Chevron Left
返回到 Applied Plotting, Charting & Data Representation in Python

學生對 密歇根大学 提供的 Applied Plotting, Charting & Data Representation in Python 的評價和反饋

4.5
3,489 個評分
571 個審閱

課程概述

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....

熱門審閱

SB

Nov 03, 2017

Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

A

Mar 06, 2018

Very helpful to understand what it takes to make a scientific and sensible visual. Recommended for someone who is interested in learning data visualization and does not have a background.

篩選依據:

26 - Applied Plotting, Charting & Data Representation in Python 的 50 個評論(共 560 個)

創建者 Michael H

Sep 09, 2019

Not a great course. Prof is obviously smart, but the lectures breeze through the material far too quickly and too lightly, with students left to do most of the work themselves via the assignments. I'm a fan of learning by doing, but I question the value of a course when most of what I pick up I get from stack overflow. The assignments aren't well explained or maintained, and the same questions keep coming up from students year after year.

Prof would be well advised to revisit this course, expand and update the content, and clarify the various points of confusion in the assignments.

創建者 Ahmad H S

Jul 28, 2019

Amazing source

創建者 Matheus G S d L

Jun 28, 2017

Good course to learned matplotlib and other Graphs libraries, but the course goes further than Python and also encourages the studies to create more meaningful and beautiful Graphic views.

創建者 Siddhartha B

Nov 03, 2017

Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

創建者 Josselin G

Sep 13, 2019

Pretty good course the material is good.

Offers good coverage and proposes some interesting problems.

Pairs grading works pretty well.

創建者 Ron M

Feb 09, 2018

Ideally, would be 2 1/2 stars if that was possible. Again, like Course 1 in the series, the time required is VERY underestimated, especially since the course is little more than a series of exercises that require extensive external research to learn how to complete. The instructor seems more interested in this subject matter than the first course, but the discussions are such high-level overview, much pouring through Stack Overflow is needed just to learn the topics. The best pieces, as in Course 1, are the extra reading that one might never otherwise be pointed towards, but other than those, a $10 web course that simply gave exercises and pointed to Google searches and Stack Overflow to learn the detailed material would accomplish 80+% of what this course does. And many find the assignments confusing which adds time or results in the wrong work product (some of that I believe is especially true for non-native language speakers) - lots of comments to that effect in the forums. Students grade each others' work product, and it is clear from doing so there are many interpretations of the exercises.

And, some students doing the evaluation of others are clearly not qualified to do so - if one does not really understand basic Python or statistics, they should not be indicating the calculations are wrong... And with three reviews required - it seems the grader uses the lowest grade of the three. If 2 reviewers give full marks, and another gives a 0, the 0 is what is recorded. This is especially annoying in tandem with the lack of value in the instruction - just getting some assignments from off the web and forcing yourself to do them would be far more satisfying.

I don't see continuing with the Michigan courses beyond this point - there are better options.

創建者 Cameron F

Jun 21, 2017

I really dislike the peer-graded assignments

Too much of the course is unstructured

I dislike being assigned a region and topic for the final project

I would prefer to dive less into interactivity and focus more on practicing essential plotting skills over and over again.

創建者 Thomas M S

Jan 02, 2018

A fundamental issue after this course is that it still takes me hours to prepare an appealing data visualization using what I learned here whereas with Excel it takes me minutes to draw and pretty a graph. So the course doesn't fulfill the practicality criterion yet.

創建者 Nigel S

Jun 10, 2019

Of the 6 Coursera courses I have done to date, this was by far the most tedious and frustrating.

There are a few different approaches to creating images in Python using Matplotlib, and this course didn't manage to set any of them out in a cohesive way that was easy to understand or implement.

An intent of the course was to educate learners about the more detailed Matplotlib control, features, e.g. canvases, so they had more control. But the course presentation is so incohesive that learners are just left utterly confused when it comes to doing the assignments, and they end up trying to pull together a mishmash of code from the internet to try and provide a credible assignment response. It is just such an inefficient use of the learner's time.

This course needs to be torn down, the assignments reviewed, and then the lecture material rebuilt in a way that will enable learners to easily implement the points from the lectures, and eliminate the chasms between course content and what's needed to do the assignments.

創建者 Sergey I

Aug 01, 2019

The course is not balanced - lectors give very brief explanations and doing it very fast. There is not much little connections to practical applications. The assignments often are vague, many times I had to research what they actually wanted instead of actually stadying Python. I finished it, but this course creates more frustration than dophamine. Not recommend it

創建者 Shuang S

Aug 15, 2019

It taught some visualization that is not use very often and sometimes I feel I couldn't catch up the knowledge, so if you are a beginner, skip this class first.

創建者 Mariusz K

Nov 10, 2019

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.

創建者 Javier P S

Mar 08, 2018

A course where you practice your googling capabilities. It could be improved.

創建者 Feng H

Aug 16, 2019

Lectures are not detailed enough and speaks too fast, assignments too difficult. If I have to do my own study 90% of the time why do I need to pay tuition?

創建者 Mack S

Jul 01, 2019

There are some rubbish assignments in this course which involve searching the web for badly made info graphics.

創建者 Yaron K

Sep 21, 2017

Disappointing. Matplotlib is built from layers of interacting functionality, and this course doesn't create a structure to understand it. Unclear and confusing. Note however that the following courses in the specialization show matplotlib code but don't necessitate writing it, so you can do them (at most auditing this course before) and only return to this course if you want a specialization certificate.

創建者 Sophia C

Oct 14, 2018

Not very well done

創建者 Yue Z

Apr 08, 2017

really bad!

創建者 Patrik T

Nov 10, 2019

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.

創建者 Jose P

Dec 07, 2018

Excellent course, challenging and very informative. Highly recommending.

創建者 Gaurav P

Dec 07, 2018

Good concepts of visualizations

創建者 Jasper R

Dec 21, 2018

This is a great course with a lot of insight

創建者 Martin U

Dec 08, 2018

Great course. Really pushed me past my comfort zone which in turned forced me to learn what I otherwise would not have.

創建者 Doronina L V

Dec 10, 2018

Thank you for a great training course!

創建者 Phat N

Dec 09, 2018

Very good course for start learning Visualization in Python! :D