R 效率挑战：拆分长字符向量

Question

问题是如何有效地解析这种格式的数据：

lineup = " C James McCann P Robbie Ray P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"

进入一个两列的数据框；一个用于位置，一个用于玩家。

名字是棒球运动员，每个名字前面都有他们的位置，这是按某种顺序精确的集合 {C, P, P, OF, 3B, SS, 1B, OF, 2B, OF}。也就是说，那些确切的位置总是会出现。

例如，“C James McCann”应该变成

data.frame(position = "C", player = "James McCann")

实际上，我有数十万个这样的字符串，我想有效地解析它们。这是我的低效解决方案：

data.frame(
    position = str_match_all(lineup, "\\s[0-9A-Z]{1,2}\\s")[[1]] %>% as.character() %>% str_trim(),
    player = str_split(lineup, "\\s[0-9A-Z]{1,2}\\s")[[1]][-1],
    stringsAsFactors = F
)

这个 tidyverse 解决方案很简单，但我怀疑我可以做得更好。有人有什么想法吗？

Answer 1

您可以使用 stringi::stri_match_all_regex: 制作一个模式，让您同时获得位置和球员姓名：

stri_match_all_regex(lineup, 
                   patt= "(C|P|OF|3B|SS|1B|OF|2B) ([A-Z][A-Za-z]+ [A-Z][A-Za-z]+)" )
[[1]]
      [,1]                   [,2] [,3]               
 [1,] "C James McCann"       "C"  "James McCann"     
 [2,] "P Robbie Ray"         "P"  "Robbie Ray"       
 [3,] "P Rafael Montero"     "P"  "Rafael Montero"   
 [4,] "OF Giancarlo Stanton" "OF" "Giancarlo Stanton"
 [5,] "3B Derek Dietrich"    "3B" "Derek Dietrich"   
 [6,] "SS Miguel Rojas"      "SS" "Miguel Rojas"     
 [7,] "1B Tommy Joseph"      "1B" "Tommy Joseph"     
 [8,] "OF Marcell Ozuna"     "OF" "Marcell Ozuna"    
 [9,] "OF Christian Yelich"  "OF" "Christian Yelich" 

我的模式比你的更严格，因为我将空格之间的一两个字母限制为仅匹配棒球位置的组合。您将获得一个列表，其中包含每行的矩阵项目。您可能应该发布一个更复杂的示例来支持需要的进一步处理。您将需要使用类似于lapply( results, function(x){ as.data.frame(x[ , -1]) })

的内容

lapply( results, function(x){ as.data.frame(x[ , -1]) })
[[1]]
  V1                V2
1  C      James McCann
2  P        Robbie Ray
3  P    Rafael Montero
4 OF Giancarlo Stanton
5 3B    Derek Dietrich
6 SS      Miguel Rojas
7 1B      Tommy Joseph
8 OF     Marcell Ozuna
9 OF  Christian Yelich

如果要使用连字符名称或中间名或首字母，则模式可能需要更复杂。

Answer 2

这是一个解决方案，它将lineup 转换为 csv 文件格式的字符串，然后由fread() 读取：

library(magrittr)  # piping used to improve readability
lineup %>% 
  stringr::str_replace_all("\\s(C|P|OF|SS|1B|2B|3B)\\s", "\\\n\\1;") %>% 
  data.table::fread(header = FALSE, col.names = c("position", "player"))

    position            player
 1:        C      James McCann
 2:        P        Robbie Ray
 3:        P    Rafael Montero
 4:       OF Giancarlo Stanton
 5:       3B    Derek Dietrich
 6:       SS      Miguel Rojas
 7:       1B      Tommy Joseph
 8:       OF     Marcell Ozuna
 9:       2B   C?sar Hern?ndez
10:       OF  Christian Yelich

“诀窍”是在位置字符前放置一个换行符，在其后放置一个列分隔符，例如，" C " 变为 "\nC;"。

lineup %>% 
  stringr::str_replace_all("\\s(C|P|OF|SS|1B|2B|3B)\\s", "\\\n\\1;")

