install.packages(“plotly”)
title: “Vehicle Performance Analysis” author: “Kapil Maraj” date: “June 15, 2026” output: ioslides_presentation

---

Automotive Metrics Overview

This interactive presentation explores performance variables from the historic mtcars dataset.

• Objective: Analyze how engine power and vehicle weight influence fuel efficiency.
• Visual Factor: Vehicle cylinders are color-coded to isolate engine build impacts.
• Interactivity: Click and drag the plot on the next slide to rotate the chart in 3D space.

3D Horsepower vs. Weight vs. MPG

# Prepare the dataset safely without using dollar signs
plot_data <- mtcars

plot_data['am'] <- factor(plot_data[['am']], labels = c("Automatic", "Manual"))
plot_data['cyl'] <- factor(plot_data[['cyl']], labels = c("4 Cylinders", "6 Cylinders", "8 Cylinders"))

# Build the interactive 3D scatter plot
plot_ly(
  data = plot_data, 
  x = ~wt, 
  y = ~hp, 
  z = ~mpg, 
  color = ~cyl, 
  colors = c('#1f77b4', '#ff7f0e', '#2ca02c'),
  text = ~paste("Transmission:", am),
  type = "scatter3d", 
  mode = "markers",
  marker = list(size = 6, opacity = 0.8, line = list(color = '#ffffff', width = 1))
) %>%
  layout(
    scene = list(
      xaxis = list(title = 'Weight (1000 lbs)'),
      yaxis = list(title = 'Gross Horsepower'),
      zaxis = list(title = 'Fuel Efficiency (MPG)')
    ),
    title = "Engine Power & Weight vs. Efficiency"
  )