Worked with Kimberly Cobarruviaz. Interactive and static plots of Tourist Arrivals by Region from 2000 to 2018.
Start with the data
group_by region so there will be a “river” for each region.
use e_charts to create an e_chart object with year on the x-axis.
use e_river to build “rivers” that contain the amount of tourist arrivals. The depth of each river represents the amount of tourist arrivals for each region.
use e_tooltip to add a tooltip that will display based on the x-axis values.
use e_title to add a title, subtitle, and link to subtitle.
use e_theme to change the theme to roma.
regional_tourism %>%
group_by(Region) %>%
e_chart(x = Year) %>%
e_river(serie = `International Tourist Arrivals`, legend = FALSE) %>%
e_tooltip(trigger = "axis") %>%
e_title(text = "Annual Tourist Arrivals by Region", subtext = "Source: Our World in Data", sublink = "https://ourworldindata.org/grapher/international-tourist-arrivals-by-world-region", left = "center") %>%
e_theme("roma")
Start with the data.
use ggplot to create a new ggplot object. Use aes to indicate that Year will be mapped to the x-axis, International Tourist Arrivals will be mapped to the y-axis, and Region will be the fill variable.
geom_area will display the amount of tourist arrivals in that region.
theme_classic sets the theme.
theme(legend.position = "bottom") puts the legend at the bottom of the plot.
labs sets the y-axis label, fill = NULL indicates that the fill variable will not have the labelled region.
regional_tourism %>%
ggplot(aes(x = Year, y = `International Tourist Arrivals`,
fill = Region)) +
geom_area() +
theme_classic() +
theme(legend.position = "bottom") +
labs( y = "in millions of arrivals",
fill = NULL)

These plots show a steady increase in tourist arrivals since 2000. Tourist arrivals continue to increase.