您可以使用包 RJSONIO 来解析列值,例如:
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$jsoncol, FUN=function(x){ as.list(fromJSON(x))}))
> res
title body url
A X http://url1.x
B Y http://url2.y
C Z http://url3.z
注意:
上面的代码假定所有单元格仅包含标题、正文和 url。如果 json 单元格中可以有其他属性,请改用此代码:
vals <- lapply(df$jsoncol,fromJSON)
res <- do.call(rbind, lapply(vals,FUN=function(v){ data.frame(title=v['title'],
body =v['body'],
url =v['url']) }))
编辑(根据评论):
我已使用以下代码阅读了该文件:
df <- read.table(file="c:\\sample.tsv",
header=T, sep="\t", colClasses="character")
然后使用此代码进行解析:
# 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)) }))