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Applied Plotting, Charting & Data Representation in Python

Applied Plotting, Charting & Data Representation in Python

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8.5/10 (Our Score)
Product is rated as #133 in category Data Science

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. The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, …

Instructor Details

Christopher Brooks is a Research Assistant Professor in the School of Information and Director of Learning Analytics and Research in the Office of Digital Education & Innovation at the University of Michigan. His research focus is on the design of tools to better the teaching and learning experience in higher education, with a particular interest in understanding how learning analytics can be applied to human computer interaction through educational data mining, machine learning, and information visualization.

Specification: Applied Plotting, Charting & Data Representation in Python

Duration

17 hours

Year

2017

Level

Intermediate

Certificate

Yes

Quizzes

Yes

62 reviews for Applied Plotting, Charting & Data Representation in Python

4.3 out of 5
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  1. Sarthak T

    An amazing and comprehensive that helps you in polishing your data viz skills

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  2. Yonatan S

    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.

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  3. Edward P

    Nice python plotting course.

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  4. Steven G

    I learned a lot.

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  5. Ricardo O

    Thanks, nice job, cool course

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  6. Alex W

    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.

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  7. Milan V

    A well structured and useful course. The lectures were interesting and the programming assignments had a just right level of difficulty. Good work.

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  8. Praveen R

    I enjoyed learning about different plotting schemes with matplotlib. The assignments were very information to learn and explore new plotting techniques. The interactive graphics was interesting to know. seaborn is really powerful and elegant viewing schema. I want to use this in my day to day work too.

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  9. Pablo B

    Great Stuff!

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  10. Oj S

    Awesome course, it is good enough who is already a beginner in matplotlib too as the course is overall of intermediate level.

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  11. Amir A C

    This course taught me various stuff in data visualization. The assignments were amazing!!

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  12. Mike W

    It’s provides both the theory and principles behind great visualizations as well as the practical experience needed to learn to build these visualizations.

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  13. Syed A A

    By doing this course I was able to learn about visualization assignments are of top grade

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  14. Mariusz K

    Too little of expounding and too much of searching the net by oneself. Too few examples. It is a self learning but what’s the Course for then? Plus the assignments. I didn’t like the peer evaluation idea, just as evaluating the others, because I don’t have time for this and that’s not what I came for. First what’s the motivation of random viewers to fairly and thoroughly evaluate my work? Plus it’s hard to finish the course quicker for this reason, because one has to wait a couple of days to get a grade. That’s the reason I resigned from waiting for the assignments evaluations for next weeks assignments and in consequence for the certificate.

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  15. Patrik T

    CONTENT: The instructor shows some examples of different plots in python (e.g. line, bar, scatter) and some concepts (e.g. histograms or heat maps) but doesn’t properly explain anything. Mostly you’ll get an example graph with snippets of code only working for that particular example and for the assignment you’re “strongly encouraged to use other sources”. That’s not what you’re supposed to get when you’re paying for an online course. You should get proper explanations. ASSIGNMENTS: You’re basically told to get data from any source you like and then plot some graphs. If you’ve had some experience with python and got your explanations for plotting from somewhere else, you’ll mostly spend more time looking for data to present than for the actual assignment. I don’t understand why there’s no selection of graphs and data sets to choose from so you can concentrate on programming and properly presenting data rather than wasting your time looking at reddit like recommended by the instructor. ASSIGNMENT GRADING: You’ll have to grade your peers’ assignments with a rubric that’s just not working: you can give points for someone uploading an image/writing a paragraph of text, but you have to either give 0 or 100%, so there’s not way to properly grade partially wrong answers. Example: yes, there is an uploaded image and the student has explained how it follows “Cairo’s principle of beauty”, but it doesn’t follow the principle of beauty. So, how to grade: zero or hundred percent? Likewise, your assignments are graded by your peers, so you’ll usually have at least one or two days to add to each assignment. You should take this into account when opting for the monthly subscription. Additionally, neither you nor your peers are qualified to grade the assignments, because you’re just learning how to curate and present data (if you’re not already a scientist and just want to learn how to do this in Python). DISCUSSION FORUMS: You won’t find answers or discussions in the discussion forum. There are only posts asking to please grade a student’s assignment because it is urgent because the subscription is ending soon (see above). SUMMARY: If you need the certificate for Applied Data Science in Python, you probably must take this course. Otherwise I strongly encourage you to skip it and find other (better) resources to learn plotting in Python.

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  16. Nishal

    Some good pointers in matplotlib, covers quite a lot but goes over a range of features and tools that you can come back to. Assignments were a bit simplistic/easy

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  17. Benjamin C

    Good course, I liked the final assignment which gives the opportunity to freely explore data.

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  18. Xiaojun M

    The course itself is great. For those complaining it’s not detailed enough I think data scientists need to learn how to search for code and adapt it for their own purposes. If it’s too hard to achieve in this course, probably start from a easier course or this is not the right career for you. However the grading system is broken. Cheaters just submit empty/irrelevant answers and trying to get 3 other people to give them good score on those empty answers. All the 3 reviews I’ve done for assignment 4 are such cases.

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  19. Mahalingam.P.R

    Well structured

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  20. Andrew V P

    Great intro course!

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  21. Darien M

    This course is anbalagous to taking a creative writing course, but all lessons are on vocabulary and grammar. Once again the lectures are unhelpful. The discussion forum in this course does not provide much help (unlike the first course in the sequence). I suppose they are applying the graduate school mentality to teaching: you want to learn it, figure it out. I myself am definitely not at that level right now. The assignments are challenging, and you will learn from them, but you won’t learn deeply. It seems all very superficial. Just look things up to get them done. Type in any question you have and a solution will certainly appear on SO. Why not give students the tools necessary to solve challenging problems on their own (like in Python for Everybody and Python 3 Programming)? Professor Brooks is clearly passionate about programming and is very accomplished/intelligent. Unfortunately the teaching in this course is of low quality.

