You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
library(rjstat)oecd.canada.url <-"https://json-stat.org/samples/oecd-canada.json"# Read from JSON-statto a list of data frames:results <- fromJSONstat(readLines(oecd.canada.url))names(results)## [1]"Unemployment rate in the OECD countries 2003-2014"## [2]"Population by sex and age group. Canada. 2012"# You can also read in using the typically terser IDs rather than labels.results <- fromJSONstat(readLines(oecd.canada.url), naming="id")names(results)## [1]"oecd""canada"# Convert from a list of data frames to a JSON-statstring.# (The data frames must have exactly one value column.)library(reshape)irises <- melt(cbind(iris, Specimen=rep(1:50,3)), id.vars=c("Species","Specimen"))irisJSONstat<- toJSONstat(list(iris=irises))cat(substr(irisJSONstat,1,76))## {"version":"2.0","class":"collection","link":{"item":[{"class":"dataset","id# You can successfully convert back and forth, but only for the features that# make sense in both R and JSON-stat.head(fromJSONstat(irisJSONstat)[[1]])## Species Specimen variable value## 1 setosa 1 Sepal.Length 5.1## 2 setosa 1 Sepal.Width 3.5## 3 setosa 1 Petal.Length 1.4## 4 setosa 1 Petal.Width 0.2## 5 setosa 2 Sepal.Length 4.9## 6 setosa 2 Sepal.Width 3.0