This question is about visualising temporal data.

The example data is on pedestrian counts in the city of Melbourne. The below plot looks at the pedestrian counts over weekdays in March, comparing 2019 to 2020.

ped %>% 
  ggplot(aes(x=Time, y=Count, group=Date, colour=as.factor(year))) +
    geom_line() +
    facet_wrap(~wday, ncol=7) + 
    scale_colour_brewer("", palette="Dark2") + 
    theme(legend.position="bottom", legend.title = element_blank())

Image failed to load

By looking at the above plots, select all statements that are TRUE. Incorrect answers are penalised.