play around to get the tick labels centred on their colours, but you get the idea.