The thing that annoys me about arrays is that we arguably need to accept both vectors and 1-row matrices as inputs.
-- John On Jun 6, 2014, at 9:20 AM, Stefan Karpinski <[email protected]> wrote: > See also https://github.com/JuliaStats/DataFrames.jl/issues/585. Using a > tuple may make more sense, but it probably wouldn't hurt to allow an array as > well. > > On Friday, June 6, 2014, John Myles White <[email protected]> wrote: > If someone wants to submit a PR to allow adding a tuple as a row to a > DataFrame, I’ll merge it. > > — John > > On May 28, 2014, at 7:43 AM, John Myles White <[email protected]> > wrote: > >> I’m happy with using tuples since that will make it easier to construct >> DataFrames from iterators. >> >> — John >> >> On May 27, 2014, at 11:37 PM, Tomas Lycken <[email protected]> wrote: >> >>> I like it - but maybe that wasn't so hard to guess I would ;) >>> >>> // T >>> >>> On Tuesday, May 27, 2014 10:11:15 PM UTC+2, Jacques Rioux wrote: >>> Let me add a thought here. I also think that adding a row to a dataframe >>> should be easier. However, I do not think that an array would be the best >>> container to represent a row because array members must all be of the same >>> type which brings up Any as the only options in your example. >>> >>> I think that appending or pushing a tuple with the right types could be >>> made to work. >>> >>> So it would be >>> >>> julia> push!(psispread, (1.0,0.1,:Fake)) >>> >>> or >>> >>> julia> append!(psispread, (1.0,0.1,:Fake)) >>> >>> since >>> >>> julia> typeof((1.0, 0.1, :fake)) >>> (Float64,Float64,Symbol) >>> >>> Note, I am not saying that this works now but that it could be made to work >>> by adding the corresponding method to either function. It seems it is the >>> right construct. >>> >>> Any thoughts? >> >
