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.

Este exercício faz parte do curso

Visualization Best Practices in R

Ver curso

Instruções do exercício

Print the md_speeding data 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'

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# 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

Editar e executar o código