Applied Plotting, Charting and Data Representation in Python Coursera

Overview

This Applied Plotting, Charting and Data Representation in Python course offered by Coursera in partnership with University of Michigan will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library.

Key facts

• The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. 

• The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework. 

• The third week will be a tutorial of functionality available in matplotlib, and demonstrate a variety of basic statistical charts helping learners to identify when a particular method is good for a particular problem. The course will end with a discussion of other forms of structuring and visualizing data. 

• This course should be taken after Introduction to Data Science in Python and before the remainder of the Applied Data Science with Python courses: Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python.

What you'll learn

• Describe what makes a good or bad visualization

• Understand best practices for creating basic charts

• Identify the functions that are best for particular problems