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如果为FALSE,则递增列,如果为TRUE,则停止递增(tidyverse、dplyr、R)

tidyverse dplyr r

0

Nick Camarda · 技术社区 · 3 年前

我有一张这样的桌子:

data <- structure(list(group = c(0L, 0L, 1L, 2L), id = c("1", "2", "3", 
"4"), m = c("ac1", "ac1", "ac1", "me0"), together = c(FALSE, 
FALSE, TRUE, TRUE)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-4L))

我想做个专栏 group 当 together == FALSE 当 together == TRUE .

这是我想要的输出:

# A tibble: 4 x 4
  id    m     together group
  <chr> <chr> <lgl>    <dbl>
1 1     ac1   FALSE        0
2 2     ac1   FALSE        1
3 3     ac1   TRUE         2
4 4     me0   TRUE         2

我已经尝试过类似的解决方案 R increment by 1 for every change in value column and restart the counter 它并没有给我想要的东西。。

# A tibble: 4 x 4
# Groups:   group [3]
  id    m     together group
  <chr> <chr> <lgl>    <int>
1 1     ac1   FALSE        0
2 2     ac1   FALSE        0
3 3     ac1   TRUE         1
4 4     me0   TRUE         2

在这种情况下,我希望组读0,1,2,2。有什么想法吗?非常感谢。

1 回复 | 直到 3 年前

1

2

DaveArmstrong 3 年前

这里有一个简洁的解决方案:

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
data <- structure(list(id = c("1", "2", "3", "4"), 
                       m = c("ac1", "ac1", "ac1", "me0"), 
                       together = c(FALSE, FALSE, TRUE, TRUE)), 
                  class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -4L))
data <- data %>% mutate(
  group = cumsum(c(0, na.omit(lag(!data$together)))))
data
#> # A tibble: 4 Ã 4
#>   id    m     together group
#>   <chr> <chr> <lgl>    <dbl>
#> 1 1     ac1   FALSE        0
#> 2 2     ac1   FALSE        1
#> 3 3     ac1   TRUE         2
#> 4 4     me0   TRUE         2

^{于2022年4月24日由

reprex package

(v2.0.1)}

2

0

Onyambu 3 年前

另一种解决方法如下所示

data %>%
       mutate(grp2 = c(0, cumsum(!na.omit(together * lag(together)))))
    # A tibble: 4 x 5
      group id    m     together  grp2
      <int> <chr> <chr> <lgl>    <dbl>
    1     0 1     ac1   FALSE        0
    2     0 2     ac1   FALSE        1
    3     1 3     ac1   TRUE         2
    4     2 4     me0   TRUE         2

使用注释中给出的数据并运行相同的代码:

data1 <- data.frame(together=c(FALSE, FALSE, TRUE, TRUE, FALSE, TRUE))
data1 %>%
   mutate(grp2 = c(0, cumsum(!na.omit(together * lag(together)))))
  together grp2
1    FALSE    0
2    FALSE    1
3     TRUE    2
4     TRUE    2
5    FALSE    3
6     TRUE    4