Adding second legend to scatter plot

问题

Is there a way to add a secondary legend to a scatterplot, where the size of the scatter is proportional to some data?

I have written the following code that generates a scatterplot. The color of the scatter represents the year (and is taken from a user-defined df) while the size of the scatter represents variable 3 (also taken from a df but is raw data):

import pandas as pd 

colors = pd.DataFrame({'1985':'red','1990':'b','1995':'k','2000':'g','2005':'m','2010':'y'}, index=[0,1,2,3,4,5])

fig = plt.figure()
ax = fig.add_subplot(111)

for i in df.keys():
    df[i].plot(kind='scatter',x='variable1',y='variable2',ax=ax,label=i,s=df[i]['variable3']/100, c=colors[i])

ax.legend(loc='upper right')
ax.set_xlabel("Variable 1")
ax.set_ylabel("Variable 2")

This code (with my data) produces the following graph:

So while the colors/years are well and clearly defined, the size of the scatter is not.

How can I add a secondary or additional legend that defines what the size of the scatter means?

回答1:

You will need to create the second legend yourself, i.e. you need to create some artists to populate the legend with. In the case of a scatter we can use a normal plot and set the marker accordingly. This is shown in the below example. To actually add a second legend we need to add the first legend to the axes, such that the new legend does not overwrite the first one.

import matplotlib.pyplot as plt
import matplotlib.colors
import numpy as np; np.random.seed(1)
import pandas as pd
plt.rcParams["figure.subplot.right"] = 0.8
v = np.random.rand(30,4)
v[:,2] = np.random.choice(np.arange(1980,2015,5), size=30)
v[:,3] = np.random.randint(5,13,size=30)

df= pd.DataFrame(v, columns=["x","y","year","quality"])
df.year = df.year.values.astype(int)
fig, ax = plt.subplots()
for i, (name, dff) in enumerate(df.groupby("year")):
    c = matplotlib.colors.to_hex(plt.cm.jet(i/7.))
    dff.plot(kind='scatter',x='x',y='y', label=name, c=c, 
             s=dff.quality**2, ax=ax)

leg = plt.legend(loc=(1.03,0), title="Year")
ax.add_artist(leg)
h = [plt.plot([],[], color="gray", marker="o", ms=i, ls="")[0] for i in range(5,13)]
plt.legend(handles=h, labels=range(5,13),loc=(1.03,0.5), title="Quality")
plt.show()