hw05 ready for grading

[sdhanani]

You did a great job dropping Oceania and manipulating the levels of country by showing the steps and code you used in order to accomplish the task at hand. It would have been nice to see table showing the mean life expectancy values upon which you based the new levels just to show that it did in fact re-order the levels in this manner. You did a good job showing the effects of arrange visually using graphing techniques for the first two plots but I'm not sure why you included the third plot as the colours argument didn't work in your graph. I like that you compared three types of writing and reading files in R and that you described some of the changes that occur with your dataset as it makes the round trip but it would have been nice if you had included that kind of information for future you. You compared two different colour palettes to a previous graph which improved a the interpretation of the graph. It would have been nice to see a graph embedded in your report from ggsave() which you can do with .png files.

Your repo is decently organized but it would have been nice to remove unnecessary folders from the repo and you have easy links to each assignment but it would have been nice to have a description as to what each assignment includes for future reference. Some more descriptions for what you were doing throughout the assignment would have helped the reader follow what you were doing with more ease. Overall, solid effort.

[jmurthy12]

Hi Hyeongcheol ,

Great job on assignment 05.Please find my comments as mentioned below:

• Your README explains the hurdles you faced to understand stat545 webpage. I appreciate your efforts.
• Factor management section provides clear comparison of output results using:fct_reorder(),fct_drop(),droplevels().
• Effects of arrange() was clearly discussed using plots and also the effects of arrange()+ fct_reorder() were expressed clearly using ggplots().
• Minor suggestion in the above section to color code countries: Probably instead of using this -> “gap_life %>% ggplot(aes(x=max_life, y=country, colours=country))+geom_point()”,you could try using this -> : “gap_life %>% ggplot(aes(x=max_life, y=country))+geom_point(aes(color=continent))” for color coding different countries.
• File I/O Operations :
  1. You’ve experimented write / Read CSV to confirm that the factor order does not survive the round trip.
  2. You have also experimented the same using read/write TSV, wherein you’ve used the system.file () functions, I have never used them and learnt of this function from your work
     3. Your work on dput/dget, this helped me a lot in learning the head(scan()) functionality.
• Visualization : You’ve compared ggplots from your previous effort with your current learnings by using scale_colour_distiller() and scale_colour_gradient2(),I liked the latter part , wherein the population metrics were differentiated using white and red dots
• Nice job in using ggsave() to save the plots in different file formats.

Good Luck for STAT 547 :+1:

Thanks, Janani.

[ksedivyhaley]

Factor management (drop & reorder): Yes File I/O (data): Yes (thorough) Visualization design: Yes File I/O (write figure): Yes (but see comment) Organized GitHub: Partial (see comments) Bonus (more forcats, eg relevel): No Reflection: Yes

Comments:

• For your repo, add “slugs” to the files, eg hw05_FactorsFigures, so you know what is in each assignment – especially since your links in the README don't explain what's in them either. I also recommend using subfolders in each assignment to store saved figures (hw05 is a bit crowded).
• “Its weird that I need to put "" inside of the read.csv ftn. ... when we do read.tsv, we don't need to put "" inside of (). ” Incorrect. The quotation marks tells R that the file name is a string. Your gap_tsv variable is a string, so it essentially already has the quotation marks. If you were giving read.tsv a file name instead of a variable containing a string, you would need the quotes.
• For the visualization design exercise, your use of colour is good, but otherwise you could stand to polish your figure more, eg by specifying titles.
• When you write files, you can include the image directly in your report using markdown, like you did in your README for HW01, rather than just link to the image.

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