Chevron Left
Volver a Applied Plotting, Charting & Data Representation in Python

Opiniones y comentarios de aprendices correspondientes a Applied Plotting, Charting & Data Representation in Python por parte de Universidad de Míchigan

4.5
estrellas
3,859 calificaciones
624 revisiones

Acerca del Curso

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....

Principales revisiones

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.

ML

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.

Filtrar por:

51 - 75 de 611 revisiones para Applied Plotting, Charting & Data Representation in Python

por Yue Z

Apr 08, 2017

really bad!

por Leonid I

Sep 17, 2018

Overall, the course is great and definitely deserves 5-star rating.

However, it starts quite slow and in my opinion first few lectures discuss irrelevant topics, like minimalism of presentation. The problem is that a person can't grasp them without experience...

For example, several videos discuss idea of Edward Tufte. I understand that CS and mathematical statistics are the background of the instructor, but really, Tufte had only repeated well-known basics. Indeed, it was Leonardo da Vinci who first said that "simplicity is the ultimate sophistication". He was followed by Antoine de Saint Exupéry with "It seems that perfection is attained not when there is nothing more to add, but when there is nothing more to remove" and the KISS principle of Kelly Johnson of Lockheed Martin Skunk Works.

Perhaps, for the authors of the course software engineering is closer: https://wiki.archlinux.org/index.php/Arch_Linux#Principles ...

por Aino J

Feb 02, 2020

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!).

por Ilya R

Jul 25, 2017

Perfect, insightful, deep, challenging! I love the way prof. Christofer Brooks teach Data Science. Interactive IPython notebooks enables creativity to implement lecture notes right in the browser during watching lections.

I enrolled to "Applied Plotting, Charting & Data Representation in Python" course right after finishing the first "Python for Data Science" module. This is one of the best experiencies I got during my online education.

There are a very active forum discussions on this course, people and course staff are helpful.

Next, I want to enroll next courses of the Specialization.

Also I would like to say "Thank you" to course team and Coursera for the financial aid opportunity.

por Vinayak

Jul 05, 2019

This course helped me understand the basics of Data Visualization unlike any other internet resourses.

It starts with one module completely dedicated to the theory behind data visualization and how to present data in a genuinely insightful manner and then delves into matplotlib and eventually seaborn to implement the same.

I enjoyed Dr. Brook's teaching and the exercises. With a solid pedagogy, challenging exercises (the last one is especially fun and gives you a feel for the subject) and insightful lectures it's a great course for people looking to gain knowledge about basics of python data visualization.

por Han C

Aug 28, 2017

I really enjoyed this course. As a python novice I had to spend lots of times in googling commands for arguments, options, examples. Well I see many peoples are only relying on course materials but the considering this course as a motivator. I often felt frustrations and pressure, but not tried to be defeated by myself. Hope you guys find your own way to get it done. I still see lots of thing to learn, but I am not worried. This is only the beginning. Course is not a magic pill, it just gives a start point. As a start point, this is really nice cource to take.

por Hari G S

Sep 12, 2019

This is an excellent course on visualization in Python. The videos are brief and covers just the right amount of information. Reading resources and assignments are carefully chosen and perfectly complements what we've learned in the lectures. Assignments, most of the time, require us to read the matplotlib documentation but is easily understandable once gone through the lectures. Assignments are not very easy/simple, but completing it with real data and help from documentation, stack overflow and discussion forums is deeply satisfying.

por David C

Jul 12, 2017

This was an interesting course. The professor was excellent and the practical exercises, in particular, were beneficial in learning the material. My only complaint would be that a lot more time in the exercises was spent formatting and manipulating Pandas dataframes than applying the matplotlib libraries to produce charts and graphs of the data. I would have preferred to spend more time experimenting and using the graphics libraries and less on trying to manipulate data to get it into formats acceptable for grading.

por Sabu J

Oct 17, 2017

U-M and Coursera together brought a great and very interesting course. Great that the learners get exposed to various aspects of DS, be it the concepts , trends etc. A great platform for participants to learn together and experiment. Course introduces what is relevant in the industry and provide multiple opportunities to apply the learning. On top that it is laced with interesting challenges, not a cake-walk -:)

