# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np

ax = plt.subplot(111)

t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2 * np.pi * t)
line, = plt.plot(t, s, lw = 2)

plt.annotate('local max', xy =(2, 1),
             xytext =(3, 1.5),
             arrowprops = dict(facecolor ='black',
                               shrink = 0.05), )

plt.ylim(-2, 2)
plt.title(" matplotlib.pyplot.ylim() Example")
plt.show()

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(9680801)

mu, sigma = 50, 13
x = mu + sigma * np.random.randn(10000)

# the histogram of the data
n, bins, patches = plt.hist(x, 50, 
                            density = True,
                            facecolor ='g',
                            alpha = 0.75)


plt.xlabel('No of Users in K')
plt.title('Histogram of IQ')
plt.text(50, .035, r'$\mu = 50,\
\ \sigma = 13$')

plt.xlim(-10, 110)
plt.ylim(0, 0.04)

plt.grid(True)
plt.title(" matplotlib.pyplot.ylim() Example")

plt.show()