How to output orgmode julia DataFrame as orgtbl?

Question

In the following link, we see that we can use a table package in Python to return in orgtbl format.

#+begin_src python :results value raw :output :return tabulate(df, headers=df.columns, tablefmt='orgtbl')
from tabulate import tabulate
import pandas as pd
df = pd.DataFrame({
    "a": [1,2,3],
    "b": [4,5,6]
})
#+end_src

#+RESULTS:
|   | a | b |
|---+---+---|
| 0 | 1 | 4 |
| 1 | 2 | 5 |
| 2 | 3 | 6 |

Get pandas data-frame as a table in org-babel

But, how can we do that in Julia? I know It's possible to utilize PyCall to import and use Python libraries. But, I seem unable to pull this one off.

What I have until now:

#+begin_src julia :session main :result output
tabulate.tabulate
#+end_src

#+RESULTS:
: PyObject <function tabulate at 0x7f182faaab80>

Trying to output calling tabulate.tabulate (doesn't work),

#+begin_src julia :session main :return tabulate.tabulate(py"df_raw, headers=df_raw.columns, tablefmt='orgtbl'")
  @chain df_raw begin
      groupby([:target, :sex])
      combine(nrow)
  end
#+end_src

Also doesn't work, tabulate.tabulate(py"df_raw, headers=df_raw.columns, tablefmt='orgtbl'") or tabulate.tabulate(df_raw)

With the following error:

julia> tabulate.tabulate(df_raw)
ERROR: (in a Julia function called from Python)
JULIA: AbstractDataFrame is not iterable. Use eachrow(df) to get a row iterator or eachcol(df) to get a column iterator
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:33
  [2] iterate(#unused#::DataFrame)
    @ DataFrames ~/.julia/packages/DataFrames/vuMM8/src/abstractdataframe/iteration.jl:23

NOTE: df_raw is a random DataFrame,

help?> df_raw
search: df_raw dof_residual default_cgrad

  No documentation found.

  df_raw is of type DataFrame.

  Summary
  ≡≡≡≡≡≡≡≡≡

  struct DataFrame <: AbstractDataFrame

  Fields
  ≡≡≡≡≡≡≡≡

  columns  :: Vector{AbstractVector{T} where T}
  colindex :: DataFrames.Index

  Supertype Hierarchy
  ≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡

  DataFrame <: AbstractDataFrame <: Any