You're right: any iterable could work. Personally, I tend to minimize the use of functionality that depends upon the columns of a DataFrame being in a specific order. It's certainly useful in many cases, so we can't get rid of it. But I'm not excited about people writing a lot more code that depends upon order than they do now.
-- John On Jun 6, 2014, at 1:07 PM, Ivar Nesje <[email protected]> wrote: > Why can't any iterable (of the correct length) be accepted? > > As long as the DataFrame have predefined types on the columns, it is just a > matter of asserting or converting the type and copy it inn. Convert would > probably be slower because the types would be unknown and it would have to > dispatch dynamically to the right convert method. > > kl. 18:58:51 UTC+2 fredag 6. juni 2014 skrev John Myles White følgende: > Yeah, I just dislike the gratuituous multiplicity of ways to do the same > thing. > > -- John > > On Jun 6, 2014, at 9:55 AM, Stefan Karpinski <[email protected]> wrote: > >> Since all three can be indexed the same way, it seems like that should be a >> minimal annoyance, no? >> >> On Friday, June 6, 2014, John Myles White <[email protected]> wrote: >> 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? >>>> >>> >> >
