R Megre数据帧列和重新编码

我有两个R数据帧，如下所示：

数据帧1:

标识符 后路 职位编号 分类 11111 0.260 1. 对 11111 0.0822 2. 对 11111 0.00797 3. 对 11111 0.04 4. 不 11111 0.245 5. 对 11111 0.432 6. 对 11112 0.342 1. 大概 11112 0.453 2. 对 11112 0.0032 3. 对 11112 0.241 5. 不 11112 0.0422 6. 对 11112 0.311 4. 不

---

使用

dplyr

和

case\u，在以下情况下，您可以非常轻松地重新编码：

df1 %>% mutate(
  classification = 
    case_when( classification == "yes" ~ 1,
               classification == "no" ~ 0,
               classification == "maybe" ~ 2)
)

我将用以下方法解决它：

library(tidyverse)
df1 <- data.frame(
  stringsAsFactors = FALSE,
  identifier = c(11111L,11111L,11111L,11111L,
                 11111L,11111L,11112L,11112L,11112L,11112L,11112L,
                 11112L),
  ef_posterior = c(0.26,0.0822,0.00797,0.04,
                   0.245,0.432,0.342,0.453,0.0032,0.241,0.0422,0.311),
  position_no = c(1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 5L, 6L, 4L),
  classification = c("yes","yes","yes","no",
                     "yes","yes","maybe","yes","yes","no","yes","no")
)

df2 <- data.frame(
  check.names = FALSE,
  study_identifier = c(11111L, 11112L),
  `%LVEF` = c(62L, 76L)
)

df1 %>% mutate(
  classification = 
    case_when( classification == "yes" ~ 1,
               classification == "no" ~ 0,
               classification == "maybe" ~ 2)
) %>% 
  pivot_wider(
    id_cols = c(identifier), names_from = c(position_no), values_from = c(classification,ef_posterior)) %>% 
left_join(df2, by = c("identifier" = "study_identifier"))
#> # A tibble: 2 x 14
#>   identifier classification_1 classification_2 classification_3 classification_4
#>        <int>            <dbl>            <dbl>            <dbl>            <dbl>
#> 1      11111                1                1                1                0
#> 2      11112                2                1                1                0
#> # … with 9 more variables: classification_5 <dbl>, classification_6 <dbl>,
#> #   ef_posterior_1 <dbl>, ef_posterior_2 <dbl>, ef_posterior_3 <dbl>,
#> #   ef_posterior_4 <dbl>, ef_posterior_5 <dbl>, ef_posterior_6 <dbl>,
#> #   `%LVEF` <int>

库（tidyverse）
df1%
支点更宽(
id\u cols=c（标识符），名称\u from=c（位置\u编号），值\u from=c（分类，ef\u后））%>%
左联接（df2，by=c（“标识符”=“研究标识符”））
#>#A tible:2 x 14
#>标识符分类\u 1分类\u 2分类\u 3分类\u 4
#>                                                        
#> 1      11111                1                1                1                0
#> 2      11112                2                1                1                0
#>#…还有9个变量：分类_5，分类_6，
#>#ef#U后#U 1，ef#U后#U 2，ef#U后#U 3，
#>#ef#U后4、ef#U后5、ef#U后6、，
#>#`%LVEF`

由reprex软件包（v0.3.0）于2021年4月12日创建