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将 data.frame 的列名增加 1

[英]increment colnames of a data.frame by 1

有一个带有 colnames 的 data.frame

nam <- c("a", paste0("a_", seq(12)))
"a" "a_1" "a_2" "a_3" "a_4" "a_5" "a_6" "a_7" "a_8" "a_9" "a_10" "a_11" "a_12"

如何将带有数字的名称的数字增加 1?

预期的结果是

"a" "a_2" "a_3" "a_4" "a_5" "a_6" "a_7" "a_8" "a_9" "a_10" "a_11" "a_12" "a_13"

到目前为止,我的解决方案看起来非常复杂......有没有比这更简单的方法

increment_names <- function(nam){
  where <- regexpr("\\d", nam)
  ind <- which(where > 0)
  increment <- as.numeric(substring(nam[ind], where[ind])) + 1
  substring(nam[ind], where[ind]) <- as.character(increment)
  nam
}

> increment_names(nam)
 [1] "a" "a_2" "a_3" "a_4" "a_5" "a_6" "a_7" "a_8" "a_9" "a_10" "a_11" "a_12" "a_13"

基本regmatches解决方案:

r <- regexpr("\\d+", nam)
regmatches(nam, r) <- as.numeric(regmatches(nam, r)) + 1
nam
# [1] "a"    "a_2"  "a_3"  "a_4"  "a_5"  "a_6"  "a_7"  "a_8"  ...

只要您的模式是“nonnumbers_numbers”,就会这样做:

nums <- as.numeric(gsub("[^0-9]", "", nam))
nam[!is.na(nums)] <- paste0(gsub("[0-9]", "", nam), nums + 1)[!is.na(nums)]

产生:

 [1] "a"    "a_2"  "a_3"  "a_4"  "a_5"  "a_6"  "a_7"  "a_8"  "a_9"  "a_10" "a_11" "a_12"
 [13] "a_13"

使用gsubfn包,你可以做一些简单的事情

library(gsubfn) 
gsubfn("\\d+", function(x) as.numeric(x) + 1, nam)
## [1] "a"    "a_2"  "a_3"  "a_4"  "a_5"  "a_6"  "a_7"  "a_8"  "a_9"  "a_10" "a_11" "a_12" "a_13"

这适用于任何模式,并且您不需要假设上面提到的“ nonnumbers_numbers ”模式,例如

(nam <- c("a", paste0(seq(12), "_a")))
## [1] "a"    "1_a"  "2_a"  "3_a"  "4_a"  "5_a"  "6_a"  "7_a"  "8_a"  "9_a"  "10_a" "11_a" "12_a"
gsubfn("\\d+", function(x) as.numeric(x) + 1, nam)
## [1] "a"    "2_a"  "3_a"  "4_a"  "5_a"  "6_a"  "7_a"  "8_a"  "9_a"  "10_a" "11_a" "12_a" "13_a"

您可以尝试使用“ore”包,您的替换可以是函数,如下所示:

nam <- c("a", paste0("a_", seq(12)))
nam
library(ore)
ore.subst("-?\\d+", function(x) as.numeric(x) + 1, nam, all = TRUE)
#  [1] "a"    "a_2"  "a_3"  "a_4"  "a_5"  "a_6"  "a_7"  "a_8"  "a_9" 
# [10] "a_10" "a_11" "a_12" "a_13"

这与“gsubfn”包的功能相似,但(至少在这种情况下)效率更高。 以下是一些基准:

library(stringi)
set.seed(1)
nam <- stri_rand_strings(10000, 5, pattern = "[A-J0-9]")

f_ORE <- function(invec = nam) {
  ore.subst("-?\\d+", function(x) as.numeric(x) + 1, invec, all = TRUE)
} 

f_GSUBFN <- function(invec = nam) {
  gsubfn("\\d+", function(x) as.numeric(x) + 1, invec)
}

f_BASE <- function(invec = nam) {
  r <- regexpr("\\d+", invec)
  regmatches(invec, r) <- as.numeric(regmatches(invec, r))+1
  invec
}

system.time(f_GSUBFN())
#    user  system elapsed 
#    5.48    0.01    5.50 

library(microbenchmark)
microbenchmark(f_BASE(), f_ORE())
# Unit: milliseconds
#      expr       min        lq      mean    median        uq      max neval
#  f_BASE() 141.79743 149.58914 161.49041 152.81038 162.10550 357.6483   100
#   f_ORE()  57.35309  59.58433  65.84678  60.92218  68.40062 116.7714   100

请注意,虽然“ore”方法和“gsubfn”方法区​​域相同,但它们似乎与基本 R 方法略有不同。

考虑:

> identical(f_ORE(), f_GSUBFN())
[1] TRUE

## Edge case...
> nam[988]
[1] "0G019"
> f_ORE()[988]     ## 019 becomes 20 (without the leading zero)
[1] "1G20"
> f_GSUBFN()[988]  ## Same
[1] "1G20"
> f_BASE()[988]    ## This seems off...
[1] "1G019"

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