Convert column dtypes to pyarrow by default in .from_dataframe()

[hombit]

Feature request

As a part of our transition to pyarrow dtypes, it would be great to convert dtypes of input arrays in .from_dataframe(). We still may have an opt-out options, when users have pyarrow-incompatible types (i.e. object) or wish to keep their types for a different reason.

Implementation ideas

Dataframe types may be converted in this way:

import pandas as pd
import pyarrow as pa

def convert_dtypes_to_pyarrow(df):
    new_series = {}
    for column in df.columns:
        try:
            pa_array = pa.array(df[column], from_pandas=True)
        except (ValueError, TypeError):
            raise ...
        series = pd.Series(
            pa_array,
            dtype=pd.ArrowDtype(pa_array.type),
            copy=False,
        )
        new_series[column] = series
    return pd.DataFrame(new_series, index=df.index, name=df.name, copy=False)

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• I have described the purpose of the suggested change, specifying what I need the enhancement to accomplish, i.e. what problem it solves.
• I have included any relevant links, screenshots, environment information, and data relevant to implementing the requested feature, as well as pseudocode for how I want to access the new functionality.
• If I have ideas for how the new feature could be implemented, I have provided explanations and/or pseudocode and/or task lists for the steps.