Code and run your first Python script with Matplotlib in minutes without installing anything! This course is designed for learners with some Python experience, providing a crash course in Matplotlib and core data visualization topics. You will learn how to use Jupyter, generate and choose the best graphs to represent your data, and style and customize charts and plots.
This course offers a truly hands-on, self-paced learning experience with video-free content. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.
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Explore Intro to Matplotlib, Intermediate Matplotlib, and Advanced Matplotlib in this comprehensive course. Gain hands-on experience and learn to create and customize charts and plots in Python.
This module provides a comprehensive introduction to Matplotlib, focusing on fundamental concepts and usage. You will learn how to create basic charts and plots, exploring various visualization options and techniques. The module offers hands-on exercises to reinforce learning and build a strong foundation in data visualization using Matplotlib.
Building on the foundational knowledge, Intermediate Matplotlib delves into more advanced chart and plot creation. You will explore customization features, advanced visualization techniques, and best practices for effective data representation. The module includes practical exercises to enhance your skills and deepen your understanding of Matplotlib.
Advanced Matplotlib is designed to further expand your expertise in data visualization. This module covers advanced customization, complex plot types, and in-depth exploration of Matplotlib's capabilities. You will gain proficiency in creating sophisticated visualizations and understanding how to apply them to real-world data analysis scenarios.
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