Orienting with the data
Let's take our first look at the new speeding dataset.
First, print the data frame to your screen and try and get a sense of it. You can use filter()s, group_by()s or any of your tidyverse functions to do this.
The supplied code is what we used to make the histogram of blue car speeds in the slides. Modify this code to look at how many miles-per-hour red cars were going over the speed limit (speed_over). Give the plot a title while you're at it to let people know what they're looking at.
Deze oefening maakt deel uit van de cursus
Visualization Best Practices in R
Oefeninstructies
- Print the
md_speedingdata frame to the console and investigate it. - Change
filter()to'RED'cars. - Change column of interest to
speed_over. - Title plot
'MPH over speed limit | Red cars'
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Print data to console
___
# Change filter to red cars
md_speeding %>%
filter(vehicle_color == 'BLUE') %>%
# switch x mapping to speed_over column
ggplot(aes(x = speed)) +
geom_histogram() +
# give plot a title