在 R 中使用 Highcharter 创建仪表图表

Question

我正在尝试创建一个仪表图，如下图所示：

df 为：

df <- structure(list(Genero = c("Hombre", "Mujer"), Media = c(46.7, 
53.3)), row.names = c(NA, -2L), class = c("etable", "data.frame"
))

我一直在尝试的代码是：

stops <- list_parse2(df)

highchart() %>%
     hc_chart(type = 'solidgauge') %>%
     hc_pane(
          startAngle = -90,
          endAngle = 90,
          background = list(
               outerRadius = '100%',
               innerRadius = '60%',
               shape = 'arc'
          )
     ) %>%
     hc_yAxis(
          stops = stops,
          lineWidth = 0,
          minorTickWidth = 0,
          tickAmount = 2,
          min = 0,
          max = 100,
          labels = list(y = 25) 
     ) %>%
     hc_add_series(
          data = df$Media,
          color = '#EB6909'
     ) %>%
     hc_exporting(enabled = TRUE) %>%
     hc_plotOptions(series = list(animation = FALSE))

Answer 1

我认为这就是您正在寻找的：

df <- df |> 
  dplyr::mutate(color = c('#FFA500', '#A9A9A9'))

pie <- df |> 
  hchart(type = "pie",
         hcaes(x = Genero, y = Media, color = color)) |> 
  hc_plotOptions(
    pie = list(
      innerSize = '70%', 
      startAngle = -90, 
      endAngle = 90, 
      dataLabels = list(
        enabled = TRUE,
        format = '<b>{point.name}</b>: {point.percentage:.1f} %'
      )
    )
  )  

pie

这个想法是从圆环图中即兴制作一个仪表图。首先，我在数据框中创建了一个新列

color

，用它为仪表图着色。接下来，在

hc_plotOptions()

的饼图列表中，我将

innerSize

参数设置为 70% 以在圆环图中创建孔，然后将

startAngle

和

endAngle

分别设置为 -90 和 90 以有效地转动将图表转换为仪表图。

我希望这对你有用！

Answer 2

有这样的事吗？

install.packages("tidyverse")
library(tidyverse)

your_df <- tibble(
  part = c("Hombre", "Mujer"),
  percentage = c(0.467, 1 - 0.467),
  start = lag(percentage, default = 0) * pi,
  end = start + percentage * pi
)
your_df


install.packages("ggforce")
library(ggforce)

gPlot <- your_df |>
  ggplot() +
  geom_arc_bar(
    aes(
      x0 = 1,
      y0 = 1,
      fill = part,
      start = start - pi / 2,
      end = end - pi / 2,
      r0 = 0.75,
      r = 1
    )
  ) +
  coord_fixed() +
  theme_void() +
  theme(
    legend.position = "none",
    plot.title = element_text(
      family = "Source Sans Pro", size = 2, face = "bold"
    )
  ) +
  annotate(geom = "text", x = .3, y = 2, hjust = 0, label = "Hombre: 46.7%", color = "black", fontface = "bold", size = 3) +
  annotate(geom = "text", x = 1.4, y = 2, hjust = 0, label = "Mujer: 53.3%", color = "black", fontface = "bold", size = 3)

gPlot

输出：