Transform all DataFrame Columns of a specific Type in Julia-CodePudding

I have a DataFrame with Int64 columns:

using DataFrames
df = DataFrame(a=1:3,b=4:6,c=["a","b","c"])

3×2 DataFrame
 Row │ a      b      c
     │ Int64  Int64  String
─────┼──────────────────────
   1 │     1      4    a
   2 │     2      5    b
   3 │     3      6    c

Now, I want to change the column types to Float64. I know that I can do something like...

using DataFramesMeta, Chain

@chain df begin
    @transform!(:a = Float64.(:a),
                :b = Float64.(:b))
end

df.a = Float64.(df.a)
df.b = Float64.(df.b)

But how can I change all columns of type Int64 to Float64. Columns of other types should stay as they are.

(As you might guess from the example above I like the combination of Chain and DataFramesMeta, but of course all answers are more than welcome.)

CodePudding user response：

The simplest way to do it is (this updates your original data frame):

df .= Float64.(df)

With transform! you can alternatively do:

transform!(df, All() .=> ByRow(Float64), renamecols=false)

or you can also do:

mapcols!(ByRow(Float64), df)

(sorry - no DataFramesMeta.jl here yet - but things might change in the future)

If you want to change only e.g. columns that have Int type then do:

julia> transform!(df, names(df, Int) .=> ByRow(Float64), renamecols=false)
3×3 DataFrame
 Row │ a        b        c
     │ Float64  Float64  String
─────┼──────────────────────────
   1 │     1.0      4.0  a
   2 │     2.0      5.0  b
   3 │     3.0      6.0  c

mapcols(df) do col
    eltype(col) === Int ? Float64.(col) : col
end