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

5,517 個評分
929 條評論


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....



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 ..


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.


826 - Applied Plotting, Charting & Data Representation in Python 的 850 個評論(共 915 個)

創建者 Benny P


The video guide is pretty good, it shows you a lot of thing that you need to learn. It covers a lot of breadth and depth, but only briefly. For further info, and for the most part of your time when doing assignment, you need to seek the relevant manuals yourself. But that is fine, because matplotlib is very very rich library and there's no way all can be taught in a single course like this, and also it makes you familiar with how to find information yourself.

The main drawback is with the assignments though. I'm okay with the peer review system. The problem is that the assignment specification is not too clear. For example, in assignment 4, you need to think yourself about what you want to visualize. So a lot of time was spent on thinking about WHAT problem to display rather than HOW to address the problem (using plotting/visualization), which is the subject of this course.

創建者 Guo X W


This course provides an overview to the matplotlib and seaborn library and guides learners to create useful visualisations with Python. My main issue with the course is that the various topics are not covered in sufficient detail. Successful completion of the assignments required far too much independent learning on commands that were not covered in the course (particularly for Assignment 3).

The course also covered Principles of Information Visualisation in great detail. I thought that was refreshing and useful. However, I felt that the portion on Matplotlib Architecture could be explained in more layman and palatable terms. In addition, it would have been more meaningful if the course drew more on actual real-world datasets instead of histograms generated from a random normal distribution.

創建者 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).

創建者 Tiberiu T


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.

創建者 brian a


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.

創建者 Oliverio J S J


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.

創建者 Bhavin P


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.

創建者 Sarah B


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.

創建者 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.

創建者 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.

創建者 Peihong H


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

創建者 Renier B


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.

創建者 Varun D P


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.

創建者 Christopher I


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.

創建者 Khokon C S


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.

創建者 am


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!

創建者 Abhijit G


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.

創建者 David P


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.

創建者 Aayush N


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.

創建者 Manikant R


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.

創建者 Jay S


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.

創建者 Frank L


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.

創建者 Leon Z


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

創建者 Meixian W


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.

創建者 Amit m


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.