cars <- mtcars
ggplot(cars, aes(wt, mpg)) +
  geom_point()

ggsave("outputs/cars-wt-mpg.png")
## Saving 7 x 5 in image
ggplot(cars, aes(hp, mpg)) + geom_point()

ggsave("outputs/cars-hp-mpg.png")
## Saving 7 x 5 in image
lm.cars.wt.mpg <- lm(mpg ~ wt, data= cars)
anova(lm.cars.wt.mpg)
## Analysis of Variance Table
## 
## Response: mpg
##           Df Sum Sq Mean Sq F value    Pr(>F)    
## wt         1 847.73  847.73  91.375 1.294e-10 ***
## Residuals 30 278.32    9.28                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
cars$cyl <- as.factor(cars$cyl)
cars.summary1 <- summarize(group_by(cars, cyl), .groups = "keep",
          n=n(), 
          mean=mean(mpg), 
          sd=sd(mpg))
kable(cars.summary1, format = "pandoc", caption = 'Table 1. A summary kable displaying number, mean, and standard deviation of gas mileage for each of three cylinder options for cars.')
Table 1. A summary kable displaying number, mean, and standard deviation of gas mileage for each of three cylinder options for cars.
cyl n mean sd
4 11 26.66364 4.509828
6 7 19.74286 1.453567
8 14 15.10000 2.560048 
cars.summary2 <- summarize(group_by(cars, gear),
                           n= n(),
                           mean= mean(mpg),
                           sd= sd(mpg))
## `summarise()` ungrouping output (override with `.groups` argument)
kable(cars.summary2, format= "pandoc", caption= "Table 2. A summary kable displaying the number, mean, and standard deviation of gas mileage for each of three gear options in cars.")
Table 2. A summary kable displaying the number, mean, and standard deviation of gas mileage for each of three gear options in cars.
gear n mean sd
3 15 16.10667 3.371618
4 12 24.53333 5.276764
5 5 21.38000 6.658979 
leaflet() %>%
  setView(-122.283770, 37.832750, zoom = 16) %>% #lat-long of the place of interest
  addTiles() %>%
  addMarkers(-122.283770, 37.832750, popup = "Cars Animation Studio")

This is where you can go to learn more about Cars the film.

Now that’s what a real car looks like.