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Introduction
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Course Introduction
PREVIEW4m 48s
Conclusion

The course is part of this learning path

Working with Python Visualization Tools
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Overview
DifficultyIntermediate
Duration1h 21m
Students35
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Description

This course will guide you through all the possible techniques that are used to visualize data using the Matplotlib Python library.

In this course, we will explore the main functionalities of Matplotlib: we will look at how to customize Matplotlib objects, how to use various plotting techniques, and finally, we will focus on how to communicate results.

If you have any feedback related to this course, feel free to contact us at support@cloudacademy.com.

Learning Objectives

  • Learn the fundamentals of Python's Matplotlib library and its main features
  • Customize objects in Matplotlib
  • Create multiple plots in Matplotlib
  • Customize plots in Matplotlib (annotations, labels, linestyles, colors, etc)
  • Understand the different plot types available

Intended Audience

  • Data scientists
  • Anyone looking to create plots and visualize data in Matplotlib

Prerequisites

To get the most out of this course, you should already be familiar with using Python, for which you can take our Introduction to Python learning path. Knowledge of Python's Pandas library would also be beneficial and you might want to take our courses Working with Pandas and Data Wrangling with Pandas before embarking on this Matplotlib course.

Resources

The data used in this course can be found in the following GitHub repository: https://github.com/cloudacademy/data-visualization-with-python-using-matplotlib

 

 

Transcript

Congratulations! You have completed this course on Data Visualization with Matplotlib! That was a long journey, but I am sure you’ll get a lot out of the features we have covered. In particular, you have seen how matplotlib works in the back-end, especially with the object-oriented interface, and the main functionalities of the plot method.

You learned about the concept of customization, which definitely enhances the readability of your plot. You have seen how to efficiently transform raw data into good-looking plots that will help you in communicating results to other people. And finally, you have covered two other important families of plots within matplotlib: the histogram and the bar chart.

I hope you enjoyed the course, if you have any feedback relating to this course, please reach out to us at support@cloudacademy.com. Thanks for watching!

Lectures

Course Introduction - Introduction to Matplotlib - Customization in Matplotlib - Multiple Plots in Matplotlib - Annotating Text with Matplotlib - Advanced Customization in Matplotlib - Different Plot Types in Matplotlib

About the Author
Students180
Labs1
Courses2
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Andrea is a Data Scientist at Cloud Academy. He is passionate about statistical modeling and machine learning algorithms, especially for solving business tasks.

He holds a PhD in Statistics, and he has published in several peer-reviewed academic journals. He is also the author of the book Applied Machine Learning with Python.