具有相同茎名的多列R dplyr

Question

当相应的列>0时，我需要将一些数据列设置为NA。

(x<-data.frame(x1=(1:4),map.x1=c(0,0,7,0),x2=c(2,2,2,2),map.x2=c(0,7,0,0)))

mutate(x, x1=ifelse(map.x1>0, NA, x1))

mutate_at(x, vars(starts_with("x")), function(v) { 
  m.name <- paste0("map.", deparse(substitute(v)))
  ifelse(get(m.name)>0, NA, v)
  )
}

我也在考虑重塑，这样我就可以做一个变异。这里最好的做法是什么？

Answer 1

下面是一种获得所需输出的方法。不需要编写自定义函数。重新塑造文件应该就足够了。

library(tibble)
library(dplyr)
library(stats)

# creating dataframe with proper names
x <-
  tibble::as_data_frame(cbind(
    x_1 = c(1:4),
    map.x_1 = c(0, 0, 7, 0),
    x_2 = c(2, 2, 2, 2),
    map.x_2 = c(0, 7, 0, 0)
  )) %>%
  tibble::rownames_to_column(df = ., var = 'id')

# converting to long format
x_long <- stats::reshape(
  as.data.frame(x),
  timevar = "level",
  varying = dput(as.character(as.vector(names(
    x[, base::grep("^x|^map", names(x))]
  )))),
  direction = "long",
  idvar = c("id"),
  sep = "_"
)
#> c("x_1", "map.x_1", "x_2", "map.x_2")

# converting the dataframe based on condition
x_long %>%
  group_by(.data = ., level) %>%
  dplyr::mutate(.data = .,
                x = base::ifelse(test = map.x > 0,
                                 yes = NA,
                                 no = x))
#> # A tibble: 8 x 4
#> # Groups:   level [2]
#>   id    level     x map.x
#>   <chr> <dbl> <dbl> <dbl>
#> 1 1      1.00  1.00  0   
#> 2 2      1.00  2.00  0   
#> 3 3      1.00 NA     7.00
#> 4 4      1.00  4.00  0   
#> 5 1      2.00  2.00  0   
#> 6 2      2.00 NA     7.00
#> 7 3      2.00  2.00  0   
#> 8 4      2.00  2.00  0

在2018-02-14由reprex包(V0.1.1.9000)创建。