r - 如何根据r中的分类列更改highchart中折线图的颜色？

Question

我正在尝试使用 highcharts 创建交互式折线图并根据分类列更改线条的颜色，即 CFR_level .
下面是ggplot(非交互版本的所需形式)

p1_cfr <- grouped_cases_df %>% 
  filter(Country.Region %in% top_10) %>% 
  
  ggplot(aes(x = Date, y = Confirmed, col = CFR_level, group = Country.Region, label = continent)) +
  geom_path() 

p1_cfr

问题 : 当我尝试使用 将其转换为交互式绘图时 Highcharts 它没有根据分类变量为线条着色，即 CFR_level而是基于每个 Country.Region 进行着色

library(tidyverse)
library(highcharter)

grouped_cases_df %>% 
  filter(Country.Region %in% top_10) %>%
  
  hchart(type = "line", hcaes(x = Date, y = Confirmed, group = Country.Region, color = CFR_level))

如何为 highchart 中的每一行着色基于分类变量 CFR_level ?

      ---------------------------------------------------------------

更新(数据详情):

top_10

######### output ##########

 [1] "US"            
 [2] "India"         
 [3] "Brazil"        
 [4] "Russia"        
 [5] "France"        
 [6] "United Kingdom"
 [7] "Italy"         
 [8] "Turkey"        
 [9] "Spain"         
[10] "Argentina"

grouped_cases_df %>% 
  filter(Country.Region %in% top_10) %>%
  head(n = 30)

####### output #########

   Country.Region continent Date       Confirmed Deaths Case_Fatality_Ratio CFR_level
   <chr>          <fct>     <date>         <int>  <int>               <dbl> <fct>    
 1 Argentina      Americas  2020-01-22         0      0                   0 Low      
 2 Argentina      Americas  2020-01-23         0      0                   0 Low      
 3 Argentina      Americas  2020-01-24         0      0                   0 Low      
 4 Argentina      Americas  2020-01-25         0      0                   0 Low      
 5 Argentina      Americas  2020-01-26         0      0                   0 Low      
 6 Argentina      Americas  2020-01-27         0      0                   0 Low      
 7 Argentina      Americas  2020-01-28         0      0                   0 Low      
 8 Argentina      Americas  2020-01-29         0      0                   0 Low      
 9 Argentina      Americas  2020-01-30         0      0                   0 Low      
10 Argentina      Americas  2020-01-31         0      0                   0 Low      
# ... with 20 more rows

grouped_cases_df %>% str()

####### output #########

tibble [64,176 x 7] (S3: tbl_df/tbl/data.frame)
 $ Country.Region     : chr [1:64176] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
 $ continent          : Factor w/ 6 levels "Africa","Americas",..: 3 3 3 3 3 3 3 3 3 3 ...
 $ Date               : Date[1:64176], format: "2020-01-22" "2020-01-23" "2020-01-24" ...
 $ Confirmed          : int [1:64176] 0 0 0 0 0 0 0 0 0 0 ...
 $ Deaths             : int [1:64176] 0 0 0 0 0 0 0 0 0 0 ...
 $ Case_Fatality_Ratio: num [1:64176] 0 0 0 0 0 0 0 0 0 0 ...
 $ CFR_level          : Factor w/ 3 levels "Low","Med","High": 1 1 1 1 1 1 1 1 1 1 ...

grouped_cases_df %>% 
  filter(Country.Region %in% top_10) %>% 
  str()

####### output #########

tibble [3,360 x 7] (S3: tbl_df/tbl/data.frame)
 $ Country.Region     : chr [1:3360] "Argentina" "Argentina" "Argentina" "Argentina" ...
 $ continent          : Factor w/ 6 levels "Africa","Americas",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ Date               : Date[1:3360], format: "2020-01-22" "2020-01-23" "2020-01-24" ...
 $ Confirmed          : int [1:3360] 0 0 0 0 0 0 0 0 0 0 ...
 $ Deaths             : int [1:3360] 0 0 0 0 0 0 0 0 0 0 ...
 $ Case_Fatality_Ratio: num [1:3360] 0 0 0 0 0 0 0 0 0 0 ...
 $ CFR_level          : Factor w/ 3 levels "Low","Med","High": 1 1 1 1 1 1 1 1 1 1 ...

grouped_cases_df %>% 
  filter(Country.Region %in% top_10) %>%
  summary()

