Разбор текстового файла в R с различными разделителями

Question

У меня есть текстовый файл в этом формате, а ужасающем HTML:

A<b>Metabolism</b> 
B 
B <b>Overview</b> 
C 01200 Carbon metabolism [PATH:bpe01200] 
D  BP3142 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D  BP1971 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D  BP1519 fba; fructose-1,6-bisphosphate aldolase K01624 FBA; fructose-bisphosphate aldolase, class II [EC:4.1.2.13] 
D  BP0801 tpiA; triosephosphate isomerase K01803 TPI; triosephosphate isomerase (TIM) [EC:5.3.1.1] 
D  BP1000 gap; glyceraldehyde-3-phosphate dehydrogenase K00134 GAPDH; glyceraldehyde 3-phosphate dehydrogenase [EC:1.2.1.12] 

Я хотел бы разобрать этот файл на столбцы в R.

таких as:

A,Metabolism 
B, 
B,Overview 
C,01200,Carbon metabolism,Path,bpe01200 
D,BP3142,Pgi,glucose-6-phosphate isomerase,GPI,glucose-6-phosphate isomerase,[EC:5.3.1.9] 
... 
D,BP1000,gap,glyceraldehyde-3-phosphate dehydrogenase,K00134,GAPDH,glyceraldehyde 3-phosphate dehydrogenase,[EC:1.2.1.12] 

Проблема заключается в том, что разделитель изменяется в каждой части линии. кажется, следовать этому образцу

например

D  BP1971 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
^Tab  ^space^Semi colon     ^tab  ^space^semi colon 

я могу думать о не так умном способе сделать it.By разбор 1 разделитель в то время. Но есть ли у кого-нибудь умные решения? или знаете инструмент, который может хорошо это интерпретировать?

Я бы очень признателен за помощь :)

Благодарности

Answer 1

library(stringr) 
library(purrr) 
file <- "A<b>Metabolism</b> 
B 
B <b>Overview</b> 
C\t01200 Carbon metabolism [PATH:bpe01200] 
D\tBP3142 pgi; glucose-6-phosphate isomerase\tK01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D\tBP1971 pgi; glucose-6-phosphate isomerase\tK01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D\tBP1519 fba; fructose-1,6-bisphosphate aldolase\tK01624 FBA; fructose-bisphosphate aldolase, class II [EC:4.1.2.13] 
D\tBP0801 tpiA; triosephosphate isomerase\tK01803 TPI; triosephosphate isomerase (TIM) [EC:5.3.1.1] 
D\tBP1000 gap; glyceraldehyde-3-phosphate dehydrogenase\tK00134 GAPDH; glyceraldehyde 3-phosphate dehydrogenase [EC:1.2.1.12] 
This line is to check behavior when parsing fails." 
cat(file) 
data <- readLines(con = textConnection(file)) 
# Pattern to capture "A<b>Metabolism</b>" for instance 
pattern_1 <- "^(\\w+)\\h*<b>\\h*(\\w+)\\h*</b>\\h*$" 
# Pattern to capture "B" for instance 
pattern_2 <- "^(\\w+)$" 
# Pattern to capture "C\t01200 Carbon metabolism [PATH:bpe01200]" for instance 
pattern_3 <- "^(\\w+)\\t+(\\w+)\\s+([^\\[\\t;]*)\\h*(\\[[^\\]]*\\])$" 
# Pattern to capture "D\tBP3142 pgi; glucose-6-phosphate isomerase\tK01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9]" for instance 
pattern_4 <- "^(\\w+)\\t+(\\w+)\\s+(\\w+);\\h*([^\\t]*)\\t+(\\w+)\\s+(\\w+);\\h*([^\\[]*)\\h*(\\[[^\\]]*\\])$" 
# Some more explanations: 
# Parens wrap groups to extract 
# "\\w+" matches words 
# "\\t+", "\\s+" or ";\\h*" are specific separators of OP's original data 
# "([^\\t]*)" matches anything until the next tab separator 
# Convoluted patterns such as "(\\[[^\\]]*\\])" extract whatever is inside brackets 
patterns <- mget(paste0("pattern_", 1:4)) 
# A list of the data parsed 4 times, once for each pattern: 
patterns %>% 
    map(~ { 
    extraction <- str_match(data, .x) 
    cbind(match = !is.na(extraction[, 1]), extraction[, - 1]) 
    }) 
# This is closer to your desired output: a list of [un]parsed rows: 
data %>% 
    map(~ { 
    # Find the first pattern that matches. 0 if none does 
    pattern_index <- detect_index(patterns, grepl, .x, perl = TRUE) 
    # If failed to parse, return original row as length 1 character vector. Else return parsed row as character vector 
    if (pattern_index == 0L) .x else str_match(.x, get(paste0("pattern_", pattern_index)))[- 1] 
    }) 

Руководитель производства выглядит следующим образом:

list(c("A", "Metabolism"), "B", c("B", "Overview"), c("C", "01200", 
"Carbon metabolism ", "[PATH:bpe01200]"), c("D", "BP3142", "pgi", 
"glucose-6-phosphate isomerase", "K01810", "GPI", "glucose-6-phosphate isomerase ", 
"[EC:5.3.1.9]")) 

Answer 2

text <- " 
A<b>Metabolism</b> 
B 
B <b>Overview</b> 
C 01200 Carbon metabolism [PATH:bpe01200] 
D  BP3142 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D  BP1971 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D  BP1519 fba; fructose-1,6-bisphosphate aldolase K01624 FBA; fructose-bisphosphate aldolase, class II [EC:4.1.2.13] 
D  BP0801 tpiA; triosephosphate isomerase K01803 TPI; triosephosphate isomerase (TIM) [EC:5.3.1.1] 
D  BP1000 gap; glyceraldehyde-3-phosphate dehydrogenase K00134 GAPDH; glyceraldehyde 3-phosphate dehydrogenase [EC:1.2.1.12] 
" 
library(stringr) 

