Transform all DataFrame Columns of a specific Type in Julia

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

or

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.)

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

or

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