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How to Change the Line Width of a Graph Plot in Matplotlib with Python?

  • Last Updated : 12 Nov, 2020
Geek Week

Prerequisite : Matplotlib 

In this article we will learn how to Change the Line Width of a Graph Plot in Matplotlib with Python. For that one must be familiar with the given concepts:

  • Matplotlib : Matplotlib is a tremendous visualization library in Python for 2D plots of arrays. Matplotlib may be a multi-platform data visualization library built on NumPy arrays and designed to figure with the broader SciPy stack. It was introduced by John Hunter within the year 2002.
  • Graph Plot : A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables.
  • Line Width : The width of a line is known as line width. One can change the line width of a graph in matplotlib using a feature.

Approach

  • Import packages
  • Import or create the data
  • Draw a graph plot with a line
  • Set the line width by using line-width feature ( lw can also be used as short form ).

Example 1:

Python3




# importing packages
import matplotlib.pyplot as plt
import numpy as np
  
# create data
x_values = np.arange(0, 10)
y_values = np.arange(0, 10)
  
# Adjust the line widths
plt.plot(x_values, y_values - 2, linewidth=5)
plt.plot(x_values, y_values)
plt.plot(x_values, y_values + 2, lw=5)
  
# add legends and show
plt.legend(['Lw = 5', 'Lw = auto', 'Lw = 5'])
plt.show()

Output :



Example 2 :

Python3




# importing packages
import matplotlib.pyplot as plt
import numpy as np
  
# create data
x_values = np.linspace(0, 10, 1000)
y_values = np.sin(x_values)
  
# Adjust the line widths
for i in range(20):
    plt.plot(x_values, y_values + i*0.5, lw=i*0.5)
      
plt.show()

Output :

Example 3 :

Python3




# importing packages
import matplotlib.pyplot as plt
import numpy as np
  
# create data
x_values = np.linspace(0, 10, 1000)
  
# Adjust the line widths
for i in range(20):
    plt.plot(x_values, np.sin(x_values) + i*0.5, lw=i*0.4)
    plt.plot(x_values, np.cos(x_values) + i*0.5, lw=i*0.4)
      
plt.show()

Output :

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