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Learner Reviews & Feedback for Applied Plotting, Charting & Data Representation in Python by University of Michigan

5,708 ratings
971 reviews

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

Jun 26, 2020

its actually a good course as it starts from fundamentals of visualization to the data visualization,the assignments this course provide are exciting and full of knowledge that you learn in course ..

May 13, 2020

I am going for the specialization and I know this is just the second course in it and I haven't even seen the further courses yet, but this is already my most favourite course in the specialization.

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876 - 900 of 956 Reviews for Applied Plotting, Charting & Data Representation in Python

By Tiberiu T

Mar 31, 2018

This is a whirlwind course that glibly covers some very important concepts without devoting enough time to each one. Week One, although important, should be replaced with more coverage of matplotlib, or a review of the different types of charts and when to use them.

Also, although I appreciate the in-video quizzes, it is difficult to go back and review the concepts you learn from them because they are not in the Jupyter notebook. For instance, there was a method Dr. Brooks used in a solution to an in-video quiz and I could not remember where I had seen it. I stumbled on it again after reviewing the video for something else.

By brian a

Apr 2, 2017

The first course in this series was really good and this one was so-so at best. I got some skills out of it since I obsessively plotted everything and over did the assignments, but the peer grading rubrics are crap. It's all or nothing so if you submit *anything*, you get a grade (and it usually approaches 100%) but I didn't really get much helpful/thoughtful feedback on anything I did since you literally get ZERO feedback from the instructors (nothing!) nor did I get much in the way of helpful info from the people who peer reviewed my work. I find that pretty disappointing really.

By Oliverio J S J

Jan 21, 2018

The contents of this course are interesting from the point of view of software engineering, but I am not sure if data scientist need such deep knowledge of graphic libraries. The main problem with the course is that the assignments require much more time than the one indicated in the course planning. In addition, assignment descriptions are often confusing, open to interpretation, and lack enough level of detail, which forces the students to begin by investigating what they have been asked to do.

By Jaime R

Jun 23, 2021

V​isualization in Python is still a bit of a chaotic mess, with so many different interfaces to matplotlib, one is left a bit confused, and its a bit hard to become a power user. Was hoping this course would provide a solid foundatation. Not sure I'm any more of a power user after this course. I'm still left to googling and looking at package code base to decipher how to best leverage. All this eats time, time not being spent doing analysis which should be ones focus.

By Bhavin P

Dec 3, 2018

This course introduces the learner to the various design principles that need to be followed while creating effective visualisations that include Alberto Cairo and Edward Tufte's work. It explains the information-visualisation wheel and proceeds to explain how to create visualisations in python using the Matplotlib Library. Various kinds of plots such as Line Charts, Bar Charts, Histograms, Scatter Charts are covered. Seaborn is introduced as additional library.

By Sarah B

Oct 15, 2018

This course gives an overview of plotting capabilities but I think it could have been presented more methodically. I think the challenge is that there are many ways to generate plots and so this is more a survey of those capabilities. I now know enough to go to stack overflow and matplotlib documentation and figure out what I need to get done, so my goal is accomplished, but my understanding of the plumbing of the different commands feels a big hazy.

By Alex W

Oct 26, 2019

The instructions for the second assignment are terrible. My peers graded my assignment based on what they thought the instructions implied I should have done instead of what it explicitly stated so I may have to repeat the assignment and could risk not passing the course which puts my whole specialization at risk. It's ridiculous since I spent sooooo much time on the assignment already due to lack of guidance from the video lectures.

By Jonathan V C

Dec 17, 2019

All material, explanations and content are great, no complains there, but I insist with the peer-graded assignments, we don't know if we are being graded well and some people just don't care, take points off for no reason associated with the rubric. Also, I like when the data source is given, I don't have time to search for a source of information that fits my investigation or the imposed topic of the last assignment.

By Peihong H

Dec 25, 2017

First, I would prefer there is a way to download the sample code professor Brooks used in the course. The screen showing his code moved too fast, and I have to pause and typed to try them out. Second, I will suggest the course show more code examples, more explanation for matplotlib architecture rather than most of the time just verbal description from the profession

By Renier B

Sep 19, 2017

The course is okey - lots of fuzzy theory such as Cairo's principles. Interesting stuff, but also quite self explanatory and seemed like a waste of time.

