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Add Text Inside the Plot in Matplotlib

In this article, We are going to see how to add text inside the plot in Matplotlib. The matplotlib.pyplot.text() function is used to add text inside the plot. The syntax adds text at an arbitrary location of the axes. It also supports mathematical expressions.

Syntax: matplotlib.pyplot.text(x, y, s, fontdict=None, **kwargs)

Parameters:

  • where x, y – coordinates
  • s – text to be added inside the plot(string)
  • fontdict – optional parameter. It overrides the default text properties
  • **kwargs – text properties

Example 1: Adding mathematical equations inside the plot.

Python3




import matplotlib.pyplot as plt
import numpy as np
  
x = np.arange(-10, 10, 0.01)
y = x**2
  
#adding text inside the plot
plt.text(-5, 60, 'Parabola $Y = x^2$', fontsize = 22)
  
plt.plot(x, y, c='g')
  
plt.xlabel("X-axis", fontsize = 15)
plt.ylabel("Y-axis",fontsize = 15)
  
plt.show()


Output:

Example 2: Adding rectangular box around the text by using the keyword ‘bbox’. bbox is a dictionary of Rectangle properties.

Python3




import matplotlib.pyplot as plt
import numpy as np
  
x = np.arange(-10, 10, 0.01)
y = x**2
  
plt.xlabel("X-axis", fontsize = 15)
plt.ylabel("Y-axis",fontsize = 15)
  
#Adding text inside a rectangular box by using the keyword 'bbox'
plt.text(-5, 60, 'Parabola $Y = x^2$', fontsize = 22
         bbox = dict(facecolor = 'red', alpha = 0.5))
  
plt.plot(x, y, c = 'g')
  
plt.show()


Output:

Example 3: Adding the text “Sine wave” inside the plot.

Python3




import matplotlib.pyplot as plt
import numpy as np
  
x = np.arange(0, 10, 0.1)
y = np.sin(x)
  
plt.plot(x,y)
  
plt.text(3.5, 0.9, 'Sine wave', fontsize = 23)
  
plt.xlabel('X-axis', fontsize = 15)
plt.ylabel('Y-axis', fontsize = 15)
  
#plt.grid(True, which='both')
plt.show()


Output: 

Example 4: Using annotation along with text inside plot

Python3




import matplotlib.pyplot as plt
import numpy as np
  
x = ['Rani', 'Meena', 'Raju', 'Jhansi', 'Ram']
y = [5, 7, 9, 2, 6]
  
plt.bar(x,y)
  
plt.text(3, 7, 'Student Marks'
         fontsize = 18, color = 'g')
  
plt.xlabel('Students', fontsize = 15)
plt.ylabel('Marks', fontsize = 15)
  
plt.annotate('Highest scored', xy = (2.4, 8), 
             fontsize = 16, xytext = (3, 9), 
             arrowprops = dict(facecolor = 'red'),
             color = 'g')
  
plt.show()


Output:

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