https://github.com/JuliaLang/julia/issues/16966
> -----Original Message----- > From: julia-users@googlegroups.com [mailto:julia- > us...@googlegroups.com] On Behalf Of Milan Bouchet-Valat > Sent: Thursday, June 16, 2016 1:33 AM > To: julia-users@googlegroups.com > Subject: Re: [julia-users] Re: parse.(Int64, x) > > Le mercredi 15 juin 2016 à 17:28 -0700, Tony Kelman a écrit : > > Try parse.([Int64], x) > > note that the output will be an Array{Any} because issue #4883 hasn't > > been fixed yet. The issue here is that broadcast doesn't treat types > > as "scalar-like." > Is the latter a separate bug? Should we open an issue for that? > > > > > map of course works, but it is quite verbose. I’ve been working a > > > group of new julia users lately, many of them from other languages > > > like R, Python etc., and they roll their eyes when something that > > > simple takes > > > > > > df[:x] = map(q->parse(Int64,q), df[:x]) > > > > > > It just is quite complicated for something pretty simple… Maybe > > > there are other simple constructs for this? > > > > > > Thanks, > > > David > > > > > > From: julia...@googlegroups.com [mailto:julia...@googlegroups.com] > > > On Behalf Of John Myles White > > > Sent: Wednesday, June 15, 2016 3:53 PM > > > To: julia-users <julia...@googlegroups.com> > > > Subject: [julia-users] Re: parse.(Int64, x) > > > > > > I would be careful combining element-wise function application with > > > partial function application. Why not use map instead? > > > > > > On Wednesday, June 15, 2016 at 3:47:05 PM UTC-7, David Anthoff > > > wrote: > > > I just tried to use the new dot syntax for vectorising function > > > calls in order to convert an array of strings into an array of > > > Int64. For example, if this would work, it would be very, very > > > handy: > > > > > > x = [“1”, “2”, “3”] > > > parse.(Int64, x) > > > > > > Right now I get an error, but I wonder whether this could be enabled > > > somehow in this new framework? If this would work for all sorts of > > > parsing, type conversions etc. it would just be fantastic. > > > Especially when working DataFrames and one is in the first phase of > > > cleaning up data types of columns etc. this would make for a very > > > nice and short notation. > > > > > > Thanks, > > > David > > > > > > -- > > > David Anthoff > > > University of California, Berkeley > > > > > > http://www.david-anthoff.com > > > > > >
