选择R高倍颜色为每个钻下水平图在Rshiny

Question

我正在创建一个类似于这个question中的解决方案的向下钻取，但是我有6个向下钻取的级别，而最初的问题有3个级别。是否有一种方法来指定每个向下钻层的颜色？例如，使用所引用的问题，我将能够指定一级城市，农场和海洋，二级公共汽车和汽车，三级卡尔和纽特等的颜色(如下图所示)。这个是可能的吗？

钻下1级

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选择一级“城市”，导致2级公共汽车和汽车

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选择二级“公共汽车”，导致卡尔和纽特等。

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我试过的是：

......
highchart() %>%
      hc_xAxis(type = "category") %>%
      hc_add_series(tibbled, "column", hcaes(x = name, y = y), color = "#E4551F", "#4572A7", 
"#AA4643", "#89A54E", "#80699B", "#3D96AE") %>%
      hc_plotOptions(column = list(stacking = "normal", events = list(click = pointClickFunction)))

这不起作用，它只是使用了第一个十六进制代码。当然，必须有一种方式说“对于类别城市使用颜色"#4572A7”等“？请帮帮忙

Answer 1

有几种不同的方法可以做到这一点。您没有提供一个可重复的问题，所以我使用了数据gapminder。

最高水平是按大陆分列的平均预期寿命。第二个层次是按国家分列的平均数。第三个层次是按国家分列的预期寿命。

我使用highcharter函数colorize创建颜色向量。我就是这样把它放在一起的：

数据

library(tidyverse)
library(highcharter)
data(gapminder, package = "gapminder")

avLE = gapminder %>% 
  group_by(continent) %>% 
  mutate(aLE = mean(lifeExp)) %>% # average by continent
  ungroup() %>% group_by(country) %>% 
  mutate(caLE = mean(lifeExp)) %>% # average by year
  ungroup() %>% arrange(desc(aLE)) %>% # order by life expectancy for continents
  mutate_if(is.numeric, round, 2)  # round to 2 decimals
summary(avLE) # check it; makes sense

gapCol = avLE %>%  # set the continets in the validated avLE as ordered
  group_by(continent) %>% 
  mutate(color = colorize(continent),
         continent = ordered(continent, 
                             levels = unique(avLE$continent)))
summary(gapCol) # check it; makes sense

钻地

# make the deepest level dropdown
gapDD2 = avLE %>% 
  arrange(year) %>%  
  group_nest(continent, country, caLE) %>% # keep these variables!
  mutate(id = country,
         type = "column", 
         data = map(data, mutate, name = year, y = lifeExp,
                    color = colorize(year)), # set the color (easier with #)
         data = map(data, list_parse))

gapDD1 = avLE %>% 
  arrange(country) %>%  # arrange by country, set as ordered, then find colors
  mutate(country = ordered(country, levels = unique(country))) %>%
  mutate(color = ordered(colorize(country),     # colors/countries align
                         levels = unique(colorize(country)))) %>% 
  group_nest(continent) %>% 
  mutate(id = continent,
         type = "column", 
         data = map(data, mutate, name = country, y = caLE, 
                    color = color,  # set the color (a few more steps than with #s)
                    drilldown = country),
         data = map(data, list_parse)) 

图表

# take a look:
hchart(gapCol, "column", name = "Continental Averages",
       hcaes(x = continent, color = continent, y = aLE, 
             name = "continent", drilldown = "continent")) %>% 
  hc_drilldown(allowPointsDrillDown = T,
               series = c(list_parse(gapDD1), list_parse(gapDD2))) 

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闪闪发亮

我提供了一个非常简单的示例，说明如何在一个闪亮的应用程序中呈现此图。在本例中，除了调用hchart之外，所有代码都是在设置ui之前调用的。

ui <- fluidPage(
  fluidRow(highchartOutput("myHC"))
)
server <- function(input, output, session){
  output$myHC <- renderHighchart({
    hchart(gapCol, "column", name = "Continental Averages",
           hcaes(x = continent, color = continent, y = aLE, 
                 name = "continent", drilldown = "continent")) %>% 
      hc_drilldown(allowPointsDrillDown = T,
                   series = c(list_parse(gapDD1), list_parse(gapDD2))) 
  })
}
shinyApp(ui = ui, server = server)

如果你有任何问题，请告诉我。