# This is an example of how to make a stacked column chart using the pilot
# package.
#
# This script is self-contained: running it will create a PNG and an SVG of the
# example chart in the same directory. To run the script will need to ensure:
#
# 1. You have installed all of the packages that the script imports
# 2. You have the dataset "stacked-column-chart.csv" in the same directory
#
# See the readme on GitHub to find out how to install the package.
#
# To run the script, type the following code in your R console:
#
# source("stacked-column-chart.R")
# Imports ---------------------------------------------------------------------
library(tidyverse)
library(pilot)
# Read in and prepare the data ------------------------------------------------
# Load the data from the csv as a dataframe
df <- read_csv("stacked-column-chart.csv")
# Convert the year to character data: we don't want to treat this as a date or
# a number in this case, it is just a label for each bar
df$year <- as.character(df$year)
# Turn the nationality column into a factor: setting the order of the levels
# controls the order of the categories in each bar from top to bottom
df$nationality <- factor(df$nationality, levels = c("Non-EU", "EU", "British"))
# Create the plot -------------------------------------------------------------
# Use ggplot to create a plot with data and mappings
plot <- ggplot(
data = df,
mapping = aes(
x = year,
y = estimate,
fill = nationality)) +
# Add a col geometry for columns
geom_col(width = 0.8) +
# Set labels for the axes, legend, and caption, but don't set titles here
labs(
x = NULL,
y = NULL,
fill = NULL,
caption = "Source: ONS, Provisional LTIM estimates") +
# Configure the the x and y axes: set the y axis breaks and limits, and
# turn off the y-axis expansion
scale_x_discrete() +
scale_y_continuous(
limits = c(0, 700),
breaks = seq(0, 700, 100),
expand = c(0,0)) +
# Add the Pilot theme: set the grid to horizontal, the legend to top-left,
# and the caption to left
theme_pilot(
grid = "h",
legend_position = "top-left",
caption_position = "left") +
# Use scale_fill_manual and pilot_color to set category colors
scale_fill_manual(values = c(
"British" = pilot_color("yellow"),
"EU" = pilot_color("navy"),
"Non-EU" = pilot_color("blue")))
# After creating the plot, add a title and subtitle with add_pilot_titles
plot <- add_pilot_titles(
plot,
title = "Immigration is stable but the composition has changed",
subtitle = "Immigration by nationality in each year ending September (000s)")
# Save the plot in different formats ------------------------------------------
# Save a high resolution export of the plot as a png
ggsave(
filename = "stacked-column-chart.png",
plot = plot,
width = 7.7,
height = 5.8,
dpi = 400)
# Save an editable verson of the plot as an svg
ggsave(
filename = "stacked-column-chart.svg",
plot = plot,
width = 7.7,
height = 5.8,
dpi = 400)
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