Highcharts is a SVG-based, multi-platform charting library. The highcharter package bring all highchartsJS capabilities to your R console. So you can chart from simple charts like column, scatter to more complex charts like streamgraph, packed bubble, vector field among others.
Basic charts
Let’s see a preview of what highchartsJS (so highcharter) can chart. First of all a simple data set:
library(dplyr)
library(stringr)
library(purrr)
n <- 6
set.seed(123)
colors <- c("#d35400", "#2980b9", "#2ecc71", "#f1c40f", "#2c3e50", "#7f8c8d")
colors2 <- c("#000004", "#3B0F70", "#8C2981", "#DE4968", "#FE9F6D", "#FCFDBF")
df <- data.frame(x = seq_len(n) - 1) |>
mutate(
y = 10 + x + 10 * sin(x - 1),
z = 5 + (x*y) - median(x*y),
e = 10 * abs(rnorm(length(x))) + 2,
e = round(e, 1),
low = y - e,
high = y + e,
value = round(y - 1),
name = sample(fruit[str_length(fruit) <= 5], size = n),
color = rep(colors, length.out = n)
) |>
mutate_if(is.numeric, round, 1) |>
select(-e)
df <- df |>
mutate(
# label = name,
from = name[c(1, 1, 1, 2, 3, 4)],
to = name[c(3, 4, 5, 3, 6, 6)],
weight = c(1, 1, 1, 1, 2, 2)
)| x | y | z | low | high | value | name | color | from | to | weight |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1.6 | -34.0 | -6.0 | 9.2 | 1 | lemon | #d35400 | lemon | olive | 1 |
| 1 | 11.0 | -23.0 | 6.7 | 15.3 | 10 | nut | #2980b9 | lemon | guava | 1 |
| 2 | 20.4 | 6.8 | 2.8 | 38.0 | 19 | olive | #2ecc71 | lemon | fig | 1 |
| 3 | 22.1 | 32.3 | 19.4 | 24.8 | 21 | guava | #f1c40f | nut | olive | 1 |
| 4 | 15.4 | 27.7 | 12.1 | 18.7 | 14 | fig | #2c3e50 | olive | pear | 2 |
| 5 | 7.4 | 3.2 | -11.8 | 26.6 | 6 | pear | #7f8c8d | guava | pear | 2 |
errorbar
example_dat <- tibble(
Type = c("Human", "High-Elf", "Orc"),
key = c("World1", "World2", "World3")
) %>%
expand.grid() %>%
mutate(mean = runif(9, 5, 7)) %>%
mutate(sd = runif(9, 0.5, 1))
hchart(
example_dat,
"column",
hcaes(x = key, y = mean, group = Type),
id = c("a", "b", "c")
) %>%
hc_add_series(
example_dat,
"errorbar",
hcaes(y = mean, x = key, low = mean - sd, high = mean + sd, group = Type),
linkedTo = c("a", "b", "c"),
enableMouseTracking = TRUE,
showInLegend = FALSE
) %>%
hc_plotOptions(
errorbar = list(
color = "black",
# whiskerLength = 1,
stemWidth = 1
)
) item
df <- data.frame(
stringsAsFactors = FALSE,
name = c(
"The Left",
"Social Democratic Party",
"Alliance 90/The Greens",
"Free Democratic Party",
"Christian Democratic Union",
"Christian Social Union in Bavaria",
"Alternative for Germany"
),
count = c(69, 153, 67, 80, 200, 46, 94),
col = c("#BE3075", "#EB001F", "#64A12D", "#FFED00",
"#000000", "#008AC5", "#009EE0"
),
abbrv = c("DIE LINKE", "SPD", "GRÜNE", "FDP", "CDU", "CSU", "AfD")
)
hchart(
df,
"item",
hcaes(
name = name,
y = count,
label = abbrv,
color = col
),
name = "Representatives",
showInLegend = TRUE,
size = "100%",
center = list("50%", "75%"),
startAngle = -100,
endAngle = 100
) %>%
hc_title(text = "Item chart with different layout") %>%
hc_legend(labelFormat = '{name} <span style="opacity: 0.4">{y}</span>')packedbubble
library(dplyr)
data(gapminder, package = "gapminder")
gapminder <- gapminder %>%
filter(year == max(year)) %>%
select(country, pop, continent)
hc <- hchart(gapminder, "packedbubble", hcaes(name = country, value = pop, group = continent))
q95 <- as.numeric(quantile(gapminder$pop, .95))
hc %>%
hc_tooltip(
useHTML = TRUE,
pointFormat = "<b>{point.name}:</b> {point.value}"
) %>%
hc_plotOptions(
packedbubble = list(
maxSize = "150%",
zMin = 0,
layoutAlgorithm = list(
gravitationalConstant = 0.05,
