data CHARDATA;
infile datalines dlm='|' dsd missover;
input var1 : $10. var2 : $10. var3 : $10. var4 : $10. var5 : $10.;
label ;
format ;
datalines4;
_missing_|text1|text2|_missing_|text3
text4|text5|_missing_|text6|text7
text8|_missing_|text9|text10|text11
;;;;
run;

data chardata01;
    set chardata;

    array xchar[*] _character_;

    do i=1 to dim(xchar);
        if lowcase(xchar[i])="_missing_" then xchar[i]="";
    end;

    drop i;
run;

Description:

• It creates a new SAS dataset named chardata01.
• It reads data from an existing SAS dataset named chardata.
• It declares an array named xchar that contains all character variables in the dataset.
• It initiates a do-loop that iterates from 1 to the number of elements in the xchar array.
• Within the do-loop, it checks if the lowercase value of each element in xchar is equal to "_missing_".
• If the condition is true, it replaces the value of that element with an empty string.
• After the do-loop, it drops the loop index variable i.
• Finally, it ends the data step with the run; statement.

library(tidyverse)

chardata<-tribble(
~var1,~var2,~var3,~var4,~var5,
"_missing_","text1","text2","_missing_","text3",
"text4","text5","_missing_","text6","text7",
"text8","_missing_","text9","text10","text11",
)

chardata01 <- chardata %>%
  mutate(across(where(is.character), ~ifelse(tolower(.) == "_missing_", "", .))) 
  

Description:

• It creates a new data frame named chardata01 using the pipe operator %>%.
• It takes the existing data frame chardata as the input data.
• It uses the mutate() function to modify the columns of the data frame.
• The across() function is used to specify the columns to apply the transformation to. In this case, it selects all columns that are of character data type (where(is.character)).
• Within the across() function, the ~ symbol indicates that a lambda or anonymous function is being defined.
• The lambda function checks if the lowercase value of each element in the selected columns is equal to "missing".
• If the condition is true, it replaces the value of that element with an empty string ("").
• The modified data frame is assigned to the variable chardata01.
• The resulting data frame chardata01 contains the original data with the character variables updated to remove any occurrences of "_missing_".