generate for loop for different csv files

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)
  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) {
  tempdata= augmented_t.test(x1,y1)$diff
  sample.t.test.results[[i]]<- tempdata

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

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 ----------------------------------------------------------

# 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 %>% 

# 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 :+1:

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Do you mean this to be a literal? Otherwise use

y = read.csv(paste0(“Sharp_window”,k,”.csv”))
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Thank you very much for your valuable tip !

Thank you very much! it works!!

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