HW #03 is ready for grading

[angmelanie]

Hi Nathan,

Great job on your homework! I agree with you that the homeworks are taking longer but things are definitely making more sense. From peer reviewing your homework 3, it looks like you're applying class material nicely in your assignment. I have a few more specific comments below:

• One suggestion, you could add {r Install gapminder, results='hide', message = FALSE, warning = FALSE}at the beginning of your load library code chunk, simply to surpress warnings and make your .md file tidyer and more streamlined.
• Looks like you did 4 out of the required 3 task, which exceeded the course requirement
• As a reader of your code, my suggestion is to enter to new line after a pipe or + (in ggplot), just to make code easier to read (as I see you did it in some code chunks)
• I'm liking that you tried the coord_cartesian() function, although I'm not sure if this is the correct use of this? I think you get the same result, but I believe its intended for viewing/zooming on a specific area of your plot without changing the data (as in a linear fit model). In this case, as your y axis is plotting life expectancy, you could use geom_bar(). I found this article that helped me understand it a bit more.
• Nice use of the glm in addition to the geom_point! Will use this in my plots in future

Overall: I thought everything was well displayed, clear and concise. Axis and aspects ratios are visible. Tables have additional stylized features that go beyond the course (kable_styling). Code is concise. Your repo is organized and it was easy to find your assignment.

See you in class! Melanie

[gbraich]

Hello,

Nice job on the homework! The README was easy to read, but it may be helpful to include links in the future.

Task 1-Life Expectancy Changing Over Time- The dplyr functions were easy to follow and the table was nicely formatted using kable. The plots were well chosen (facet wrapped by continent with points) and fitting a line made it easy to see the trend by continent. It would be helpful if you included some commentary on the data.

Task 2-Max and min gap per capita by continent- The functions and table were laid out well. The plot looked good, although it might have been useful to put a line through the min and max points to clearly see the trends and not have any confusion in the two points plotted on the same x coordinate.

Task 3-Trimmed life expectancy- This was well done in terms of the table and the plot. My only suggestion would be that if you wanted to keep the descending order from the table into the x axis of your plot, your could in the future designate your resulting table as a new variable and use that variable to pipe into ggplot.

Task 3-Low life expectancy and low GDP per capita-Also well done and easy to follow. Excellent tables and plots.

Overall I thought the homework was done well and you exceed expectations by completing four out of the three required tasks. I thought it would have been helpful to have more commentary in your document about the tasks and inferences on the findings of your tables and plots. Your use of formatting for the tables and the plots was great and made the document very easy to read.

Great work!

Ginni

[derekcho]

Hi @nbendriem! Here are some comments about your hw03

• Nice use of headers, they definitely make your assignment much more readable and organized!
• Did your first table show what you were expecting? I am not sure what you were going for there but you probably could have used a group_by() statement or something! Also, does the reader need to see every single country, or are there better ways to summarize this information?
• Your plots look nice and it is easy for me to tell what you are trying to show without having to look at your code
• Your repo is well organized and things are easy to find!
• Good coding style, your code is generally easy to read and efficient
• You can turn off messages and warnings by specifying the arguments warning = FALSE and message = FALSE in Rmarkdown.
• Good explanations for each task, they make it much easier for readers to understand what you are trying to show
• Do these life expectancies change over time? If so, then maybe a scatterplot over time would have been a more appropriate graph. You could always superimpose a line that represents the mean on top of this!
• Interesting exploration for your fourth task, it seems like low life expectancies are correlated with low GDP per capita!

Note: your mark (check minus, check, check plus) will be distributed later.