I have a dataframe imported from excel with read_excel that looks like this:

The main task is to handle the different formats of dates:

I would like to implement it into a custom function (and I am not good at all in creating functions):

df <- structure(list(date = c("40574", "40861", "40870", "40990", "07.03.2022", 
"14.03.2022", "16.03.2022", "27.03.2022", "24.03.2022", "24.03.2022"
)), row.names = c(NA, -10L), class = c("tbl_df", "tbl", "data.frame"
))

# A tibble: 10 x 1
   date      
   <chr>     
 1 40574     
 2 40861     
 3 40870     
 4 40990     
 5 07.03.2022
 6 14.03.2022
 7 16.03.2022
 8 27.03.2022
 9 24.03.2022
10 24.03.2022

I solved this task with this code:

library(tidyverse)
library(janitor)
library(lubridate)

df %>% 
  mutate(new_col = excel_numeric_to_date(as.numeric(as.character(date)), date_system = "modern"), .before=1) %>% 
  mutate(date = ifelse(!str_detect(date, '\\.'), NA_character_, date)) %>% 
  mutate(date = dmy(date)) %>% 
  mutate(date = coalesce(date, new_col), .keep="unused")

From this code I would like to make a custom function with this code:

mixed_dateColumn_excel <- function(df, x) {
  x <- {{x}}
  df %>% 
    mutate(new_col = excel_numeric_to_date(as.numeric(as.character(x)), date_system = "modern"), .before=1) %>% 
    mutate(x = ifelse(!str_detect(x, '\\.'), NA_character_, x)) %>% 
    mutate(x = dmy(x)) %>% 
    mutate(x = coalesce(x, new_col), .keep="unused")
}

I would like to know why:

This works not:

mixed_dateColumn_excel(df, "date")

This works not also:

mixed_dateColumn_excel(df, date)

And this works:

mixed_dateColumn_excel(df, df$date)

CodePudding user response：

You can't unquote in this way using the curly-curly operator TarJae. It has to be done directly inside the tidyverse functions.

In your version, the line:

x <- {{x}}

doesn't really do anything - you would get the same results if you removed this line altogether. Your third version where you use df$date doesn't really work, since it creates a column called x, with the calculations inside the mutate functions simply working on the passed vector df$date. The version with "date" doesn't work because you are passing a literal character string for the calculations, and date doesn't work because without using data masking properly, R cannot find this variable.

Perhaps the easiest way to do this, since you also want to use the unquoted x for the column name inside mutate is to use rlang::ensym, but you still need to unquote with the bang-bang operator, and when you are assigning columns you need the assignment operator, :=

mixed_dateColumn_excel <- function(df, x) {
  
  x <- rlang::ensym(x)
  
  df %>% 
    mutate(new_col = suppressWarnings(janitor::excel_numeric_to_date(
                       as.numeric(as.character(!!x)), 
                       date_system = "modern")), .before = 1) %>% 
    mutate(!!x := ifelse(!str_detect(!!x, '\\.'), NA_character_, !!x)) %>% 
    mutate(!!x := lubridate::dmy(!!x)) %>% 
    mutate(!!x := coalesce(!!x, new_col), .keep="unused")
}


mixed_dateColumn_excel(df, date)
#> # A tibble: 10 x 1
#>    date      
#>    <date>    
#>  1 2011-01-31
#>  2 2011-11-14
#>  3 2011-11-23
#>  4 2012-03-22
#>  5 2022-03-07
#>  6 2022-03-14
#>  7 2022-03-16
#>  8 2022-03-27
#>  9 2022-03-24
#> 10 2022-03-24

^{Created on 2022-04-12 by the reprex package (v2.0.1)}

CodePudding user response：

{{ is not a real operator, tidyverse functions are designed to recognise it in arguments and do some magic.

{{ can be used in names too so no need for ensym() here, you can do :

mixed_dateColumn_excel <- function(df, x) {
  df %>% 
    mutate(
      new_col = excel_numeric_to_date(
        as.numeric(as.character({{ x }})), 
        date_system = "modern"
      ), 
      .before = 1
    ) %>% 
    mutate("{{ x }}" := ifelse(!str_detect({{ x }}, '\\.'), NA_character_, {{ x }})) %>% 
    mutate("{{ x }}" := lubridate::dmy({{ x }})) %>% 
    mutate("{{ x }}" := coalesce({{ x }}, new_col), .keep="unused")
}