如何将文本与空格组合成R中的单个列？

Question

我的上一列(“详细信息”)包含有空格或制表符的信息。我如何将所有细节作为R中的一列来阅读？

输入

date    month   year    type    expenditure details
10/31/2017  Oct 2017    food    10.89   Point Of Sale Withdrawal 17203473997 TRESIDDER U2           STANFORD     CAUS
10/31/2017  Oct 2017    uber    4.80    Point Of Sale Withdrawal 44519795098 UBER   TRIP F73MU      HELP.UBER.COMCAUS
10/31/2017  Oct 2017    instacart   99.00   Point Of Sale Withdrawal 44534891998 INSTACART SUBSCRIPTION HTTPSINSTACARCAUS
10/31/2017  Oct 2017    food    8.45    Point Of Sale Withdrawal 22607113998 CLARK CENTER-BIO-X CAF STANFORD     CAUS
10/31/2017  Oct 2017    food    4.00    Point Of Sale Withdrawal 33426639883 COUPA CAFE Y2E2        STANFORD     CAUS
10/31/2017  Oct 2017    uber    4.52    Point Of Sale Withdrawal 42029000200217 UBER TRIP QZ7W5 HELP.UB800-5928996  CAUS
10/30/2017  Oct 2017    food    5.85    Point Of Sale Withdrawal 44519950998 UBER   TRIP HOOMP      HELP.UBER.COMCAUS
10/30/2017  Oct 2017    uber    23.20   Point Of Sale Withdrawal 33428390882 COUPA CAFE LYTTON      PALO ALTO    CAUS
10/30/2017  Oct 2017    food    7.52    Point Of Sale Withdrawal 34530890882 PANDA EXPRESS #2035    STANFORD     CAUS

Answer 1

如果是excel文件，您可以使用一个R包将该文件读入Excel。我使用您的示例数据并使用openxlsx打开它，它不需要java，它按需要读取details列。守则将是：

read.xlsx("file", detectDates = T)

Answer 2

我不是这方面的专家，但我找到了一种可行的方法。它使用readLines作为一个字符串从文件中读取每一行，然后拆分前五个单词( date、month、year、type和expenditure列)，并将行的其余部分作为最后一列details使用。

raw_txt <- readLines("123.txt")

splitted <- lapply(strsplit(raw_txt[-1], " +"), function(x){
   one_to_five <- x[1:5]
   six         <- paste0(x[5:length(x)], collapse=" ")
   c(one_to_five, six)
})

# Bind together the elements in "splitted":
df <- do.call(rbind, splitted)

# Give the columns the right names:
colnames(df) <- strsplit(raw_txt[1], " +")[[1]]

结果：

      date         month year   type        expenditure details                                                                               
 [1,] "10/31/2017" "Oct" "2017" "food"      "10.89"     "10.89 Point Of Sale Withdrawal 17203473997 TRESIDDER U2 STANFORD CAUS"               
 [2,] "10/31/2017" "Oct" "2017" "uber"      "4.80"      "4.80 Point Of Sale Withdrawal 44519795098 UBER TRIP F73MU HELP.UBER.COMCAUS"         
 [3,] "10/31/2017" "Oct" "2017" "instacart" "99.00"     "99.00 Point Of Sale Withdrawal 44534891998 INSTACART SUBSCRIPTION HTTPSINSTACARCAUS" 
 [4,] "10/31/2017" "Oct" "2017" "food"      "8.45"      "8.45 Point Of Sale Withdrawal 22607113998 CLARK CENTER-BIO-X CAF STANFORD CAUS"      
 [5,] "10/31/2017" "Oct" "2017" "food"      "4.00"      "4.00 Point Of Sale Withdrawal 33426639883 COUPA CAFE Y2E2 STANFORD CAUS"             
 [6,] "10/31/2017" "Oct" "2017" "uber"      "4.52"      "4.52 Point Of Sale Withdrawal 42029000200217 UBER TRIP QZ7W5 HELP.UB800-5928996 CAUS"
 [7,] "10/30/2017" "Oct" "2017" "food"      "5.85"      "5.85 Point Of Sale Withdrawal 44519950998 UBER TRIP HOOMP HELP.UBER.COMCAUS"         
 [8,] "10/30/2017" "Oct" "2017" "uber"      "23.20"     "23.20 Point Of Sale Withdrawal 33428390882 COUPA CAFE LYTTON PALO ALTO CAUS"         
 [9,] "10/30/2017" "Oct" "2017" "food"      "7.52"      "7.52 Point Of Sale Withdrawal 34530890882 PANDA EXPRESS #2035 STANFORD CAUS"