结合 case_when 和 mutate 的条件语句

Conditional statement combining case_when and mutate

我想创建一个绘制两个变量的双变量地图:productionpossession。为了给部分数据提供正确的颜色,我想为一个变量和另一个 1, 2, 3 添加一个颜色代码为 "A", "B", "C" 的列。然后将两者联系起来。只是为了让数据像下面的例子一样编码:

这是我的示例 df 和失败代码:

library(dplyr)

example_df <- structure(list(production = c(0.74, 1.34, 2.5), possession = c(5, 
23.8, 124.89)), .Names = c("production", "possession"), row.names = c(NA, 
-3L), class = c("tbl_df", "tbl", "data.frame"))

example_df %>%
  mutate(colour_class_nr = case_when(.$production %in% 0.068:0.608 ~ "1",
                                     .$production %in% 0.609:1.502 ~ "2",
                                     .$production %in% 1.503:3.061 ~ "3",
                                     TRUE ~ "none"),
         colour_class_letter = case_when(.$possession %in% 0.276:9.6 ~ "A",
                                         .$possession %in% 9.7:52 ~ "B",
                                         .$possession %in% 52.1:155.3 ~ "C",
                                         TRUE ~ "none"))

有了这些结果...:[=​​20=]

# A tibble: 3 x 4
  production possession colour_class_nr colour_class_letter
       <dbl>      <dbl> <chr>           <chr>              
1      0.740       5.00 4               none               
2      1.34       23.8  4               none               
3      2.50      125    4               none  

但这是所需的输出:

# A tibble: 3 x 4
  production possession colour_class_nr colour_class_letter
       <dbl>      <dbl>           <dbl> <chr>              
1      0.740       5.00 2                A               
2      1.34       23.8  2                B               
3      2.50      125    3                C 

我是 case_when() 与 mutate 结合的新手,希望有人能提供帮助。

也许是这样:

example_df %>%
  mutate(colour_class_nr = case_when(production < 0.608 ~ "1",
                                     production > 0.609 & production < 1.502 ~ "2",
                                     production > 1.503 ~ "3",
                                     TRUE ~ "none"),
         colour_class_letter = case_when(possession < 9.6 ~ "A",
                                         possession > 9.6 & possession < 52 ~ "B",
                                         possession > 52 ~ "C",
                                         TRUE ~ "none"))

结果:

# A tibble: 3 x 4
  production possession colour_class_nr colour_class_letter
       <dbl>      <dbl> <chr>           <chr>              
1      0.740       5.00 2               A                  
2      1.34       23.8  2               B                  
3      2.50      125    3               C

唯一的区别是 >< 的使用,尽管某些条件在您的示例中没有多大意义。您也不需要最新版本的 dplyr 中的 .$