Unable to convert JSON to dataframe - json

Question

I want to convert a json-file into a dataframe in R. With the following code:
link <- 'https://www.dropbox.com/s/ckfn1fpkcix1ccu/bevingenbag.json'
document <- fromJSON(file = link, method = 'C')
bev <- do.call("cbind", document)
i'm getting this:
type features
1 FeatureCollection list(type = "Feature", geometry = list(type = "Point", coordinates = c(6.54800000288927, 52.9920000044505)), properties = list(gid = "1496600", yymmdd = "19861226", lat = "52.992", lon = "6.548", mag = "2.8", depth = "1.0", knmilocatie = "Assen", baglocatie = "Assen", tijd = "74751"))
which is the first row of a matrix. All the other rows have the same structure. I'm interested in the properties = list(gid = "1496600", yymmdd = "19861226", lat = "52.992", lon = "6.548", mag = "2.8", depth = "1.0", knmilocatie = "Assen", baglocatie = "Assen", tijd = "74751") part, which should be converted into a dataframe with the columns gid, yymmdd, lat, lon, mag, depth, knmilocatie, baglocatie, tijd.
I searched for and tryed several solutions but none of them worked. I used the rjson package for this. I also tryed the RJSONIO & jsonlite package, but was unable to extract the desired information.
Anyone an idea how to solve this problem?

Answer 1

Here's a way to obtain the data frame:
library(rjson)
document <- fromJSON(file = "bevingenbag.json", method = 'C')
dat <- do.call(rbind, lapply(document$features,
function(x) data.frame(x$properties)))
Edit: How to replace empty values with NA:
dat$baglocatie[dat$baglocatie == ""] <- NA
The result:
head(dat)
gid yymmdd lat lon mag depth knmilocatie baglocatie tijd
1 1496600 19861226 52.992 6.548 2.8 1.0 Assen Assen 74751
2 1496601 19871214 52.928 6.552 2.5 1.5 Hooghalen Hooghalen 204951
3 1496602 19891201 52.529 4.971 2.7 1.2 Purmerend Kwadijk 200914
4 1496603 19910215 52.771 6.914 2.2 3.0 Emmen Emmen 21116
5 1496604 19910425 52.952 6.575 2.6 3.0 Geelbroek Ekehaar 102631
6 1496605 19910808 52.965 6.573 2.7 3.0 Eleveld Assen 40114

Answer 2

This is just another, quite similar, approach.
#SvenHohenstein's approach creates a dataframe at each step, an expensive process. It's much faster to create vectors and re-type the whole result at the end. Also, Sven's approach makes each column a factor, which might or might not be what you want. The approach below runs about 200 times faster. This can be important if you intend to do this repeatedly. Finally, you will need to convert columns lon, lat, mag, and depth to numeric.
library(microbenchmark)
library(rjson)
document <- fromJSON(file = "bevingenbag.json", method = 'C')
json2df.1 <- function(json){ # #SvenHohenstein approach
df <- do.call(rbind, lapply(json$features,
function(x) data.frame(x$properties, stringsAsFactors=F)))
return(df)
}
json2df.2 <- function(json){
df <- do.call(rbind,lapply(json[["features"]],function(x){c(x$properties)}))
df <- data.frame(apply(result,2,as.character), stringsAsFactors=F)
return(df)
}
microbenchmark(x<-json2df.1(document), y<-json2df.2(document), times=10)
# Unit: milliseconds
# expr min lq median uq max neval
# x <- json2df.1(document) 2304.34378 2654.95927 2822.73224 2977.75666 3227.30996 10
# y <- json2df.2(document) 13.44385 15.27091 16.78201 18.53474 19.70797 10
identical(x,y)
# [1] TRUE