在R循环中批量格式化HOBOware数据CSV文件遇问题求助

Hey Chris, let's break down what's going wrong and get your batch processing working smoothly!

First, the Root Cause of That Error #

You hit a classic mix-up between base R and readr package functions:

• Your single-file code uses read_csv() (from the readr package), which supports the col_types argument to define column formats.
• But in your loop, you switched to read.csv() (base R's CSV reader), which doesn't recognize col_types—that's exactly why you're seeing that "unused argument" error.

Fix #1: Correct the Loop with read_csv #

Let's rewrite the loop to match your working single-file code, plus add a way to store all your datasets instead of overwriting them each time:

# First, make sure you load the readr package (critical!)
library(readr)

# Set up your paths
setwd("E:/R Hobo/Conversion test/Converted HOBO files")
mydir = "Pool 6"
myfiles = list.files(path = mydir, pattern = "*.csv", full.names = TRUE)

# Create an empty list to hold each month's data
pool_data <- list()

# Loop through each file
for (file_index in seq_along(myfiles)) {
  # Read the file with the same logic as your single-file code
  current_month <- read_csv(
    myfiles[file_index],
    col_types = cols(`Date Time, GMT-05:00` = col_datetime(format = "%m/%d/%y %H:%M:%S")),
    skip = 1
  )[, 2:4]
  
  # Name the list entry after the file (so you can track which month is which)
  names(pool_data)[file_index] <- basename(myfiles[file_index])
  
  # Add the data to the list
  pool_data[[file_index]] <- current_month
}

# Optional: Combine all data into one big data frame
pool_combined <- do.call(rbind, pool_data)

Fix #2: Using lapply (Works in R 3.5.3!) #

You mentioned hearing about lapply but thought it was incompatible with R 3.5.3—don't worry, lapply is a core base R function that works in every version! The issue was likely missing the readr package or a syntax misstep. Here's a clean lapply version:

library(readr)

setwd("E:/R Hobo/Conversion test/Converted HOBO files")
mydir = "Pool 6"
myfiles = list.files(path = mydir, pattern = "*.csv", full.names = TRUE)

# Read all files at once with lapply
pool_data <- lapply(myfiles, function(file_path) {
  read_csv(
    file_path,
    col_types = cols(`Date Time, GMT-05:00` = col_datetime(format = "%m/%d/%y %H:%M:%S")),
    skip = 1
  )[, 2:4]
})

# Name the list elements for clarity
names(pool_data) <- basename(myfiles)

# Combine into a single data frame if needed
pool_combined <- do.call(rbind, pool_data)

Quick Note for R 3.5.3 Compatibility #

If you run into issues with readr, make sure you're using a version that supports R 3.5.3. The latest compatible version is readr 1.3.1—install it with:

install.packages("readr", version = "1.3.1")

内容的提问来源于stack exchange，提问作者Chris McNabb