Support DataFrame Interchange Protocol

[jonmmease]

Closes #243

This PR adds support for Python objects that implement the DataFrame Interchange Protocol. Altair is adding support for this protocol in version 5.

Here is an example with polars (and Altair 5 and pyarrow 11.0.0)

import vegafusion as vf
import altair as alt
import polars as pl

vf.enable()
pl_df = pl.read_parquet("https://vegafusion-datasets.s3.amazonaws.com/vega/movies_1m.parquet")

chart = alt.Chart(pl_df).mark_bar().encode(
    alt.X("IMDB_Rating:Q", bin=True),
    alt.Y("count()")
)
chart

Internally, the polars DataFrame is zero-copy converted into a PyArrow table, which is then processed by DataFusion. No conversion to/from pandas is involved, so it's really fast. Here's a speed comparison

Polars

%%time
pl_df = pl.read_parquet("https://vegafusion-datasets.s3.amazonaws.com/vega/movies_1m.parquet")

CPU times: user 297 ms, sys: 136 ms, total: 433 ms
Wall time: 1.2 s

%%time
chart = alt.Chart(pl_df).mark_bar().encode(
    alt.X("IMDB_Rating:Q", bin=True),
    alt.Y("count()")
)
vf.transformed_data(chart)

CPU times: user 231 ms, sys: 69.5 ms, total: 301 ms
Wall time: 223 ms

pandas

%%time
pd_df = pd.read_parquet("https://vegafusion-datasets.s3.amazonaws.com/vega/movies_1m.parquet")

CPU times: user 454 ms, sys: 203 ms, total: 657 ms
Wall time: 3.2 s

%%time
chart = alt.Chart(pd_df).mark_bar().encode(
    alt.X("IMDB_Rating:Q", bin=True),
    alt.Y("count()")
)
vf.transformed_data(chart)

CPU times: user 558 ms, sys: 101 ms, total: 659 ms
Wall time: 601 ms

Geo Interface

By being more careful about the input data types, this PR also closes #250