# get the header items (beginning with C blank) 
headers <- str_match(text, "C\\s+(.+)\n")[,2] 
header_items <- trimws(str_match(headers, "(\\d+)\\s+([^\\[]+)(.+)")[2:4]) 

# get the detail items (liens beginning with D blank) 
details <- str_match_all(text, "D\\s+(.+)\n")[[1]][,2] 

# parse each item within detail 

# split on ";" and organize into dataframe 
items <- as.data.frame(t(data.frame(
    str_split(details,";\\s") 
)), row.names = 1:length(details), stringsAsFactors = FALSE) 

# parse each part using pattern matches 

# capture() beginning of string^and all characters not whitespace [^\\s]+ 
items$V1A <- str_match(items$V1,"(^[^\\s]+)")[,2] 

# capture() end of string $ and a non-whitespace sequence [^\\s]+ 
items$V1B <- str_match(items$V1,"([^\\s]+)$")[,2] 

# capture() beginning of string exluding two non-whitespace sequences [^\\s]+ at end $ 
items$V2A <- str_match(items$V2,"^(.+)\\s[^\\s]+\\s[^\\s]+$")[,2] 

# capture() non-whitespace sequence [^\\s]+ at end of string $ 
items$V2C <- str_match(items$V2,"([^\\s]+)$")[,2] 

# capture() second to last non-whitespace sequence [^\\s]+ at end of string $ 
items$V2B <- str_match(items$V2,"([^\\s]+)\\s[^\\s]+$")[,2] 

# capture() begining of string^excluding last non-whitespace sequence [^\\s]+ 
items$V3A <- str_match(items$V3,"^(.+)\\s[^\\s]+$")[,2] 

# capture() non-whitespace sequence at end $ 
items$V3B <- str_match(items$V3,"([^\\s]+)$")[,2] 

select & reorder 
items <- items[, c("V1A", "V1B", "V2A", "V2B", "V2C", "V3A", "V3B")] 

элементы

#  V1A V1B          V2A V2B V2C          V3A   V3B 
#1 BP3142 pgi   glucose-6-phosphate isomerase K01810 GPI   glucose-6-phosphate isomerase [EC:5.3.1.9] 
#2 BP1971 pgi   glucose-6-phosphate isomerase K01810 GPI   glucose-6-phosphate isomerase [EC:5.3.1.9] 
#3 BP1519 fba  fructose-1,6-bisphosphate aldolase K01624 FBA fructose-bisphosphate aldolase, class II [EC:4.1.2.13] 
#4 BP0801 tpiA    triosephosphate isomerase K01803 TPI   triosephosphate isomerase (TIM) [EC:5.3.1.1] 
#5 BP1000 gap glyceraldehyde-3-phosphate dehydrogenase K00134 GAPDH glyceraldehyde 3-phosphate dehydrogenase [EC:1.2.1.12] 

Answer 3

И более простой вариант извлечения детали только с использованием тех же строк регулярных выражений в одном матче

text <- " 
A<b>Metabolism</b> 
B 
B <b>Overview</b> 
C 01200 Carbon metabolism [PATH:bpe01200] 
D  BP3142 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D  BP1971 pgi; glucose-6-phosphate isomerase K01810 GPI; glucose-6-phosphate isomerase [EC:5.3.1.9] 
D  BP1519 fba; fructose-1,6-bisphosphate aldolase K01624 FBA; fructose-bisphosphate aldolase, class II [EC:4.1.2.13] 
D  BP0801 tpiA; triosephosphate isomerase K01803 TPI; triosephosphate isomerase (TIM) [EC:5.3.1.1] 
D  BP1000 gap; glyceraldehyde-3-phosphate dehydrogenase K00134 GAPDH; glyceraldehyde 3-phosphate dehydrogenase [EC:1.2.1.12] 
" 

library(stringr) 

# get the detail items (liens beginning with D blank) 
details <- str_match_all(text, "D\\s+(.+)\n")[[1]][,2] 

details 
pattern <- "([^\\s]+)\\s([^\\s]+);(.*)\\s([^\\s]+)\\s([^\\s]+);\\s(.*)\\s([^\\s]+)$" 
trimws(str_match(details, pattern)[,-1]) 

#[,1]  [,2] [,3]          [,4]  [,5] 
#[1,] "BP3142" "pgi" "glucose-6-phosphate isomerase"   "K01810" "GPI" 
#[2,] "BP1971" "pgi" "glucose-6-phosphate isomerase"   "K01810" "GPI" 
#[3,] "BP1519" "fba" "fructose-1,6-bisphosphate aldolase"  "K01624" "FBA" 
#[4,] "BP0801" "tpiA" "triosephosphate isomerase"    "K01803" "TPI" 
#[5,] "BP1000" "gap" "glyceraldehyde-3-phosphate dehydrogenase" "K00134" "GAPDH" 
#    [,6]          [,7]   
#[1,] "glucose-6-phosphate isomerase"   "[EC:5.3.1.9]" 
#[2,] "glucose-6-phosphate isomerase"   "[EC:5.3.1.9]" 
#[3,] "fructose-bisphosphate aldolase, class II" "[EC:4.1.2.13]" 
#[4,] "triosephosphate isomerase (TIM)"   "[EC:5.3.1.1]" 
#[5,] "glyceraldehyde 3-phosphate dehydrogenase" "[EC:1.2.1.12]"