README.md

ggbump

The R package ggbump creates elegant bump charts in ggplot.Bump charts are good to use to plot ranking over time.

Installation

You can install the released version of ggbump from github with:

devtools::install_github("davidsjoberg/ggbump")

Bump chart Examples

Basic example:

A more advanced example:

Example2

Click here for code to the plot above

Flags could be used instead of names:

Example3

Click here for code to the plot above

With geom_sigmoid you can make custom sigmoid curves:

Example4

Click here for code to the plot above

Tutorial

Prep

Load packages and get some data with rank:

if(!require(pacman)) install.packages("pacman")
library(ggbump)
pacman::p_load(tidyverse, cowplot, wesanderson)

df <- tibble(country = c("India", "India", "India", "Sweden", "Sweden", "Sweden", "Germany", "Germany", "Germany", "Finland", "Finland", "Finland"),
             year = c(2011, 2012, 2013, 2011, 2012, 2013, 2011, 2012, 2013, 2011, 2012, 2013),
             rank = c(4, 2, 2, 3, 1, 4, 2, 3, 1, 1, 4, 3))

knitr::kable(head(df))

| country | year | rank | | :------ | ---: | ---: | | India | 2011 | 4 | | India | 2012 | 2 | | India | 2013 | 2 | | Sweden | 2011 | 3 | | Sweden | 2012 | 1 | | Sweden | 2013 | 4 |

Make a bump chart

Most simple use case:

ggplot(df, aes(year, rank, color = country)) +
    geom_bump()

Pimp the bump chart!

Improve the bump chart by adding:


ggplot(df, aes(year, rank, color = country)) +
  geom_point(size = 7) +
  geom_text(data = df %>% filter(year == min(year)),
            aes(x = year - .1, label = country), size = 5, hjust = 1) +
  geom_text(data = df %>% filter(year == max(year)),
            aes(x = year + .1, label = country), size = 5, hjust = 0) +
  geom_bump(size = 2, smooth = 8) +
  scale_x_continuous(limits = c(2010.6, 2013.4),
                     breaks = seq(2011, 2013, 1)) +
  theme_minimal_grid(font_size = 14, line_size = 0) +
  theme(legend.position = "none",
        panel.grid.major = element_blank()) +
  labs(y = "RANK",
       x = NULL) +
  scale_y_reverse() +
  scale_color_manual(values = wes_palette(n = 4, name = "GrandBudapest1"))

geom_bump with factors

To use geom_bump with factors or character axis you need to prepare the data frame before. You need to prepare one column for the numeric position and one column with the name. If you want to have character/factor on both y and x you need to prepare 4 columns.

# Original df
df <- tibble(season = c("Spring", "Summer", "Autumn", "Winter", 
                        "Spring", "Summer", "Autumn", "Winter", 
                        "Spring", "Summer", "Autumn", "Winter"),
             position = c("Gold", "Gold", "Bronze", "Gold",
                          "Silver", "Bronze", "Gold", "Silver",
                          "Bronze", "Silver", "Silver", "Bronze"),
             player = c(rep("David", 4),
                        rep("Anna", 4),
                        rep("Franz", 4)))

# Create factors and numeric columns
df <- df %>% 
  mutate(season = factor(season, 
                         levels = c("Spring", "Summer", "Autumn", "Winter")),
         x = as.numeric(season),
         position = factor(position, 
                           levels = c("Gold", "Silver", "Bronze")),
         y = as.numeric(position))

# Add manual axis labels to plot
p <- ggplot(df, aes(x, y, color = player)) +
  geom_bump(size = 2, smooth = 8, show.legend = F) +
  geom_point(size = 5, aes(shape = player)) +
  scale_x_continuous(breaks = df$x %>% unique(),
                     labels = df$season %>% levels()) +
  scale_y_reverse(breaks = df$y %>% unique(),
                     labels = df$position %>% levels())
p

And some nice theme features

p +
  theme_minimal_grid(font_size = 14, line_size = 0) +
  theme(panel.grid.major = element_blank(),
        axis.ticks = element_blank()) +
  labs(y = "Medal",
       x = "Season",
       color = NULL,
       shape = NULL) +
  scale_color_manual(values = wes_palette(n = 3, name = "IsleofDogs1"))

Feedback

If you find any error or have suggestions for improvements you are more than welcome to contact me :)



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ggbump documentation built on April 24, 2020, 5:05 p.m.