Visualization with ApexCharts
type: widget_page
—this sets you up to now copy over widgets from content/home/
in this new folder.
Build data visualizations with the ApexCharts JavaScript library, as well as to give an overview of the different graphics available.
library(ggplot2)
library(scales)
library(dplyr)
library(apexcharter)
library(ggplot2)
library(scales)
library(dplyr)
library(apexcharter)
Bar charts
Simple bar charts can be created with:
data("mpg")
n_manufac <- mpg%>%count(manufacturer)
apex(data = n_manufac, type = "column", mapping = aes(x = manufacturer, y = n))
Flipping coordinates can be done by using type = "bar"
:
apex(data = n_manufac, type = "bar", mapping = aes(x = manufacturer, y = n))
To create a dodge bar charts, use aesthetic fill
:
n_manufac_year <- mpg%>%count(manufacturer, year)
apex(data = n_manufac_year, type = "column", mapping = aes(x = manufacturer, y = n, fill = year))
For stacked bar charts, specify option stacked
in ax_chart
:
apex(data = n_manufac_year, type = "column", mapping = aes(x = manufacturer, y = n, fill = year)) %>%
ax_chart(stacked = TRUE)
Line charts
Simple line charts can be created with (works with character
, Date
or POSIXct
):
data("economics")
economics <- tail(economics, 100)
apex(data = economics, type = "line", mapping = aes(x = date, y = uempmed))
To represent several lines, use a data.frame
in long format and the group
aesthetic:
data("economics_long")
economics_long <- economics_long %>%
group_by(variable) %>%
slice((n()-100):n())
apex(data = economics_long, type = "line", mapping = aes(x = date, y = value01, group = variable)) %>%
ax_yaxis(decimalsInFloat = 2) # number of decimals to keep
Create area charts with type = "area"
:
apex(data = economics_long, type = "area", mapping = aes(x = date, y = value01, fill = variable)) %>%
ax_yaxis(decimalsInFloat = 2) %>% # number of decimals to keep
ax_chart(stacked = TRUE) %>%
ax_yaxis(max = 4, tickAmount = 4)
Scatter charts
Simple bar charts can be created with:
apex(data = mtcars, type = "scatter", mapping = aes(x = wt, y = mpg))
Color points according to a third variable:
apex(data = mtcars, type = "scatter", mapping = aes(x = wt, y = mpg, fill = cyl))
And change point size using z
aesthetics:
apex(data = mtcars, type = "scatter", mapping = aes(x = wt, y = mpg, z = scales::rescale(qsec)))
Pie charts
Simple pie charts can be created with:
poll <- data.frame(
answer = c("Yes", "No"),
n = c(254, 238)
)
apex(data = poll, type = "pie", mapping = aes(x = answer, y = n))
Radial charts
Simple radial charts can be created with (here we pass values directly in aes
, but you can use a data.frame
) :
apex(data = NULL, type = "radialBar", mapping = aes(x = "My value", y = 65))
Multi radial chart (more than one value):
fruits <- data.frame(
name = c('Apples', 'Oranges', 'Bananas', 'Berries'),
value = c(44, 55, 67, 83)
)
apex(data = fruits, type = "radialBar", mapping = aes(x = name, y = value))
Radar charts
Simple radar charts can be created with:
mtcars$model <- rownames(mtcars)
apex(data = head(mtcars), type = "radar", mapping = aes(x = model, y = qsec))
With a grouping variable:
# extremely complicated reshaping
new_mtcars <- reshape(
data = head(mtcars),
idvar = "model",
varying = list(c("drat", "wt")),
times = c("drat", "wt"),
direction = "long",
v.names = "value",
drop = c("mpg", "cyl", "hp", "dist", "qsec", "vs", "am", "gear", "carb")
)
apex(data = new_mtcars, type = "radar", mapping = aes(x = model, y = value, group = time))
Polar area
With some custom options for color mapping:
apex(mtcars, aes(rownames(mtcars), mpg), type = "polarArea") %>%
ax_legend(show = FALSE) %>%
ax_colors(col_numeric("Blues", domain = NULL)(mtcars$mpg)) %>%
ax_fill(opacity = 1) %>%
ax_stroke(width = 0) %>%
ax_tooltip(fillSeriesColor = FALSE)
Heatmap
Create a heatmap with :
txhousing2 <- txhousing %>%
filter(city %in% head(unique(city)), year %in% c(2000, 2001)) %>%
rename(val_med = median)
apex(
data = txhousing2,
type = "heatmap",
mapping = aes(x = date, y = city, fill = scales::rescale(val_med))
) %>%
ax_dataLabels(enabled = FALSE) %>%
ax_colors("#008FFB")
Treemap
Create a treemap with:
data("mpg", package = "ggplot2")
n_manufac <- dplyr::count(mpg, manufacturer)
apex(n_manufac, aes(x = manufacturer, y = n), "treemap")
Candlestick
Create a candlestick chart with:
data("candles", package = "apexcharter")
apex(
candles,
aes(x = datetime, open = open, close = close, low = low, high = high),
type = "candlestick"
)