Legend in separate subplot and grid - python-3.x

Question

I have a collection of plots, arranged in two grids. In the left grid, I have one plot in the top (whole width) and two in the bottom (side-by-side). The two in the bottom are sharing legends. In my right grid, I want the legends, it is a lots of data series, and I would like to use the whole height of my figure.
The appearance of the data series are animated, but I would like the legends not to be.
My idea was to draw the time series in my right grid with legends, and hide the data series. But my only solution is ax.set_visible(False), which removes everything.
This is principally how the script looks like (simplified version):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as anim
from matplotlib.gridspec import GridSpec
data = np.array([[1],[2],[3],[4]])
sett = np.array([1,2,3,4])
data1 = np.hstack((data,data*2, data*3, data*4))
data2 = np.hstack((3*data, 3*data/2, 3*data/3, 3*data/4))
df1 = pd.DataFrame(data = np.array(data1), index = [1,2,3,4], columns =
sett).transpose()
df2 = pd.DataFrame(data = np.array(data2), index = [1,2,3,4], columns =
sett).transpose()
gs1 = GridSpec(2,2)
gs1.update(left=0.05, right = 0.80, hspace = 0.05)
gs2 = GridSpec(3,1)
gs2.update(left=0.85, right = 0.98, hspace = 0.05)
figure = plt.figure()
plt.clf()
ax1 = plt.subplot(gs1[0,:])
ax2 = plt.subplot(gs1[1,0])
ax3 = plt.subplot(gs1[1,1], sharey = ax2)
ax4 = plt.subplot(gs2[:,0])
ax1.set_ylim(0,25)
label = ['s0', 's1', 's2', 's3', 's4']
ax4.plot(df1[1], df2[:])
ax4.legend(labels = label)
def make_frame(i):
ct=sett[i]
ax2.plot(df1[1], df1[ct])
ax3.plot(df1[1], df2[ct])
ax3.legend(labels = label)
ani = anim.FuncAnimation(figure, make_frame, frames = len(sett),
interval =500, repeat = False)
plt.show()
How can I remove the data series and keep the legend in gs2/ax4?
Don't bother I plot the first data series twice in ax2 and ax3 - it is ok in my original script. However - if someone can enlighten me on why, it is very much appreciated.

Answer 1

I'm not entirely sure what the desired output should be. Are you trying to put the legend at the place of ax4 right now, but not have the plot shown in ax4 at the moment.
My solution would be to not create ax4 at all. Instead you can use bbox_to_anchor to move the position of the legend. Here I use the transform from ax1 to establish a location in reference to ax1 and I move the legend slightly past the right edge and at the top of ax1.
See "legend guide" for more information.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as anim
from matplotlib.gridspec import GridSpec
data = np.array([[1], [2], [3], [4]])
sett = np.array([1, 2, 3, 4])
data1 = np.hstack((data, data * 2, data * 3, data * 4))
data2 = np.hstack((3 * data, 3 * data / 2, 3 * data / 3, 3 * data / 4))
df1 = pd.DataFrame(data=np.array(data1), index=[1, 2, 3, 4], columns=sett).transpose()
df2 = pd.DataFrame(data=np.array(data2), index=[1, 2, 3, 4], columns=sett).transpose()
gs1 = GridSpec(2, 2)
gs1.update(left=0.05, right=0.80, hspace=0.05)
figure = plt.figure()
plt.clf()
ax1 = plt.subplot(gs1[0, :])
ax2 = plt.subplot(gs1[1, 0])
ax3 = plt.subplot(gs1[1, 1], sharey=ax2)
label = ['s0', 's1', 's2', 's3', 's4']
def make_frame(i):
ct = sett[i]
ax2.plot(df1[1], df1[ct])
ax3.plot(df1[1], df2[ct])
ax3.legend(labels=label, loc='upper left', bbox_to_anchor=(1.05, 1.), bbox_transform=ax1.transAxes)
ani = anim.FuncAnimation(figure, make_frame, frames=len(sett),
interval=500, repeat=False)
plt.show()
EDIT: using a proxy artist to create all the legends before the animation starts
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as anim
from matplotlib.gridspec import GridSpec
data = np.array([[1], [2], [3], [4]])
sett = np.array([1, 2, 3, 4])
data1 = np.hstack((data, data * 2, data * 3, data * 4))
data2 = np.hstack((3 * data, 3 * data / 2, 3 * data / 3, 3 * data / 4))
df1 = pd.DataFrame(data=np.array(data1), index=[1, 2, 3, 4], columns=sett).transpose()
df2 = pd.DataFrame(data=np.array(data2), index=[1, 2, 3, 4], columns=sett).transpose()
gs1 = GridSpec(2, 2)
gs1.update(left=0.05, right=0.80, hspace=0.05)
figure = plt.figure()
plt.clf()
ax1 = plt.subplot(gs1[0, :])
ax2 = plt.subplot(gs1[1, 0])
ax3 = plt.subplot(gs1[1, 1], sharey=ax2)
ax1.set_ylim(0, 25)
labels = ['s0', 's1', 's2', 's3', 's4']
colors = ['C0', 'C1', 'C2', 'C3', 'C4']
proxies = [plt.plot([], [], c=c)[0] for c in colors]
ax1.legend(proxies, labels, bbox_to_anchor=(1., 1.), loc="upper left")
def init_frame():
pass
def make_frame(i):
ct = sett[i]
ax2.plot(df1[1], df1[ct], c=colors[i], label=labels[i])
ax3.plot(df1[1], df2[ct], c=colors[i], label=labels[i])
ax3.legend()
ani = anim.FuncAnimation(figure, make_frame, init_func=init_frame, frames=len(sett),
interval=500, repeat=False)
plt.show()

Answer 2

I would create the line plots prior to animating anything. You can initialize them with empty lists and then set the data one by one.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as anim
from matplotlib.gridspec import GridSpec
data = np.array([1,2,3,4,5])
data1 = np.vstack((data,data*2, data*3, data*4))
data2 = np.vstack((3*data, 3*data/2, 3*data/3, 3*data/4))
df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)
sett = np.arange(len(df1.columns))
gs1 = GridSpec(2,2)
gs1.update(left=0.05, right = 0.80, hspace = 0.05)
figure = plt.figure()
ax1 = plt.subplot(gs1[0,:])
ax2 = plt.subplot(gs1[1,0])
ax3 = plt.subplot(gs1[1,1], sharey = ax2, sharex= ax2)
ax2.set_ylim(0,25)
lines1 = ax2.plot(*[[] for _ in range(len(sett)*2)])
lines2 = ax3.plot(*[[] for _ in range(len(sett)*2)])
label = ['s0', 's1', 's2', 's3', 's4']
ax1.legend(handles = lines1, labels=label, bbox_to_anchor=(1.05,1), loc="upper left")
def init():
for line in lines1+lines2:
line.set_data([],[])
def make_frame(i):
ct=sett[i]
lines1[i].set_data(df1.index, df1[ct])
lines2[i].set_data(df1.index, df2[ct])
ax2.relim()
ax2.autoscale_view()
ani = anim.FuncAnimation(figure, make_frame, init_func=init, frames = len(sett),
interval =500, repeat = False)
ani.save("anigif.gif", writer="imagemagick")
plt.show()