Julia dataframe where a column is an array of arrays? -

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i'm trying create table each row has time-series data associated particular test-case.

julia> df = dataframe(var1 = int64[], var2 = int64[], ts = array{array{int64, 1}, 1}) 0x3 dataframes.dataframe

i'm able create data frame. each var1, var2 pair intended have associated time series.

i want generate data in loop , want append dataframe using push!

i've tried

julia> push!(df, [1, 2, [3,4,5]]) error: argumenterror: length of iterable not match dataframe column count.   in push! @ /users/stro/.julia/v0.4/dataframes/src/dataframe/dataframe.jl:871

and 

julia> push!(df, (1, 2, [3,4,5])) error: argumenterror: error adding [3,4,5] column :ts. possible type mis-match.  in push! @ /users/stro/.julia/v0.4/dataframes/src/dataframe/dataframe.jl:883

what's best way go this? intended approach right path?

you've accidentally put type of vector in instead of actual vector. declaration work:

df = dataframe(var1 = int64[], var2 = int64[], ts = array{int64, 1}[])

note change array{array{int64, 1}, 1}, type, array{int64, 1}[], actual vector type.

then things work:

julia> push!(df, (1, 2, [3,4,5]))  julia> df 1x3 dataframes.dataframe │ row │ var1 │ var2 │ ts      │ ┝━━━━━┿━━━━━━┿━━━━━━┿━━━━━━━━━┥ │ 1   │ 1    │ 2    │ [3,4,5] │

note other example, using [1, 2, [3,4,5]] still not work. because quirk in julia's array syntax means comma , operator concatenation, in fact [1, 2, [3,4,5]] means [1, 2, 3, 4, 5]. behaviour weird , fixed in julia 0.5, preserved in 0.4 backwards compatibility.


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