How to write a JSON object from R dataframe with grouping - json

Question

In general I feel there is a need to make JSON objects by folding multiple columns. There is no direct way to do this afaik. Please point it out if there is ..
I have data of this from
A B C
1 a x
1 a y
1 c z
2 d p
2 f q
2 f r
How do I write a json which looks like
{'query':'1', 'type':[{'name':'a', 'values':[{'value':'x'}, {'value':'y'}]}, {'name':'c', 'values':[{'value':'z'}]}]}
and similarly for 'query':'2'
I am looking to spit them in the mongo import/export individual json lines format.
Any pointers are also appreciated..

Answer 1

You've got a little "non-standard" thing going with two keys of "value" (I don't know if this is legal json), as you can see here:
(js <- jsonlite::fromJSON('{"query":"1", "type":[{"name":"a", "values":[{"value":"x"}, {"value":"y"}]}, {"name":"c", "values":[{"value":"z"}]}]}'))
## $query
## [1] "1"
##
## $type
## name values
## 1 a x, y
## 2 c z
... with a data.frame cell containing a list of data.frames:
js$type$values[[1]]
## value
## 1 x
## 2 y
class(js$type$values[[1]])
## [1] "data.frame"
If you can accept your "type" variable containing a vector instead of a named-list, then perhaps the following code will suffice:
jsonlite::toJSON(lapply(unique(dat[, 'A']), function(a1) {
list(query = a1,
type = lapply(unique(dat[dat$A == a1, 'B']), function(b2) {
list(name = b2,
values = dat[(dat$A == a1) & (dat$B == b2), 'C'])
}))
}))
## [{"query":[1],"type":[{"name":["a"],"values":["x","y"]},{"name":["c"],"values":["z"]}]},{"query":[2],"type":[{"name":["d"],"values":["p"]},{"name":["f"],"values":["q","r"]}]}]