hw02 ready for grading

[NSKrstic]

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

You can find the relevant files for Homework 2 here: https://github.com/NSKrstic/STAT545-hw01-Krstic-Nikolas/tree/master/hw02

[angmelanie]

Hi Nikolas!

Nice job on your homework 2! I’m liking your README file and the way you split your code into the 2 markdown doc – it’s very well structured and made it a breeze for me to navigate your repo. A few specific comments:

Exploratory Analysis Your .md file is clear and I like your additional comments in answering the questions. I see you tried out kable. Looks good, I think I’ll be using it in the future to display my results, although it seems a bit more clunky in its code then a regular table. For example in your frequency table code, where you had to matrix and transform it to be in the correct format for kable. I also tried using the count() function to perform the similar operation, just another (of many) alternatives I’m sure: gapminder %>% group_by(continent) %>% count() %>% knitr::kable()

Plot Gapminder Beautiful graphs! Looks to me like you answered all the assignment questions. I also learned how to change the angle of the axis text and justifying from you. I’ll definitely be using that in my next homework assignment so thanks for sharing!

It was a pleasure reviewing your homework. Good luck in the rest of the course :) Melanie

[wswade2]

Hi Nikolas,

Overall it looks to me like you did a great and thorough job on this assignment and I learned some new techniques from your style of coding. I have been looking for a way to keep those irritating package loading warnings to stop and your R code showed me the way. I have not yet encountered the kable function that you used to generate your tables, so that will probably be handy as well.

I noticed that you used "=" to assign names to dataframes. While this does work, it is better practice to use
"<-" because R uses the equal sign for several other functions. At the very least, this makes your code a little more confusing to read; it was difficult for me to tell the difference between your code that was naming something and the functions you were applying to your named variable.

Your plots look great, and I like that you explored the theme function. You nailed the analysis of what was wrong with the code presented in the assignment as well. Since I learned from your code, you went above and beyond with the plots, etc., and it was easy to navigate to your homework, my evaluation of your assignment is a check plus.

Wade

[ksedivyhaley]

Smell test of data: Yes Explores at least one categorical/quantitative variable: Yes Uses various ggplot types: Yes (boxplot, line, scatterplot) Uses filter(), select(), and %>%: Yes Bonus (evaluate code, tables, more dplyr): Yes, code evaluation, kable Reflection on process: Yes

Comments:

• I prefer the assignment to be in one markdown file - I almost missed half your assignment!
• Additional question: excellent discussion of why the example code fails!
• Good piping – though you can actually pipe things into kable as well.
• select() doesn't actually do anything when piped into ggplot – it's for displaying tables.
• I like that you've explored faceting, but the resulting graph is confusing – doesn't seem to have a clear message.

Your mark will be distributed later. If you would like more feedback, please feel free to message me on slack.