Creating sparklines in tables

2018-03-16

by Andrie de Vries

Sparklines is a useful tool for visualizing time series data using small inline plots. In this post I demonstrate how to create sparklines in tables, using the gapminder data.

The code

Load the required packages

library(tidyverse)
## -- Attaching packages ----------------------------------------------------------- tidyverse 1.2.1 --
## v ggplot2 2.2.1     v purrr   0.2.4
## v tibble  1.4.2     v dplyr   0.7.4
## v tidyr   0.8.0     v stringr 1.3.0
## v readr   1.1.1     v forcats 0.3.0
## -- Conflicts -------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
library(gapminder)
library(sparkline)
library(formattable)
library(DT)

Some helper functions to round numbers and get the last element of a vector

round_0 <- function(x) round(x, digits = 0)
round_1 <- function(x) round(x, digits = 1)
last_round_1 <- function(x) dplyr::last(x) %>% round_1()
last_round_0 <- function(x) dplyr::last(x) %>% round_0()

Compute the summaries

gapminder %>%
  filter(continent == "Africa") %>% 
  group_by(country) %>%
  summarise(
    `life expectancy` = spk_chr(round_1(lifeExp)),
    `life expectancy (years)` = last_round_1(lifeExp),
    `gdp per capita` = spk_chr(gdpPercap %>% round_0()),
    `gdp per capita (USD)` = last_round_0(gdpPercap),
    `population (M)` = last_round_1(pop / 1e6)
  ) %>% 
  formattable() %>% 
  as.datatable() %>%
  spk_add_deps()