This can solve the occasional issue where for whatever reason, some data is not on the dashboard yet and instead of having to wait for me to update the dashboard, someone can run the analysis on their own. So rather than going on the ecological dashboard to get fish biomass plots from Indonesia, they can do something like
df <- fish.surveys %>% dplyr::filter(country == "Indonesia")
p <- plot_fish_biomass(df)
p$plot
p$data
This can also solve the issue where instead of dumpster diving in github to find the code for a certain plot (that happens a lot with the HHS dashboard), you can do
View(plot_function_example) to see the source code without having to leave Rstudio
This can solve the occasional issue where for whatever reason, some data is not on the dashboard yet and instead of having to wait for me to update the dashboard, someone can run the analysis on their own. So rather than going on the ecological dashboard to get fish biomass plots from Indonesia, they can do something like
This can also solve the issue where instead of dumpster diving in github to find the code for a certain plot (that happens a lot with the HHS dashboard), you can do
View(plot_function_example)to see the source code without having to leave Rstudio