Removing specific values in R from entire dataframe

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I need to remove specific text/values from all cells it is present within a dataset. This should be the equivalent of the 'Find and Replace All' tool within Excel. This cannot be simply removing/omitting all 'NA' values as several entries are NA and need to remain such, thus meaning it needs to be removing "NA |". This also cannot be limited to just the columns listed below and must be applied to the entire data frame, as there are 20+ additional columns to the right of V6.

Input:

V1            V2           V3           V4          V5         V6
NA|TR1000     NA|chr1      NA|1000      1200        A          + 
TR1000        chr1         1100         NA|1200     B          + 
NA|TR1000     NA|chr1      NA|1000      NA          C          +  
TR2000        NA|chr2      2000         NA          D          +   
TR2000        NA|chr2      2100         2500        E          + 
TR3000        NA           3000         3500        F          + 
NA|TR3000     chr3         NA|3000      3500        F          +

I Need:

V1         V2         V3         V4         V5        V6
TR1000     chr1       1000       1200       A          + 
TR1000     chr1       1100       1200       B          + 
TR1000     chr1       1000       NA         C          +  
TR2000     chr2       2000       NA         D          +   
TR2000     chr2       2100       2500       E          + 
TR3000     NA         3000       3500       F          + 
TR3000     chr3       3000       3500       F          +
dataframe r
2 Answers

This should do it:

df[] = lapply(df, sub, pattern = "NA|", replacement = "", fixed = TRUE)

Demo:

df = read.table(text = 'V1            V2           V3           V4          V5         V6
NA|TR1000     NA|chr1      NA|1000      1200        A          + 
TR1000        chr1         1100         NA|1200     B          + 
NA|TR1000     NA|chr1      NA|1000      NA          C          +  
TR2000        NA|chr2      2000         NA          D          +   
TR2000        NA|chr2      2100         2500        E          + 
TR3000        NA           3000         3500        F          + 
NA|TR3000     chr3         NA|3000      3500        F          + ', header = T)

df[] = lapply(df, sub, pattern = "NA|", replacement = "", fixed = TRUE)

df
  #       V1   V2   V3   V4 V5 V6
  # 1 TR1000 chr1 1000 1200  A  +
  # 2 TR1000 chr1 1100 1200  B  +
  # 3 TR1000 chr1 1000 <NA>  C  +
  # 4 TR2000 chr2 2000 <NA>  D  +
  # 5 TR2000 chr2 2100 2500  E  +
  # 6 TR3000 <NA> 3000 3500  F  +
  # 7 TR3000 chr3 3000 3500  F  +

If you like using dplyr, here's a method there:

df %>% 
  mutate(across(everything(), sub, pattern = "NA|", replacement = "", fixed = TRUE))
user_9030610 
type.convert(data.frame(sub("NA|", "", as.matrix(df), fixed = TRUE)), as.is = TRUE)

      V1   V2   V3   V4 V5 V6
1 TR1000 chr1 1000 1200  A  +
2 TR1000 chr1 1100 1200  B  +
3 TR1000 chr1 1000   NA  C  +
4 TR2000 chr2 2000   NA  D  +
5 TR2000 chr2 2100 2500  E  +
6 TR3000 <NA> 3000 3500  F  +
7 TR3000 chr3 3000 3500  F  +
user_83802720
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