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Asked: 2026-05-31T11:15:42+00:00

I have a folder with 20 text files from several instrument runs. The data

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I have a folder with 20 text files from several instrument runs. The data section all have the same format like this

22/05/11;   16:03:28;       0.000;   6.079;   31.41;   84881;   25.60; E0;
22/05/11;   16:03:29;       0.017;   6.063;   31.44;   84868;   25.60; E0;
22/05/11;   16:03:30;       0.034;   6.079;   31.41;   84868;   25.60; E0;
22/05/11;   16:03:31;       0.051;   6.079;   31.41;   84868;   25.60; E0;
22/05/11;   16:03:32;       0.068;   6.068;   31.43;   84868;   25.60; E0;
22/05/11;   16:03:33;       0.085;   6.068;   31.43;   84881;   25.60; E0;
22/05/11;   16:03:34;       0.102;   6.079;   31.41;   84874;   25.60; E0;

What I would like to do is read in every file within my folder, run a linear regression, and pull out the slope and R2 value.

As of now, this is my code for doing this for a single file.

O2=read.table("Coral 1_Dark.txt",skip=58, sep=";",header=FALSE)
names(O2)<-c("Date","Time","Log_Time","O2_mgL","Phase","Amp","Temp C","Error Message")
O2$id<-seq_len(nrow(O2)) #creates unique ID for each measurement (use for regression)
attach(O2)
fit=lm(O2_mgL~id)
summary(fit)

After running this code, I have been manually entering the slope and R2 data.

For now I can create a variable that contains all the files I am interested in with

F=list.files()

Which gives me all 20 files

[1] "Coral 1_Dark.txt"   "Coral 1_Light.txt"  "Coral 10_Dark.txt"  "Coral 10_Light.txt" "Coral   2_Dark.txt"  
[6] "Coral 2_Light.txt"  "Coral 3_Dark.txt"   "Coral 3_Light.txt"  "Coral 4_Dark.txt"   "Coral  4_Light.txt" 
[11] "Coral 5_Dark.txt"   "Coral 5_Light.txt"  "Coral 6_Dark.txt"   "Coral 6_Light.txt"  "Coral 7_Dark.txt"  
[16] "Coral 7_Light.txt"  "Coral 8_Dark.txt"   "Coral 8_Light.txt"  "Coral 9_Dark.txt"   "Coral 9_Light.txt"

And what I would like to end up with would be something like this for all 20 files

Coral            Slope        R2
Coral 1_Dark      0.23         98.3
Coral 2_Dark      0.33         99.3

ect

Any suggestions? I’ve never worked with any of the apply functions or any kind of loop- but I’m thinking this is about to change…..

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1 Answer

  1. Editorial Team

    Something like this?

    wd <- "C:/Data"
files    <- dir(wd)
varnames <- c("Date", "Time", "Log_Time", "O2_mgL", "Phase", "Amp", "Temp C",
            "Error Message")
results  <- data.frame()

for (i in 1:length(files)) {
  fname <- paste(wd, files[i], sep="/")
  data <- read.table(fname, sep=";", skip=58)
  colnames(data) <- varnames
  data$id <- 1:nrow(data)
  fit <- summary(lm(O2_mgL~id, data=data))
  results[i,1] <- fit$coefficients[2]
  results[i,2] <- fit$r.squared
}

rownames(results) <- sub(".txt", "", files)
colnames(results) <- c("Slope", "R2")

print(results)
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