r - 创建“for循环”以合并多对csv文件

Question

首先，我是一名追踪海鸟运动和行为的生物学家。在这些海鸟上，我附上了两个同时收集数据的独立生物记录器。一种是 GPS，每 2 分钟记录一次坐标，另一种称为时间深度记录器（TDR），每 1 秒记录一次深度（当鸟类潜入超过一定深度时，可以认为潜水事件是觅食潜水）。结合这些数据将有助于在空间上识别鸟类正在潜水觅食的位置。因此，我追踪的每只鸟都有一对 GPS 和 TDR 数据，需要根据它们的时间戳进行组合。然而，让生活更轻松的是，使用 For 循环或其他方法对这些进行批处理，因为我已经跟踪了 20 多只鸟，并且将它们一一组合起来非常乏味。我几乎没有编写循环的经验，需要帮助。

我目前所做的是通过将 GPS 数据（日期）上的时间戳与 TDR 数据（日期时间）上的时间戳相匹配，将这两个数据集一一组合，过滤掉没有对应的坐标。

# Read in GPS and TDR files for each bird
rh01gps <- read.csv(file.choose(), sep=",", stringsAsFactors = F, strip.white = T, na.strings = c(""))

head(rh01gps)
          x        y              date      id
1 -123.0033 37.69831 6/3/2018 01:02:00 2018_01
2 -123.0033 37.69826 6/3/2018 01:04:00 2018_01
3 -123.0032 37.69821 6/3/2018 01:06:00 2018_01
4 -123.0033 37.69829 6/3/2018 01:08:00 2018_01
5 -123.0033 37.69830 6/3/2018 01:10:00 2018_01
6 -123.0033 37.69832 6/3/2018 01:12:00 2018_01

rh01tdr <- read.csv(file.choose(), sep=",", stringsAsFactors = F, strip.white = T, na.strings = c(""))

head(rh01tdr)
      Date Pressure   Temp        Time          DateTime
1 6/3/2018    -0.94 25.203 12:00:00 AM 6/3/2018 00:00:00
2 6/3/2018    -0.94 25.203 12:00:01 AM 6/3/2018 00:00:01
3 6/3/2018    -0.94 25.203 12:00:02 AM 6/3/2018 00:00:02
4 6/3/2018    -0.94 25.203 12:00:03 AM 6/3/2018 00:00:03
5 6/3/2018    -0.94 25.203 12:00:04 AM 6/3/2018 00:00:04
6 6/3/2018    -0.94 25.203 12:00:05 AM 6/3/2018 00:00:05

# Create a dataframe with dates from TDR file that match GPS datetime (many 
# more data points from TDRs than GPS, need to filter out dates that won't 
# have a match in the GPS file)
rh_gps_tdr <- subset(rh01tdr, DateTime %in% rh01gps$date)

# Merge newly created data
merge <- cbind(rh_gps_tdr, rh01gps$x, rh01gps$y)

# Rename longitude (rh01gps$x) and latitude (rh01gps$y) columns to "x" and "y"
colnames(merge)[colnames(merge)=="rh01gps$x"] <- "x"
colnames(merge)[colnames(merge)=="rh01gps$y"] <- "y"

# Subset data to filter out unnecessary columns
rh01_gt <- subset(merge, select = c(5, 6, 7, 2, 3))

# Combined GPS coordinates plus pressure data.
head(rh01_gt)
           DateTime         x        y Pressure   Temp
1 6/3/2018 01:02:00 -123.0033 37.69831    -0.94 24.828
2 6/3/2018 01:04:00 -123.0033 37.69826    -0.91 24.703
3 6/3/2018 01:06:00 -123.0032 37.69821    -0.94 24.625
4 6/3/2018 01:08:00 -123.0033 37.69829    -0.94 24.578
5 6/3/2018 01:10:00 -123.0033 37.69830    -0.91 24.531
6 6/3/2018 01:12:00 -123.0033 37.69832    -0.94 24.516

write.csv(rh01_gt, "RHAU01_2018_TDR&GPS.csv")

我提供的代码可用于处理一只鸟的数据集，但我想看看是否有一种方法可以在一个进程中为每只鸟运行此代码。

标签： rcsvfor-loopfiltermerge

Answer 1

我已将您的代码放入 for 循环中。只要每个 csv 文件的数量相等并且它们具有相同的名称模式，这个循环就应该起作用。在我的测试中，文件名是 rh01gps.csv、rh02gps.csv……和 rh01tdr.csv、rh02tdr.csv……我必须设置日期格式，否则它不起作用（请注意，我假设您的日期格式是dd/mm/yyyyy）。我也更改了subset，因为如果有日期列，我认为没有必要使用 DateTime 列（随意更改）。

# your directory with all the csv files
setwd('yourpath')

# list tdr files by pattern 'tdr'
tdr.list<-list.files(pattern='tdr')

# list gps files by pattern 'gps'
gps.list<-list.files(pattern='gps')

# starting loop
for (i in 1:length(gps.list)) 
{
  # open each csv
  tdr<-read.csv(tdr.list[i], sep=",", stringsAsFactors = F, strip.white = T, na.strings = c(""))
  gps<-read.csv(gps.list[i], sep=",", stringsAsFactors = F, strip.white = T, na.strings = c(""))

  # set date format 
  gps$date<-as.Date(gps$date, '%d/%m/%Y')
  tdr$Date<-as.Date(tdr$Date, '%d/%m/%Y')

  # Create a dataframe with dates from TDR file that match GPS datetime (many 
  # more data points from TDRs than GPS, need to filter out dates that won't 
  # have a match in the GPS file)
  rh_gps_tdr <- subset(tdr, Date %in% gps$date) # subset made with date

  # Merge newly created data
  merge <- cbind(rh_gps_tdr, gps$x, gps$y)

  # Rename longitude (rh01gps$x) and latitude (rh01gps$y) columns to "x" and "y"
  colnames(merge)[colnames(merge)=="gps$x"] <- "x"
  colnames(merge)[colnames(merge)=="gps$y"] <- "y"

  # Subset data to filter out unnecessary columns
  gt <- subset(merge, select = c(5, 6, 7, 2, 3))

  # get the file number to have it in the output file
  filenumber<-substr(gps.list[i], 3,4) # 3 & 4 are the position of the number in the name (rhXXgps.csv)

  # writing csv file
  write.csv(gt, paste0("RHAU", filenumber, "_2018_TDR&GPS.csv"))
}