using RDatasets, JDF, DataFrames

a = dataset("datasets", "iris");

first(a, 2)

@time jdffile = JDF.save("iris.jdf", a) @time a2 = DataFrame(JDF.load("iris.jdf"))

all(names(a2) .== names(a)) # true all(skipmissing([all(a2[!,name] .== Array(a[!,name])) for name in names(a2)])) #true

a2_selected = DataFrame(JDF.load("iris.jdf", cols = [:Species, :SepalLength, :PetalWidth]))

jdf"path/to/JDF.jdf"

path_to_JDF = "path/to/JDF.jdf" JDFFile(path_to_JDF)

afile = JDFFile("iris.jdf")

afile[:Species] # load Species column

using Tables ajdf = JDFFile("iris.jdf") Tables.columnaccess(ajdf)

Tables.columns(ajdf)

Tables.schema(ajdf)

getproperty(Tables.columns(ajdf), :Species)

jdffile = jdf"iris.jdf" for col in eachcol(jdffile)

do something to col

where col is the content of one column of iris.jdf

end

jdffile = jdf"iris.jdf" for (name, col) in zip(names(jdffile), eachcol(jdffile))

name::Symbol is the name of the column

col is the content of one column of iris.jdf

end

using JDF, DataFrames df = DataFrame(a = 1:3, b = 1:3) JDF.save(df, "plsdel.jdf")

names(jdf"plsdel.jdf") # [:a, :b]

clean up

rm("plsdel.jdf", force = true, recursive = true)

@time jdffile = ssavejdf("iris.jdf", a) @time jdffile = sloadjdf("iris.jdf")

type_compress!(df)

type_compress!(df, compress_float = true)