hw02 ready for grading

[suminwei2772]

@vincenzocoia @gvdr @ksedivyhaley @joeybernhardt @mynamedaike @pgonzaleze @derekcho

Latest commit: 06485a1

README.md for hw02 Gapminder_dplyr_explore_hw02.md explores the gapminder dataset with dplyr and ggplot2 README.md for entire repo modified to include hw02 links

[danaj191]

Hey Lisa! Your HW2 md file that I found via your README is great! You really thoroughly explored the gapminder dataset using a ton of different functions, including different packages, different arguments, and different formatting options. And, it was very easy to follow the progression in your assignment because you really clearly outlined the md file according to the instructions in HW2. Thus, it was always easy to tell what question you were responding to, what your answer was, and how you got there (including the multiple ways it's possible to get the same answer).

Also excellent documentation of your workflow at the bottom of your file, including how you troubleshooted problems you were having and any sources you relied on.

I learned a lot from what you did and it was neat for me to see some different plot types that I haven't tried yet myself, like the violin plots! Great job, check plus.

[yidie]

Hi Lisa, here are some comments:

• Your repo is very organized. I can find everything easily.

• Good README which outlines what you did for hw02. Good md file which is outlined according to the instructions. Every question was answered clearly and you indicate what function you used to get the answer. It is easy to follow what you are doing.

• It is nice that you showed multiple ways of how to approach the same problem. I learned a lot.

• Graphs are labeled properly and you make observations about them. Easy to read. Violin plots are interesting to see.

• Excellent job exploring functions other than those that were taught in class: stat_function, annotate, sort, ggtitle etc.

• Some of the code are not showing properly. Seems like they are being cut. I guess it is because that the code is long and you didn't start a new line. It would nice if you could fix them.

• You did the additional practice. And the reflection was thorough enough. Thanks for sharing useful resources with us. There are good efforts in your hw02!

[suminwei2772]

Hey @yidie, Actually for the code chunks that looks like they're being "cut", if you scroll the horizontal scroll bars, you can see the rest of the code :) Just fyi

[pgonzaleze]

Hi @suminwei2772 here are some comments concerning to your homework:

Smell test of data: Yes Explores at least one categorical/quantitative variable: Yes Uses various ggplot types: Yes Uses filter(), select(), and %>%: Yes Extras : Yes Reflection on process: Yes

• Detailed and well organised homework
• Good that you provided a brief explanation of what you were doing/getting.
• Your exploration data was good, it would be nice if explain what some functions do. E.g. you used unique() and n_distinct() that are intuitive but not always they are.
• I liked your plot exploration as well. Well selection of features according what you wanted to show.
• I think that you mentioned but it is hard to jump from one way to another if you are already use to work with one (plot to ggplot or use of pipe operator, for example).
• I think you are aware that there are many ways to get/compute the same results.
• Fulfilled requirements and beyond.

Well done! Regards.