Task 1: Reflection

In this challange, I explored car efficiency data using the mpg dataset. I tried to built an interactive plot showing the relationship between engine size, fuel efficiency, and vehicle class. In Task 2 I used geom_point to make a plot of Engine Size vs Highway MPG classed by Vehicle Type. The use of plotly enabled me to improve the tooltip experience and make the visualization more engaging and informative. For Task 3 I experimented with a few more interactive plots and made the dashboard.

Task 2: Interactive plots

library(tidyverse)
library(plotly)

data(mpg)
sample_diamonds <- diamonds %>% sample_n(1000)

p <- ggplot(mpg, aes(x = displ, y = hwy,
                     color = class,
                     text = paste("Model:", model,
                                  "<br>Manufacturer:", manufacturer,
                                  "<br>Displ (L):", displ,
                                  "<br>Highway MPG:", hwy,
                                  "<br>Class:", class))) +
  geom_point(size = 3, alpha = 0.7) +
  labs(title = "Engine Size vs Highway MPG",
       x = "Displacement (Liters)",
       y = "Highway Miles per Gallon",
       color = "Vehicle Class") + theme_bw()

ggplotly(p, tooltip = "text")