Consider necessary columns from complex arguments when interchanging dataframes

[guyrosin]

This PR fixes a regression from #4286, where only plain string arguments were considered as necessary columns when interchanging dataframes. This PR considers complex arguments as well (such as hover_data).

For example, running the code below resulted in ValueError: Value of 'hover_data_0' is not the name of a column in 'data_frame'. Expected one of ['petal_length', 'sepal_length'] but received: species

import numpy as np
import plotly.express as px
import polars as pl

df = px.data.iris()
px.scatter(
    pl.from_pandas(df),
    x="petal_length",
    y="sepal_length",
    hover_data=["species"],  # <-- this was unsupported
)

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• I have added tests (if submitting a new feature or correcting a bug) or
  modified existing tests.
• For a new feature, I have added documentation examples in an existing or
  new tutorial notebook (please see the doc checklist as well).
• I have added a CHANGELOG entry if fixing/changing/adding anything substantial.
• For a new feature or a change in behaviour, I have updated the relevant docstrings in the code to describe the feature or behaviour (please see the doc checklist as well).

[alexcjohnson]

Thanks so much @guyrosin ! Would you add a changelog entry, in a new ## UNRELEASED section at the top? Then I think this is ready to go, and we'll try to get a patch out shortly.

[guyrosin]

Done. That's great to hear! Thanks @alexcjohnson for the feedback

[alexcjohnson]

💃 Very nice! Thanks again for identifying AND fixing this regression @guyrosin