Regex 在R-'中处理字符串；Word格式'；列表

除了少数例外，我们可以在Word（.doc）文档中找到物种（尤其是鸟类物种）列表，而且它们的结构形式通常对任何类型的数据分析都是无用的

列表如下所示，包含空格和其他所有内容： 它包括分类学（科）和具有共同学名的物种

数据 像这样的列表是技术报告、地理分布设计、区域保护状况、摘要等的重要信息来源。 这一点对于几乎没有可用或公布的地区尤其重要（上述例子是www.birdsangola.org上安哥拉鸟类名录的一部分）。 如果格式正确，数据将得到更好的使用。数据帧将是对数据进行任何后续分析的良好候选

我想把上面的列表转换成一些有用的东西，提取物种的通用名、学名和分类科。data.frame是一个很好的、自然的候选者。

在运行此代码之前，请将上面的数据复制到剪贴板。 R代码： 摘要（针对941个物种的整个数据集）

库（plyr）
summary.nesp我看不到这个问题，我建议您重新发布这个问题，在答案部分保留问题并移动答案，以提高可读性
1 STRUTHIONIDAE (1)
Common Ostrich Struthio camelus


2 DIOMEDEIDAE (5 – 1 + 1)

++Northern Royal Albatross Diomedea sanfordi

Black-browed Albatross Thalassarche melanophris

Shy Albatross Thalassarche cauta

Grey-headed Albatross Thalassarche chrysostoma

Atlantic Yellow-nosed Albatross Thalassarche chlororhynchos


3 Procellaridae (11 – 1 + 1)

Southern Giant Petrel Macronectes giganteus

Pintado Petrel Daption capense

Great-winged Petrel Pterodroma macroptera

Soft-plumaged Petrel Pterodroma mollis

Antarctic Prion Pachyptila desolata

White-chinned Petrel Procellaria aequinoctialis

++Spectacled Petrel Procellaria conspicillata

Cory's Shearwater Calonectris [diomedea] borealis

Great Shearwater Puffinus gravis

Sooty Shearwater Puffinus griseus

Manx Shearwater Puffinus puffinus


4 HYDROBATIDAE (3)

Wilson's Storm-Petrel Oceanites oceanicus

British Storm-Petrel Hydrobates pelagicus

Leach's Storm-Petrel Oceanodroma leucorhoa

library(stringr)
# Read from clipboard (blank.lines.skip = T)
orig.list <- read.delim2('clipboard', header = F, stringsAsFactors = F)
l.species <- data.frame()
for(i in 1:nrow(orig.list)) {
  tmp.string <- unlist(str_extract_all(orig.list[i, ], "[A-Za-z]+"))
  l.species[i, 1] <- ifelse(length(tmp.string) == 1, tmp.string,
                            paste(tmp.string[1:(length(tmp.string)-2)],
                                  collapse = ' '))
  l.species[i, 2] <- paste(tmp.string[(length(tmp.string) - 1) : length(tmp.string)],
                           collapse = ' ')
  l.species[i, 3]<-ifelse(length(tmp.string) == 1, 1, 0)
}
names(l.species) <- c('common name', 'species', 'is.family')
taxon.family <- toupper(subset(l.species, is.family == 1,
                               select = species)$species)
rows.family <- as.numeric(row.names(subset(l.species, is.family == 1)))
l.species$family <- rep(taxon.family, times = diff(c(rows.family,
                                                     nrow(l.species)+1)))
l.spec.family <- subset(l.species, is.family == 0, select = -is.family) 

> head(l.spec.family)                            
                      common name                     species        family
2                  Common Ostrich            Struthio camelus STRUTHIONIDAE
4        Northern Royal Albatross           Diomedea sanfordi   DIOMEDEIDAE
5          Black browed Albatross    Thalassarche melanophris   DIOMEDEIDAE
6                   Shy Albatross          Thalassarche cauta   DIOMEDEIDAE
7           Grey headed Albatross    Thalassarche chrysostoma   DIOMEDEIDAE
8 Atlantic Yellow nosed Albatross Thalassarche chlororhynchos   DIOMEDEIDAE

library(plyr)
summary.nesp <- ddply(l.spec.family, .(family), summarise,
                      prop_esp = length(family)/nrow(*all.data*)*100)
top.summary.nesp <- head(summary.nesp[order(summary.nesp$prop_esp, decreasing = T),], 6)

> top.summary.nesp
          family prop_esp
79     SYLVIIDAE 8.076514
1   ACCIPITRIDAE 5.419766
48    PASSERIDAE 5.100956
24   ESTRILDIDAE 4.250797
83      TURDIDAE 3.613177
44 NECTARINIIDAE 3.506908