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Creating a bump chart in R using ggplot2 is a simple and efficient process that allows for easy visualization of the ranking or progression of data over time. This can be achieved by first arranging the data in a tidy format, then using the ggplot2 package to plot the data points and lines according to their respective ranks. The resulting bump chart will clearly display the changes and trends in the data, making it a useful tool for data analysis and comparison. With its user-friendly interface and customizable options, ggplot2 makes it easy to create a professional looking bump chart in R.
Easily Create a Bump Chart in R Using ggplot2
A bump chart is a type of chart that shows rankings of different groups over time instead of absolute values to emphasize the order of the groups instead of the magnitude of change.
This tutorial explains how to easily create a bump chart in R using ggplot2.
Example: Creating a Bump Chart
To create a bump chart in R, we first need to load two packages: dplyr and ggplot2:
library(ggplot2) #for creating bump chart library(dplyr) #for manipulating data
Next, we’ll create some data to work with:
#set the seed to make this example reproducible
set.seed(10)
data <- data.frame(team = rep(LETTERS[1:5], each = 10),
random_num = runif(50),
day = rep(1:10, 5))
data <- data %>%
group_by(day) %>%
arrange(day, desc(random_num), team) %>%
mutate(rank = row_number()) %>%
ungroup()
head(data)
# team random_num day rank
#1 C 0.865 1 1
#2 B 0.652 1 2
#3 D 0.536 1 3
#4 A 0.507 1 4
#5 E 0.275 1 5
#6 C 0.615 2 1
This data frame simply shows the “rank” of five different teams across a time span of 10 days.
We can use ggplot2 to create a bump chart to visualize the rank of each team during each day over this time span:
ggplot(data, aes(x = day, y = rank, group = team)) + geom_line(aes(color = team, alpha = 1), size = 2) + geom_point(aes(color = team, alpha = 1), size = 4) + scale_y_reverse(breaks = 1:nrow(data))
This bump chart shows the data in the format that we want, but it’s fairly ugly. With some aesthetic changes, we can make this chart look much better.
Styling the Bump Chart
To make the chart look better, we can use the following theme created by :
my_theme <- function() { # Colors color.background = "white" color.text = "#22211d" # Begin construction of chart theme_bw(base_size=15) + # Format background colors theme(panel.background = element_rect(fill=color.background, color=color.background)) + theme(plot.background = element_rect(fill=color.background, color=color.background)) + theme(panel.border = element_rect(color=color.background)) + theme(strip.background = element_rect(fill=color.background, color=color.background)) + # Format the grid theme(panel.grid.major.y = element_blank()) + theme(panel.grid.minor.y = element_blank()) + theme(axis.ticks = element_blank()) + # Format the legend theme(legend.position = "none") + # Format title and axis labels theme(plot.title = element_text(color=color.text, size=20, face = "bold")) + theme(axis.title.x = element_text(size=14, color="black", face = "bold")) + theme(axis.title.y = element_text(size=14, color="black", face = "bold", vjust=1.25)) + theme(axis.text.x = element_text(size=10, vjust=0.5, hjust=0.5, color = color.text)) + theme(axis.text.y = element_text(size=10, color = color.text)) + theme(strip.text = element_text(face = "bold")) + # Plot margins theme(plot.margin = unit(c(0.35, 0.2, 0.3, 0.35), "cm")) }
We’ll create the bump chart again, but this time we’ll remove the legend, add some chart labels, and use the theme defined in the code above:
ggplot(data, aes(x = as.factor(day), y = rank, group = team)) + geom_line(aes(color = team, alpha = 1), size = 2) + geom_point(aes(color = team, alpha = 1), size = 4) + geom_point(color = "#FFFFFF", size = 1) + scale_y_reverse(breaks = 1:nrow(data)) + scale_x_discrete(breaks = 1:10) + theme(legend.position = 'none') + geom_text(data = data %>% filter(day == "1"), aes(label = team, x = 0.5) , hjust = .5, fontface = "bold", color = "#888888", size = 4) + geom_text(data = data %>% filter(day == "10"), aes(label = team, x = 10.5) , hjust = 0.5, fontface = "bold", color = "#888888", size = 4) + labs(x = 'Day', y = 'Rank', title = 'Team Ranking by Day') + my_theme()
We can also easily highlight one of the lines by adding a scale_color_manual() argument. For example, in the following code we make the line for team A purple and the line for all of the other lines grey:
ggplot(data, aes(x = as.factor(day), y = rank, group = team)) +
geom_line(aes(color = team, alpha = 1), size = 2) +
geom_point(aes(color = team, alpha = 1), size = 4) +
geom_point(color = "#FFFFFF", size = 1) +
scale_y_reverse(breaks = 1:nrow(data)) +
scale_x_discrete(breaks = 1:10) +
theme(legend.position = 'none') +
geom_text(data = data %>% filter(day == "1"),
aes(label = team, x = 0.5) , hjust = .5,
fontface = "bold", color = "#888888", size = 4) +
geom_text(data = data %>% filter(day == "10"),
aes(label = team, x = 10.5) , hjust = 0.5,
fontface = "bold", color = "#888888", size = 4) +
labs(x = 'Day', y = 'Rank', title = 'Team Ranking by Day') +
my_theme() +
scale_color_manual(values = c('purple', 'grey', 'grey', 'grey', 'grey'))
We could also highlight more than one line if we’d like:
ggplot(data, aes(x = as.factor(day), y = rank, group = team)) +
geom_line(aes(color = team, alpha = 1), size = 2) +
geom_point(aes(color = team, alpha = 1), size = 4) +
geom_point(color = "#FFFFFF", size = 1) +
scale_y_reverse(breaks = 1:nrow(data)) +
scale_x_discrete(breaks = 1:10) +
theme(legend.position = 'none') +
geom_text(data = data %>% filter(day == "1"),
aes(label = team, x = 0.5) , hjust = .5,
fontface = "bold", color = "#888888", size = 4) +
geom_text(data = data %>% filter(day == "10"),
aes(label = team, x = 10.5) , hjust = 0.5,
fontface = "bold", color = "#888888", size = 4) +
labs(x = 'Day', y = 'Rank', title = 'Team Ranking by Day') +
my_theme() +
scale_color_manual(values = c('purple', 'steelblue', 'grey', 'grey', 'grey'))