We really need to standardize on a single type that reflects a single row of a
tabular data structure that gets used both by DBI and by DataFrames.
DataFrameRow is really nice because it's a zero-copy operation for DataFrames,
but we can't provide zero-copy semantics when pulling rows out of a database.
I tend to think we should have all tabular data systems use an OrderedDict to
represent a single row of data.
We could then change eachrow(df) to mutate a one-time allocated OrderedDict.
This involves non-trivial copying, but it syncs up closer with the idioms you'd
use when working with DBI.
-- John
On Sep 12, 2014, at 10:15 AM, Leah Hanson <astriea...@gmail.com> wrote:
> Oh, I didn't realize that. So, `eachrow(df)` is giving you
> `[(:a,"hi"),(:x,0.703943)]` when you need `["hi",0.703943]` to use `push!`.
>
> ~~~
> julia> df = DataFrame(a=["hi","there"],x = rand(2))
> 2x2 DataFrame
> |-------|---------|----------|
> | Row # | a | x |
> | 1 | "hi" | 0.703943 |
> | 2 | "there" | 0.269876 |
>
> julia> df2 = DataFrame(a=["oh","yeah"],x = rand(2))
> 2x2 DataFrame
> |-------|--------|----------|
> | Row # | a | x |
> | 1 | "oh" | 0.138966 |
> | 2 | "yeah" | 0.856162 |
>
> julia> for e = eachrow(df)
> push!(df2,[v for (_,v) in e])
> end
>
> julia> df2
> 4x2 DataFrame
> |-------|---------|----------|
> | Row # | a | x |
> | 1 | "oh" | 0.138966 |
> | 2 | "yeah" | 0.856162 |
> | 3 | "hi" | 0.703943 |
> | 4 | "there" | 0.269876 |
> ~~~
>
> Does this work for you?
>
> -- Leah
>
> On Fri, Sep 12, 2014 at 8:54 AM, Florian Oswald <florian.osw...@gmail.com>
> wrote:
> yeah I wasn't very clear in that example. i really need to append one row at
> a time.
>
> On 12 September 2014 14:50, Leah Hanson <astriea...@gmail.com> wrote:
> Have you tried append!(df2,df)?
>
> ~~~
> julia> using DataFrames
>
>
>
> julia> df = DataFrame(a=["hi","there"],x = rand(2))
>
>
> 2x2 DataFrame
> |-------|---------|----------|
> | Row # | a | x |
> | 1 | "hi" | 0.862957 |
> | 2 | "there" | 0.101378 |
>
>
>
> julia> df2 = DataFrame(a=["oh","yeah"],x = rand(2))
>
>
> 2x2 DataFrame
> |-------|--------|------------|
> | Row # | a | x |
> | 1 | "oh" | 0.00803615 |
> | 2 | "yeah" | 0.0222873 |
>
>
>
> julia> append!(df2,df)
>
>
> 4x2 DataFrame
> |-------|---------|------------|
> | Row # | a | x |
> | 1 | "oh" | 0.00803615 |
> | 2 | "yeah" | 0.0222873 |
> | 3 | "hi" | 0.862957 |
> | 4 | "there" | 0.101378 |
> ~~~
>
>
>
> On Fri, Sep 12, 2014 at 7:57 AM, Florian Oswald <florian.osw...@gmail.com>
> wrote:
> i'm trying to do this:
>
> using DataFrames
> df = DataFrame(a=["hi","there"],x = rand(2))
> df2 = DataFrame(a=["oh","yeah"],x = rand(2))
>
> for e in eachrow(df)
> append!(df2,e)
> end
>
> ERROR: `append!` has no method matching append!(::DataFrame,
> ::DataFrameRow{DataFrame})
> in anonymous at no file:2
>
> or
>
> julia> for i in 1:nrow(df)
> push!(df2,df[i,:])
> end
>
> but that errors as well.
>
> this works:
>
> julia> for i in 1:nrow(df)
> push!(df2,array(df[i,:]))
> end
>
> but wondering whether that's the best way of achieving this efficiently.
>
>
>
