Parsing BLS JSON with R - json

Question

I would like to run some canned reports with Knitr in R relying on a number of third party resources, some offered as text files, and some offered through public APIs.
I am not particulary well versed parsing JSON files, however, and quickly lose my bearings when they get mildly complicated (which I don't particularly think my example is, anyway, but still.)
Here's the call:
library(rjson)
addr = 'http://api.bls.gov/publicAPI/v1/timeseries/data/ENU0607510010'
json_data <- fromJSON(file=addr, method='C')
Here's what it looks like--any way to stuff that into a dataframe for further (automatic) melting and plotting?
> str(json_data)[1:100]
List of 4
$ status : chr "REQUEST_SUCCEEDED"
$ responseTime: num 14
$ message : list()
$ Results :List of 1
..$ series:List of 1
.. ..$ :List of 2
.. .. ..$ seriesID: chr "ENU0607510010"
.. .. ..$ data :List of 35
.. .. .. ..$ :List of 5
.. .. .. .. ..$ year : chr "2013"
.. .. .. .. ..$ period : chr "M09"
.. .. .. .. ..$ periodName: chr "September"
.. .. .. .. ..$ value : chr "615958"
.. .. .. .. ..$ footnotes :List of 1
.. .. .. .. .. ..$ :List of 2
.. .. .. .. .. .. ..$ code: chr "P"
.. .. .. .. .. .. ..$ text: chr " Preliminary."
.. .. .. ..$ :List of 5
.. .. .. .. ..$ year : chr "2013"
.. .. .. .. ..$ period : chr "M08"
.. .. .. .. ..$ periodName: chr "August"
.. .. .. .. ..$ value : chr "615326"
.. .. .. .. ..$ footnotes :List of 1
.. .. .. .. .. ..$ :List of 2
.. .. .. .. .. .. ..$ code: chr "P"
.. .. .. .. .. .. ..$ text: chr " Preliminary."
.. .. .. ..$ :List of 5
.. .. .. .. ..$ year : chr "2013"
.. .. .. .. ..$ period : chr "M07"
.. .. .. .. ..$ periodName: chr "July"
.. .. .. .. ..$ value : chr "611071"
.. .. .. .. ..$ footnotes :List of 1
.. .. .. .. .. ..$ :List of 2
.. .. .. .. .. .. ..$ code: chr "P"
.. .. .. .. .. .. ..$ text: chr " Preliminary."
.. .. .. ..$ :List of 5

Answer 1

Give this a go. I need to move from RJSONIO to jsonlite at some point, but this will get you your data. It's all a matter of figuring out the structure so you can do the sapply's. I added the bar chart because I had it in a gist example for BLS data already.
library(RCurl)
library(RJSONIO)
library(ggplot2)
bls.content <- getURLContent("http://api.bls.gov/publicAPI/v1/timeseries/data/ENU0607510010")
bls.json <- fromJSON(bls.content, simplify=TRUE)
tmp <-bls.json$Results[[1]][[1]]
bls.df <- data.frame(year=sapply(tmp$data,"[[","year"),
period=sapply(tmp$data,"[[","period"),
periodName=sapply(tmp$data,"[[","periodName"),
value=as.numeric(sapply(tmp$data,"[[","value")),
stringsAsFactors=FALSE)
head(bls.df, n=10)
## year period periodName value
## 1 2013 M09 September 615958
## 2 2013 M08 August 615326
## 3 2013 M07 July 611071
## 4 2013 M06 June 610893
## 5 2013 M05 May 610750
## 6 2013 M04 April 607797
## 7 2013 M03 March 603286
## 8 2013 M02 February 600868
## 9 2013 M01 January 593770
## 10 2012 M13 Annual 586538
gg <- ggplot(data=bls.df, aes(x=year, y=value, group=period))
gg <- gg + geom_bar(stat="identity", position="dodge", aes(fill=period))
gg