One legend for all the pipot subplots

Question

Currently, I draw the same data, but I visualize them differently in two subheadings (see figure):

The code snippet used to create the above image:

# Figure plt.figure(figsize=(14,8), dpi=72) plt.gcf().suptitle(r'Difference between TI and $\lambda$D', size=16) # Subplot 1 ax1 = plt.subplot2grid((1,3),(0,0),colspan=2) # Plot scattered data in first subplot plt.scatter(LE_x, LE_y, s=40, lw=0, color='gold', marker='o', label=r'$\lambda$D') plt.scatter(MD_x, MD_y, s=40, lw=0, color='blue', marker='^', label=r'TI') # Subplot 2 ax2 = plt.subplot2grid((1,3),(0,2)) plt.barh(vpos1, LE_hist, height=4, color='gold', label=r'$\lambda$D') plt.barh(vpos2, MD_hist, height=4, color='blue', label=r'TI') # Legend legend = plt.legend() 

Is there a way to make the legend show both scatter points and columns? Will it also go for a mannequin as described here ? Can someone please write a minimal working example for this, since I cannot wrap this around me.

Answer 1

This worked for me, you essentially grab the patch descriptors for each plot you build and manually create a legend at the end.

 import pylab as plt import numpy as NP plt.figure(figsize=(14,8), dpi=72) plt.gcf().suptitle(r'Difference between TI and $\lambda$D', size=16) # Subplot 1 ax1 = plt.subplot2grid((1,3),(0,0),colspan=2) N = 100 LE_x = NP.random.rand(N) LE_y = NP.random.rand(N) MD_x = NP.random.rand(N) MD_y = NP.random.rand(N) # Plot scattered data in first subplot s1 = plt.scatter(LE_x, LE_y, s=40, lw=0, color='gold', marker='o', label=r'$\lambda$D') s2 = plt.scatter(MD_x, MD_y, s=40, lw=0, color='blue', marker='^', label=r'TI') data = NP.random.randn(1000) LE_hist, bins2 = NP.histogram(data, 50) data = NP.random.randn(1000) MD_hist, bins2 = NP.histogram(data, 50) # Subplot 2 ax2 = plt.subplot2grid((1,3),(0,2)) vpos1 = NP.arange(0, len(LE_hist)) vpos2 = NP.arange(0, len(MD_hist)) + 0.5 h1 = plt.barh(vpos1, LE_hist, height=0.5, color='gold', label=r'$\lambda$D') h2 = plt.barh(vpos2, MD_hist, height=0.5, color='blue', label=r'TI') # Legend #legend = plt.legend() lgd = plt.legend((s1, s2, h1, h2), (r'$\lambda$D', r'TI', r'$\lambda$D', r'TI'), loc='upper center') plt.show()