Reputation: 715
I'm having trouble with a very nasty nested JSON.
The format is like this
{
"matches": [
{
"matchId": 1,
"region": "BR",
"participants": [
{
"participantId": 0,
"teamId": 200,
"stats": {
"winner": true,
"champLevel": 16,
"item0": 3128,
}
{
"matchId": 2,
"region": "BR",
"participants": [
{
"participantId": 0,
"teamId": 201,
"stats": {
"winner": false,
"champLevel": 18,
"item0": 3128,
"item1": 3157,
"item1": 3158,
}
As you can see in the second match the number of items increased, but in the data frame the first row will have the same columns:
MatchId region ... stats.winner stats.champLevel stats.item0 stats.item1 stats.item2
1 BR TRUE 16 3128 1 BR
1 BR TRUE 16 3128 3157 3158
See the first row is smaller than the second, so R recycle the values ....
If you want the full data you can grab it at: http://pastebin.com/HQDf2ase
How I parsed the json to data.frame:
json.matchData <- fromJSON(file="file.json"))
#Unlist the elements of the Json and convert it to a data frame
matchData.i <- lapply(json.matchData$matches, function(x){ unlist(x)})
#Transform into Data Frame
matchData <- do.call("rbind", matchData.i)
matchData <- as.data.frame(matchData)
But the dataframe is messed up, because some fields should be NA but they are filled with wrong values.
Upvotes: 10
Views: 6481
Reputation: 206167
I think using the plyr
rbind.fill()
function would be helpful here. How about this
library(plyr)
matchData <- rbind.fill(lapply(matchData.i,
function(x) do.call("data.frame", as.list(x))
))
the lapply()
bit is to turn the intermediate lists into data.frames which rbind.fill requires.
Upvotes: 5