返回

[1] "\nC;James McCann\nP;Robbie Ray\nP;Rafael Montero\nOF;Giancarlo  Stanton\n3B;Derek Dietrich\nSS;Miguel Rojas\n1B;Tommy Joseph\nOF;Marcell Ozuna\n2B;C?sar Hern?ndez\nOF;Christian Yelich"

这种方法不会对名称做出很多假设。它甚至可以使用 James P. McCann 或 Robbie Ray, Jr 这样的名称。

lineup2 %>% 
  stringr::str_replace_all("\\s(C|P|OF|SS|1B|2B|3B)\\s", "\\\n\\1;") %>% 
  data.table::fread(header = FALSE, col.names = c("position", "player"))

    position            player
 1:        C   James P. McCann
 2:        P    Robbie Ray, Jr
 3:        P  Rafael D Montero
 4:       OF Giancarlo Stanton
 5:       3B    Derek Dietrich
 6:       SS      Miguel Rojas
 7:       1B      Tommy Joseph
 8:       OF     Marcell Ozuna
 9:       2B   C?sar Hern?ndez
10:       OF  Christian Yelich

必须满足三个先决条件：

1. 名称部分不得包含任何也用作位置指示符的首字母，例如，首字母 C 和 P 必须用点完成以避免混淆。
2. 列分隔符; 不得在lineup 的其他地方使用。
3. 字符串必须以空格开头。

条件 3 可以通过改进的正则表达式进行挥动，并且可以检查条件 2：

lineup3 %T>% 
  {stopifnot(!stringr::str_detect(., ";"))} %>% 
  stringr::str_replace_all("(^\\s?|\\s)(C|P|OF|SS|1B|2B|3B)\\s", "\\\n\\2;") %>% 
  data.table::fread(header = FALSE, col.names = c("position", "player"))

    position            player
 1:        C   James P. McCann
 2:        P    Robbie Ray, Jr
 3:        P    Rafael Montero
 4:       OF Giancarlo Stanton
 5:       3B    Derek Dietrich
 6:       SS      Miguel Rojas
 7:       1B      Tommy Joseph
 8:       OF     Marcell Ozuna
 9:       2B   C?sar Hern?ndez
10:       OF  Christian Yelich

数据

# original
lineup = " C James McCann P Robbie Ray P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"

# other use cases
lineup1 = "C James McCann P Robbie Ray P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"
lineup2 = " C James P. McCann P Robbie Ray, Jr P Rafael D Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"
lineup2a = " C James P. McCann P Robbie Ray P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"
lineup2b = " C James McCann P Robbie Ray, Jr P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"
lineup3 = "C James P. McCann P Robbie Ray, Jr P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"
lineup4 = " C James P. McCann P Robbie Ray; Jr P Rafael Montero OF Giancarlo Stanton 3B Derek Dietrich SS Miguel Rojas 1B Tommy Joseph OF Marcell Ozuna 2B C?sar Hern?ndez OF Christian Yelich"

Answer 3

这是一个stringr::str_split 选项，使用积极的后视和前瞻

pos <- c("C", "P", "P", "OF", "3B", "SS", "1B", "OF", "2B", "OF")
pat <- sprintf("(%s)", paste(pos, collapse = "|"))

library(stringr)
matrix(unlist(str_split(trimws(lineup), sprintf(
    "((?<=(%s))\\s|\\s(?=(%s)))", pat, pat))), ncol = 2, byrow = T)
#    [,1] [,2]
#[1,] "C"  "James McCann"
#[2,] "P"  "Robbie Ray"
#[3,] "P"  "Rafael Montero"
#[4,] "OF" "Giancarlo Stanton"
#[5,] "3B" "Derek Dietrich"
#[6,] "SS" "Miguel Rojas"
#[7,] "1B" "Tommy Joseph"
#[8,] "OF" "Marcell Ozuna"
#[9,] "2B" "C?sar Hern?ndez"
#[10,] "OF" "Christian Yelich"

我不知道这在多大程度上涵盖了任何边缘情况。一个更复杂和有代表性的示例字符串将有助于测试。