Back to Applied Plotting, Charting & Data Representation in Python
Learner Reviews & Feedback for Applied Plotting, Charting & Data Representation in Python by University of Michigan
6,278 ratings
About the Course
This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. 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.
Top reviews
IR
Feb 28, 2018
It contains very good recommended lectures, good material and explanation about matplotlib to grasp a big picture. However, you must invest a lot of time on your own to research deeper in the topic
EL
Oct 1, 2017
it is a good course to help me have a glance to the data visualization area. However, I think I cannot learned a lot from the course and the homework is so easy that I haven't practice enough.
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