How do I come from here ...
| ID | JSON Request                                                          |
==============================================================================
|  1 | {"user":"xyz1","weightmap": {"P1":0,"P2":100}, "domains":["a1","b1"]} |
------------------------------------------------------------------------------
|  2 | {"user":"xyz2","weightmap": {"P1":100,"P2":0}, "domains":["a2","b2"]} |
------------------------------------------------------------------------------
to here (The requirement is to make a table of JSON in column 2):
| User | P1 | P2 | domains | 
============================
| xyz1 |  0 |100 | a1, b1  |
----------------------------
| xyz2 |100 | 0  | a2, b2  |
----------------------------
Here is the code to generate the data.frame:
raw_df <- 
  data.frame(
    id   = 1:2,
    json = 
      c(
        '{"user": "xyz2", "weightmap": {"P1":100,"P2":0}, "domains": ["a2","b2"]}', 
        '{"user": "xyz1", "weightmap": {"P1":0,"P2":100}, "domains": ["a1","b1"]}'
      ), 
    stringsAsFactors = FALSE
  )
                The JSON. parse() method parses a string and returns a JavaScript object. The string has to be written in JSON format.
Here's a tidyverse solution (also using jsonlite) if you're happy to work in a long format (for domains in this case):
library(jsonlite)
library(dplyr)
library(purrr)
library(tidyr)
d <- data.frame(
  id = c(1, 2),
  json = c(
    '{"user":"xyz1","weightmap": {"P1":0,"P2":100}, "domains":["a1","b1"]}',
    '{"user":"xyz2","weightmap": {"P1":100,"P2":0}, "domains":["a2","b2"]}'
  ),
  stringsAsFactors = FALSE
)
d %>% 
  mutate(json = map(json, ~ fromJSON(.) %>% as.data.frame())) %>% 
  unnest(json)
#>   id user weightmap.P1 weightmap.P2 domains
#> 1  1 xyz1            0          100      a1
#> 2  1 xyz1            0          100      b1
#> 3  2 xyz2          100            0      a2
#> 4  2 xyz2          100            0      b2
mutate... is converting from a string to column of nested data frames.unnest... is unnesting these data frames into multiple columnsCould not get the flatten parameter to work as I expected so needed to unlist and then "re-list" before rbinding with do.call:
library(jsonlite)
 do.call( rbind, 
          lapply(raw_df$json, 
                  function(j) as.list(unlist(fromJSON(j, flatten=TRUE)))
        )       )
     user   weightmap.P1 weightmap.P2 domains1 domains2
[1,] "xyz2" "100"        "0"          "a2"     "b2"    
[2,] "xyz1" "0"          "100"        "a1"     "b1"    
Admittedly, this will require further processing since it coerces all the lines to character.
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