Dynamic name dataframe R for loop

Question

I am trying to produce 16 dataframes each with the name of the 16 different proteins, the code I have tried doesn't work

for (i in seq(1,len_TSPAN)){
  temp_TSPAN <- TSPANS$V1[i]
  print(temp_TSPAN)
  paste(temp_TSPAN) <- data.frame(Lum_A_Q1_means = rep(NA, 67), Lum_A_Q2_means = rep(NA,67),
                            Lum_A_Q3_means = rep(NA, 67), Lum_A_Q4_means = rep(NA,67),
                            Lum_B_Q1_means = rep(NA, 67), Lum_B_Q2_means = rep(NA,67),
                            Lum_B_Q3_means = rep(NA, 67), Lum_B_Q4_means = rep(NA,67),
                            Her_2_Q1_means = rep(NA, 67), Her_2_Q2_means = rep(NA,67),
                            Her_2_Q3_means = rep(NA, 67), Her_2_Q4_means = rep(NA,67),
                            Basal_Q1_means = rep(NA, 67), Basal_Q2_means = rep(NA,67),
                            Basal_Q3_means = rep(NA, 67), Basal_Q4_means = rep(NA,67),
                            Normal_Q1_means = rep(NA, 67), Normal_Q2_means = rep(NA,67),
                            Normal_Q3_means = rep(NA, 67), Normal_Q4_means = rep(NA,67))
}

It would be assign(as.character(temp_TSPAN), value = data.frame(...)) — akrun
– akrun, Commented Feb 15, 2020 at 18:43

akrun · Accepted Answer · 2020-02-15 18:45:18Z

paste on the lhs of <- shouldd be replaced by assign if we want to create multiple objects in the global env (not recommended though)

for (i in seq(1,len_TSPAN)){
  temp_TSPAN <- TSPANS$V1[i]
    print(temp_TSPAN)
    assign(as.character(temp_TSPAN), value = data.frame(Lum_A_Q1_means = rep(NA, 67), Lum_A_Q2_means = rep(NA,67),
                            Lum_A_Q3_means = rep(NA, 67), Lum_A_Q4_means = rep(NA,67),
                            Lum_B_Q1_means = rep(NA, 67), Lum_B_Q2_means = rep(NA,67),
                            Lum_B_Q3_means = rep(NA, 67), Lum_B_Q4_means = rep(NA,67),
                            Her_2_Q1_means = rep(NA, 67), Her_2_Q2_means = rep(NA,67),
                            Her_2_Q3_means = rep(NA, 67), Her_2_Q4_means = rep(NA,67),
                            Basal_Q1_means = rep(NA, 67), Basal_Q2_means = rep(NA,67),
                            Basal_Q3_means = rep(NA, 67), Basal_Q4_means = rep(NA,67),
                            Normal_Q1_means = rep(NA, 67), Normal_Q2_means = rep(NA,67),
                            Normal_Q3_means = rep(NA, 67), Normal_Q4_means = rep(NA,67))
                            )
}

It seems that we are creating the same 'data.frame' object in each loop. It may be easier with replicate and store in a list

lst1 <- replicate(len_TSPAN), 
           data.frame(Lum_A_Q1_means = rep(NA, 67), Lum_A_Q2_means = rep(NA,67),
                            Lum_A_Q3_means = rep(NA, 67), Lum_A_Q4_means = rep(NA,67),
                            Lum_B_Q1_means = rep(NA, 67), Lum_B_Q2_means = rep(NA,67),
                            Lum_B_Q3_means = rep(NA, 67), Lum_B_Q4_means = rep(NA,67),
                            Her_2_Q1_means = rep(NA, 67), Her_2_Q2_means = rep(NA,67),
                            Her_2_Q3_means = rep(NA, 67), Her_2_Q4_means = rep(NA,67),
                            Basal_Q1_means = rep(NA, 67), Basal_Q2_means = rep(NA,67),
                            Basal_Q3_means = rep(NA, 67), Basal_Q4_means = rep(NA,67),
                            Normal_Q1_means = rep(NA, 67), Normal_Q2_means = rep(NA,67),
                            Normal_Q3_means = rep(NA, 67), Normal_Q4_means = rep(NA,67)), simplify = FALSE)

M_Shimal · Accepted Answer · 2020-02-15 19:04:46Z

Here is another solution, worked off from your loop. Note that I have made up a dataframe for illustration

TSPANS <- data.frame(V1 = letters[1:12])

myList <- list()

for (i in seq(1,12)){
  temp_TSPAN <- TSPANS$V1[i]
  print(temp_TSPAN)
  x <- data.frame(Lum_A_Q1_means = rep(NA, 67), Lum_A_Q2_means = rep(NA,67),
                                  Lum_A_Q3_means = rep(NA, 67), Lum_A_Q4_means = rep(NA,67),
                                  Lum_B_Q1_means = rep(NA, 67), Lum_B_Q2_means = rep(NA,67),
                                  Lum_B_Q3_means = rep(NA, 67), Lum_B_Q4_means = rep(NA,67),
                                  Her_2_Q1_means = rep(NA, 67), Her_2_Q2_means = rep(NA,67),
                                  Her_2_Q3_means = rep(NA, 67), Her_2_Q4_means = rep(NA,67),
                                  Basal_Q1_means = rep(NA, 67), Basal_Q2_means = rep(NA,67),
                                  Basal_Q3_means = rep(NA, 67), Basal_Q4_means = rep(NA,67),
                                  Normal_Q1_means = rep(NA, 67), Normal_Q2_means = rep(NA,67),
                                  Normal_Q3_means = rep(NA, 67), Normal_Q4_means = rep(NA,67), temp_TSPAN = temp_TSPAN)
  myList[[temp_TSPAN]] <- x
}
# I have added a column named, temp_TSPAN, with name of temp_TSPAN  in it. This is because converting the list to a dataframe, as below, will put everything into one. 


library(tidyverse)

# You may use this dataframe to subset for your temp_TSPAN variable. Its better to have them in one, them lots of separate dataframes.
df <- bind_rows(myList)

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