Week5-Tidytuesday-commentary

[jonireimer]

Code/Tools/approaches we have seen in class that I saw used over the week:

• ggplot, tidyverse (glimpse() , tibble()) , pipe (%>%) , janitor (clean_names())

Code/Tools/approaches that I enjoyed or that surprised me that we have not seen in class:

• glue_collapse ()

Data visualizations (figures) that I enjoyed:

I appreciated the aesthetic features of @dmncschmtz's graph. I also enjoyed @cnicault's. Clean, simple, easy to get an overall idea of the data being presented quickly! I especially like how they cleaned up the large amount of data by focusing on the top 4 countries and grouping the less significant ones together.

Data Visualization (Figures) that could be improved:

I have a newfound appreciation for animated graphs such as @tanya_shapiro's, but this one in particular I found difficult to follow. Perhaps there is just too many data points in this particular study to animate, but I had to watch the graphic many times to understand the overall data trend as it moves very quickly. @GrabowMarius's graph in comparison is over simplified and, though it is significantly easier to understand the overall trend, the simplification seems to have sacrificed some of the data, such as how it relates globally.