Quite an extensive course - as a beginner it went a bit over my head at times. The Assignments were challenging and the final one was a bit dissapointing - not all the elements were covered in the labs so had to trawl the internet looking for answers. Learned alot though

Course is great but the part with Folium should be separate course (some Advanced Visualization) rather than graded part of this corse. Instead of using Folium in final project it would be better to use some Seaborn advanced visualizations or other plots in Matplotlib.

The most interesting course in the specialization up to now, for me at least. A brief but informative overview of all kind of plots that can be done on pandas dataframes.

To the course author: repeating the data wrangling/cleanup in EVERY video gets annoying.

Teh course went well. Would have liked to have seen more education on the DASH function definition under the input/output callback. Would have also liked to have seen more education sorting the data by month and then plotting by abbreviated month labels.

Although the content of this course is very interesting and has a lot of depth in the field, I believe that it needs further improvement, specifically with more examples in the labs, in order to get a better hang on the different types of visualizations.

The materials are OK, the labs are really helpful, but the test-related data files that needed are hard to get. In fact, some of the csvs required to complete the test are out of time, and students can only get the data through the forum, that's a pity.

Hey! Thanks for the course. At the beginning everything was good and understandable, but at the end of the course the teaching material was not sufficiently developed. In the laboratory, it is necessary to describe more actions and possible solutions.

Overall the content of this course was good. There were some headaches with getting folium working. It was annoying listening to the description of the dataset we've been using for half the video every video. But it did help with learning matplotlib

Short videos but well-worked notebooks with many examples on Visualizations with Python. Exercises had tricky questions that the student must pay attention. The final assignment is difficult, since it uses some features not explained in the classes.

It is a great learning experience, but if course staff can look into issues candidate face it will help them. But for me it was a challenge as am i am new to programming. Thanks to forums and of course Google and python community for big support.

While the course was very good and showed lots of different data visualizations available in Python, the final assignment required topics that were just briefly touched upon and required quite a bit of outside research to figure out the syntax

Mostly really good. great practical projects. would have liked a few more practice sets to better understand some of the unfamiliar concepts that popped up in final assignments, but other than that i really liked it, great helpful TA as well.

This course is interesting to learn and the final assignment is not something you can copy from the lab sessions and easily pass, which is good. However I noticed the questions posted on discussion forum are rarely answered by teaching staff.

Labs are very interesting. Would suggest including more data wrangling techniques (to better align with the final assignment), and removing Mapbox Bright references. On the whole, this was a far more interesting module than I had expected.

The Course helped me to clear my doubts and made my concepts of Data Visualization more strong.

The Ungraded assignments helped me to apply the concepts in practice. The quizzes were easy and I think there should be more questions in quiz.

This was more difficult than expected, but I did enjoy the lab work as challenging as they were, I found it helped in bringing previous learning all together. I took much longer in completing the labs than the estimated time provided.

OK overall - but I wish there were more and smaller hands-on exercises. Also, waiting to load 3rd party libraries in exercises is quite slow (3-5 mins for choropleth, for example) - it would be nice if these could be pre-loaded somehow.

Course provided very detailed introduction and lab sessions were great however at of today April 11,2022. A few line of codes have been deprecated, though it might (or not) affect the experience, I hope the course will be updated soon.

Good intro to matplotlib, visualization of dataframes. Some of the more advance content, e.g. choropleth maps, relies on older versions of some of the python packages (folium) so the examples need to be updated for the newer versions.

the course is great, however, I think matplotlib's structure should have been explained in greater detail, this would help the student to accelerate the understanding of the library's documentation and implement his visualizing needs.

Good materials but need to be continuously updated since the libraries and such change often. There were times that only a specific version of Python and a library would work at all. It would be better if it weren't so fragile.

Great module to learn about the most common different types of plots we could generate with Python coding. I would suggest to deepen more in Matplotlib's Pyplot scenarios, including tick, label, legenda nd filling options.

I enjoyed the course to the fullest. My only complaint is regarding question number 2 in the final assignment. The bar chart that we were requested to create and display is not shown in the videos or labs how to create it.

Generally good content with great lab additions except for Folium. Folium 0.5.0 is outdated (it is 0.11.0) now and the choropleth method is deprecated. Also, the final assignment threshold label differs between versions.

Course content is good. But there're some replication for each video about "recap of the data". The final assignment is quite difficult because I need to find some codes from the internet to meet some task requirements.