How to open a .mongo file and export the content into csv? - json

Question

EDIT 2014-05-01: I tried fromJSON first (as suggested below), but that only parsed the first line. I found out that there were commas missing between the brackets of each JSON line so I changed that in TextEdit and saved the file. I also added [ at the beginning of the file and ] at the end and then it worked with JSON. Now the next step: from a list (with embedded lists) to a dataframe (or csv).
I get a data package from edX every now and then on the courses we are evaluating. Some of these are just plain .csv files which are quite easy to handle, others are more difficult for me (not having a CS or programming background).
I have 2 files I want to open and parse into csv files for analysis in R. I have tried many many json2csv tools out there, but to no avail. I also tried the simple methods described here to turn json into csv.
The data is confidential, so I cannot share the entire data set, but will share the first two lines of the file, maybe that helps. The problem is that nowhere I find anything about .mongo files, which to me seems quite strange, do they even exist? Or is this just a JSON file that may be corrupted (which could explain the errors)?
Any suggestions are welcome.
The first 2 lines in one of the .mongo files:
{
"_id": {
"$oid": "52d1e62c350e7a3156000009"
},
"votes": {
"up": [
],
"down": [
],
"up_count": 0,
"down_count": 0,
"count": 0,
"point": 0
},
"visible": true,
"abuse_flaggers": [
],
"historical_abuse_flaggers": [
],
"parent_ids": [
],
"at_position_list": [
],
"body": "the delft university accredited course with the scholarship (fundamentals of water treatment) is supposed to start in about a month's time. But have the scholarship list been published? Any tentative date??",
"course_id": "DelftX/CTB3365x/2013_Fall",
"_type": "Comment",
"endorsed": false,
"anonymous": false,
"anonymous_to_peers": false,
"author_id": "269835",
"comment_thread_id": {
"$oid": "52cd40c5ab40cf347e00008d"
},
"author_username": "tachak59",
"sk": "52d1e62c350e7a3156000009",
"updated_at": {
"$date": 1389487660636
},
"created_at": {
"$date": 1389487660636
}
}{
"_id": {
"$oid": "52d0a66bcb3eee318d000012"
},
"votes": {
"up": [
],
"down": [
],
"up_count": 0,
"down_count": 0,
"count": 0,
"point": 0
},
"visible": true,
"abuse_flaggers": [
],
"historical_abuse_flaggers": [
],
"parent_ids": [
{
"$oid": "52c63278100c07c0d1000028"
}
],
"at_position_list": [
],
"body": "I got it. Thank you!",
"course_id": "DelftX/CTB3365x/2013_Fall",
"_type": "Comment",
"endorsed": false,
"anonymous": false,
"anonymous_to_peers": false,
"parent_id": {
"$oid": "52c63278100c07c0d1000028"
},
"author_id": "2655027",
"comment_thread_id": {
"$oid": "52c4f303b03c4aba51000013"
},
"author_username": "dmoronta",
"sk": "52c63278100c07c0d1000028-52d0a66bcb3eee318d000012",
"updated_at": {
"$date": 1389405803386
},
"created_at": {
"$date": 1389405803386
}
}{
"_id": {
"$oid": "52ceea0cada002b72c000059"
},
"votes": {
"up": [
],
"down": [
],
"up_count": 0,
"down_count": 0,
"count": 0,
"point": 0
},
"visible": true,
"abuse_flaggers": [
],
"historical_abuse_flaggers": [
],
"parent_ids": [
{
"$oid": "5287e8d5906c42f5aa000013"
}
],
"at_position_list": [
],
"body": "if u please send by mail \n",
"course_id": "DelftX/CTB3365x/2013_Fall",
"_type": "Comment",
"endorsed": false,
"anonymous": false,
"anonymous_to_peers": false,
"parent_id": {
"$oid": "5287e8d5906c42f5aa000013"
},
"author_id": "2276302",
"comment_thread_id": {
"$oid": "528674d784179607d0000011"
},
"author_username": "totah1993",
"sk": "5287e8d5906c42f5aa000013-52ceea0cada002b72c000059",
"updated_at": {
"$date": 1389292044203
},
"created_at": {
"$date": 1389292044203
}
}

Answer 1

R doesn't have "native" support for these files but there is a JSON parser with the rjson package. So I might load my .mongo file with:
myfile <- "path/to/myfile.mongo"
myJSON <- readLines(myfile)
myNiceData <- fromJSON(myJSON)
Since RJson converts into a data structure that fits the object being read, you'll have to do some additional snooping but once you have an R data type you shouldn't have any trouble working with it from there.
Another package to consider when parsing JSON data is jsonlite. It will make data frames for you so you can write them to a csv format with write.table or some other applicable method for writing objects.
NOTE: if it is easier to connect to the MongoDB and get the data from a request, then RMongo may be a good bet. The R-Bloggers also made a post about using RMongo that has a nice little walkthrough.

Answer 2

I used RJSON as suggested by #theWanderer and with the help of a colleague wrote the following code to parse the data into columns, choosing the specific columns that are needed, and checking each of the instances if they return the right variables.
Entire workflow:
Checked some of the data in jsonlint - corrected the errors → },{ instead of }{ between each line and [ and ] at the beginning and end of the file
Made a smaller file to play with, containing about 11 JSON lines
Used the code below to parse the datafile - however, checking the different listItems first if they are not lists themselves (that gives problems) // as you will see, I also removed things like \n because that gave errors and added an empty value for parent_id if there is none in the data (otherwise it would mix up the data)
The code to import the .mongo file into R and then parse it into CSV:
library(rjson)
###### set working directory to write out the data file
setwd("/your/favourite/dir/json to csv/")
#never ever convert strings to factors
options(stringsAsFactors = FALSE)
#import the .mongo file to R
temp.data = fromJSON(file="temp.mongo", method="C", unexpected.escape="error")
file.remove("temp.csv") ## removes the old datafile if there is one
## (so the data is not appended to the file,
## but a new file is created)
listItem = temp.data[[1]] ## prepare the listItem the first time
for (listItem in temp.data){
parent_id = ""
if (length(listItem$parent_id)>0){
parent_id = listItem$parent_id
}
write.table(t(c(
listItem$votes$up_count, listItem$visible, parent_id,
gsub("\n", "", listItem$body), listItem$course_id, unlist(listItem["_type"]),
listItem$endorsed, listItem$anonymous, listItem$author_id,
unlist(listItem$comment_thread_id), listItem$author_username,
as.POSIXct(unlist(listItem$created_at)/1000, origin="1970-01-01"))), # end t(), c()
file="temp.csv", sep="\t", append=TRUE, row.names=FALSE, col.names=FALSE)
}