My sincere thanks to U-M, Coursera, teaching staff and all who made this happen

por Eric G

Feb 20, 2019

You are going to learn by doing, less then getting a deep lecture of Matplotlib. Yes you will learn it quickly, but the lecture videos are only about 15-30 minutes a week, while the projects will take you a few hours to complete (With the last two taking significantly more time if you want them to). I was a little disappointed that I didn't get I 100% clear picture on how to use Matplotlib and Seaborn, but I do feel like I gained comfort, so it was worth taking!

por Kenia S

Apr 04, 2017

I continue to like the way the Prof. Brooks explains the different topics, the selection of the topics themselves and the scientific articles are very enriching. I was previously an HCI researcher and it was a pleasant surprise to find such great art Thanks for sharing them! It was defenetly a challenge for me, learning it all and doing the assignments. At the end, I'm proud, I've learned a lot and l'll definitely share what I've learn so far. Thank you!

por Jiongnan L

Dec 02, 2019

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.

por Val A B

Sep 22, 2018

I found this module to be the most enjoyable of all the Data Science courses offered by UMich. The method of instruction isn't only aimed at plotting data in various charts but it also focuses on the subjective part of visualization. I had fun doing the assignments, especially the 3rd and 4th week assignments, and I could say that I have improved a lot with my visualization skills. 10/10

por Krishna P B

Dec 26, 2019

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.

por Brandon H

Dec 26, 2017

There are so many components to plotting that I didn't take into consideration, and this is after having gone through a Master's program in statistics. I have taken many of the simple things into mind each time I create a visualization at my job. Thus far, I have found the first two courses in this series invaluable and highly recommend it!

por Daniel H

Apr 30, 2019

Very clear explanations and wide range of tools to know different ways of data representation. I like a lot it is more a practical than a teorical course. Also, is very interesting to learn some kind of 'rules' for data rep (truthfulness, beauty, insightful, and others. Congratulations and thank you for this really good learning experience

por Paweł R

Apr 03, 2017

Very good course, solid introduction to matplotlib and interesting assignments. I was skeptical about the peer review format at first, but then I embraced it - good choice! I liked how the course built on the foundations of the previous one. To pass the assignments I had to use Python, pandas, matplotlib and other tools combined!

por Aditi Y

Feb 05, 2019

This was a very informational course, when you can visually see actual trends that has happened in the history or interesting facts from all over the world, with proper data backing up. What I liked the fact was how Tufte's and Cairo's principles are strongly emphasized throughout the course to get the best results possible.

por Aayush G

Apr 06, 2019

Course was very well-framed. It actually covers all the possible parts of Matplotlib in a well-paced & content-rich lectures with real world problems as Assignments.

I would request my peer learners to take up a Statistics Course which will make this more clear as one can co-relate the plots & the stats behind them.

por Praveen R

Oct 29, 2019

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.

por Sanjay N

May 29, 2018

What I like about this course is its pace and content. It can be a bit un-nerving in the beginning since the lessons are pacey. But that is what is great about online courses. You can re watch the videos and refer to the notebook examples provided to catch up. Most important - the content is great !

por Shubham D

May 15, 2019

It's a really good course for data visualization, it starts from very basic of visualization including Cairo's Parameters, ethics behind visualizing data and then provide an understanding of matplotlib, seaborn and other visualization related libraries. Assignments are really helpful and amazing.

por Fuat Y

Jan 07, 2018

Wow, it was a very interesting and challenging 4 weeks, I can not even compare my knowledge now to the time I started to this course, I learned a lot, searched a lot and coded a lot. I am happy now that I can create infographics, and gained a good background about what a good infographic is

por Michael L

Jun 17, 2017

Excellent course with in depth explanations. It is well structured. It learn me to applied Plotting, charting and Data representation in Python from very basics to optimum level. It help me to understand details of using Python to Applied Plotting, Charting and Representing Data.

por Servio P

Feb 04, 2018

This is a fantastic course. The lecturer is amazing and I learned tons of information about publication quality charts and data cleaning.

It takes plenty of time though.

I recommend this course to anyone serious in learning data science. At least to those starting in this area.