In [19]:

    

import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

x = np.linspace(-3, 3, 50)
y = 2*x + 1

plt.figure(num=1, figsize=(8, 5),)
plt.plot(x, y)

ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))

x0 = 1
y0 = 1 + x0*2
plt.scatter(x0, y0, color='r')
plt.plot([x0,x0],[y0, 0], 'k--',lw=2.5)

# method 1:
#####################
plt.annotate(r'$2x+1=%s$' % 'ss', xy=(x0, y0), xycoords='data', xytext=(+30, -30),
             textcoords='offset points', fontsize=16,
             arrowprops=dict(arrowstyle='->', connectionstyle="arc3,rad=.2"))

# method 2:
########################
plt.text(-3.7, 3, r'$This\ is\ the\ some\ text. \mu\ \sigma_i\ \alpha_t$',
         fontdict={'size': 16, 'color': 'r'})


    

    
Out[19]:





<matplotlib.text.Text at 0xaf55e7b0>