Thank you! That makes it much easier to answer.

So I think @josevalim’s answer was what you want (for now, see below):

df = DF.new([
  %{start_day: 244, end_day: 248, fw: 15.0},
  %{start_day: 247, end_day: 249, fw: 16.0}
])

df
|> DF.to_rows()
|> Enum.with_index()
|> Enum.flat_map(fn {row, index} ->
  row["start_day"]..row["end_day"]
  |> Enum.map(&Map.merge(row, %{"day" => &1, "index" => index}))
end)
|> DF.new()
|> DF.arrange(index) # You can order by any column
|> DF.print(limit: :infinity)
# +---------------------------------------------------------+
# |        Explorer DataFrame: [rows: 8, columns: 5]        |
# +-----------+-----------+---------+-----------+-----------+
# |    day    |  end_day  |   fw    |   index   | start_day |
# | <integer> | <integer> | <float> | <integer> | <integer> |
# +===========+===========+=========+===========+===========+
# | 244       | 248       | 15.0    | 0         | 244       |
# +-----------+-----------+---------+-----------+-----------+
# | 245       | 248       | 15.0    | 0         | 244       |
# +-----------+-----------+---------+-----------+-----------+
# | 246       | 248       | 15.0    | 0         | 244       |
# +-----------+-----------+---------+-----------+-----------+
# | 247       | 248       | 15.0    | 0         | 244       |
# +-----------+-----------+---------+-----------+-----------+
# | 248       | 248       | 15.0    | 0         | 244       |
# +-----------+-----------+---------+-----------+-----------+
# | 247       | 249       | 16.0    | 1         | 247       |
# +-----------+-----------+---------+-----------+-----------+
# | 248       | 249       | 16.0    | 1         | 247       |
# +-----------+-----------+---------+-----------+-----------+
# | 249       | 249       | 16.0    | 1         | 247       |
# +-----------+-----------+---------+-----------+-----------+

Also, I don’t want to speak for the core team, but explode does appear to be on the roadmap:

https://github.com/elixir-explorer/explorer/issues/296

So if/when that functionality is added, you can do a nearly one-to-one translation of the Pandas code.