Matplotlib's standard color cylce is ok if your data lines are distinct, but if each line is related to the others, then it is best to use a sequential color cycle.

matplotlib_sequential_color_plot.py

a = np.arange(0, 3*np.pi, .1)

loops = range(5)

# Choose a colormap and create a list of colors with same length as our loop.
cmap = plt.get_cmap("YlGnBu")
colors = [cmap(i) for i in np.linspace(.15, .85, len(loops))]


fig, (ax1, ax2) = plt.subplots(1,2)

for i, color in zip(loops, colors):
    ax1.plot(np.sin(a)*(i-1.5), label=i)
    ax2.plot(np.sin(a)*(i-1.5), color=color, label=i)

    
ax1.set_title('No apparent relation')
ax2.set_title('Colors are sequential')
    
ax1.legend()
ax2.legend()

Matplotlib's standard color cylce is ok if each line represents distinct, separate entities. But if each line is related to the others, then it is best to use a sequential color cycle.

Consider this example where each line is the same function, just multiplied by a different constant in each loop. The left image is the standard colormap, and the colors do not indicate any apparent relationship between each line. But the right image has a sequential colormap that helps illustrate there is a relationship between each line.