splitSeries = TRUE, # TRUE to group points
seriesInteraction = TRUE,
dragBetweenSeries = TRUE,
parentNodeLimit = TRUE
),
dataLabels = list(
enabled = TRUE,
format = "{point.name}",
filter = list(
property = "y",
operator = ">",
value = q95
),
style = list(
color = "black",
textOutline = "none",
fontWeight = "normal"
)
)
)
)solidgauge
col_stops <- data.frame(
q = c(0.15, 0.4, .8),
c = c('#55BF3B', '#DDDF0D', '#DF5353'),
stringsAsFactors = FALSE
)
highchart() %>%
hc_chart(type = "solidgauge") %>%
hc_pane(
startAngle = -90,
endAngle = 90,
background = list(
outerRadius = '100%',
innerRadius = '60%',
shape = "arc"
)
) %>%
hc_tooltip(enabled = FALSE) %>%
hc_yAxis(
stops = list_parse2(col_stops),
lineWidth = 0,
minorTickWidth = 0,
tickAmount = 2,
min = 0,
max = 100,
labels = list(y = 26, style = list(fontSize = "22px"))
) %>%
hc_add_series(
data = 90,
dataLabels = list(
y = -50,
borderWidth = 0,
useHTML = TRUE,
style = list(fontSize = "40px")
)
) %>%
hc_size(height = 300)tilemap
# http://www.maartenlambrechts.com/2017/10/22/tutorial-a-worldtilegrid-with-ggplot2.html
library(dplyr)
library(readr)
library(stringr)
url <- "https://gist.githubusercontent.com/maartenzam/787498bbc07ae06b637447dbd430ea0a/raw/9a9dafafb44d8990f85243a9c7ca349acd3a0d07/worldtilegrid.csv"
data <- suppressMessages(read_csv(url))
data <- data %>%
rename_all(str_replace_all, "\\.", "_") %>%
select(x, y, name, region, alpha_2)
hchart(data, "tilemap", hcaes(x = x, y = -y, name = name, group = region)) %>%
hc_chart(type = "tilemap") %>%
hc_plotOptions(
series = list(
dataLabels = list(
enabled = TRUE,
format = "{point.alpha_2}",
color = "white",
style = list(textOutline = FALSE)
)
)
) %>%
hc_tooltip(
headerFormat = "",
pointFormat = "<b>{point.name}</b> is in <b>{point.region}</b>"
) %>%
hc_xAxis(visible = FALSE) %>%
hc_yAxis(visible = FALSE) %>%
hc_size(height = 800)venn
highchart() %>%
hc_chart(type = "venn") %>%
hc_add_series(
dataLabels = list(style = list(fontSize = "20px")),
name = "Venn Diagram",
data = list(
list(
name = "People who are<br>breaking my heart.",
sets = list("A"), value = 5
),
list(
name = "People who are shaking<br> my confidence daily.",
sets = list("B"), value = 5
),
list(
name = "Cecilia", sets = list("B", "A"), value = 1)
)
)
highchart() %>%
hc_chart(type = "venn") %>%
hc_add_series(
name = "Euler Diagram",
dataLabels = list(style = list(fontSize = "20px")),
data = list(
list(sets = list("A"), name = "Animals", value = 5),
list(sets = list("B"), name = "Four Legs", value = 1),
list(sets = list("B", "A"), value = 1),
list(sets = list("C"), name = "Mineral", value = 2)
)
)wordcloud
library(rvest)
library(tidytext)
data <- read_html("http://www.htmlwidgets.org/develop_intro.html") |>
html_nodes("p") |>
html_text() |>
map(str_to_lower) |>
reduce(str_c) |>
str_split("\\s+") |>
unlist() |>
tibble() |>
setNames("word") |>
count(word, sort = TRUE) |>
anti_join(tidytext::stop_words, by = "word") |>
head(60)
hchart(data, "wordcloud", hcaes(name = word, weight = log(n)))xrange
library(lubridate)
N <- 7
set.seed(1234)
df <- tibble(
start = Sys.Date() + months(sample(10:20, size = N)),
end = start + months(sample(1:3, size = N, replace = TRUE)),
cat = rep(1:5, length.out = N) - 1,
progress = round(stats::runif(N), 1)
) |>
mutate_if(is.Date, datetime_to_timestamp)
hchart(
df,
"xrange",
hcaes(x = start, x2 = end, y = cat, partialFill = progress),
dataLabels = list(enabled = TRUE)
) %>%
hc_xAxis(
title = FALSE,
type = "datetime"
) %>%
hc_yAxis(
title = FALSE,
categories = c("Prototyping", "Development", "Testing", "Validation", "Modelling")
)