dplyr根據向量中的名稱更改多列

Question

我想通過使用dplyr's mutate函數將兩列彼此相乘。

但是，我不想為每個變異條件寫新行，而是使用存儲在向量var1和var2中的列的名稱。 例如，最后，我想在我現有的bankdata有一個名為result1的附加列，該列通過將現金和貸款列彼此相乘來包含結果。 這將繼續直到創建了3個新列。

可復制的代碼：

bankname <- c("Bank A", "Bank B", "Bank C", "Bank D", "Bank E")
bankid <- c(1, 2, 3, 4, 5)
year <- c(1881, 1881, 1881, 1881, 1881)
totass <- c(244789, 195755, 107736, 170600, 32000000)
cash <- c(7250, 10243, 13357, 35000, 351266)
bond <- c(20218, 185151, 177612, 20000, 314012)
loans <- c(29513, 2800, NA, 5000, NA)
bankdata <- data.frame(bankname, bankid, year, totass, cash, bond, loans)

向量var1和var2包含我要相乘的列名（ cash*loans, bond*cash, loans*bankid ）， 輸出是新列的名稱：

var1 <- c("cash", "bond", "loans")
var2 <- c("loans","cash", "bankid")
output <- c("result1", "result2", "result3")

我想做類似的事情：

bankdata %>%
  mutate_at(.funs = funs(output = var1*var2), vars(var1, var2))

bankdata %>%
  mutate_at(.funs = funs(result1 = cash*., result2 = bond*., result3 = loans*.), vars(var2))

Answer 1

使用tidyeval方法 ，我們構建了一個函數，該函數可以將字符串作為輸入，然后創建新列。 注意使用rlang::sym和!! （嘭嘭）。

之后，我們可以使用purrr::pmap_dfc遍歷var1 ， var2來創建新列，其名稱由output提供

library(tidyverse)

bankname <- c("Bank A", "Bank B", "Bank C", "Bank D", "Bank E")
bankid <- c(1, 2, 3, 4, 5)
year <- c(1881, 1881, 1881, 1881, 1881)
totass <- c(244789, 195755, 107736, 170600, 32000000)
cash <- c(7250, 10243, 13357, 35000, 351266)
bond <- c(20218, 185151, 177612, 20000, 314012)
loans <- c(29513, 2800, NA, 5000, NA)
bankdata <- data.frame(bankname, bankid, year, totass, cash, bond, loans)

originalNames <- names(bankdata)
var1   <- c("cash", "bond", "loans")
var2   <- c("loans","cash", "bankid")
output <- c("result1", "result2", "result3")

my_mutate <- function(df, var1, var2, output) {      
  var1   <- rlang::sym(var1)
  var2   <- rlang::sym(var2)
  output <- rlang::sym(output)

  df <- df %>% 
    mutate(!! output := !! var1 * !! var2)

  return(df)
}

# test
my_mutate(bankdata, var1[1], var2[1], output[1])

#>   bankname bankid year   totass   cash   bond loans   result1
#> 1   Bank A      1 1881   244789   7250  20218 29513 213969250
#> 2   Bank B      2 1881   195755  10243 185151  2800  28680400
#> 3   Bank C      3 1881   107736  13357 177612    NA        NA
#> 4   Bank D      4 1881   170600  35000  20000  5000 175000000
#> 5   Bank E      5 1881 32000000 351266 314012    NA        NA

# loop through 3 lists simultaneously 
# keep only original and result* columns
pmap_dfc(list(var1, var2, output), ~ my_mutate(bankdata, ..1, ..2, ..3)) %>% 
  select(!! originalNames, starts_with("result"))

#>   bankname bankid year   totass   cash   bond loans   result1      result2
#> 1   Bank A      1 1881   244789   7250  20218 29513 213969250    146580500
#> 2   Bank B      2 1881   195755  10243 185151  2800  28680400   1896501693
#> 3   Bank C      3 1881   107736  13357 177612    NA        NA   2372363484
#> 4   Bank D      4 1881   170600  35000  20000  5000 175000000    700000000
#> 5   Bank E      5 1881 32000000 351266 314012    NA        NA 110301739192
#>   result3
#> 1   29513
#> 2    5600
#> 3      NA
#> 4   20000
#> 5      NA

由reprex軟件包 （v0.2.0）於2018-04-18創建。