[julia] 参照元のデータフレームの値が変わってしまう問題

Question

Juliaでデータフレームを参照する関数を使用した際に参照元のデータフレームの値が変わってしまいます。変わらないで参照する方法はありますか？

↓これだとaの値が変わる
a = Dataframe(a=[1,2,3], b = [3,4,5])
function add(df)
    df[c] = fill(NaN, size(df, 1))
    for row in eachrow(df)
        row.c = a * b
    end
    return df
end

↓これでもaの値が変わる
a = Dataframe(a=[1,2,3], b = [3,4,5])
function add(oldDF)
    df = oldDF
    df[c] = fill(NaN, size(df, 1))
    for row in eachrow(df)
        row.c = a * b
    end
    return df
end

↓これでもaの値が変わる
a = Dataframe(a=[1,2,3], b = [3,4,5])
function add(oldDF)
    df = oldDF[:, :]
    df[c] = fill(NaN, size(df, 1))
    for row in eachrow(df)
        row.c = a * b
    end
    return df
end

Answer 1

Argument Passing Behavior - Functions · The Julia Language

Julia function arguments follow a convention sometimes called "pass-by-sharing", which means that values are not copied when they are passed to functions. Function arguments themselves act as new variable bindings (new "names" that can refer to values), much like assignments argument_name = argument_value, so that the objects they refer to are identical to the passed values. Modifications to mutable values (such as Arrays) made within a function will be visible to the caller. (This is the same behavior found in Scheme, most Lisps, Python, Ruby and Perl, among other dynamic languages.)

なので、データフレームを deep copy します。

using DataFrames

a = DataFrame(a=[1,2,3], b = [3,4,5])
function add(df)
    df = deepcopy(df)
    df[!, "c"] = fill(NaN, size(df, 1))
    for row in eachrow(df)
        row.c = row.a * row.b
    end
    return df
end

println(add(a))
println(a)

# 3×3 DataFrame
#  Row │ a      b      c
#      │ Int64  Int64  Float64
# ─────┼───────────────────────
#    1 │     1      3      3.0
#    2 │     2      4      8.0
#    3 │     3      5     15.0
#
# 3×2 DataFrame
#  Row │ a      b
#      │ Int64  Int64
# ─────┼──────────────
#    1 │     1      3
#    2 │     2      4
#    3 │     3      5

Comments

[akirayoshimura]

melianさん回答ありがとうございます！
解決出来ました！