DEV Community

George Karanikolas
George Karanikolas

Posted on • Edited on

2 1

Tutorial Matplotlib

What is Matplotlib?

Matplotlib is one of the most popular Python packages used for data visualization. It is a cross-platform library for making 2D plots from data in arrays. It provides an object-oriented API that helps in embedding plots in applications using Python GUI toolkits such as PyQt, WxPythonotTkinter. It can be used in Python and IPython shells, Jupyter notebook and web application servers also.
Matplotlib is often used along with package like NumPy.

Install Matplotlib

pip install matplotlib
Enter fullscreen mode Exit fullscreen mode

Import Matplotlib

import matplotlib.pyplot as plt
Enter fullscreen mode Exit fullscreen mode

Create Title

plt.title("Name")
Enter fullscreen mode Exit fullscreen mode

Create X and Y Labels

plt.xlabel('Name')
plt.ylabel('Name')
Enter fullscreen mode Exit fullscreen mode
plt.xlabel('Name', color='red')
plt.ylabel('Name', color='#ff0000')
Enter fullscreen mode Exit fullscreen mode

Create Plot

plt.plot()
Enter fullscreen mode Exit fullscreen mode
plt.plot(name_x, name_y)
Enter fullscreen mode Exit fullscreen mode
plt.plot(name_x, name_y, color='#ff0000')
Enter fullscreen mode Exit fullscreen mode
plt.plot(name_x, name_y, color='#ff0000', linestyle='--')
Enter fullscreen mode Exit fullscreen mode
plt.plot(name_x, name_y, color='#ff0000', linestyle='--', label="Name")
Enter fullscreen mode Exit fullscreen mode

Add Labels in Plot

plt.legend()
Enter fullscreen mode Exit fullscreen mode

Show Plot

plt.show()
Enter fullscreen mode Exit fullscreen mode

Save Plot In Image

plt.savefig('name.png')
Enter fullscreen mode Exit fullscreen mode
plt.savefig('name.png', transparent = True) # Transparent Figure
Enter fullscreen mode Exit fullscreen mode

Close And Clear

plt.cla() # Clear an axis
plt.clf() # Clear the entire figure
plt.close() # Close a window
Enter fullscreen mode Exit fullscreen mode

Examples:

Example 1:
import matplotlib.pyplot as plt

years_x = [2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018]
greece_y = [8.4,7.8,9.6,12.7,17.9,24.5,27.5,26.5,24.9,23.6,21.5,19.3]
europe_y = [7.2,7,9,9.6,9.7,10.5,10.9,10.2,9.4,8.6,7.6,6.8]

plt.title("Comparison of Unemployment")

plt.plot(years_x, greece_y, color='#ff0000', label="Greece")
plt.plot(years_x, europe_y, color='#00ff00', label="Europe", linestyle='--')

plt.xlabel('Years', color='#ff0000')
plt.ylabel('Percentage %', color='#ff0000')

plt.savefig('plot.png')

plt.legend()
plt.show()
Enter fullscreen mode Exit fullscreen mode

Github: https://github.com/SeijinD/Python-World/blob/master/main/extends_libraries/matplotlib.md

API Trace View

How I Cut 22.3 Seconds Off an API Call with Sentry

Struggling with slow API calls? Dan Mindru walks through how he used Sentry's new Trace View feature to shave off 22.3 seconds from an API call.

Get a practical walkthrough of how to identify bottlenecks, split tasks into multiple parallel tasks, identify slow AI model calls, and more.

Read more →

Top comments (0)

AWS Security LIVE!

Join us for AWS Security LIVE!

Discover the future of cloud security. Tune in live for trends, tips, and solutions from AWS and AWS Partners.

Learn More

👋 Kindness is contagious

Please leave a ❤️ or a friendly comment on this post if you found it helpful!

Okay