Unable to transform variables by user defined transformation function in r-CodePudding

I am trying to transform variables using a user defined function but facing issues in same.

1. sample dataframe:

librar(tidyverse)

df_test <- tribble(
 ~sales, ~var1, ~var2,
  22, 230.1,  37.8,
  10, 44.5,  39.3,
  9,  17.2,  45.9,
  19, 151.5,  41.3,
  13, 180.8,  10.8,
  7,  8.7,    48.9,
  12, 57.5,   32.8,
  13, 120.2,  19.6,
  5,  8.6,    2.1,
  11, 199.8,  2.6)

df_test

2. Tranformation table

# transfm dataframe
df_transfm <- df_test %>% 
  select(var1,var2)

df_transfm

3. User defined function to transform variable

# function to transform variables

adstock_transfrm <- function(x, df, adstock_rate = .5){
  df %>% 
    mutate(x = if_else(row_number() == 1, x, x * adstock_rate)) %>% 
    select(x)
}

4. Apply function

df_transfm$var1 <- adstock_transfrm(x = var1,df = df_transfm)
df_transfm

5. Error

Error in `mutate()`:
! Problem while computing `x = if_else(row_number() == 1, x, x * adstock_rate)`.
Caused by error in `if_else()`:
! object 'var1' not found
Backtrace:
 1. global adstock_transfrm(x = var1, df = df_transfm)
 9. dplyr::if_else(row_number() == 1, x, x * adstock_rate)
 Error in mutate(., x = if_else(row_number() == 1, x, x * adstock_rate)) : 

Caused by error in `if_else()`:
! object 'var1' not found

6. function2: changed function & applied but getting tibble instead of values:

# function2 to transform variables

adstock_transfrm2 <- function(x, df, adstock_rate = .5){
  x = enquo(x)
  df %>% 
    mutate(!!x := if_else(row_number() == 1, !!x, !!x * adstock_rate)) %>% 
    select(!!x)
}

df_transfm$var1 <- adstock_transfrm2(x = var1,df = df_transfm)
df_transfm

var1
<tibble>
var2
<dbl>
<tibble>    37.8            
<tibble>    39.3            
<tibble>    45.9            
<tibble>    41.3            
<tibble>    10.8            
<tibble>    48.9            
<tibble>    32.8            
<tibble>    19.6            
<tibble>    2.1         
<tibble>    2.6

Any help is much appreciated.

CodePudding user response：

Try pull() instead of select

library(dplyr)

df_test <- tribble(
  ~sales, ~var1, ~var2,
  22, 230.1,  37.8,
  10, 44.5,  39.3,
  9,  17.2,  45.9,
  19, 151.5,  41.3,
  13, 180.8,  10.8,
  7,  8.7,    48.9,
  12, 57.5,   32.8,
  13, 120.2,  19.6,
  5,  8.6,    2.1,
  11, 199.8,  2.6)

# transfm dataframe
df_transfm <- df_test %>% 
  select(var1,var2)


adstock_transfrm2 <- function(x, df, adstock_rate = .5){
  x = enquo(x)
  df %>% 
    mutate(!!x := if_else(row_number() == 1, !!x, !!x * adstock_rate)) %>% 
    pull(!!x)
}
df_transfm$var1 <- adstock_transfrm2(x = var1,df = df_transfm)
df_transfm
#> # A tibble: 10 × 2
#>      var1  var2
#>     <dbl> <dbl>
#>  1 230.    37.8
#>  2  22.2   39.3
#>  3   8.6   45.9
#>  4  75.8   41.3
#>  5  90.4   10.8
#>  6   4.35  48.9
#>  7  28.8   32.8
#>  8  60.1   19.6
#>  9   4.3    2.1
#> 10  99.9    2.6