Homework 05 is ready for grading

[HScheiber]

Link to the main page of my homework repo.

Link to the homework 5 Section.

Link to the homework 5 - Factor and Figure Management

Last SHA: 7dfa5f214172a7659a2567de35463b8d5a244732

[mattssca]

Peer Review STAT545 HW05

Carl-Adam Mattsson

Hi Hayden Scheiber. My name is Carl Adam and this is my peer review for you final assignment in STAT545. First of all, great job on your assignment. You truly demonstrate an extensive knowledge in R and it's obvious that your an ambitious student. You have done everything (and more) that was required from you in this assignment. I really like what you did with your README.md the table "Homework assignments" is very neatly presented. It gives a good overview of your efforts in STAT545. Other than that, you have provided appropriate links which helps the viewer in navigating your repository. I don't really have much to comment on your work, but here's my peer review for your assignment.

• In the first part of this assignment the goal is to drop the "Oceania" level from the continent factor. Initially you inspect the class and level of the continent factor which is vital in understanding your data set. Also, you inspect the "Oceania" level by investigating the number of entries in this level. I like your approach here.

• You filter out Oceania by calling gap.rm.oceania <- gapminder %>% filter(continent != "Oceania")and your observations are correct, by filtering out a level of a factor the factor remains in the data set and you present two different ways to get rid of the empty factor. You also provide strong evidence for what you did and achieved, great!

• In the "Reorder the levels of country or continent" part I don't have much to say besides that truly demonstrate a vast knowledge in how to manipulate and reshape your data. Your code is nicely commented and confirms that you are on top of things here.

• In your last part of this assignment (Visualaztion design) I like that you successfully merged the gapminderdata with some outside data by calling the ìnner_join()` function and your figures defiantly looks awesome and shows some interesting correlations!

• You've also tackled the "But I want to do more!" part with elegance.

Like I previously stated, I don't have much to comment on your assignment besides its awesomeness. Keep up the good work and I'll see you in STAT547!

[julianheavyside]

Hey @HScheiber !

Nice work on the last assignment! Going out of 545 in style!

Here are some comments, in no particular order!

First off, I really like your main repo README-- super organized! It's really easy to find everything from there, and you have all the major useful resources contained in one place. Not sure if you already had it like this, but if you organized it for the HW05 task, then superb effort!

You use of droplevels() is great, but I also like your alternative method using factor()

I'm going to copy your table of contents organizing method!

Your plots are beautiful. Great use of the "channels" that Tamara discussed in her guest lecture.

Your dialogue throughout the analysis is easy to follow, and very clear for me. Thank you!

All in all, a really really nice job! I tried but I can't actually find any major issues with your work! I learned a lot from reviewing your homework.

Good luck with everything in your futuRe!

[ksedivyhaley]

Factor management (drop & reorder): Partial (no “common part”) File I/O (data): Yes Visualization design: Yes File I/O (write figure): Yes Organized GitHub: OK (see comments) Bonus (more forcats, eg relevel): Yes Reflection: Yes

Comments:

• For your repo, add “slugs” to the files, eg hw05_FactorsFigures, so you know what is in each assignment (and don't have to scroll down and search through the table of contents) – nice table of contents, though! I also recommend using subfolders in each assignment to store saved files (hw05 is a bit crowded).
• For the Factor Management portion, you were expected to demonstrate the effect of reordering factors vs arrange() on a figure.
• Interesting use of showing factors' numeric values, and of fct_inorder()
• Nice use of as.character(1960:2015) to get multiple column names.
• The figures for visualization design look very neat. To improve, try using a non-default colour palette.
• Interesting solution for the bonus.
• Clear, organized, good problem solving.

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