ggplot Customization with National Park Visitation Data (Solution)

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Published

February 26, 2024

Solution

Download as R Script

Exercise Without Solutions

Load National Park Visitation data

Code 
np_data <- read.csv("https://raw.githubusercontent.com/melaniewalsh/Neat-Datasets/main/1979-2022-National-Park-Visits-By-State.csv",
 stringsAsFactors = FALSE)

View the np_data dataframe by clicking on the spreadsheet icon in the Global Environment

Load libraries

Code 
library("dplyr")
library("stringr")
library("ggplot2")
library("scales")
  • How have visits to a particular National Park changed over time?
  • What is the most interesting period of change?

Exercise 1

First, filter the dataframe for a park of your choice. Then, pick a National Park that you haven’t worked with yet, and filter the data for only that park.

Code 
my_parks_df <- np_data %>% 
  filter(ParkName == "Mount Rainier NP")

head(my_parks_df)
ParkName Region State Year RecreationVisits
Mount Rainier NP Pacific West WA 1979 1516703
Mount Rainier NP Pacific West WA 1980 1268256
Mount Rainier NP Pacific West WA 1981 1233671
Mount Rainier NP Pacific West WA 1982 1007300
Mount Rainier NP Pacific West WA 1983 1106306
Mount Rainier NP Pacific West WA 1984 1152411

Exercise 2

Now, make a line plot that shows the number of visits per year to that park from 1979 to 2022.

2a.

Choose a color for the line.

2b.

Give the plot a title that also functions as a kind of “headline” for the most interesting story of the plot.

2c.

Change the x-axis ticks so that they increase 5 years at a time.

2d.

Change the y-axis tick labels so that they abbreviate millions to M and thousands to K.

Code 
ggplot(my_parks_df) +
  geom_line(aes(
    x = Year,
    y = RecreationVisits
  ),
  color = "green") +
  scale_x_continuous(
    breaks = seq(from = 1980, to = 2020, by = 5),
  ) +
  scale_y_continuous(labels = label_number(scale_cut = cut_short_scale()),
  limits = c(0, 2000000)) +
  labs(title = "Visits to Mt. Rainier Are Surprisingly Stable")

Exercise 3

Now, create a plot that zooms in on the most interesting time period for this particular National Park.

3a.

Change the x-axis limits so that it only shows the most interesting years.

3b.

Come up with a new title that describes this time period.

Code 
ggplot(my_parks_df) +
  geom_line(aes(
    x = Year,
    y = RecreationVisits
  ),
  color = "green") +
  scale_x_continuous(
    breaks = seq(from = 1980, to = 2020, by = 5), 
    limits = c(2005, 2023),
  ) +
  scale_y_continuous(labels = label_number(scale_cut = cut_short_scale()),
   limits = c(0, 2000000)) +
  labs(title = "After a COVID Dip, Mt. Rainier Visits Are Higher Than Ever")