Coursera: Applied Plotting, Charting & Data Representation in Python Review

Applied Plotting, Charting and Data Representation in Python is the second course in the Applied Data Science with Python Specialization offered by the University of Michigan on Coursera. It is a 4-week intro to data visualization in Python, focusing on the Matplotlib library. You should know the basics of Python before taking this course; the course recommends that you complete the first course in the specialization first, although that isn't strictly necessary. Course grading is based on 4 weekly peer graded projects that require paying for the full course to submit. As a freeware student you can view the lectures, but can't complete the course since you are locked out of assignments.


Each week consists of a few short lecture videos and at lest one reading. The lectures are supported by accompanying Jupyter notebooks that contain code you can use to follow along and reproduce visualizations. The lectures and supporting materials are of good quality, but there isn't a lot of content per week. The first week covers visualization theory, while the last week only has 15 minutes of lecture that touches on plotting with packages that build on Matplotlib, including Pandas and Seaborn. That only leaves 2 weeks in the middle of the course that address the course's core topic. The sections on Matplotlib spend about 15 minutes introducing the package itself and the rest of the time covering the various plots you can make, including scatterplots, line plots, bar charts, histograms, box plots and heat maps. It also touches on animation and interactivity.


The previous course in the Applied Data Science with Python Specialization, Introduction to Data Science in Python, had many auto-graded homework problems available to all students which gave you a lot of practice using Pandas. Applied Plotting, Charting and Data Representation in Python takes an about face on that model as there are not short homework problems to give you practice using Matplotlib and the few assignments they do have require paying for the full course to submit.


Applied Plotting, Charting and; Data Representation in Python is a brief introduction to Matplotlib that feels more like a short Youtube series than a full MOOC. It does a fine job going over the basics of Matplotlib, but lacks the main thing that made the first course in the specialization valuable: a variety of short, freely accessible homework problems that let you gain practice using a new package.


I give Applied Plotting, Charting and Data Representation in Python 2.5 out of 5 stars: Poor.