How to flatten nested data frames returned from js

I am loading this JSON data with jsonlite

<snip>  
"rawData": {
    "fortune": {}, 
    "plaintext": {}, 
    "db": {}, 
    "update": {
      "duda": [
        {
          "latencyAvg": "201.40us", 
          "latencyMax": "727.00us", 
          "latencyStdev": "54.85us", 
          "totalRequests": 561810, 
          "startTime": 1413890149, 
          "endTime": 1413890164
        }
      ]
      }, 
    "json": {
      "duda": [
        {
          "latencyAvg": "201.40us", 
          "latencyMax": "727.00us", 
          "latencyStdev": "54.85us", 
          "totalRequests": 561810, 
          "startTime": 1413890149, 
          "endTime": 1413890164
        }
      ]
    }, 
    "query": {}
  }

Which results in a structure with nested data frames

data <- structure(list(fortune = structure(list(), .Names = character(0)), 
    plaintext = structure(list(), .Names = character(0)), db = structure(list(), .Names = character(0)), 
    update = structure(list(duda = structure(list(latencyAvg = "201.40us", 
        latencyMax = "727.00us", latencyStdev = "54.85us", totalRequests = 561810L, 
        startTime = 1413890149L, endTime = 1413890164L), .Names = c("latencyAvg", 
    "latencyMax", "latencyStdev", "totalRequests", "startTime", 
    "endTime"), class = "data.frame", row.names = 1L)), .Names = "duda"), 
    json = structure(list(duda = structure(list(latencyAvg = "201.40us", 
        latencyMax = "727.00us", latencyStdev = "54.85us", totalRequests = 561810L, 
        startTime = 1413890149L, endTime = 1413890164L), .Names = c("latencyAvg", 
    "latencyMax", "latencyStdev", "totalRequests", "startTime", 
    "endTime"), class = "data.frame", row.names = 1L)), .Names = "duda"), 
    query = structure(list(), .Names = character(0))), .Names = c("fortune", 
"plaintext", "db", "update", "json", "query"))

I'd like to create a single data.frame that looks like this:

Type   | Name | latencyAvg | latencyMax | latencyStdev | totalRequests | startTime | endTime
json   | duda | 201.40us   | <etc..>
update | duda | 201.40us   | <etc..>

By flatting the nested data frames. I'm figuring out how to do this manually by removing the items I want and using rbind/cbind to move them into a new data frame, but is there a simple way to do this type of recursive flattening?

回答1:

Assuming that object is named the unfortunate name of "data":

newdat <- rbind.data.frame( Type= c(rep("json",   nrow(data$json$duda)), 
                                    rep("update", nrow(data$update$duda)) ), 
                            rbind( data$json$duda, data$update$duda) )

回答2:

Another oneliner

do.call(rbind, lapply(data[c('json', 'update')], '[[', 'duda'))

回答3:

use flatten function. it gets a data frame and returns a flat data frame. if you need to exclude some columns from source data frame then use df[[-i]] to exclude column i.