Interactive bar and map from a single data source

This is a layered geographic visualization that shows population by country in Africa

import altair as alt
import geopandas as gpd
import gpdvega

alt.renderers.enable('notebook') # render for Jupyter Notebook

world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

brush = alt.selection_single(encodings=["y"],on="mouseover", empty='none')
color = alt.Color('pop_est', scale= alt.Scale(type='pow', exponent=0.4))

alt.hconcat(
    alt.Chart().mark_bar().encode(
        x=alt.X('pop_est', scale=alt.Scale(nice=False)),
        y=alt.Y('name', sort=alt.EncodingSortField(field='pop_est',
                                            op='sum', order='descending')),
        tooltip=['name','pop_est','gdp_md_est'],
        color=alt.condition(brush, alt.value('lightgray'), color)
        ).add_selection(
            brush
        ).properties(
            width=200,
            height=450
        ),
    alt.Chart().mark_geoshape().project().encode(
        color=alt.condition(
            brush,
            alt.value('lightgray'),
            color,
        ),
        tooltip=['name','pop_est','gdp_md_est'],
        ).properties(
            width=300,
            height=450,
            title='Africa population'
        ),
    data=world[world.continent == 'Africa']
)