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gapminder, ggplot
Introduction to the Tidyverse
Run the hidden code cell below to import the data used in this course.
# Load the Tidyverse
library(tidyverse)
# Read in the gapminder file
gapminder <- read.csv("datasets/gapminder.csv", sep = "\t")
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# Add your code snippets here
ggplot(gapminder_1952, aes(x = pop, y = lifeExp)) +
geom_point() + scale_x_log10()
ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
geom_point() + scale_x_log10() + facet_wrap(~ year)
gapminder %>%
filter(year == 1957) %>%
group_by(continent) %>%
summarize(medianLifeExp = median(lifeExp), maxGdpPercap = max(gdpPercap))
# Summarize medianGdpPercap within each continent within each year: by_year_continent
by_year_continent <- gapminder %>%
group_by(continent, year) %>%
summarize(medianGdpPercap = median(gdpPercap))
# Plot the change in medianGdpPercap in each continent over time
ggplot(by_year_continent, aes(x = year, y = medianGdpPercap, color = continent)) +
geom_point() +
expand_limits(y = 0)
# Summarize the median gdpPercap by year, then save it as by_year
by_year <- gapminder %>%
group_by(year) %>%
summarize(medianGdpPercap = median(gdpPercap))
# Create a line plot showing the change in medianGdpPercap by continent over time
ggplot(by_year_continent, aes(x = year, y = medianGdpPercap, color = continent)) +
geom_line() +
expand_limits(y = 0)
# Create a histogram of population (pop), with x on a log scale
ggplot(gapminder_1952, aes(x = pop)) +
geom_histogram(bins = 50) + scale_x_log10()
# Create a boxplot comparing gdpPercap among continents
ggplot(gapminder_1952, aes(x = continent, y = gdpPercap)) +
geom_boxplot() + scale_y_log10()
# Add a title to this graph: "Comparing GDP per capita across continents"
ggplot(gapminder_1952, aes(x = continent, y = gdpPercap)) +
geom_boxplot() +
scale_y_log10()+
ggtitle("Comparing GDP per capita across continents")