hw05 ready for grading

[Tangjiahui26]

@vincenzocoia @gvdr @ksedivyhaley @JoeyBernhardt @mynamedaike @pgonzaleze @derekcho

SHA: commit 847b0b945266bd58773960af356f37708c14948c Homework05 folder hw05-Tang-Jiahui.md

Thanks~

[peterwhitman]

Hi,

You did a really nice job on this assignment. You more than adequately addressed each section and went above and beyond by revaluing factors. You also did a good job of articulating your process. I found your captions very helpful as well. In regards to your visualization design, I liked your artist familiarity vs artist hotness plot. I do think that you are trying to present a lot of information in one plot. Remember: more isn't always better. I also think that using a color ramp that indicates the progression of time more intuitively would have made plot even better.

Nice job!

Peter

[vmichalowski]

Hello @Tangjiahui26

Excellent job on your assignment! I just have a few comments:

• For your figures, you clearly have a really great grasp on ggplot. A few minor things I would suggest for future graphs is to consider making axis labels more intuitive. For example, "Artist Name" rather than "artist_name".
• I would also suggest interpreting your figures for the reader. Particularly, there was a lot of information in your artist familiarity versus artist hotness plot, and it would have been easier to see what was going on if there was some text underneath to walk me through it.
• Nice exploration of ways to write files in and out! I also found that categorical factors get rewritten into characters when written back into R.
• I also liked your idea to put how the data looked before you dropped 0 and after you dropped 0 into a table - very neat and clear way to compare changes to data. :)

Nice work overall!

Victoria

[pgonzaleze]

Hi @Tangjiahui26 here are some comments about your homework: Reorder a factor: yes File I/O: yes Implement visualization: yes Write data to file: yes Clean up: yes Extras: yes

Part I

• Nice approach in the tasks of this part,
• I liked that you used a different data base to accomplish the task,
• I appreciate that you compared the R base and forecast,
• I liked that you gave brief and explanations of what you were doing,
• I agree with the comment of one of your reviewers in the figures you can “space” the words to make it nicer, something that you cannot do when assigning variable names, in that case you should use “_”, for example.
• I liked that you used and showed different figures to explain the arrange() function, just try to be more specific in the explanation, e.g. you mentioned “As we can see from above figures, arrange() did not change the order, while reordering or fct_reorder coupled with arrange() will change the order of factors”, so the readers have to return to check each figure and compare them to see what you are saying, you can maybe make the comments after each figure.

  Part II

• Import/ export accomplished!
• Nice subset to tackle the question,
• Nice comparisons.

  Part III

• I also liked the approach for this task,
• Maybe would be better to subset or use less values to avoid an overpopulated figure, but in terms of your practice I found it good!
• To round of your nice work it would be nice to make some comments/discuss about your output, e.g. I liked the artist figure with high hottest, but at the end who was/were? And what does a “double” point mean in some artist like Michael Jackson?

  Part IV

• Nice

  Part V

• Clean repo

  Part VI

• Nice exploration, it would be perfect to add more explanation of your output,
• I liked the tidy code and integration of functions,

Overall, great homework! Your grades would be distributed later, Regards, Pedro G