Suppose my data is organized in the following way:
x_values = [6.2, 3.6, 7.3, 3.2, 2.7]
y_values = [1.5, 3.2, 5.4, 3.1, 2.8]
colours = [1, 1, 0, 1, -1]
label
Just a remark, not exactly answering the question:
If use "seaborn" it would be EXACTLY ONE LINE:
import seaborn as sns
x_values = [6.2, 3.6, 7.3, 3.2, 2.7]
y_values = [1.5, 3.2, 5.4, 3.1, 2.8]
#colors = [1, 1, 0, 1, -1]
labels = ["a", "a", "b", "a", "c"]
ax = sns.scatterplot(x=x_values, y=y_values, hue=labels)
PS
But the question is about matplotlib, so. We have answers above, also one might look at: https://matplotlib.org/3.1.1/gallery/lines_bars_and_markers/scatter_with_legend.html Subsection: "Automated legend creation".
However I feel not easy to modify those examples to what you need.
You can always make your own legend as follows:
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
x_values = [6.2, 3.6, 7.3, 3.2, 2.7]
y_values = [1.5, 3.2, 5.4, 3.1, 2.8]
a = 'red'
b = 'blue'
c = 'yellow'
colours = [a, a, b, a, c]
labels = ["a", "a", "b", "a", "c"]
axis = plt.gca()
axis.scatter(x_values, y_values, c=colours)
# Create a legend
handles = [mpatches.Patch(color=colour, label=label) for label, colour in [('a', a), ('b', b), ('c', c)]]
plt.legend(handles=handles, loc=2, frameon=True)
plt.show()
Which would look like:
If you want to use a colormap you can create a legend entry for each unique entry in the colors
list as shown below. This approach works well for any number of values. The legend handles are the markers of a plot
, such that they match with the scatter points.
import matplotlib.pyplot as plt
x_values = [6.2, 3.6, 7.3, 3.2, 2.7]
y_values = [1.5, 3.2, 5.4, 3.1, 2.8]
colors = [1, 1, 0, 1, -1]
labels = ["a", "a", "b", "a", "c"]
clset = set(zip(colors, labels))
ax = plt.gca()
sc = ax.scatter(x_values, y_values, c=colors, cmap="brg")
handles = [plt.plot([],color=sc.get_cmap()(sc.norm(c)),ls="", marker="o")[0] for c,l in clset ]
labels = [l for c,l in clset]
ax.legend(handles, labels)
plt.show()