使用plt的scatter函数画带label的散点图，终于会了--

需确保matplot版本为3.4.2及以上

 

fig, ax = plt.subplots()
x = [1,2,3,4]
y = [1,1,1,1]
scatter = ax.scatter(x,y, marker='.', c=[1,2,3,4])
legend1 = ax.legend(*scatter.legend_elements(),loc="lower left", title="Classes")
ax.add_artist(legend1)
plt.show()

 

官方例子测试

volume = np.random.rayleigh(27, size=40)
amount = np.random.poisson(10, size=40)
ranking = np.random.normal(size=40)
price = np.random.uniform(1, 10, size=40)

fig, ax = plt.subplots()

# Because the price is much too small when being provided as size for ``s``,
# we normalize it to some useful point sizes, s=0.3*(price*3)**2
scatter = ax.scatter(volume, amount, c=ranking, s=0.3*(price*3)**2,
                     vmin=-3, vmax=3, cmap="Spectral")

# Produce a legend for the ranking (colors). Even though there are 40 different
# rankings, we only want to show 5 of them in the legend.
legend1 = ax.legend(*scatter.legend_elements(num=5),
                    loc="upper left", title="Ranking")
ax.add_artist(legend1)

# Produce a legend for the price (sizes). Because we want to show the prices
# in dollars, we use the *func* argument to supply the inverse of the function
# used to calculate the sizes from above. The *fmt* ensures to show the price
# in dollars. Note how we target at 5 elements here, but obtain only 4 in the
# created legend due to the automatic round prices that are chosen for us.
kw = dict(prop="sizes", num=5, color=scatter.cmap(0.7), fmt="$ {x:.2f}",
          func=lambda s: np.sqrt(s/.3)/3)
legend2 = ax.legend(*scatter.legend_elements(**kw),
                    loc="lower right", title="Price")

plt.show()

参考连接：

 matplotlib scatter的legend和edgecolors_iTom's blog-CSDN博客

Scatter plots with a legend — Matplotlib 3.5.1 documentation

用plt.scatter()画带label的散点图（无需循环，直接根据标签生成）