hw05 ready for grading

[vibudh2209]

The link to markdown file is this

[rishadhabib]

Hi Vibudh

It was great going through your homework. Your repo and files were very well organized and linked to everything. You also reported the process clearly and shared some good links.

I really liked your table of contents and looked at the raw file to see how to do that. I've been using a YAML header to add a table of contents but that isn't as customizable as your technique. Your tables were clean as you used kable. One of the things that would have helped me while looking at your assignment is if the code was in separate lines so I wouldn't need to scroll to see the full code. I liked your boxplots but the different arrangements were not affecting the graph much; I think using geom_point would have helped visualize the effect of changing the order. I also liked your use of colour especially in the life expectancy vs gdp graphs and overall thought you did a great job.

Rishad

[yeonukkim]

Peer review from Yeonuk:

Hi.

Overall, you did a great job.

• Your repo is well organized and connected to each hw from readme.md through links.
• Tried to hit all elements.
• Worked for gapminder as well as singer.
• I worked for gapminder only, so I didn't know the difference between as_factor and as.factor before review your homework. It is helpful for me. Great job.
• Reflections in md file are helpful to see your workflow.

Comments:

• It is good style to break up your lines of code so others don't have to scroll sideways (it is somewhat hard to read your code.)
• This part of your code "knitr::kable(list(head(levels(new_s......" is difficult to see due to many brackets. Why don't you use piping?

[derekcho]

Hi @vibudh2209 ! Here are some comments about your hw05:

• For the first part of your report (factorising), you did a good job converting the title in singer locations to a factor. I understood what you did but it took me a few reads to see the difference between base and forcats in your examples. I think that it might have been better if you showed the table as side by side columns rather than two separate tables.
• The second part of your assignment was done well! You were able to drop Oceania as a factor successfully. I would suggest showing the factor levels rather than the number of factors left since there are so few of them. That way the reader knows that your code did what you described rather than having to take your word for it
• For the third part, I think that it would be best to only show the effects of reordering by median rather than mean as well. The middle line in the boxplot does not necessarily correspond to the mean population and therefore your plots do not look very ordered
• Also, try not to connect so many pipes in one long line of code since it makes your code harder to read
• Great work showing the differences between read_csv, readRDS, dget! I really liked the table showing the order of the factor levels after loading.
• Nice work in the visual design section. You were able to show several ways to change the colors of your graph.
• For your scatterplot of lifeExp vs gdpPercap, I think you were trying to show one too many things. It is important for the reader to be able to distinguish which points correspond to which countries
• Good work overall! Your report is well organized and your repo is easy to navigate. Well done in STAT 545A! Note: your mark (check minus, check, check plus) will be distributed later.