pacman::p_load('plotly', 'tidyverse', 'ggtern')
# require(devtools)
# install_version("ggtern", version = "3.4.1", repos = "http://cran.us.r-project.org")
# library(ggtern)Hands-on Exercise 5.1: Building Ternary Plot with R
1 Getting Started
1.1 Install and loading R packages.
ggtern, a ggplot extension specially designed to plot ternary diagrams. The package will be used to plot static ternary plots.
Plotly R, an R package for creating interactive web-based graphs via plotly’s JavaScript graphing library, plotly.js . The plotly R libary contains the ggplotly function, which will convert ggplot2 figures into a Plotly object.
1.2 Importing the data
pop_data <- read_csv("../../data/respopagsex2000to2018_tidy.csv") 1.3 Preparing the data
Using the mutate() function of dplyr package to derive three new measures, namely: young, active, and old.
Click to view the code.
#Deriving the young, economy active and old measures
agpop_mutated <- pop_data %>%
mutate(`Year` = as.character(Year))%>%
spread(AG, Population) %>%
mutate(YOUNG = rowSums(.[4:8]))%>%
mutate(ACTIVE = rowSums(.[9:16])) %>%
mutate(OLD = rowSums(.[17:21])) %>%
mutate(TOTAL = rowSums(.[22:24])) %>%
filter(Year == 2018)%>%
filter(TOTAL > 0)2 Plotting Ternary Diagram with R
2.1 Plotting a static ternary diagram
Use ggtern() function of ggtern package to create a simple ternary plot.
Click to view the code.
#Building the static ternary plot
ggtern(data=agpop_mutated,aes(x=YOUNG,y=ACTIVE, z=OLD)) +
geom_point()
Click to view the code.
#Building the static ternary plot
ggtern(data=agpop_mutated, aes(x=YOUNG,y=ACTIVE, z=OLD)) +
geom_point() +
labs(title="Population structure, 2015") +
theme_rgbw()
2.2 Plotting an interative ternary diagram
The code below create an interactive ternary plot using plot_ly() function of Plotly R.
Click to view the code.
# reusable function for creating annotation object
label <- function(txt) {
list(
text = txt,
x = 0.1, y = 1,
ax = 0, ay = 0,
xref = "paper", yref = "paper",
align = "center",
font = list(family = "serif", size = 15, color = "white"),
bgcolor = "#b3b3b3", bordercolor = "black", borderwidth = 2
)
}
# reusable function for axis formatting
axis <- function(txt) {
list(
title = txt, tickformat = ".0%", tickfont = list(size = 10)
)
}
ternaryAxes <- list(
aaxis = axis("Young"),
baxis = axis("Active"),
caxis = axis("Old")
)
# Initiating a plotly visualization
plot_ly(
agpop_mutated,
a = ~YOUNG,
b = ~ACTIVE,
c = ~OLD,
color = I("black"),
type = "scatterternary"
) %>%
layout(
annotations = label("Ternary Markers"),
ternary = ternaryAxes
)