CODEWITHSUNDEEP
rtextdata-conversion
HSJ
HSJ

Reputation: 841

Converting text file in special format into data frame

I am a R user and I have a plain text file which looks like this:

t # 0 * 3
v 0 4
v 1 7
e 0 1 1
x 0 1 2

t # 1 * 2
v 0 4
v 1 7
v 2 10
e 0 1 1
e 1 2 1
x 0 1

t # 2 * 2
v 0 7
v 1 10
e 0 1 1
x 0 2

I need to convert it into three data frames which looks like this:

# First data frame    
object id number
0 0 4
0 1 7
1 0 4
1 1 7
1 2 10
2 0 7
2 1 10

# Second data frame    
object from to number
0 0 1 1
1 0 1 1
1 1 2 1
2 0 1 1

# Third data frame
x t0 t1 t2
0 1 1 1
1 1 1 0
2 1 0 1

Correspondences are illustrated below: enter image description here

I appreciate your suggestions to read the original text file and convert it into desired format. I could read text file using some functions such as readLines("sample.txt") and scan("sample.txt", what=character(), sep="\n", blank.lines.skip=T), however I have no knowledge to deal with these text data into data frames.

Upvotes: 0

Views: 78

Answers (2)

HSJ
HSJ

Reputation: 841

Somehow I could make it using the following inefficient scripts.

#### Load text file
result <- scan("result.txt", what=character(), sep="\n", blank.lines.skip=T)

## Line number of subgraphs
nsub <- grep("t", result)

#### Initial data frame
## Node and edge
node.s <- data.frame(matrix(ncol=3, nrow=0, dimnames=list(NULL, c("object", "id", "func"))))
edge.s <- data.frame(matrix(ncol=4, nrow=0, dimnames=list(NULL, c("object", "from", "to", "connect"))))

## Equivalence table of original graphs and subgraphs
eq.s.1 <- data.frame(t=c(0:(nrow(g)-1)))
eq.s.2 <- data.frame(matrix(ncol=length(nsub), nrow=nrow(g), dimnames=list(NULL, c(paste0("sub",c(0:(length(nsub)-1)))))))
eq.s <- cbind(eq.s.1, eq.s.2)

#### Loop to update data frames
for (i in 1:length(result)) {

  ## Store t number for other data frames
  if (grepl("t", result[i])==1) {  
    t <- word(result[i],3)
  }
  
  #### Update node list (node.s)
  if (grepl("v", result[i])==1) {
    ## Extract node
    tent.v <- data.frame(object=t, id=word(result[i],2), fun=word(result[i],3))
    ## Append
    node.s <- rbind(node.s, tent.v)
  }
  
  #### Update edge list (edge.s)
  if (grepl("e", result[i])==1) {
    ## Extract edge
    tent.e <- data.frame(object=t, from=word(result[i],2), to=word(result[i],3), connect=word(result[i],4))
    ## Append
    edge.s <- rbind(edge.s, tent.e)
  }
  
  #### Update equivalent table (eq.s)
  if (grepl("x", result[i])==1) {
    ## Equivalence between original graphs and subgraphs
    tent.e <- data.frame(t=as.integer(unlist(strsplit(result[i], " "))[-1]), a=1)
    ## Update field name
    names(tent.e) <- c("t",paste0("sub",t))
    ## Overwrite join
    eq.s <- merge_dfs_overwrite_col(eq.s, tent.e, cols=names(tent.e)[2], bycol="t")
  }
}

Upvotes: 0

Onyambu
Onyambu

Reputation: 79348

You could do the following:

dat <- readLines('file.txt')
f <- cumsum(grepl('^t', dat))
dat1 <- paste(dat, f - 1)
df1 <- read.table(text = grep('^v', dat1, value = TRUE))[c(4,2:3)]
df1

  V4 V2 V3
1  0  0  4
2  0  1  7
3  1  0  4
4  1  1  7
5  1  2 10
6  2  0  7
7  2  1 10

df2 <- read.table(text = grep('^e', dat1, value = TRUE))[c(5,2:4)]
df2
  V5 V2 V3 V4
1  0  0  1  1
2  1  0  1  1
3  1  1  2  1
4  2  0  1  1

x <- read.table(text = grep('^x', dat, value = TRUE), fill=T)[-1]
df3 <- data.frame(cbind(x=0:2, apply(x, 1, \(y) 0:2 %in% y)))
df3

  x V2 V3 V4
1 0  1  1  1
2 1  1  1  0
3 2  1  0  1

Upvotes: 1

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