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
5,161 個評分
852 條評論

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

OK

Jun 27, 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 14, 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.

篩選依據:

601 - Applied Plotting, Charting & Data Representation in Python 的 625 個評論(共 839 個)

創建者 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.

創建者 Christos G

Sep 01, 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.

創建者 Katya H

Apr 05, 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.

創建者 Juan M

Sep 18, 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.

創建者 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.

創建者 Noah K

Feb 01, 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!

創建者 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.

創建者 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.

創建者 Alexander 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.

創建者 Luke G

Mar 03, 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.

創建者 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.

創建者 KylinMountain

Apr 27, 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.

創建者 Alan J

Apr 02, 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!

創建者 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.

創建者 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.

創建者 Mohamed A H

Oct 26, 2018

The instructor is very professional. The course has really high-quality academical information that come very valuable and handy when you get to create charts and visualize the data. Definitely recommended!

創建者 Steve M

Mar 03, 2018

An very good overview of how to develop honest, functional and aesthetically pleasing data visualizations. With additional instruction in how to use matplotlib and Seaborn, it would be a five-star course!

創建者 ayush k

Jul 05, 2018

Practical course with hands on exercise to make you well versed in Applied Plotting, Charting & Data Representation in Python. I recommend at least every college student should experience this course

創建者 Ivan R

Mar 01, 2018

It contains very good recommended lectures, good material and explanation about matplotlib to grasp a big picture. However, you must invest a lot of time on your own to research deeper in the topic

創建者 Vishal S

Mar 20, 2018

Week 1 is a little bit theory and boring for me because that doesn't interest me but week 2 and week 4 is amazing. Especially week 4 assignment is too good. Overall the course is worth learning.

創建者 Brandy B

Aug 18, 2017

I thought this was a really good introduction to matplotlib and some of the things you can do with it. The final project we got to apply what we'd learned to real data, which was a lot of fun.

創建者 Tarun Y

Aug 03, 2020

This course is really helped me not only to increase my knowledge about the tools but also with the help of the additional reading and optional assignment help me out to improve my skill.

創建者 Vidya M S

Aug 23, 2019

It's a good intermediate level course . Prior work in Python plotting functions does help . Assignments are good and make you stretch your skills . Discussion forum is quite supportive.

創建者 Ezequiel P

Sep 08, 2020

Good course! Could be improved by assignments better suited to the lectures. But having them pushing a bit further and forcing you to figure things out on your own is definitely great

創建者 Temuge B

May 17, 2019

Week 1 of the course is complete waste of time but weeks 2 to 4 are decent. Only complaint is that the assignments are not very clear and also it doesn't go very deep into matplotlib.