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Applied Plotting, Charting & Data Representation in Python に戻る

ミシガン大学(University of Michigan) による Applied Plotting, Charting & Data Representation in Python の受講者のレビューおよびフィードバック

4.5
5,989件の評価
1,014件のレビュー

コースについて

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....

人気のレビュー

OK

2020年6月26日

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

2020年5月13日

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.

フィルター:

Applied Plotting, Charting & Data Representation in Python: 826 - 850 / 998 レビュー

by Richard B

2018年9月5日

Good background - some of the presentations (such as on seaborn) are rushed

by Jiangzhou F

2020年6月8日

Only thing I don't like is the peer review part. The rest is pretty good.

by M M

2017年3月17日

I found the lectures interesting and thorough yet short and to the point.

by Amine D

2019年10月13日

Really good , you need to read documentation and look at your peers work

by Jose E R

2019年9月2日

Excellent course. I learned plotting and data representation in Python

by Jeffrey D B

2018年10月16日

Class was OK, would have liked some discussion of Bokeh and/or Altair.

by Didac B

2020年10月21日

Really useful course to master the matplotlib visualisation pacakge

by Haldankar S N

2020年5月6日

week 3 is slightly faster as compared to other weeks of the course

by Kishan D

2020年4月20日

The versions of pandas and numpy used in this course are outdated.

by Jialie ( Y

2017年12月29日

It would be greater, if teacher can cover more API in the lecture.

by Srinivas R

2017年10月9日

a quick but sparse introduction to plotting and charting in python

by Abir H R

2020年5月26日

Should be updated with the updated pandas and matplotlib library

by Fatemeh M

2018年7月24日

That was great !

Thanks all the instructors and their colleagues!

by ravi c

2021年9月21日

The course helped me to perform data visualization using python.

by Fabian R

2017年6月30日

Very good overview. Could have been a little bit more material.

by Manoj K K M

2018年6月3日

Good course to get a feel on plotting, what is chart junk etc.

by Iván C S R

2019年2月7日

Really helpful to improve skillset of visual communication.

by Alexander C

2017年7月23日

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

by Lan Y

2020年5月27日

Don't like to review the assignment part. Others are good

by Shuyi Y

2017年4月2日

Great training in matplotlib and the plotting experience.

by VP P

2021年6月7日

This was very strenuous. There are better graphing tools

by 布鲁斯然

2018年1月15日

I learned something that helps with my work. Thank you.

by Qiyu L

2018年2月5日

Somewhat easier compared to other courses in the pack.

by ALISON J D

2018年1月15日

A fun course, well-taught and with some lovely charts.

by Nuno d S

2017年6月29日

Very nice course, however It could cover more topics.