import pandas as pd
import matplotlib.pyplot as plt
d = {'series a' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
'series b' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
title_string = "This is the title"
subtitle_string = "This is the subtitle"
plt.figure()
df.plot(kind='bar')
plt.suptitle(title_string, y=1.05, fontsize=18)
plt.title(subtitle_string, fontsize=10)
import matplotlib.pyplot as plt
import numpy as np
# Simple data to display in various forms
x = np.linspace(0, 2 * np.pi, 400)
y = np.sin(x ** 2)
fig, axarr = plt.subplots(2, 2)
fig.suptitle("This Main Title is Nicely Formatted", fontsize=16)
axarr[0, 0].plot(x, y)
axarr[0, 0].set_title('Axis [0,0] Subtitle')
axarr[0, 1].scatter(x, y)
axarr[0, 1].set_title('Axis [0,1] Subtitle')
axarr[1, 0].plot(x, y ** 2)
axarr[1, 0].set_title('Axis [1,0] Subtitle')
axarr[1, 1].scatter(x, y ** 2)
axarr[1, 1].set_title('Axis [1,1] Subtitle')
# Fine-tune figure;
# hide x ticks for top plots and y ticks for right plots
plt.setp([a.get_xticklabels() for a in axarr[0, :]], visible=False)
plt.setp([a.get_yticklabels() for a in axarr[:, 1]], visible=False)
# Tight layout often produces nice results
# but requires the title to be spaced accordingly
fig.tight_layout()
fig.subplots_adjust(top=0.88)
plt.show()