根据与其他列匹配的部分字符串在数据框中创建新列

I have a dataframe with 2 columns GL and GLDESC and want to add a 3rd column called KIND based on some data that is inside of column GLDESC.

我有一个包含2列GL和GLDESC的数据框，并希望根据GLDESC列中的一些数据添加名为KIND的第3列。

The dataframe is as follows:

数据框如下：

      GL                             GLDESC
1 515100         Payroll-Indir Salary Labor
2 515900 Payroll-Indir Compensated Absences
3 532300                           Bulk Gas
4 539991                     Area Charge In
5 551000        Repairs & Maint-Spare Parts
6 551100                 Supplies-Operating
7 551300                        Consumables

For each row of the data table:

对于数据表的每一行：

If GLDESC contains the word Payroll anywhere in the string then I want KIND to be Payroll
如果GLDESC在字符串中的任何地方包含单词Payroll，那么我希望KIND为Payroll
If GLDESC contains the word Gas anywhere in the string then I want KIND to be Materials
如果GLDESC在字符串中的任何地方包含单词Gas，那么我希望KIND为Materials
In all other cases I want KIND to be Other
在所有其他情况下，我希望KIND是其他

I looked for similar examples on * but could not find any, also looked in R for dummies on switch, grep, apply and regular expressions to try and match only part of the GLDESC column and then fill the KIND column with the kind of account but was unable to make it work.

我在*上找了类似的例子，但是找不到任何东西，也在R上查看了对于switch，grep，apply和正则表达式的假人来尝试匹配GLDESC列的一部分，然后用这种帐户填写KIND列但是无法使它工作。

1 个解决方案

#1

Since you have only two conditions, you can use a nested ifelse:

由于您只有两个条件，因此可以使用嵌套的ifelse：

#random data; it wasn't easy to copy-paste yours  
DF <- data.frame(GL = sample(10), GLDESC = paste(sample(letters, 10), 
  c("gas", "payroll12", "GaSer", "asdf", "qweaa", "PayROll-12", 
     "asdfg", "GAS--2", "fghfgh", "qweee"), sample(letters, 10), sep = " "))

DF$KIND <- ifelse(grepl("gas", DF$GLDESC, ignore.case = T), "Materials", 
         ifelse(grepl("payroll", DF$GLDESC, ignore.case = T), "Payroll", "Other"))

DF
#   GL         GLDESC      KIND
#1   8        e gas l Materials
#2   1  c payroll12 y   Payroll
#3  10      m GaSer v Materials
#4   6       t asdf n     Other
#5   2      w qweaa t     Other
#6   4 r PayROll-12 q   Payroll
#7   9      n asdfg a     Other
#8   5     d GAS--2 w Materials
#9   7     s fghfgh e     Other
#10  3      g qweee k     Other

EDIT 10/3/2016 (..after receiving more attention than expected)

编辑2016年10月3日（之后受到的关注超出预期）

A possible solution to deal with more patterns could be to iterate over all patterns and, whenever there is match, progressively reduce the amount of comparisons:

处理更多模式的可能解决方案可能是迭代所有模式，并且只要匹配，就逐渐减少比较量：

ff = function(x, patterns, replacements = patterns, fill = NA, ...)
{
    stopifnot(length(patterns) == length(replacements))

    ans = rep_len(as.character(fill), length(x))    
    empty = seq_along(x)

    for(i in seq_along(patterns)) {
        greps = grepl(patterns[[i]], x[empty], ...)
        ans[empty[greps]] = replacements[[i]]  
        empty = empty[!greps]
    }

    return(ans)
}

ff(DF$GLDESC, c("gas", "payroll"), c("Materials", "Payroll"), "Other", ignore.case = TRUE)
# [1] "Materials" "Payroll"   "Materials" "Other"     "Other"     "Payroll"   "Other"     "Materials" "Other"     "Other"

ff(c("pat1a pat2", "pat1a pat1b", "pat3", "pat4"), 
   c("pat1a|pat1b", "pat2", "pat3"), 
   c("1", "2", "3"), fill = "empty")
#[1] "1"     "1"     "3"     "empty"

ff(c("pat1a pat2", "pat1a pat1b", "pat3", "pat4"), 
   c("pat2", "pat1a|pat1b", "pat3"), 
   c("2", "1", "3"), fill = "empty")
#[1] "2"     "1"     "3"     "empty"

#1