Highcharter是基于HighCharts javascript库及其模块的R包。这个包的主要功能是:可以创建交互式的各种图表，如散点图、气泡图、时间序列、热图、树形图、条形图等；支持各种R对象；支持Highstocks图表、Choropleths；支持管道方法和各种各样的主题与外观。
Highcharter有两个主要函数：从数据创建图表，向现有对象添加数据。 hchart():一个泛型函数，它接受一个对象(如向量、时间序列、数据框、likert对象等)并返回一个对象(chart)，和ggplot2中qplot()用法类似。 hc_add_series():根据数据的类型将数据添加到现有对象的通用函数，和ggplot2中geom_类似。 hcaes():和ggplot2中ase()用法相似。
准备数据
代码语言：javascript复制data("mpg", "diamonds", "economics_long", package = "ggplot2")
head(mpg)
## # A tibble: 6 x 11
## manufacturer model displ year cyl trans drv cty hwy fl class
## <chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
## 1 audi a4 1.8 1999 4 auto(l5) f 18 29 p compa~
## 2 audi a4 1.8 1999 4 manual(m5) f 21 29 p compa~
## 3 audi a4 2 2008 4 manual(m6) f 20 31 p compa~
## 4 audi a4 2 2008 4 auto(av) f 21 30 p compa~
## 5 audi a4 2.8 1999 6 auto(l5) f 16 26 p compa~
## 6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compa~
基本图形
基本的绘图语法
代码语言：javascript复制hchart(<data.frame>, <type_of_chart>, hcaes(<aesthetics>), ...)
一个示例
代码语言：javascript复制hchart(mpg, "point", hcaes(x = displ, y = cty, group = year))
制作一个热图
代码语言：javascript复制library(dplyr)
dfdiam <- diamonds %>%
group_by(cut, clarity) %>%
summarize(price = median(price))
hchart(dfdiam, "heatmap", hcaes(x = cut, y = clarity, value = price), name = "Median Price")
添加其他参数
添加其他参数以修改每个组的名称。这些名称在图例和工具提示中使用。还可以修改颜色和其他属性。
代码语言：javascript复制mpgman2 <- count(mpg, manufacturer, year)
hchart(
mpgman2,
"bar",
hcaes(x = manufacturer, y = n, group = year),
color = c("#7CB5EC", "#F7A35C"),
name = c("Year 1999", "Year 2008"),
showInLegend = c(TRUE, FALSE) # only show the first one in the legend
)
更高级的图形绘制
首先绘制原始数据图表，并存储在变量中
代码语言：javascript复制library(broom)
modlss <- loess(dist ~ speed, data = cars)
fit <- arrange(augment(modlss), speed) %>%
mutate(.se = predict(modlss, se = TRUE)$se.fit)
hc <- hchart(
cars,
type = "scatter",
hcaes(x = speed, y = dist),
name = "Speed and Stopping Distances of Cars",
showInLegend = TRUE
)
hc
使用hc_add_serieschart()向图表中添加更多的series(就像ggplot中的图层一样)。 在本例中，将添加 2 组series，样条线和面积范围。
代码语言：javascript复制qtint <- qt(0.975, predict(modlss, se = TRUE)$df)
hc %>%
hc_add_series(
fit,
type = "spline",
hcaes(x = speed, y = .fitted),
name = "Fit",
id = "fit", # this is for link the arearange series to this one and have one legend
lineWidth = 1,
showInLegend = TRUE
) %>%
hc_add_series(
fit,
type = "arearange",
name = "SE",
hcaes(x = speed, low = .fitted - qtint*.se, high = .fitted qtint*.se),
linkedTo = "fit", # here we link the legends in one.
showInLegend = FALSE,
color = hex_to_rgba("gray", 0.2), # put a semi transparent color
zIndex = -3 # this is for put the series in a back so the points are showed first
)
