replace missing values in julia DataFrame only for subset of columns

New to Julia alert! I have the following Julia DataFrame that includes missing values:

dat = DataFrame(a = [1,missing,3], b = [missing,5,6], c = [7,8,missing])

I want to replace missing values only for the following subset of the columns

relevant_cols = [:a, :b]

and leave the other column (c) the way it is.

The following options replace the missing values in the relevant columns, but they both drop the other column c which I want to keep just the way it is.

 coalesce.(dat[!,relevant_cols], 0)
 mapcols(col -> replace(col, missing => 0), dat[!,relevant_cols])

How can I replace missing values in a subset of columns but still keep the others?

Using ifelse might be the most straightforward way

cols = [:a, :b]

dat[:, cols] = ifelse.(ismissing.(dat[:, cols]), 0, dat[:, cols]);

dat
3×3 DataFrame
 Row │ a       b       c
     │ Int64?  Int64?  Int64?
─────┼─────────────────────────
   1 │      1       0        7
   2 │      0       5        8
   3 │      3       6  missing

or using a loop and replace

cols = [:a, :b]

for i in cols
  dat[:, i] = replace(dat[:, i], missing => 0)
end

dat
3×3 DataFrame
 Row │ a       b       c
     │ Int64?  Int64?  Int64?
─────┼─────────────────────────
   1 │      1       0        7
   2 │      0       5        8
   3 │      3       6  missing