I'm attempting to visualize a cluster tree using this awesome D3 layout! However, it needs data in JSON format - how do I go from a hclust-object in R to a hierarchical JSON structure?
set.seed(123)
m <- matrix(runif(100), nrow=10)
cl <- hclust(dist(m))
plot(cl)
My googling turned up this hclustToTree function which returns a list that looks promising - but I don't really know where to go from there. Any advice would be much appreciated.
halfway <- hclustToTree(cl)
You're almost there:
jsonTree <- toJSON(halfway) # part of the RJSONIO library
Related
Is there a way to change values, or assign new variables in a json file and after give it back in the same format?
It can be used rjson pachage to get the json file in R in data.frame format but how to covert back this data.frame to json after my changes?
EDIT:
sample code:
json file:
{"__v":1,"_id":{"$oid":"559390f6fa76bc94285fa68a"},"accountId":6,"api":false,"countryCode":"no","countryName":"Norway","date":{"$date":"2015-07-01T07:04:22.265Z"},"partnerId":1,"query":{"search":[{"label":"skill","operator":"and","terms":["java"],"type":"required"}]},"terms":[{"$oid":"559390f6fa76bc94285fa68b"}],"time":19,"url":"eyJzZWFyY2giOlt7InRlcm1zIjpbImphdmEiXSwibGFiZWwiOiJza2lsbCIsInR5cGUiOiJyZXF1aXJlZCIsIm9wZXJhdG9yIjoiYW5kIn1dfQ","user":11}
{"__v":1,"_id":{"$oid":"5593910cfa76bc94285fa68d"},"accountId":6,"api":false,"countryCode":"se","countryName":"Sweden","date":{"$date":"2015-07-01T07:04:44.565Z"},"partnerId":1,"query":{"search":[{"label":"company","operator":"or","terms":["microsoft"],"type":"required"},{"label":"country","operator":"or","terms":["se"],"type":"required"}]},"terms":[{"$oid":"5593910cfa76bc94285fa68e"},{"$oid":"5593910cfa76bc94285fa68f"}],"time":98,"url":"eyJzZWFyY2giOlt7InRlcm1zIjpbIm1pY3Jvc29mdCJdLCJsYWJlbCI6ImNvbXBhbnkiLCJ0eXBlIjoicmVxdWlyZWQiLCJvcGVyYXRvciI6Im9yIn0seyJ0ZXJtcyI6WyJzZSJdLCJsYWJlbCI6ImNvdW50cnkiLCJ0eXBlIjoicmVxdWlyZWQiLCJvcGVyYXRvciI6Im9yIn1dfQ","user":13}
Code:
library('rjson')
c <- file(Usersfile,'r')
l <- readLines(c,-1L)
json <- lapply(X=l,fromJSON)
json[[1]]$countryName <- 'Jamaica'
result <- cat(toJSON(json))
Output(is one line and start with [:
[{"__v":1,"_id":{"$oid":"559390f6fa76bc94285fa68a"},"accountId":6,"api":false,"countryCode":"no","countryName":"Jamaica","date":{"$date":"2015-07-01T07:04:22.265Z"},"partnerId":1,"query":{"search":[{"label":"skill","operator":"and","terms":"java","type":"required"}]},"terms":[{"$oid":"559390f6fa76bc94285fa68b"}],"time":19,"url":"eyJzZWFyY2giOlt7InRlcm1zIjpbImphdmEiXSwibGFiZWwiOiJza2lsbCIsInR5cGUiOiJyZXF1aXJlZCIsIm9wZXJhdG9yIjoiYW5kIn1dfQ","user":11},{"__v":1,"_id":{"$oid":"5593910cfa76bc94285fa68d"},"accountId":6,"api":false,"countryCode":"se","countryName":"Sweden","date":{"$date":"2015-07-01T07:04:44.565Z"},"partnerId":1,"query":{"search":[{"label":"company","operator":"or","terms":"microsoft","type":"required"},{"label":"country","operator":"or","terms":"se","type":"required"}]},"terms":[{"$oid":"5593910cfa76bc94285fa68e"},{"$oid":"5593910cfa76bc94285fa68f"}],"time":98,"url":"eyJzZWFyY2giOlt7InRlcm1zIjpbIm1pY3Jvc29mdCJdLCJsYWJlbCI6ImNvbXBhbnkiLCJ0eXBlIjoicmVxdWlyZWQiLCJvcGVyYXRvciI6Im9yIn0seyJ0ZXJtcyI6WyJzZSJdLCJsYWJlbCI6ImNvdW50cnkiLCJ0eXBlIjoicmVxdWlyZWQiLCJvcGVyYXRvciI6Im9yIn1dfQ","user":13}]
convert data frame to json
So this question has already been answered in full here ^^^
Quick Summary ::
There are 2 options presented.
(A) rjson library
import the library
use to the toJSON() method to create a JSON object. (Not exactly sure what the unname() function does... :p ).
(B) jsonlite library
import the jsonlite library
just use the toJSON() method (same as above, but with no modification).
cat() the above object.
Code examples are at that link. Hope this helps!
