hw06 ready for grading

[menglinzhou]

Hi, @arsbar24 NICE work overall!

• For Q2, it's really a useful function in our later exploration. And you really think about different conditions in your function! I love your function and it will be a goof reference for me.
• For the fillvar argument, because your default of the argument is the last column of the input data, I think it will be better you add a if chunk in your function to judge whether the last variable is quantitative or not.
• Q3 is really an interesting work! Doing basic viewing of candy dataset and making some interesting exploration.
• For the part that you count the number of JOYs in each row, maybe you can try the apply() function, which can avoid loop in R and be more efficient.
• It will be better if you could try to suppress the warning messages with warning = FALSE.
• For the README file, when you insert the links of your work files and reference pages, I think we do not need the exclamation mark, cause it was used to insert a picture, we can use [Text](...) straightly.

Best, Menglin

[gbraich]

Hello!

Great work on the assignment!

For Task 2: Excellent job revisiting our previous lessons (joins, gapminder, dplyr). The function you wrote is impressive and thanks for the explanations, it was easy to understand your reasoning. My only comment on this section is that it might have been helpful to include a legend for ggplot in the function as it was difficult to discern at first glance what each country fill meant.

I enjoyed reading for exploration fo the candy dataset, again great job on combining aspects from our lessons all the way back to stat545. The function you wrote was easy to understand, and your use of the lm function was a nice to see!

For the Trump tweet analysis, I would also suggest the wrapper suppress warning to avoid warnings in the md file. I learned a lot from your analysis of this task, specifically on how you made you included all tweet counts and used the gather function.

The reflections for this assignment were helpful and everything was organized well. You might want to use more informative titles for your md files (to refer to the task and make it easier to navigate) and there were some issues in the hw06 README with respect to links.

Great work!

[derekcho]

Hi @arsbar24 ! Here are some comments about your hw06:

• Your first task was well done and really cool! You were able to come up with a novel task and your process was really well explained. In addition, you incorporated many features of creating functions such as error checking and default values. I like that your function was generic as well and could handle different types of country data (not just from gapminder) and was robust to missing items (like Russia and Antarctica). Nice job!
• Task 2 was also well done! When manually selecting columns from a dataset, I recommend avoiding hard code like candy[1:96,100]. There are many better ways to handle this, but using the select argument in dplyr is just one (it is much easier to read, and less prone to mistakes).
• You produced some neat graphs showing the relationship between njoys and age. The regression line does seem to indicate that as people get older, there are fewer joys (when it comes to Halloween candy), but I wouldn’t go so far as to say that there is correlation here (at least not from the plots and numbers that you showed). In any case, it is a minor point since this class isn’t really about statistical modelling. Your data wrangling of the candy dataset was very well done!!
• For your third task, I think that your points may have been better illustrated if you had used a different set of tweets for your examples rather than the head. In addition, I would recommend actually showing the tweets so that the reader can get an idea of what they look like. Nice choice to Trumpisms though (you missed “Big league” and “Lock her up”, although maybe he uses them more in speeches). Nonetheless, I was able to follow what you were doing since you had good explanations for each part. Also, nice plot at the end!
• Overall, very well done for this assignment, it was a pleasure to read! You exceeded the number of required tasks and did things that were interesting and complex. Nice work!

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