Conditionally adding an "NA" row to a list of data frames using a loop

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I have a list of 52 datasets that are between 5 and 6 rows; they will all need an added column but to add this column the row number needs to be the same. To the sets with 5 rows, I want to add a 6th row with "NA" filling the row as a place holder. Here is where I have started, but I am unsure how to complete the loop because I am unsure what to use for the "df" in the nrow() function. I want this to do nothing to the datasets with 6 rows already.

testrows<-if lapply(listallht_allwk, nrow) = 5 { 
    df[nrow(df) + 1 ,] <- NA
}
add r list loops
1 Answers

Data

Here I've created two dummy data frames for demonstration.

df <- data.frame(row = 1:5, col1 = LETTERS[1:5])
df2 <- data.frame(row = 1:6, col1 = LETTERS[1:6])

df_list <- list(df, df2)

df_list
[[1]]
  row col1
1   1    A
2   2    B
3   3    C
4   4    D
5   5    E

[[2]]
  row col1
1   1    A
2   2    B
3   3    C
4   4    D
5   5    E
6   6    F

Code

It might be better to use if else inside lapply. Simply rbind the dataframe with NA to get an extra row of NA.

lapply(df_list, function(x) {
  if (nrow(x) == 5) {
    rbind(x, NA)
  } else {
    x
  }
})

[[1]]
  row col1
1   1    A
2   2    B
3   3    C
4   4    D
5   5    E
6  NA <NA>

[[2]]
  row col1
1   1    A
2   2    B
3   3    C
4   4    D
5   5    E
6   6    F
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