LeAnthony,
I'm wondering if you're on an old version of DataFrames? There haven't been
any issues "show"-ing DataFrames with NullableArray columns for quite some
time. You can check (and post back here) your current package versions by
doing:
Pkg.installed()
You can also ensure you're on the latest valid release by doing:
Pkg.update()
-Jacob
On Thu, Nov 3, 2016 at 3:15 PM, Milan Bouchet-Valat <nalimi...@club.fr>
wrote:
> Le jeudi 03 novembre 2016 à 13:35 -0700, LeAnthony Mathews a écrit :
> > Thanks Michael,
> > I been thinking about this all day. Yes, basically I am going to
> > have to create a macro CSVreadtable that mimics the readtable
> > command, but in the expantion uses CSV.read. The macro will manually
> > constructs a similar readtable sized dataframe array, but use the
> > column types I specify or inherit from the original readtable
> > command. The macro can use the current CSV.read parameters.
> >
> > So this would work.
> > df1_CSVreadtable = CSVreadtable("$df1_path"; types=Dict(1=>String))
> >
> > so a:
> > eltypes(df1_CSVreadtable)
> > 3-element Array{Type,1}:
> > Int32
> > String
> > String
> >
> >
> > Anyway, I was looking for a quick fix, but it least I will learn
> > some Julia.
> If you don't have missing values and just want a Vector{String}, you
> can pass nullable=false to CSV.read().
>
>
> Regards
>
> >
> >
> > > DataFrames is currently undergoing a very major change. Looks like
> > > CSV creates the new type of DataFrames. I hope someone can help you
> > > with using that. As a workaround, on the normal DataFrames version,
> > > I have generally just replaced with a string representation:
> > > ```
> > > df[:account_numbers] = ["$account_number" for account_number in
> > > df[:account_numbers]]
> > >
> > > On Thu, Nov 3, 2016 at 3:05 PM, LeAnthony Mathews <leant...@gmail.c
> > > om> wrote:
> > > > Sure, so I need col #1 in my CSV to be a string in my data frame.
> > > >
> > > >
> > > > So as a test I tried to load the file 3 different ways:
> > > >
> > > > df1_CSV = CSV.read("$df1_path"; types=Dict(1=>String)) #forcing
> > > > the column to stay a string
> > > > df1_readtable = readtable("$df1_path") #Do not know how to force
> > > > the column to stay a string
> > > > df1_convertDF = convert(DataFrame, df1_CSV)
> > > >
> > > > Here is the output: If they are all dataframes then showcols
> > > > should work an all three df1:
> > > >
> > > > julia> names(df1_CSV)
> > > > 3-element Array{Symbol,1}:
> > > > :account_number
> > > > Symbol("Discharge Date")
> > > > :site
> > > >
> > > > julia> names(df1_readtable)
> > > > 3-element Array{Symbol,1}:
> > > > :account_number
> > > > :Discharge_Date
> > > > :site
> > > >
> > > > julia> names(df1_convertDF)
> > > > 3-element Array{Symbol,1}:
> > > > :account_number
> > > > Symbol("Discharge Date")
> > > > :site
> > > >
> > > >
> > > > julia> eltypes(df1_CSV)
> > > > 3-element Array{Type,1}:
> > > > Nullable{String}
> > > > Nullable{WeakRefString{UInt8}}
> > > > Nullable{WeakRefString{UInt8}}
> > > >
> > > > julia> eltypes(df1_readtable)
> > > > 3-element Array{Type,1}:
> > > > Int32 #Do not know how to force the column to stay a string
> > > > String
> > > > String
> > > >
> > > > julia> eltypes(df1_convertDF)
> > > > 3-element Array{Type,1}:
> > > > Nullable{String}
> > > > Nullable{WeakRefString{UInt8}}
> > > > Nullable{WeakRefString{UInt8}}
> > > >
> > > > julia> showcols(df1_convertDF)
> > > > 1565x3 DataFrames.DataFrame
> > > > ERROR: MethodError: no method matching
> > > > countna(::NullableArrays.NullableArray{St
> > > > ring,1})
> > > > Closest candidates are:
> > > > countna(::Array{T,N}) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFrames\src\other\ut
> > > > ils.jl:115
> > > > countna(::DataArrays.DataArray{T,N}) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFram
> > > > es\src\other\utils.jl:128
> > > > countna(::DataArrays.PooledDataArray{T,R<:Integer,N}) at
> > > > C:\Users\lmathews\.ju
> > > > lia\v0.5\DataFrames\src\other\utils.jl:143
> > > > in colmissing(::DataFrames.DataFrame) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFram
> > > > es\src\abstractdataframe\abstractdataframe.jl:657
> > > > in showcols(::Base.TTY, ::DataFrames.DataFrame) at
> > > > C:\Users\lmathews\.julia\v0.
> > > > 5\DataFrames\src\abstractdataframe\show.jl:574
> > > > in showcols(::DataFrames.DataFrame) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFrames
> > > > \src\abstractdataframe\show.jl:581
> > > >
> > > > julia> showcols(df1_readtable)
> > > > 1565x3 DataFrames.DataFrame
> > > > │ Col # │ Name │ Eltype │ Missing │
> > > > ├───────┼────────────────┼────────┼─────────┤
> > > > │ 1 │ account_number │ Int32 │ 0 │
> > > > │ 2 │ Discharge_Date │ String │ 0 │
> > > > │ 3 │ site │ String │ 0 │
> > > >
> > > > julia> showcols(df1_CSV)
> > > > 1565x3 DataFrames.DataFrame
> > > > ERROR: MethodError: no method matching
> > > > countna(::NullableArrays.NullableArray{St
> > > > ring,1})
> > > > Closest candidates are:
> > > > countna(::Array{T,N}) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFrames\src\other\ut
> > > > ils.jl:115
> > > > countna(::DataArrays.DataArray{T,N}) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFram
> > > > es\src\other\utils.jl:128
> > > > countna(::DataArrays.PooledDataArray{T,R<:Integer,N}) at
> > > > C:\Users\lmathews\.ju
> > > > lia\v0.5\DataFrames\src\other\utils.jl:143
> > > > in colmissing(::DataFrames.DataFrame) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFram
> > > > es\src\abstractdataframe\abstractdataframe.jl:657
> > > > in showcols(::Base.TTY, ::DataFrames.DataFrame) at
> > > > C:\Users\lmathews\.julia\v0.
> > > > 5\DataFrames\src\abstractdataframe\show.jl:574
> > > > in showcols(::DataFrames.DataFrame) at
> > > > C:\Users\lmathews\.julia\v0.5\DataFrames
> > > > \src\abstractdataframe\show.jl:581
> > > >
> > > >
> > > >
> > > > > The result of CSV should be a DataFrame by default. What
> > > > > return type do you get?
> > > > >
> > > >
> > >
> > >
>
