Strategies for formatting JSON output from R

Question

I\'m trying to figure out the best way of producing a JSON file from R. I have the following dataframe tmp in R.

> tmp
  gender         


        

Answer 1

Building further on Andrie and Richie's ideas, use alply instead of apply to avoid converting numbers to characters:

library(RJSONIO)
library(plyr)
modified <- list(
  traits = colnames(tmp),
  values = unname(alply(tmp, 1, identity))
)
cat(toJSON(modified))

plyr's alply is similar to apply but returns a list automatically; whereas without the more complicated function inside Richie Cotton's answer, apply would return a vector or array. And those extra steps, including t, mean that if your dataset has any non-numeric columns, the numbers will get converted to strings. So use of alply avoids that concern.

For example, take your tmp dataset and add

tmp$grade <- c("A","B","C","D","E","F")

Then compare this code (with alply) vs the other example (with apply).

Answer 2

Building upon Andrie's idea with apply, you can get exactly what you want by modifying the tmp variable before calling toJSON.

library(RJSONIO)
modified <- list(
  traits = colnames(tmp),
  values = unname(apply(tmp, 1, function(x) as.data.frame(t(x))))
)
cat(toJSON(modified))

Answer 3

Using the package jsonlite:

> jsonlite::toJSON(list(traits = names(tmp), values = tmp), pretty = TRUE)
{
  "traits": ["gender", "age", "welcoming", "proud", "tidy", "unique"],
  "values": [
    {
      "gender": 1,
      "age": 30,
      "welcoming": 4,
      "proud": 4,
      "tidy": 4,
      "unique": 4
    },
    {
      "gender": 2,
      "age": 34,
      "welcoming": 4,
      "proud": 2,
      "tidy": 4,
      "unique": 4
    },
    {
      "gender": 1,
      "age": 34,
      "welcoming": 5,
      "proud": 3,
      "tidy": 4,
      "unique": 5
    },
    {
      "gender": 2,
      "age": 33,
      "welcoming": 2,
      "proud": 3,
      "tidy": 2,
      "unique": 4
    },
    {
      "gender": 2,
      "age": 28,
      "welcoming": 4,
      "proud": 3,
      "tidy": 4,
      "unique": 4
    },
    {
      "gender": 2,
      "age": 26,
      "welcoming": 3,
      "proud": 2,
      "tidy": 4,
      "unique": 3
    }
  ]
} 

Answer 4

Another option is to use the split to split your data.frame with N rows into N data.frames with 1 row.

library(RJSONIO)
modified <- list(
   traits = colnames(tmp),
   values = split(tmp, seq_len(nrow(tmp)))
)
cat(toJSON(modified))

Answer 5

It seems to me you can do this by sending each row of your data.frame to JSON with the appropriate apply statement.

For a single row:

library(RJSONIO)

> x <- toJSON(tmp[1, ])
> cat(x)
{
 "gender": 1,
"age":     30,
"welcoming": 4,
"proud": 4,
"tidy": 4,
"unique": 4 
}

The entire data.frame:

x <- apply(tmp, 1, toJSON)
cat(x)
{
 "gender": 1,
"age":     30,
"welcoming": 4,
"proud": 4,
"tidy": 4,
"unique": 4 
} {

...

} {
 "gender": 2,
"age":     26,
"welcoming": 3,
"proud": 2,
"tidy": 4,
"unique": 3 
}