generate for loop for different csv files

[safara]

Hi,
I have the following code which works successfully

t.test.results<- list()
for (i in 1:6) {
  y=read.csv('Sharpe_window1.csv',header = T)
  y$Data<-NULL
  x1=as.numeric(y[,2])
  y1=as.numeric(y[,i])
  tempdata= augmented_t.test(x1,y1)$diff
  t.test.results[[i]]<- tempdata
}

I want to generate this former code for different csv files and store the results same as what I did before .

I have 4 csv files. I read those files by

for(i in 1:4)
{
  oname = paste("Sharpe_window", i, sep="")
  assign(oname, read.csv(paste(oname, ".csv", sep="")))
}

Now I am trying to generate for loop for each files and store the results for each files as follow:

total.t.test.results<- list()
for (k in 1:4){
 sample.t.test.results<- list()
for (i in 1:6) {
  y=read.csv('Sharpe_window[[k]].csv')
  y$Data<-NULL
  x1=as.numeric(y[,2])
  y1=as.numeric(y[,i])
  tempdata= augmented_t.test(x1,y1)$diff
  sample.t.test.results[[i]]<- tempdata
}
 total.t.test.results[[k]]=sample.t.test.results
}

but I am receiving an error . Can you please help me to solve the problem

[Leon]

This might not be exactly what you are looking for, but based on what you are trying to achieve, it might be a good approach to look into:

# Load Libraries ----------------------------------------------------------
library("tidyverse")
library("broom")


# Create Example Data -----------------------------------------------------
map(1:6, \(i) write_csv(x = tibble(x = rnorm(10), y = rnorm(10)),
                        file = str_c("~/my_csv_file_", i, ".csv")) )


# Load Data ---------------------------------------------------------------
my_csv_files <- list.files(path = "~", full.names = TRUE, pattern = "csv$")
my_data <- my_csv_files %>% 
  map(read_csv)


# Run tests ---------------------------------------------------------------
my_test_results <- my_data %>% 
  bind_rows(.id = "file_number") %>% 
  group_by(file_number) %>% 
  nest %>% 
  ungroup %>% 
  mutate(test = map(data, ~t.test(pluck(.x, "x"),
                                  pluck(.x, "y"), data = .x)),
         tidy_test = map(test, tidy)) %>% 
  unnest(tidy_test) %>% 
  select(-data, -test) %>% 
  mutate(q.value = p.adjust(p.value))

...and hot tip: Want to understand what is going on? Ask chatGPT Please explain the following code in simple terms and then paste the above

[technocrat]

@safara

y=read.csv('Sharpe_window[[k]].csv')

Do you mean this to be a literal? Otherwise use

y = read.csv(paste0(“Sharp_window”,k,”.csv”))

[safara]

Thank you very much for your valuable tip !

[safara]

Thank you very much! it works!!