从数据框粘贴一行以匹配另一个数据框的行长 [英] Paste a row from a dataframe to match the length of rows of another dataframe

问题描述

几个月以来，我一直在RStudio工作，一件事很难办.我有一个包含多个csv文件的目录，需要在RStudio中导入.每个名称和日期都有多个文件.

I'm working with RStudio since a few months now and I'm having a hard time with one thing. I have a directory with multiple csv files that I need to import in RStudio. There are multiples files per name and date.

csv文件的格式化方式实际上很奇怪. CSV的所有数据(数字)都从第7行开始.问题在于，需要分别提取所收集文件中的信息(名称，日期，设备等).

The way the csv file is formatted is actually pretty weird. All data (numbers) in the csv's s start at the row #7. The problem is that the informations from the collected file (name, date, equipment, etc) need to be extracted separately.

基本上，for循环中的temp数据帧都具有不同的行数(+200).另一方面，info数据帧都只有一行(每个csv一行).

Basically, the temp dataframes in the for loop all have a different numbers of rows (+200). On the other hand, the info dataframes all have a single row (one row per csv).

我想将两个文件与在关联数据df_groinbar的长度(在csv中)重复的info行绑定在一起.不要忘记每个csv(df_groinbar数据帧)的长度不同，因此需要为每个csv调整info和df_groinbar的绑定.

I would like to bind the two files together with the info row duplicated for the length of the associated data df_groinbar (in the csv). Don't forget that the length of each csv (df_groinbar dataframe) is different, so the bind of info and df_groinbar would need to be ajusted for each csv.

df_groinbar <- data.frame()
info <- data.frame()
for (i in list.files("/Users/Nicolas/Dropbox/Groin Bar/"))
{
  type <- str_extract(i, "([A-Z]+)")
  temp <- read_csv(i, skip = 6, col_names = c("elapsed_time", "left_squeeze", "right_squeeze", "left_pull", "right_pull"))
  info_temp <- select(read_csv(i, skip = 2, n_max = 1), 1:6)
  df_groinbar <- rbind(df_groinbar, temp)
  info <- rbind(info, info_temp)
}

我已经尝试过smartbind函数，并且还有很多，但是没有用.

I've tried smartbind functions and many more and nothing worked.

非常感谢！

尼古拉斯

推荐答案

这是您要的吗?

library(tidyverse)

filePattern <- "\\.csv$"
fileList <- list.files(path = "./Csv test/", recursive = FALSE,
                       pattern = filePattern, full.names = TRUE)

read_file_custom <- function(fileName) {

  # skip 6 lines and select only the first 5 columns
  dat <- readr::read_csv(file = fileName, skip = 6, col_names = FALSE) %>% 
    select(., 1:5) 

  colName <- c("TimeFrame", "Left(squeeze)", "Left(pull)", "Right(squeeze)", "Right(pull)")
  names(dat) <- colName

  # now read the 3rd and 4th lines & keep only the first 6 columns
  indi_info <- readr::read_csv(file = fileName, skip = 2, col_names = TRUE, n_max = 1) %>% 
    select(., 1:6)

  # transfer individual data to dat
  dat <- dat %>% 
    mutate(NAME   = indi_info$NAME,
           DATE   = indi_info$DATE,
           TIME   = indi_info$TIME,
           DEVICE = indi_info$DEVICE,
           MODE   = indi_info$MODE,
           TEST   = indi_info$TEST)

  return(dat)
}

# Loop through all the files using map_df, read data 
# and create a FileName column to store filenames
# Clean up filename: remove file path and extension
# Bind all files together

result <- fileList %>%
  purrr::set_names(nm = (basename(.) %>% tools::file_path_sans_ext())) %>%
  purrr::map_df(read_file_custom, .id = "FileName") 
result

#> # A tibble: 10,460 x 12
#>    FileName        TimeFrame `Left(squeeze)` `Left(pull)` `Right(squeeze)`
#>    <chr>               <dbl>           <dbl>        <dbl>            <dbl>
#>  1 Arianne-Robill~    0.0200          -1.00          2.25           -1.25 
#>  2 Arianne-Robill~    0.0400          -1.00          2.25           -1.25 
#>  3 Arianne-Robill~    0.0600          -1.00          2.25           -1.25 
#>  4 Arianne-Robill~    0.0800          -1.00          2.25           -1.25 
#>  5 Arianne-Robill~    0.100           -1.00          2.25           -1.25 
#>  6 Arianne-Robill~    0.120           -1.00          2.00           -1.25 
#>  7 Arianne-Robill~    0.140           -1.00          2.00           -1.00 
#>  8 Arianne-Robill~    0.160           -0.750         2.00           -1.00 
#>  9 Arianne-Robill~    0.180           -0.750         1.75           -0.750
#> 10 Arianne-Robill~    0.200           -0.750         1.75           -0.750
#> # ... with 10,450 more rows, and 7 more variables: `Right(pull)` <dbl>,
#> #   NAME <chr>, DATE <chr>, TIME <time>, DEVICE <chr>, MODE <chr>,
#> #   TEST <chr>

由 reprex程序包(v0.2.0)创建于2018-03-28.

Created on 2018-03-28 by the reprex package (v0.2.0).

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