Code/Tools/approaches we have seen in class that you saw used over the week:
summarize, Janitor, group_by, filter, mutate, ggplot
Code/Tools/approaches that you enjoyed or that surprised you that we have not seen in class:
guides, ggtext, patchwork
Data visualizations (figures) that you enjoyed:
Dan Oghm’s graph took the mean weight of pumpkins throughout the US and showed how they were bigger in the East. I really liked the visuals of the small pumpkins, as it made it more interesting and just gave an overwhelming happy feeling, because I love Halloween. This was one of my favourite TidyTuesday's!
Christophr Nicault’s graph had a very nice colour pallet and was very easy to follow. It did a good job reflecting the data and really caught my eye when viewing numerous projects.
Data Visualization (Figures) that could be improved (and how you would improve them):
Erin Franke’s Tidy-Tuesday was inconsistent, not having pictures for the last two plots. I did like the idea but it seemed to lack the information seen in the previous two projects I viewed. Adding a little more information and other pictures would make it more consistent and viewable.
Additionally, Erin Skarstein’s Tidy Tuesday seemed to focus on visuals and lacked a lot of information and the information given (using I believe violin plots) was very confusing. More information would be needed on a more viewer friendly plot.
Code/Tools/approaches we have seen in class that you saw used over the week: summarize, Janitor, group_by, filter, mutate, ggplot
Code/Tools/approaches that you enjoyed or that surprised you that we have not seen in class: guides, ggtext, patchwork
Data visualizations (figures) that you enjoyed: Dan Oghm’s graph took the mean weight of pumpkins throughout the US and showed how they were bigger in the East. I really liked the visuals of the small pumpkins, as it made it more interesting and just gave an overwhelming happy feeling, because I love Halloween. This was one of my favourite TidyTuesday's!
Christophr Nicault’s graph had a very nice colour pallet and was very easy to follow. It did a good job reflecting the data and really caught my eye when viewing numerous projects.
Data Visualization (Figures) that could be improved (and how you would improve them): Erin Franke’s Tidy-Tuesday was inconsistent, not having pictures for the last two plots. I did like the idea but it seemed to lack the information seen in the previous two projects I viewed. Adding a little more information and other pictures would make it more consistent and viewable.
Additionally, Erin Skarstein’s Tidy Tuesday seemed to focus on visuals and lacked a lot of information and the information given (using I believe violin plots) was very confusing. More information would be needed on a more viewer friendly plot.