####### output #########

 Country.Region        continent         Date              Confirmed            Deaths      
 Length:3360        Africa  :   0   Min.   :2020-01-22   Min.   :       0   Min.   :     0  
 Class :character   Americas:1008   1st Qu.:2020-04-14   1st Qu.:   46875   1st Qu.:  1382  
 Mode  :character   Asia    : 336   Median :2020-07-07   Median :  283225   Median : 26286  
                    Europe  :2016   Mean   :2020-07-07   Mean   : 1338426   Mean   : 39411  
                    Oceania :   0   3rd Qu.:2020-09-29   3rd Qu.: 1344549   3rd Qu.: 41590  
                    Unknown :   0   Max.   :2020-12-22   Max.   :18230242   Max.   :322765  
 Case_Fatality_Ratio CFR_level  
 Min.   : 0.000      Low : 455  
 1st Qu.: 1.746      Med : 719  
 Median : 2.791      High:2186  
 Mean   : 4.722                 
 3rd Qu.: 6.214                 
 Max.   :23.835             

更新 2(回复“coloredline”)
我已经按照您的建议尝试了几种方法，但我不确定为什么会出现空行，即使这些数据点存在于那里
1.

grouped_cases_df %>% 

  # filtering only couple of countries for simplicity
  filter(Country.Region %in% c("France","India")) %>%
  
  hchart(type = "coloredline", 
         hcaes(x = Date, y = Confirmed, group = Country.Region, segmentColor = CFR_level)) %>%
  hc_add_series(name = "Low", 
                color = "green", marker = list(symbol = "line")) %>% 
  
  hc_add_series(name = "Med", 
                color = "yellow", marker = list(symbol = "line")) %>% 
  
  hc_add_series(name = "High", 
                color = "red", marker = list(symbol = "line")) %>% 
  
  hc_add_dependency("plugins/multicolor_series.js")

灵感来自共享源链接

grouped_cases_df %>% 
  filter(Country.Region %in% c("France","India")) %>%
  
  hchart(type = "coloredline", 
         hcaes(x = Date, y = Confirmed, group = Country.Region, segmentColor = CFR_level)) %>%
  hc_add_dependency("plugins/multicolor_series.js")

如果我使用 hc_add_series(data = .,然后我得到错误

解决方案更新 (感谢@Ben 的建议)

grouped_cases_df %>% 
  filter(Country.Region %in% top_10) %>%
  mutate(CFR_col = case_when(CFR_level == "Low" ~ "#FFFF00",
                         CFR_level == "Med" ~ "#008000",
                         TRUE ~ "#FF0000")
         ) %>% 
  
  hchart(type = "coloredline", 
         hcaes(x = Date, y = Confirmed, group = Country.Region, segmentColor = CFR_col)) %>%
  hc_add_dependency("plugins/multicolor_series.js")

Answer 1

请参阅与 highcharter github 问题 here 类似的问题的简要说明.
我正在使用 COVID19包有一些现成的数据用作说明。我假设将几个国家设置为不同的 CFR_level值作为示例(这只是为了证明，它们并不反射(reflect)实际的病死率)。
与 hchart使用 coloredline和 multicolor_series模块，它允许个人 segmentColor要使用的值(更多 info and examples here on plugins and modules )。然后，您可以使用 group 的列以及 segmentColor 的不同列.
另外，我包括了hc_add_series使用空数据添加自定义图例。
编辑 (12/24/20) : 如果你设置 color在 hcaes在 hchart您可以根据 CFR_level 获得要匹配的工具提示悬停颜色.在本例中，我将颜色以十六进制表示(CFR_level 在这种情况下是颜色而不是字符值)。

library(tidyverse)
library(highcharter)
library(COVID19)

df <- covid19()    
            
df$CFR_level <- "#008000"
df$CFR_level[df$id == "IND"] <- "#FFFF00"
df$CFR_level[df$id == "USA"] <- "#FF0000"

df %>%
  filter(id %in% c("USA", "BRA", "RUS", "IND")) %>%
  hchart(type = "coloredline", 
         hcaes(x = date, y = confirmed, group = id, color = CFR_level, segmentColor = CFR_level),
         showInLegend = F) %>%
  hc_add_series(name = "Low", color = "#008000", marker = list(symbol = "line")) %>% 
  hc_add_series(name = "Med", color = "#FFFF00", marker = list(symbol = "line")) %>% 
  hc_add_series(name = "High", color = "#FF0000", marker = list(symbol = "line")) %>% 
  hc_add_dependency("plugins/multicolor_series.js")

剧情