r-根据一个固定的文本将单列数据帧转换为带有行的数据帧

Question

Update 1

Linking the actual dataset since the solutions given for the example data are not working out for me.

Link: https://app.box.com/s/65j1enr13pi51i44mfrymccklw1artot

Please note that LOT is the end of the row marker.

--

I've data frame like the following (single column):

D
2
f
h
k
END_ROW_WORD
k
1
2
END_ROW_WORD
e
g
j
2
k
END_ROW_WORD

I'd like to convert it into following format:

As you can see there is a specific word (END_ROW_WORD) that marks the end of the row.

Answer 1

Here is a similar approach to Alejandro's, but using split instead of a for loop:

colstarts <- diff(c(0, which(df == "END_ROW_WORD")))
rows <- split(df[[1]], rep(1:length(colstarts), colstarts))
rows <- lapply(rows, `length<-`, max(lengths(rows)))
as.data.frame(do.call(rbind, rows))

Answer 2

A solution without for -loops, but with stringr

library(stringr)
new_text <- str_c(df$V1, collapse = " ")
new_text <- str_replace_all(new_text, "END_ROW_WORD", "END_ROW_WORD\n")
read.table(text = new_text, fill = T)

#   V1 V2 V3           V4 V5           V6
# 1  D  2  f            h  k END_ROW_WORD
# 2  k  1  2 END_ROW_WORD                
# 3  e  g  j            2  k END_ROW_WORD

Data

df <- 
  structure(list(V1 = structure(c(3L, 2L, 6L, 8L, 10L, 5L, 10L, 1L, 2L, 5L, 4L, 7L, 9L, 2L, 10L, 5L),
                                .Label = c("1", "2", "D", "e", "END_ROW_WORD", "f", "g", "h", "j", "k"),
                                class = "factor")),
            .Names = "V1", class = "data.frame", row.names = c(NA, -16L))

Answer 3

This might not be the best way to do it but it works

pos_help = which(grepl("END_ROW_WORD",data))

d = list()
for(i in 1:length(pos_help)){
  if(i == 1){
    d[[i]] = data[1:pos_help[1]]
  } else {
    d[[i]] = data[(pos_help[i-1]+1):pos_help[i]]
  }
}
dataFrame = do.call(rbind,lapply(d, "length<-", max(lengths(d))))

Answer 4

This first puts a newline character, "\\n" , after every "END_ROW_WORD" marker, then pastes the result into a long character string.
Then, it uses read.table to read the data in from a text connection.

end <- "END_ROW_WORD"

inx <- c(0, grep(end, dat[[1]]))
s <- NULL
for(i in seq_along(inx)[-1]){
    s <- c(s, dat[[1]][(inx[(i - 1)] + 1):inx[i]], "\n")
}

con <- textConnection(paste(s, collapse = " "))
result <- read.table(con, fill = TRUE)
close(con)
result
#  V1 V2 V3           V4 V5           V6
#1  D  2  f            h  k END_ROW_WORD
#2  k  1  2 END_ROW_WORD                
#3  e  g  j            2  k END_ROW_WORD

DATA.

dat <-
structure(list(V1 = c("D", "2", "f", "h", "k", "END_ROW_WORD", 
"k", "1", "2", "END_ROW_WORD", "e", "g", "j", "2", "k", "END_ROW_WORD"
)), .Names = "V1", class = "data.frame", row.names = c(NA, -16L
))

EDIT.

After the question's edit by the OP, I revised the code to see if that file can be properly read into a data.frame . The main difficulty is that the file has many non printable characters, and read.table was having trouble getting to the end of the file.

Credits to the solution of this problem go to the accepted answer in read.csv warning 'EOF within quoted string' prevents complete reading of file . I upvoted both the question and that answer.

Credits must also be given to @kath, in the answer the idea of using a string replace to put newline characters as EOL markers is much better than my ugly for loop above. Unlike kath, I use base R only, I don't find it necessary to load an external package.

Now the revised code.

# Use this first pattern if AUCTION also marks the end of a row
#pattern <- "(^LOT|^AUCTION)"
pattern <- "(^LOT)"

dat <- readLines("data_.csv")
s <- gsub("[[:cntrl:]]", "", dat)
s <- sub(pattern, "\\1\n", s)

con <- textConnection(paste(s, collapse = "\t"))
result <- read.table(con, sep = "\t", fill = TRUE, quote = "", row.names = NULL)
close(con)

head(result)
tail(result)
str(result)

I thought that there would be some empty rows, so I checked it with the following code.

#
# See if there are any empty rows
#
empty <- apply(result, 1, function(x) nchar(trimws(paste0(x, collapse = ""))) == 0)
sum(empty)
#[1] 0

Answer 5

without loop, but using map and split.... (because why not :p )

library(tidyverse)
df <- tibble(x=c(
  "D",
  "2",
  "f",
  "h",
  "k",
  "END_ROW_WORD",
  "k",
  "1",
  "2",
  "END_ROW_WORD",
  "e",
  "g",
  "j",
  "2",
  "k",
  "END_ROW_WORD"
)  

)
split(df,cut(1:16,breaks=c(0,which(df == "END_ROW_WORD")))) %>%
  map_dfc(~rbind(.x,tibble(x=rep(NA,(6-nrow(.x)))))) %>% 
  t() %>% as.data.frame()