我在使用非常讨厌的嵌套JSON时遇到了麻烦.
i'm having trouble with a very nasty nested JSON.
格式如下
{ "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, }您可以在第二个匹配项中看到增加的项目数,但是在数据框中,第一行将具有相同的列:
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 collumns:
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看到第一行小于第二行,因此R回收值....
See the first row is smaller than the second, so R recycle the values ....
如果您想要完整的数据,可以在以下位置获取: pastebin/HQDf2ase
If you want the full data you can grab it at: pastebin/HQDf2ase
我如何将json解析为data.frame:
How I parsed the json to data.frame:
json.matchData <- fromJSON(file="file.json"))取消列出Json的元素并将其转换为数据框
matchData.i <- lapply(json.matchData$matches, function(x){ unlist(x)})转换为数据框
matchData <- do.call("rbind", matchData.i) matchData <- as.data.frame(matchData)但是数据帧被弄乱了,因为某些字段应该是NA,但是它们填充了错误的值.
But the dataframe is messed up, because some fields should be NA but they are filled with wrong values.
推荐答案我认为在这里使用plyr rbind.fill()函数会有所帮助.怎么样
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)) ))lapply()位用于将中间列表转换为rbind.fill所需的data.frames.
the lapply() bit is to turn the intermediate lists into data.frames which rbind.fill requires.
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将嵌套的JSON解析为R中的数据框
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