请求R代码：批量读取文件夹中多列TXT文件并拆分保存为三类文件

Got it, let's tackle this problem step by step. Here's a robust R solution that works for any number of your TXT files (whether it's 4 or more) and neatly combines the corresponding columns across all files.

Step-by-Step Explanation & Code #

First, we'll grab all your target files, read each one to extract the three columns, merge the data by measurement row, then save the results as three separate TXT files.

# 1. Set your working directory to where your TXT files are stored
# Replace the path below with your actual folder path
setwd("C:/your/folder/path")

# 2. Get all TXT files matching the "fileX.txt" naming pattern
file_list <- list.files(pattern = "^file\\d+\\.txt$")

# 3. Initialize empty lists to store each column's data from all files
day_records <- list()
temp_records <- list()
press_records <- list()

# 4. Loop through each file to extract data
for (file_name in file_list) {
  # Read the file - adjust 'sep' if your data uses commas, spaces, etc.
  # Use header=TRUE if your files have column headers (like "day", "temperature")
  raw_data <- read.table(file_name, header = FALSE, sep = "\t")
  
  # Extract each column (assuming columns 1=day, 2=temperature, 3=pressure)
  day_records[[file_name]] <- raw_data[, 1]
  temp_records[[file_name]] <- raw_data[, 2]
  press_records[[file_name]] <- raw_data[, 3]
}

# 5. Combine all records into data frames (each row = same measurement across files)
combined_days <- do.call(cbind, day_records)
combined_temps <- do.call(cbind, temp_records)
combined_pressures <- do.call(cbind, press_records)

# 6. Add meaningful column names (remove .txt extension from file names)
colnames(combined_days) <- gsub("\\.txt$", "", file_list)
colnames(combined_temps) <- gsub("\\.txt$", "", file_list)
colnames(combined_pressures) <- gsub("\\.txt$", "", file_list)

# 7. Save the combined data to three separate TXT files
write.table(combined_days, "combined_day_data.txt", 
            sep = "\t", row.names = FALSE, quote = FALSE)
write.table(combined_temps, "combined_temperature_data.txt", 
            sep = "\t", row.names = FALSE, quote = FALSE)
write.table(combined_pressures, "combined_pressure_data.txt", 
            sep = "\t", row.names = FALSE, quote = FALSE)

Key Notes to Adjust for Your Data #

• Separator: If your data uses spaces instead of tabs, change sep = "\t" to sep = " " (or use sep = "," for CSV-style files).
• Headers: If your input files have column headers (e.g., first line is "day", "temperature", "pressure"), set header = TRUE in read.table, and you can extract columns by name instead of index (e.g., raw_data$day instead of raw_data[,1]).
• Row Consistency: This code assumes all files have the same number of measurement rows. If some files have missing rows, you can use dplyr::bind_cols with tidyr::fill to handle gaps, but that's an extra step if needed.

内容的提问来源于stack exchange，提问作者AstroCab