When plotting means and confidence intervals, sometimes the mean lines are hard to see and it’s nice to have included in your legend the color of the confidence interval shading. It turns out this is a bit of a chore in Matplotlib, but building off of their online examples you can get something that looks pretty alright:

So here’s code for getting the above plot, with an option for solid or dashed lines. The sky is the limit!

import matplotlib.pyplot as plt import matplotlib.patches as mpatches from matplotlib.colors import colorConverter as cc import numpy as np def plot_mean_and_CI(mean, lb, ub, color_mean=None, color_shading=None): # plot the shaded range of the confidence intervals plt.fill_between(range(mean.shape[0]), ub, lb, color=color_shading, alpha=.5) # plot the mean on top plt.plot(mean, color_mean) # generate 3 sets of random means and confidence intervals to plot mean0 = np.random.random(50) ub0 = mean0 + np.random.random(50) + .5 lb0 = mean0 - np.random.random(50) - .5 mean1 = np.random.random(50) + 2 ub1 = mean1 + np.random.random(50) + .5 lb1 = mean1 - np.random.random(50) - .5 mean2 = np.random.random(50) -1 ub2 = mean2 + np.random.random(50) + .5 lb2 = mean2 - np.random.random(50) - .5 # plot the data fig = plt.figure(1, figsize=(7, 2.5)) plot_mean_and_CI(mean0, ub0, lb0, color_mean='k', color_shading='k') plot_mean_and_CI(mean1, ub1, lb1, color_mean='b', color_shading='b') plot_mean_and_CI(mean2, ub2, lb2, color_mean='g--', color_shading='g') class LegendObject(object): def __init__(self, facecolor='red', edgecolor='white', dashed=False): self.facecolor = facecolor self.edgecolor = edgecolor self.dashed = dashed def legend_artist(self, legend, orig_handle, fontsize, handlebox): x0, y0 = handlebox.xdescent, handlebox.ydescent width, height = handlebox.width, handlebox.height patch = mpatches.Rectangle( # create a rectangle that is filled with color [x0, y0], width, height, facecolor=self.facecolor, # and whose edges are the faded color edgecolor=self.edgecolor, lw=3) handlebox.add_artist(patch) # if we're creating the legend for a dashed line, # manually add the dash in to our rectangle if self.dashed: patch1 = mpatches.Rectangle( [x0 + 2*width/5, y0], width/5, height, facecolor=self.edgecolor, transform=handlebox.get_transform()) handlebox.add_artist(patch1) return patch bg = np.array([1, 1, 1]) # background of the legend is white colors = ['black', 'blue', 'green'] # with alpha = .5, the faded color is the average of the background and color colors_faded = [(np.array(cc.to_rgb(color)) + bg) / 2.0 for color in colors] plt.legend([0, 1, 2], ['Data 0', 'Data 1', 'Data 2'], handler_map={ 0: LegendObject(colors[0], colors_faded[0]), 1: LegendObject(colors[1], colors_faded[1]), 2: LegendObject(colors[2], colors_faded[2], dashed=True), }) plt.title('Example mean and confidence interval plot') plt.tight_layout() plt.grid() plt.show()

Side note, really enjoying the default formatting in Matplotlib 2+.