I would say its worth it to do this course if you have not had any exposure to Matplotlib or seaborn, but if you've done any significant using those then this course will feel a bit underwhelming.

By Venkatesh P

Mar 24, 2021

The python course followed a reinforcement approach with multiple examples and practice problems after every video. I liked the assignments in this course very much. They are very challenging. However the course isn't very informative. It will be helpful if the course is modified in a similar style to Python courses.

By Varun D P

May 6, 2018

Lot of working is required from our side. Not at all an introductory course! More like advanced level course. Requires lot of time, we have to find the documentation ourselves and ask question on stackoverflow. If you are looking for introductory course like Dr. Chucks courses I suggest not to take this course.

By Christopher I

Dec 22, 2017

This course is really as good or as bad as you make it for yourself, since it is quite bare, more a sort scaffold for you to do your own learning and projects. This is arguably the best way to learn though, which is why I like it. But, it may be challenging for beginners to get the most out of it.

By Khokon C S

Jul 17, 2020

I think length of the tutorial should have been a little bit longer for extensive discussion. The professor should have used words which are most of the cases self-explained or easily understandable from the perspective of audience, so those were somewhat tougher to catch up with professor.

By am

Apr 14, 2017

The last week assignment is easier and no strict rules to achieve. The majority will do the minimum to finish the course.

It would be more efficient to push all students to make hard plots in Matplotlib (interactive + animation) with strict rules.

This is not a level of an intermediate course!

By Abhijit G

May 18, 2018

The course is great and Mr Brooks is excellent is teaching the concepts. The assignments are fairly complex and they are not very well explained. I would like to see more input provided in the assignments and projects. Also, Iwhat books/websites can be referred for additional readings.

By David P

Mar 28, 2017

Decent overview but could have spend more time showing plotting techniques in more detail than showing what makes an appealing plot. Also The section on the back-end of MatPlotLib was more detailed than it needed to be for quick overview but not detailed enough to be very useful.

By Aayush N

May 3, 2020

Video lectures could have been covered with more clarity as far as the difficulty of the assignments are concerned. All the assignments should not be peer-graded because most of the students are just reviewing the assignments just for the sake of progressing in the course.

By Manikant R

May 5, 2020

The course has a lot of things, which are covered in short time, most of the time we have to look to other resources in order to complete assignments. If one is taking this course then they have to put their extra efforts. The best part is they provide a great references.

By Jay S

Apr 26, 2017

This course was disappointing compared to the first course in the series (Introduction to Data Science). If you enjoy reading academic papers and peer reviews then this course is for you. If you don't then just search the web for tutorials on Matplotlib and Seaborn.

By Frank L

May 7, 2017

Could do with some improvement, better examples for the more complicated graphs. Week 4's examples and explanations were not very good. I have not learnt how to use pandas well in plotting, and have not managed to complete any graphs with pandas and seaborn.

By Leon Z

Sep 2, 2018

The first week is fantastic, I learned a lot, such as chart junk, ink. However, the content in the following weeks seems be really heavy and there is no a path to help us get over it. It seems we need have a lot previous knowledge to work well

By Meixian W

Jul 22, 2018

Please unlock Week 2 ~ 4. I finished week 1 and had to wait 15 days so that I could do week 2 assignment. Is this kind of waste your time and money? I paid $49 just for waiting? 2 starts down for this. Otherwise, the materials so far are good.

By Amit m

Apr 9, 2017

The first week was interesting as it broke down the different layers that occur behind the scenes of matplotlib. The next couple of weeks felt a little shallow and rushed. Maybe we will explore more of the functionality in the later courses.

By Corey

Jul 7, 2018

Not enough in-lesson quizzes and somewhat confusing presentation of what's going on under the hood of matplotlib. Way too many "go read this" segments that seemed mostly a waste of time. Outside of that, the lecture quality was very good.