Compute a function whose arguments stored in rows of a data frame in R-CodePudding

I have a very long function whose arguments take in different threshold values for different variables and give an event study result at the end. I want to compute this function over different list of values.

V1         4                4            0.05              2                            0.8
V2         5                4            0.05              2                            0.8

V1 and V2 are two different combinations of my function's arguments. Each column represent an argument of my function. How can I iterate through each row given each column is a different argument of the function?

CodePudding user response：

Something like this perhaps assuming your columns are a, b, c, d, e and dataset is df. Would be better if you provided some data. Gives you a named list of results using V1, V2, etc as the name.

results <- list()
for (V in 1:nrow(df)){
 results[[df$a[V]]] <- myfunction(arg1 = df$b[V], arg2 = df$c[V],
                      arg3 = df$d[V], arg4 = df$e[V])
}

CodePudding user response：

Here's an example using purrr::pmap. It captures the results as a column in the same dataframe that holds the data.

library(dplyr)
library(purrr)

#sample data set
data <- data.frame(
               a = c(1, 2, 3),
               b = c(7, 8, 9),
               c = c(4, 5, 6))

rownames(data) <- c("V1", "V2", "V3")

data %>%
    mutate(results = pmap_dfr(., function(a, b, c) {data.frame(results = a   b   c)} ))

#   a b c results
#V1 1 7 4      12
#V2 2 8 5      15
#V3 3 9 6      18