1. Code/Tools/approaches we have seen in class that you saw used over the week
@annapurani93 did a nice density plot, which was legible and clear but missed a stellar opportunity to color the fill according to the countries' national flags. In terms of packages and functions that we have already seen in class, here are a few that I saw over the course of the week:
2. Code/Tools/approaches that you enjoyed or that surprised you that we have not seen in class
I had not yet seen a circular barplot, such as the one created by @tamayolaiva_j. It does seem somewhat simple according to the code though, just a matter of calling coord_polar to make the plot circular and arranging the angles of the labels to match.
3. Data visualizations (figures) that you enjoyed
@danoehm produced a very clear and interesting figure showing the age distributions and finishing times for two different races. I think she managed to convey a lot of information in one figure, and it was interesting how you could see that most winners are below average age, and there seems to be a larger proportion of older runners in Hardrock 100.
4. Data Visualization (Figures) that could be improved (and how you would improve them)
I really enjoyed the concept of @shank4494's graphic showing the difference in participation between men and women, with the elevation gains shown on the side of the hill. However, the final result was not very visually pleasing: The colors did not go together nicely, and there was a lot of information conveyed via text. I think graphics should only try to tell one or two different "stories", otherwise it gets visually confusing, which seems to have happened here. I don't think it was necessary to include the paragraph explaining how the data was derived, and I also think the placement of the axes was a bit confusing. Perhaps the author could have placed the tallies of each race beside the relevant point, instead of in a separate paragraph at the top of the page.
1. Code/Tools/approaches we have seen in class that you saw used over the week @annapurani93 did a nice density plot, which was legible and clear but missed a stellar opportunity to color the fill according to the countries' national flags. In terms of packages and functions that we have already seen in class, here are a few that I saw over the course of the week:
From @nikithadani's bar plot:_
From @annapurani93's plot:
2. Code/Tools/approaches that you enjoyed or that surprised you that we have not seen in class I had not yet seen a circular barplot, such as the one created by @tamayolaiva_j. It does seem somewhat simple according to the code though, just a matter of calling coord_polar to make the plot circular and arranging the angles of the labels to match.
3. Data visualizations (figures) that you enjoyed @danoehm produced a very clear and interesting figure showing the age distributions and finishing times for two different races. I think she managed to convey a lot of information in one figure, and it was interesting how you could see that most winners are below average age, and there seems to be a larger proportion of older runners in Hardrock 100.
4. Data Visualization (Figures) that could be improved (and how you would improve them) I really enjoyed the concept of @shank4494's graphic showing the difference in participation between men and women, with the elevation gains shown on the side of the hill. However, the final result was not very visually pleasing: The colors did not go together nicely, and there was a lot of information conveyed via text. I think graphics should only try to tell one or two different "stories", otherwise it gets visually confusing, which seems to have happened here. I don't think it was necessary to include the paragraph explaining how the data was derived, and I also think the placement of the axes was a bit confusing. Perhaps the author could have placed the tallies of each race beside the relevant point, instead of in a separate paragraph at the top of the page.