I am scoring a PES-brief scale at work for a study. One of the scales requires a frequency of event: if the participant scored 1-3, +1. If 0, then +0. I need to obtain this score for each person.
EDIT: There are additional rows that I do NOT want to add. I don't want to sum 'dontadd'
Here is my dataframe sample:
pesb0101 <- c(1,2,3,0,1,0,3,2,1,0)
pesb0102 <- c(1,1,0,0,3,2,3,2,1,0)
pesb0103 <- c(1,2,3,2,1,0,1,0,1,1)
df <- data.frame(pesb0101,pesb0102,pesb0103)
rownames(df) <- c('person1','person2','person3','person4','person5','person6','person7','person8','person9','person10')
df
pesb0101 pesb0102 pesb0103 dontadd
person1 1 1 1 1
person2 2 1 2 2
person3 3 0 3 3
person4 0 0 2 4
person5 1 3 1 5
person6 0 2 0 3
person7 3 3 1 9
person8 2 2 0 2
person9 1 1 1 1
person10 0 0 1 2
I need a score column for each person of a sum where if the score is NOT 0, +1. So my dataframe should be:
> df
pesb0101 pesb0102 pesb0103 dontadd pesbScore
person1 1 1 1 1 3
person2 2 1 2 2 3
person3 3 0 3 3 2
person4 0 0 2 4 1
person5 1 3 1 5 3
person6 0 2 0 3 1
person7 3 3 1 9 3
person8 2 2 0 2 2
person9 1 1 1 1 3
person10 0 0 1 2 1
I've tried a few different methods (rowSums mostly) and I think I'm probably missing something simple.
apply() can run a function for each row of a dataframe. If you make a simple function to score the way you want, apply can do the rest:
score_counter <- function(row) {
sum(row != 0)
}
# first make a new data frame with just the columns you want to add
df_pesb = df[, grepl("pesb", names(df))]
# use the new data frame to count a score for each row
df$pesbScore = apply(df_pesb, 1, score_counter)