I am using R with jsonlite to get data back from a url. It's pretty straightforward except that when I view the URL in a browser, there are 50 results. But when I view my results from jsonlite there are only 25 results in my data set. I have checked the jsonlite documentation and I can't find any parameters that would indicate paging or limits of any kind. Has anyone seen this before? The code I'm using is pretty straightforward, but I'm including it anyways. I've already checked the data in between the flatten step and the fromJSON command only returns 25 rows.
library(jsonlite)
url="https://myjson"
mydata = fromJSON(url)
mydata = flatten(mydata$mydataframe,recursive=TRUE)
I am parsing JSON objects from pipl.com.
Specifically I am passing a CSV of contacts using lapply fromJSON under the jsonlite library to the api. Then I want to cbind specific elements into a flat dataframe. I have tried mapply, sapply and lapply to then rbind as below but this isn't working as I expect for any other elements than the ones below. I have tried it individually using the 'mini.test[1]$records$user_ids' syntax but the original contacts dataframe has hundreds of records so I was thinking a loop would be able to extract the elements I want.
I am looking to find only the user names for linkedin, facebook and twitter for each user. Thus I was thinking some sort of grepl would help me subset it. I have that vector created and posted the code below too.
I have read multiple r-bloggers articles on the different "apply" functions, looked at the R Cookbook pdf, and read questions on stackoverflow. I am stumped so really appreciate any help.
library(jsonlite)
#sample data
first<-c('Victor','Steve','Mary')
last<-c('Arias','Madden','Johnson')
contacts<-cbind(first,last)
#make urls
urls<-paste('http://api.pipl.com/search/v3/json/?first_name=',contacts[,1],'%09&last_name=',contacts[,2],'&pretty=True&key=xxxxxxx', sep='')
#Parse api
mini.test<-lapply(urls,fromJSON,simplifyMatrix=TRUE,flatten=TRUE)
#Data frame vector name
names <- do.call(rbind, lapply(mini.test, "[[", 5))
display <-do.call(rbind, lapply(names, "[[", 3))
#Grepl for 3 sources
records <- lapply(mini.test, "[[", 7)
twitter <-grepl("twitter.com",records,ignore.case = TRUE)
facebook <-grepl("facebook.com",records,ignore.case = TRUE)
linkedin <-grepl("linkedin.com",records,ignore.case = TRUE)
I know because of pipl's response that contacts may have multiple profile user names. For this purpose I just need it unlisted as a string not a nested list in the dataframe. In the end I would like a flat file that looks like below. Again, I am sincerely appreciate the help. I have been reading about it for 3 days without much success.
twitter <- c('twitter.username1','twitter.username2','NA')
linkedin <- c('linkedin.username1','linedin.username2','linkedin.username3')
facebook <- c('fb1','fb2','fb3,fb3a')
df<-cbind(display,twitter,linkedin,facebook)
In the Blekko search engine you can get the search results in JSON format, e.g. with the search term 'lifehacker':
http://blekko.com/ws/?q=lifehacker+%2Fjson
How could you carry out this query from R and parse the content?
[There is a URL, a RSS URL and a snippet with the main text.]
I have tried packages tm.plugin.webmining and boilerpipeR, but couldn't figure it out.
Using Rcurl and RJSONIO packages is very handy to retrieve rjson results:
library(RCurl)
library(RJSONIO)
doc <- getURL('http://blekko.com/ws/?q=lifehacker+%2Fjson')
doc.ll <- fromJSON(doc)
Then you can check the result like this :
doc.ll$RESULT
I apologize if this has been asked previously, but I haven't been able to find an example online or elsewhere.
I have very dirty data file in a text file (it may be JSON). I want to analyze the data in R, and since I am still new to the language, I want to read in the raw data and manipulate as needed from there.
How would I go about reading in JSON from a text file on my machine? Additionally, if it isn't JSON, how can I read in the raw data as is (not parsed into columns, etc.) so I can go ahead and figure out how to parse it as needed?
Thanks in advance!
Use the rjson package. In particular, look at the fromJSON function in the documentation.
If you want further pointers, then search for rjson at the R Bloggers website.
If you want to use the packages related to JSON in R, there are a number of other posts on SO answering this. I presume you searched on JSON [r] already on this site, plenty of info there.
If you just want to read in the text file line by line and process later on, then you can use either scan() or readLines(). They appear to do the same thing, but there's an important difference between them.
scan() lets you define what kind of objects you want to find, how many, and so on. Read the help file for more info. You can use scan to read in every word/number/sign as element of a vector using eg scan(filename,""). You can also use specific delimiters to separate the data. See also the examples in the help files.
To read line by line, you use readLines(filename) or scan(filename,"",sep="\n"). It gives you a vector with the lines of the file as elements. This again allows you to do custom processing of the text. Then again, if you really have to do this often, you might want to consider doing this in Perl.
Suppose your file is in JSON format, you may try the packages jsonlite ou RJSONIO or rjson. These three package allows you to use the function fromJSON.
To install a package you use the install.packages function. For example:
install.packages("jsonlite")
And, whenever the package is installed, you can load using the function library.
library(jsonlite)
Generally, the line-delimited JSON has one object per line. So, you need to read line by line and collecting the objects. For example:
con <- file('myBigJsonFile.json')
open(con)
objects <- list()
index <- 1
while (length(line <- readLines(con, n = 1, warn = FALSE)) > 0) {
objects[[index]] <- fromJSON(line)
index <- index + 1
}
close(con)
After that, you have all the data in the objects variable. With that variable you may extract the information you want.