Ratings and Reviews for Applied Plotting, Charting & Data Representation in Python

Not well organized.

Thanks a lot !!! Awesome stuff

Perfect, insightful, deep, challenging! I love the way prof. Christofer Brooks teach Data Science. Interactive IPython notebooks enables creativity to implement lecture notes right in the browser during watching lections. I enrolled to "Applied Plotting, Charting & Data Representation in Python" course right after finishing the first "Python for Data Science" module. This is one of the best experiencies I got during my online education. There are a very active forum discussions on this course, people and course staff are helpful. Next, I want to enroll next courses of the Specialization. Also I would like to say "Thank you" to course team and Coursera for the financial aid opportunity.

Insightful course indeed!

Very good course. Requires a lot of work but well worth it.

Awesome course

good course to get started with matplotlib, needs more hands on exercises though!

The course taught me well how matplotlib works, as well as quite a bit of theory of making plots and what to look for. This knowledge is very useful and applicable in many situations when doing data science. On the other hand, it required perhaps too much work. Ocassionaly I had a feeling some of the work was repetitive and not leading to new knowledge any more. But overall, very well worth it!

This was an interesting course. The professor was excellent and the practical exercises, in particular, were beneficial in learning the material. My only complaint would be that a lot more time in the exercises was spent formatting and manipulating Pandas dataframes than applying the matplotlib libraries to produce charts and graphs of the data. I would have preferred to spend more time experimenting and using the graphics libraries and less on trying to manipulate data to get it into formats acceptable for grading.

Great course to get one very comfortable with the matplotlib library without going too deep under the hood. I wish there was a bit more focus on the various advantages of using other libraries such as seaborn and Bokeh, but given the course's length that would have been hard to squeeze in. I am hoping there will be a second part to this course, focusing on real-world data visualization problems and converting graphics, with newly acquired data science skills from other courses in the series, into a full portfolio.