converting a column in json format into a new data frame - json

Question

I have a csv file and one of the column is in json format.
that particular column in json format looks like this:
{"title":" ","body":" ","url":"thedailygreen print this healthy eating eat safe Dirty Dozen Foods page all"}
I have read this file using read.csv in R. Now, how to I create a new data frame from this column which should have field names as title, body and url.

Answer 1

You can use package RJSONIO to parse the column values, e.g. :
library(RJSONIO)
# create an example data.frame with a json column
cell1 <- '{"title":"A","body":"X","url":"http://url1.x"}'
cell2 <- '{"title":"B","body":"Y","url":"http://url2.y"}'
cell3 <- '{"title":"C","body":"Z","url":"http://url3.z"}'
df <- data.frame(jsoncol = c(cell1,cell2,cell3),stringsAsFactors=F)
# parse json and create a data.frame
res <- do.call(rbind.data.frame,
lapply(df$jsoncol, FUN=function(x){ as.list(fromJSON(x))}))
> res
title body url
A X http://url1.x
B Y http://url2.y
C Z http://url3.z
N.B. :
the code above assumes all the cells contains title, body and url only. If there can be other properties in the json cells, use this code instead :
vals <- lapply(df$jsoncol,fromJSON)
res <- do.call(rbind, lapply(vals,FUN=function(v){ data.frame(title=v['title'],
body =v['body'],
url =v['url']) }))
EDIT (as per comment):
I've read the file using the following code :
df <- read.table(file="c:\\sample.tsv",
header=T, sep="\t", colClasses="character")
then parsed using this code :
# define a simple function to turn NULL to NA
naIfnull <- function(x){if(!is.null(x)) x else NA}
vals <- lapply(df$boilerplate,fromJSON)
res <- do.call(rbind,
lapply(vals,FUN=function(v){ v <- as.list(v)
data.frame(title=naIfnull(v$title),
body =naIfnull(v$body),
url =naIfnull(v$url)) }))