# Define a function to generate random strings of a specified length

library(gt)
library(dplyr)

random_string <- function(length) {
  char_set <- c(letters, LETTERS, 0:9)
  paste0(sample(char_set, length, replace = TRUE), collapse = "")
}

# Loop through 100 times to create 100 CSV files
for (i in 1:100) {
  
  # Generate a random number of rows between 10 and 50
  num_rows <- sample(10:20, 1)
  
  # Generate a random number of columns between 3 and 10
  num_cols <- sample(3:10, 1)
  
  # Create a data frame with the specified number of rows and columns
  df <- data.frame(ID = replicate(num_rows, random_string(6)),
                   matrix(paste0("C", rep(1:(num_cols-1), each = num_rows),
                                 sample(2:4, num_rows*(num_cols-1), replace = TRUE)), ncol = num_cols-1), stringsAsFactors = FALSE)
  
  # Set the column names for the additional columns
  colnames(df)[-1] <- paste0("D", 1:(num_cols-1))
  
  # Write the data frame to a CSV file with the appropriate name
  filename <- sprintf("P%03d.csv", i)
  write.csv(df, filename, row.names = FALSE, quote = FALSE)
}


#P004 <- read.csv("P004.csv")

#P004table = gt(read.csv("P004.csv"))

#P004table <- P004table %>%
#  tab_row_group(
#    rows = which(rownames(P004) %in% rownames(P004[P004$D1 == "C12", ])),
#    label = "P004A"
#  ) %>%
#  tab_row_group(
#    rows = which(rownames(P004) %in% rownames(P004[P004$D1 == "C13", ])),
#    label = "P004B"
#  )




#P004 <- P004 %>%
#  mutate(Type = case_when(
#    D1 == "C12" & D2 == "C23" & D3 == "C32" ~ "P004A",
#    D1 == "C12" & D2 == "C23" & D3 == "C33" ~ "P004B",
#    TRUE ~ "Uncat"
#  ))


#P004A <- subset(P004, D1 == "C12" & D2 == "C23" & D3 == "C32")
#P004B <- subset(P004, D1 == "C12" & D2 == "C23" & D3 == "C33")

#P004Z=rbind(P004A,P004B)

#head(P004)

#P004_table <- gt(P004)


#table <- gt(P004)

#table <- table %>%
#  tab_row_group(groups = list("Type"))



#library(gt)

# Create a data frame
#data <- data.frame(
#  Name = c("John", "Emily", "Michael", "Emma", "Daniel"),
#  Age = c(25, 32, 41, 29, 36),
#  Country = c("USA", "Canada", "UK", "Australia", "USA")
#)

# Create a gt table
#table <- gt(data)

# Select rows based on a condition
#selected_rows <- data[data$Age > 30, ]  # Select rows where Age is greater than 30

# Add row groups
#table <- table %>%
#  tab_row_group(
#    rows = which(rownames(data) %in% rownames(selected_rows)),  # Get row indices of selected rows
#    label = "Group 1 (Age > 30)"
#  )

# Print the table
#print(table)
#library(gt)

# Create a data frame
#data <- data.frame(
#  Name = c("John", "Emily", "Michael", "Emma", "Daniel"),
#  Age = c(25, 32, 41, 29, 36),
#  Country = c("USA", "Canada", "UK", "Australia", "USA")
#)

# Create a gt table
#table <- gt(data)

# Select rows based on a condition
#selected_rows <- data[data$Age > 30, ]  # Select rows where Age is greater than 30

# Add row groups
#table <- table %>%
#  tab_row_group(
#    rows = which(rownames(data) %in% rownames(selected_rows)),  # Get row indices of selected rows
#    label = "Group 1 (Age > 30)"
#  )

# Print the table
#print(table)
#gtsave(P004table, file = "P004_table.html")
#system("wkhtmltopdf P004_table.html table.pdf")