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  22. Md A R

    Great Course to learn Data Science

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  23. Qiuyi H

    Overall, it is a good course, however, the professor should be more specific about visualisation.

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  24. Rohan K

    Good Course

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  25. Jiongnan L

    In addition to giving practical guidance in plotting and charting, the professors also give a simple but comprehensive explanation of the structure and functioning of the matplotlib.pyplot module, even though it doesn’t require you to understand the deeper structure when you use the function, it certainly doesn’t hurt you for learning more, especially when you want to be an expert in this.

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  26. Sean L

    Less demanding than the first course. Learnt a lot, mainly from matplotlib and Seaborn documents.

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  27. Kareem H

    Plotting concepts need more deep explanation or more practice, generally the provided information wasn’t meet the course’s level “in my opinion.”

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  28. NODADO, K M (

    great subject I learned a lot

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  29. peyman s

    The videos have a lot of room for improvement, but the Notebooks and the Exams are well designed.

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  30. Jens–Alrik A

    The overall content of this course is superb but I just don’t like the concept of peer reviewed submissions. That’s why I remove one star

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  31. Jens Alrik A

    The overall content of this course is superb but I just don’t like the concept of peer reviewed submissions. That’s why I remove one star

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  32. Jonathan V C

    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.

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  33. Krishna P B

    Taking up this course is a great way to understand how visualization libraries are organized in python. Instead of just stating down functions, the instructor has actually gone through the trouble of explaining the whole underlying architecture of how data is stored and rendered from back end. Great work! And thank you for organizing a superb course.

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  34. Avirup D

    Excellent course.

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  35. Zhang Y

    Great course!

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  36. Rohan G

    This course is absolutely terrible, and in no way self sufficient. The professor basically tells you what can be done using matplotlib, give you a cursory example and leaves you all on your own to understand what actually happened by referring to sources such as google or stack overflow.

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  37. Nobuyuki H

    Very good to learn the basics of visualization. One problem for me was it took much longer time than I had expected

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  38. chris l

    Practical useful course

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  39. Ryan W

    Excellent course. Thanks so much for putting this together!

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  40. Masud H

    Very good! Learned so much : )

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  41. praveen s

    This is a fantastic course…!!

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  42. Callum Z Y Y

    It was a great introduction to the fundamentals data visualization. I enjoy how the course was structured to teach both theoretical and practical knowledge.

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  43. Xuanye C

    useful course, but a little bit useless homework

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  44. David K

    I was a bit apprehensive about this part, but once the course progressed the options for plotting and charting became clear, I learned a lot about this subject and I could have done with this information years ago !!

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  45. Arshdeep S H

    Really effective and least spoon feeding. Helped in developing thought process

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  46. Bishnu k

    awesome

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  47. Mohammed A R K

    Good course with hands on assignments

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  48. Alice L Y

    Great learning experience!

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  49. Muhammad Z H

    Thanks Professor

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  50. Aino J

    I found the course very rewarding, and I was surprised how easy it is to make nice looking graphs in python. Extra points to teachers for putting substantial emphasis on good design and aesthetics. You can pass the course without making any animations or interactive graphics; however, I found those assignments most rewarding so I recommend you give them a try. Workload wise, this course took me about double the amount indicated on the course website, but it would have taken considerably less time if I had set the bar lower for myself. As with Course 1 of this specialisation, the lectures only give an introduction to the topics and you’ll have to look up matplotlib documentation and answers from stackoverflow to complete the assignments. I found this course less challenging than the first one (but still challenging enough for sure!).

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  51. takashi t

    Excellent course ever I have.

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  52. omid p s e

    it’s awsome

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  53. Georgii B

    Peer grading is horrible. Nobody reads assignments or checks your work they just give top grade for every category and leave “.” as a comment, all to breeze through the mandatory peer grading. This certificate has very low value.

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  54. Eklavya J

    na

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  55. Philipp A R

    I liked the first course in this specialization more. As in the first one, the assignments require you to search StackOverflow, documentations and the discussion forums; videos are nice, but you won’t learn a lot from them. Peer review is a double edged sword. Some reviewers will give quite elaborate feedback, others do not put a lot of effort into their reviews. Peer reviewing others can be quite annoying as often you have to wait several hours for submissions of other learners. Not to mention the quite large amount of learners who hand in plagiarized code (please look out for these cases if you participate in this course).

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  56. akash p

    it was helpful

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  57. Tatek K

    Excellent presentation, exercise and reading materials. Thank you

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  58. Qiang L

    The construction of this course is fine, but content is really bad. Instructor could not give detailed introduction in matplotlib. So basically you need to learn everything by yourself. On the other hand, there is huge gap between course and assignment. I would say that you should have at least intermediate level of matplotlib before you take this course, which strongly against the principal of this course. I suggest instructor giving a more general idea first and gradually providing more specific application and harder examples.

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  59. Emmanuel M P

    Excellent course

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  60. Jiefei W

    It covers the basics of plotting. Peer grading provides feedback on assignments efficiently.

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  61. Eliezer

    Excellent course!.

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  62. Martin A L

    Great material, good classes and very practical exercises

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    Applied Plotting, Charting & Data Representation in Python
    Applied Plotting, Charting & Data Representation in Python

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