Peer Review Comments

[15jennlee15]

@alexisadamsclark @datalorax

Hi Alexis! It was really great to see your code, nice work! I left a text file with the edits in my forked version and I also added the comments here. My biggest problem was I wasn't able to install some of your packages and it seemed like there wasn't code to import data so I wasn't able to fully see your visuals. Your code was very lovely though. Nice work on your project!

I wasn’t able to install some of your packages and your script didn’t include data to import (maybe it’s part of one of the packages?), so I made my review based on the code as best I could.

Visualization 1:

Strengths: You did a great job at putting in a lot customization into the plot, text and custom color and it makes for a really nice visual. You paid attention to the little details and it really shows! It was also great to see your different iterations.

I have never used geom_segment before so it was great for me to learn about this and see how you used it in your data.

Also this "\n" was a great trick to learn!

Potential area for improvement: I agree with a comment you made, I think you could try out playing around with your y scale limits and this may improve the graph a little bit, but overall great job!

Visualization 2:

Strengths: Great to use different color scales. Again, really great to see the different iterations and the work you put into trying different things. You also do a great job of making sure everything is really clearly labelled and easy to follow.

I really couldn’t come up with a suggestion for improvement here because I wasn’t able to run the code and visualize the plot. From the code it looks great.

Visualization 3:

Strengths: Great attention to details and labels again, really excellent.

Had a hard time visualizing what the geom_segment piece represented here, maybe would be more clear if I was able to run the visualization.

Areas for Improvement: Making the Y axis Title “Percent” rather than “%” would be nice I think

[alexisadamsclark]

Hi @15jennlee15,

the Salaries data is part of the "car" package. If you install.packages("car"), you should be able to have access to the Salaries dataset automatically. Thanks for your comments!

[15jennlee15]

Thanks @alexisadamsclark This makes sense. I had tried to download this package and keep getting errors. I will see if I can get it to work and update any feedback I have if I do!

[15jennlee15]

@alexisadamsclark @datalorax

Hi Alexis, I was finally able to download the car package without any errors (woo hoo!) so was able to see your visuals and wanted to leave some additional comments.

First off just commenting on how really beautiful they are, you really paid a lot of attention to the details and it makes the visuals very aesthetically pleasing and also easy to read.

On your first visual, I really like the degree of symmetry in the scale of the axes. One more point of improvement is that I feel that the current location of the annotations isn't ideal as for the male side it obscures one of the points.

For your second visual, you mention wanting to merge the waffle plots, one option is to create a single waffle plot like this:

partsf <- c("Female Assistant Professor" = 11, "Female Associate Professor" = 10, "Female Full Professor" = 18, "Male Assistant Professor" = 56, "Male Associate Professor" = 54, " Male Full Professor" = 247) plot2cw <- waffle(partsf, rows = 10, title = "", size = 4) plot2cw + scale_fill_viridis_d()

For your third plot, I wanted to comment that I like the line you added at the 100% pay for men and I think the annotations are very helpful. For some reason the color of the line though (red) makes me think of danger or something you don't want to be approaching, but just a personal thought there.

For your fourth plot, one improvement I might suggest is if you can make the shadow of the geom_smooth more transparent, the female points get a little washed out in it and are harder to see.

Loved your visuals, inspired me to make mine more pretty!! Excellent job!

[datalorax]

Nice review Jenn! I particularly appreciate that after Alexis provided you with some feedback from your review you went back and conducted your review again. Very thorough!

Alexis - the point about the annotations obscuring the points could relate to aspect ratios (I don't know... I haven't actually looked at your plots/project). You might want to play around with this some, because the effectiveness of an annotation can definitely depend on aspect ratio.

Nice suggestion to make a single waffle plot!