rjson::fromJSON returns only the first item - json

Question

I have a sqlite database file with several columns. One of the columns has a JSON dictionary (with two keys) embedded in it. I want to extract the JSON column to a data frame in R that shows each key in a separate column.
I tried rjson::fromJSON, but it reads only the first item. Is there a trick that I'm missing?
Here's an example that mimics my problem:
> eg <- as.vector(c("{\"3x\": 20, \"6y\": 23}", "{\"3x\": 60, \"6y\": 50}"))
> fromJSON(eg)
$3x
[1] 20
$6y
[1] 23
The desired output is something like:
# a data frame for both variables
3x 6y
1 20 23
2 60 50
or,
# a data frame for each variable
3x
1 20
2 60
6y
1 23
2 50

Answer 1

What you are looking for is actually a combination of lapply and some application of rbind or related.
I'll extend your data a little, just to have more than 2 elements.
eg <- c("{\"3x\": 20, \"6y\": 23}",
"{\"3x\": 60, \"6y\": 50}",
"{\"3x\": 99, \"6y\": 72}")
library(jsonlite)
Using base R, we can do
do.call(rbind.data.frame, lapply(eg, fromJSON))
# X3x X6y
# 1 20 23
# 2 60 50
# 3 99 72
You might be tempted to do something like Reduce(rbind, lapply(eg, fromJSON)), but the notable difference is that in the Reduce model, rbind is called "N-1" times, where "N" is the number of elements in eg; this results in a LOT of copying of data, and though it might work alright with small "N", it scales horribly. With the do.call option, rbind is called exactly once.
Notice that the column labels have been R-ized, since data.frame column names should not start with numbers. (It is possible, but generally discouraged.)
If you're confident that all substrings will have exactly the same elements, then you may be good here. If there's a chance that there will be a difference at some point, perhaps
eg <- c(eg, "{\"3x\": 99}")
then you'll notice that the base R solution no longer works by default.
do.call(rbind.data.frame, lapply(eg, fromJSON))
# Error in (function (..., deparse.level = 1, make.row.names = TRUE, stringsAsFactors = default.stringsAsFactors()) :
# numbers of columns of arguments do not match
There may be techniques to try to normalize the elements such that you can be assured of matches. However, if you're not averse to a tidyverse package:
library(dplyr)
eg2 <- bind_rows(lapply(eg, fromJSON))
eg2
# # A tibble: 4 × 2
# `3x` `6y`
# <int> <int>
# 1 20 23
# 2 60 50
# 3 99 72
# 4 99 NA
though you cannot call it as directly with the dollar-method, you can still use [[ or backticks.
eg2$3x
# Error: unexpected numeric constant in "eg2$3"
eg2[["3x"]]
# [1] 20 60 99 99
eg2$`3x`
# [1] 20 60 99 99