Let's introduce unnest_wider() in TidierData.jl!

[atantos]

Hey there!

In R's tidyverse, the unnest_wider() function provides a convenient way to spread the contents of a column, which contains arrays or lists of values, across multiple new columns. Let's consider a DataFrame named test and see how we'd like the result to appear:

test = DataFrame(a = [1,2], b = [["c","d"],["e", "f"]])

# result
result = DataFrame(a = [1,2], b_1 = ["c" , "e"], b_2 = ["d", "f"])

To achieve that with R's tidyverse we would have:

> data <- tibble(
  a = c(1,2),
  b = list(c("c","d"), c("e", "f"))
)

> data_wide <- data %>% 
  unnest_wider(b, names_sep = "_")

> data_wide
# A tibble: 2 × 3
      a b_1   b_2  
  <dbl> <chr> <chr>
1     1 c     d    
2     2 e     f    

To achieve a similar result in Julia using the DataFrames.jl package, the process is straightforward, albeit with a distinct Julia-idiomatic flavor. First, we'd define a function, split_uniformly(), to handle the transformation. Then, we'd use this function within the transformation pipeline provided by the DataFrames minilanguage:

julia> test = DataFrame(a = [1,2], b = [["c","d"],["e", "f"]])

julia> function split_uniformly(v)
    n = length(first(v))
    [NamedTuple(Symbol.("b", 1:n) .=> Tuple(amem))
     for amem in v]
end

julia> test_wide = @chain test begin
    transform(:b => split_uniformly => AsTable)
    select(Not(:b))
end
2×3 DataFrame
 Row │ a      b1      b2     
     │ Int64  String  String 
─────┼───────────────────────
   1 │     1  c       d
   2 │     2  e       f

[atantos]

A more appropriate place to open this issue is TidierData.jl