feature request: make graph_objects also dataframe agnostic

I was wondering, since narwhals was such a success in the plotly express api, whether the graph_objects api could get the same treatment. For the few trace types I tried (Scatter, Bar), arguments such as x, y, marker_color etc., accept tuple, list, numpy array, or pandas Series.

It would be great to be able to pass arrow or polars series as well, via narwhals, though I have no idea how feasible that would really be.

Desired outcome would be something like this:

"""
Fresh environment
>>> uv init
>>> uv add plotly polars
"""

import plotly.graph_objects as go
import polars as pl

df = pl.DataFrame({"x": [0, 1, 2, 3, 4], "y": [0, 1, 4, 9, 16]})

fig = go.Figure()
fig.add_trace(
    go.Scatter(x=df["x"], y=df["y"]),
)
fig.show()

Currently one has to either transform to a list, pandas series, or if numpy is installed, there is some implicit transformation, which allows to pass polars series directly.

Comienza reproduciendo el ejemplo de polars proporcionado mediante la API de graph_objects, centrándote en go.Figure.add_trace con Scatter y Bar. Inspecciona cómo sus argumentos x, y y marker_color manejan actualmente listas, arrays de NumPy y Series de pandas. Se considera terminado cuando los argumentos relevantes de los traces de graph_objects acepten series de polars y Arrow mediante narwhals sin requerir conversión.