Convert JSON file to a CSV file using R

Question

I have the JSON file in a .txt file which I'm trying to load into R but I'm getting the following error:

Error in feed_push_parser(readBin(con, raw(), n), reset = TRUE) : 
  parse error: trailing garbage
      " : "SUCCESS"  }    /* 1 */  {    "_id" : "b736c374-b8ae-4e9
                 (right here) ------^

I'm assuming the error is because of multiple instances of /* (number) */ and I can't manually remove them all as my file has 10k instances of these. Is there a way to remove such instances before loading the data into R?

My JSON file looks like below:

/* 0 */
{
  "_id" : "93ccbdb6-8947",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1KKP",
    "queryId" : "93ccbdb6-8947",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 0,
  "requestDate" : 20151205,
  "totalRecords" : 0,
  "status" : "SUCCESS"
}

/* 1 */
{
  "_id" : "b736c374-b8ae",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1KKP",
    "queryId" : "b736c374-b8ae",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 0,
  "requestDate" : 20151205,
  "totalRecords" : 0,
  "status" : "SUCCESS"
}

/* 2 */
{
  "_id" : "3312605f-8304",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1SXE",
    "queryId" : "3312605f-8304",
    "subRequests" : [{
        "origin" : "LON",
        "destination" : "IAD",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 2,
  "requestDate" : 20151205,
  "totalRecords" : 0,
  "status" : "SUCCESS"
}

/* 3 */
{
  "_id" : "6b668cfa-9b79",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1NXA",
    "queryId" : "6b668cfa-9b79",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 1,
  "requestDate" : 20151205,
  "totalRecords" : 1388,
  "status" : "SUCCESS"
}

/* 4 */
{
  "_id" : "41c373a1-e4cb",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP6CXS",
    "queryId" : "41c373a1-e4cb",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 0,
  "requestDate" : 20151205,
  "totalRecords" : 1388,
  "status" : "SUCCESS"
}

/* 5 */
{
  "_id" : "2c8331c4-21ca",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1KKP",
    "queryId" : "2c8331c4-21ca",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 0,
  "requestDate" : 20151205,
  "totalRecords" : 1388,
  "status" : "SUCCESS"
}

/* 6 */
{
  "_id" : "71a09900-1c13",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP6CXS",
    "queryId" : "71a09900-1c13",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AF",
        "fareClasses" : "",
        "owrt" : "1,2"
      }, {
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }, {
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "DL",
        "fareClasses" : "",
        "owrt" : "1,2"
      }, {
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "LH",
        "fareClasses" : "",
        "owrt" : "1,2"
      }, {
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "BA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 0,
  "requestDate" : 20151205,
  "totalRecords" : 6941,
  "status" : "SUCCESS"
}

/* 7 */
{
  "_id" : "a036a42a-918b",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1MMM",
    "queryId" : "a036a42a-918b",
    "subRequests" : [{
        "origin" : "WAS",
        "destination" : "LON",
        "carrier" : "AA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 0,
  "requestDate" : 20151205,
  "totalRecords" : 1388,
  "status" : "SUCCESS"
}

/* 8 */
{
  "_id" : "c547be36-805c",
  "uiSearchRequest" : {
    "travelDate" : 20151206,
    "travelDuration" : 7,
    "shopperDuration" : 30,
    "oneWay" : false,
    "userId" : "ATP1SXB",
    "queryId" : "c547be36-805c",
    "subRequests" : [{
        "origin" : "CHI",
        "destination" : "LON",
        "carrier" : "BA",
        "fareClasses" : "",
        "owrt" : "1,2"
      }]
  },
  "downloadCount" : 2,
  "requestDate" : 20151205,
  "totalRecords" : 1072,
  "status" : "SUCCESS"
}

My code is below (Although I haven't gotten much far):

library(jsonlite)
library(RJSONIO)
json_data_raw<-fromJSON("mydata.txt")

json_file <- lapply(json_data_raw, function(x) {
  x[sapply(x, is.null)] <- NA
  unlist(x)
})

output <-- do.call("rbind", json_file)
write.csv(a, file="json.csv",row.names = FALSE)
file.show("json.csv")

I'm trying to get my output into a CSV file like below

Answer 1

There are several issues with your text file. As you already noticed, you need to remove the lines of the form /* 0 */. What results is still not valid json. If you want to have several json objects in a file, you need to store them in an array. The json objects are the parts that are closed in curly brakets, e.g.,

{
  "_id" : "93ccbdb6-8947-4687-8e12-edf4e40d6650",
  ...
  "totalRecords" : 0,
  "status" : "SUCCESS"
}

The structure of an array of objects is as follows:

[
  {
    ...
  },
  {
    ...
  }
]

To get your file in shape, you need to add a comma between the objects and add the square brackets. You could do this as follows:

raw <- readLines("mydata.txt")

# get rid of the "/* 0 */" lines
json <- grep("^/\\* [0-9]* \\*/", raw, value = TRUE, invert = TRUE)

# add missing comma after }
n <- length(json)
json[-n] <- gsub("^}$", "},", json[-n])

# add brakets at the beginning and end
json <- c("[", json, "]")

This can be read by fromJSON(), so I assume it is valid json:

library(jsonlite)
table <- fromJSON(json)

The table is nested, that is, some of the tables cells contain a data frame or a list themselves. For example,

table[1,2]
##   travelDate travelDuration shopperDuration oneWay  userId                              queryId
## 1   20151206              7              30  FALSE ATP1KKP 93ccbdb6-8947-4687-8e12-edf4e40d6650
##               subRequests
##     1 WAS, LON, AA, , 1,2

You could use flatten() from the jsonlite package, to get a table with one level of nesting less

flatten(table)[1:3, c(1, 6, 12)]
##                                    _id uiSearchRequest.travelDate uiSearchRequest.subRequests
## 1 93ccbdb6-8947-4687-8e12-edf4e40d6650                   20151206         WAS, LON, AA, , 1,2
## 2 b736c374-b8ae-4e99-8073-9c54517fecd5                   20151206         WAS, LON, AA, , 1,2
## 3 3312605f-8304-4ab8-96d6-6e1a03cfbd9e                   20151206         LON, IAD, AA, , 1,2

The last column is still a list. There are many ways you could handle this. One possibility, is to create a row per subrequest, where the contents of all the other columns (X_id, downloadCount, etc.) are repeated. (This is almost the form that you give in your question, with the only difference that you left cells empty in the reapeated columns, while I repeat the contents.) This is how it can be done:

table <- flatten(fromJSON(json))
tab_list <- lapply(1:nrow(table),
                  function(i) data.frame(table[i, -12], table[i, 12],
                              stringsAsFactors = FALSE))
library(dplyr)
flat_table <- bind_rows(tab_list)

The second line creates a list of data frames. These are combined into a single data frame using bind_rows() from dpylr. (To be more precise, flat_table will be a tbl_df, but the difference to a data.frame is small.) This can then be written to a csv file in the usual way:

write.csv(flat_table, file = "mydata.csv")