Instructions

In Chapter 12, we explored many different ways to “look at” the numbers. For this lab, let’s explore the mtcars dataset that is included within R.

This activity description does not provide the same level of code prompts as previous labs – it is assumed that you remember or can look up the necessary code. The overall goal of this activity is to use ggplot2 to show different attributes of the mtcars dataset. Please be sure to include both the code and the images that were generated with your assignment.

Add all of your libraries that you use for this assignment here.

# Add your libraries here
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.4.3
# Generate the following visualizations:

## Step 1 - Histogram

# Write your code below.
# Histogram of mpg

ggplot(mtcars, aes(x = mpg)) +
  geom_histogram(binwidth = 2, fill = "skyblue", color = "black") +
  labs(title = "Histogram of MPG", x = "Miles per Gallon (mpg)", y = "Count")

Step 2 - Boxplots

Boxplots of mpg by cyl (i.e. 3 box plots: one for all cars with 4 cylinders, one for all cars with 6 cylinders, and one with all the cars with 8 cylinders).

# Write your code below.
# Boxplots of mpg by cyl
ggplot(mtcars, aes(x = factor(cyl), y = mpg, fill = factor(cyl))) +
  geom_boxplot() +
  labs(title = "MPG by Number of Cylinders", x = "Cylinders", y = "Miles per Gallon (mpg)") +
  scale_fill_manual(values = c("orange", "forestgreen", "dodgerblue")) +
  theme(legend.position = "none")

Step 3 - MultiLine chart

MultiLine chart of wt on the x-axis, mpg for the y-axis. With a line for each am (i.e. two lines). Also be sure to show each point on the chart.

# Write your code below.
# MultiLine chart of wt vs mpg for each am, with points
ggplot(mtcars, aes(x = wt, y = mpg, group = factor(am), color = factor(am))) +
  geom_line() +
  geom_point(size = 3) +
  labs(title = "MPG vs Weight by Transmission", x = "Weight (wt)", y = "Miles per Gallon (mpg)", color = "AM (0 = Auto, 1 = Manual)") +
  scale_color_manual(values = c("red", "blue"))

Step 4 - Barchart

Barchart with the x-axis being the name of each car, and the height being wt. Make sure to rotate the x-axis labels, so we can actually read the car name.

# Write your code below.
# Barchart with car names on x-axis, wt as height
ggplot(mtcars, aes(x = reorder(rownames(mtcars), wt), y = wt)) +
  geom_bar(stat = "identity", fill = "violet") +
  labs(title = "Car Weight by Model", x = "Car Name", y = "Weight (wt)") +
  theme(axis.text.x = element_text(angle = 60, hjust = 1))

Step 5 - Scatter chart

Scatter chart with the x-axis being the mpg and the y-axis being the wt of the car. Have the color and the size of each “symbol” (i.e., circle) represent how fast the car goes (based on the qsec attribute).

# Write your code below.
# Scatter chart: mpg vs wt, color and size mapped to qsec
ggplot(mtcars, aes(x = mpg, y = wt, color = qsec, size = qsec)) +
  geom_point(alpha = 0.7) +
  labs(title = "MPG vs Weight Colored by Quarter Mile Time",
       x = "Miles Per Gallon (mpg)", y = "Weight (wt)", color = "qsec", size = "qsec") +
  scale_color_gradient(low = "gold", high = "purple")