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

4.5
stars
6,219 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

OK

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 ..

RM

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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776 - 800 of 1,035 Reviews for Applied Plotting, Charting & Data Representation in Python

By Darell B

May 27, 2018

I found the course to be very informative and requiring the student to think differently about data and how to represent that data. I also like the ethical aspects of the course, that require the author of the charts to really thinking about the message being conveyed, how it is be presented and the message that might be inferred.

By Dairui Y

Aug 26, 2020

Overall great class, you will nead tons of research outside the class material, but you do learn a lot. P.s. so many learners just copy and paste the final project which is annoying. I was expecting to see some new way to to analyze problem by utilizing new skill that people acquired from this class. Otherwise all good.

By Gennady I

Mar 19, 2017

Good intro to plotting, charting and visualization in Python. Focuses mainly on matplotlib. I feel good about the content that I learned, but also feel like I wanted to learn more in this class. Maybe more coverage of other python charting libraries. More examples of financial type charts -- High/Low/Open/Close etc.

By Fabian G

Apr 26, 2020

Theory part was kept quite short and most of the time is spent programming, which I liked a lot. You will need to research lots of stuff on your own to finsih the assignments. Maybe some more information would have been helpful at times.

Overall a solid course and I certainly improved my coding doing the exercsises.

By Yonatan S

Oct 23, 2019

Good introduction to working with matplotlib.

All the parts about theoretical/aesthetic considerations when making figures were, in my opinion, very fuzzy, unenjoyable and somewhat of a waste of time. These are things which should be taught through experience or many specific examples, not long-form articles.

By Emily B

Nov 28, 2020

Great course. I learned how to use matplotlib. The professor is excellent and all of the material makes sense. The only regret I have is that the class was a bit too short and relied too much on googling features of matplotlib. But, that's how industry goes so I am OK with the course overall.

By Ben B

Dec 14, 2017

Most of the learning was self-directed as I worked through the assignments using Stackoverflow and other online resources and documentation. It would have helped to provide a lot more instruction on customizing templates such as the Seaborn library, adding notations, and fixing alignment issues.

By Dillon M

Jun 3, 2020

Provided enough structure and worked examples to give a meaningful introduction to the topic, but left the assignments open-ended enough that they were interesting and challenging. I ended up spending a lot of time on the various assignments, but actually found the whole process quite rewarding.

By Victor A D S

Apr 8, 2020

This course is okay. I think it tries to cover to much ground in to few lectures, particularly when it comes to more advance features and functions of matplotlib like animations and interactivty. It devotes a whole week to theoretical discussion of graphic design which is okay but not great.

By Sergio P d R

Apr 26, 2020

Good course overall. Like previous one, you can do as much as you want. How much you learn is completely dependant on you. It is not difficult to pass it, but if you want to get the best out of it during the assignments, you will have to spend some time in stackoverflow and matplotlib help.

By Christos G

Sep 1, 2017

Great exploration and navigation through the not so straightforward matplotlib for Python. The lecture would have been perfect if there were not so many references to a local library, which helped with the concepts but left the student with nothing to reuse in the future.

By Katya H

Apr 4, 2017

good lectures and theory. I miss automatic code evaluation and more numpy data transformations. I suck at these and I was hoping this course would have more of the same kind of tasks as the first + plotting.

Overall, good class as a starter point for plotting in pandas.

By Juan M

Sep 17, 2018

The course and material is great. The videos are not too long, but they provide the necessary guidance. I do think that the peer-reviewed grading could be improved. Feedback is minimal, and I do not think anyone really gets feedback on the quality of their code.

By Juan C E

May 21, 2017

Several different API's are touched (matplotlib matlab-style and object oriented interfaces, seaborn, pandas, and it's easy to get lost. Some additional reference material would be helpful: cheat sheets, course slides with a bit more detail of the API's touched.

By Noah K

Jan 31, 2018

Great course to learn matplotlib and some other plotting tools! I do believe that that gap between the lecture videos and the assignments was huge though, but I guess self-study and exploring the internet is part of learning this type of stuff. Great course!

By Jared P

Mar 22, 2017

This a pretty good introduction to plotting libraries in python. I would have preferred a deeper dive into some of the built-in methods. A little more on visualizations from libraries like seaborn, bokeh, or plotly would have been nice. Overall, great work.

By Tonderayi K

Nov 30, 2017

It was an applied one where I learnt how to handle real world data. Also the parts of what makes a good visualization were principles that really helped me. This course will always help me in my data analysis future - I will always refer to it.

By Xan P

Aug 31, 2019

Useful overview of data visualization design principles, matplotlib, and seaborn. But for me also required a lot of self-learning from Stack Overflow in order to make attractive charts. The assignments were useful and practical overall.

By Luke G

Mar 3, 2018

This course is pretty good. There's a lot of general guidance and the topics covered are very broad. Expect to spend some time reading documentation, but overall you'll get a really good coverage of a lot of different things.

By Michael H

Feb 11, 2018

The course was very informative and provided good exposure to plotting tools in Python. However, I don't feel that the peer-reviewed assignments were very effective as nearly anything submitted would receive a passing grade.

By KylinMountain

Apr 26, 2018

About pandas plot and seaborn, it is very short and it looks like ends suddenly. Besides, the design of practice is not very good as well as first class 'Introduction to Data Science in Python'. It need improvement.

By Alan J

Apr 2, 2017

Excellent course to begin matplotlib. It shows us the intricacies of the matplotlib by showing the basics and prodding us to go deeper by reading the documentation. The assignments are also really good. Recommended!

By Shou-Chung W

Aug 14, 2018

This course gives me an overview of data visualization, and I felt pretty accomplished with that goal. Data science is a broad subject, this course is a good place to start. It is an intermediate level course.

By Arvind S

Oct 25, 2020

It is a nice course ,if you are looking to start your journey in data visualization then this course may interest you a lot, although this course covers basic as well as some advance lessons in visualization.

By Manuela D

Feb 11, 2018

The very last 2 weeks were quite interesting and full con concepts, whereas weeks 1 and 2 were more theorical. I would suggest to summarize initial theorical concepts and give more practical coding examples.