带散点图的Altair链接地图

Question

I am trying to create a linked plot similar to examples here and here . I want a scatter plot on one side and a geomap on the other. The dots in the scatter plot will show up as dots on their corresponding geolocations on the map. Once I select a few points on the scatter plot, I'd like to see only those points on the map, or vice versa. However, couldn't get it done.

I think the problem is the base, or the values used in their x and y axes of these plots. The scatter plot's base uses just values (the dataframe, two numeric columns selected), while geomap has lat and long (the topojson file, the latitude and longitude columns used for adding the points onto the map). You can think of the dataset as the one from vegasets: data.airports() with two more numeric columns. And the topojson as data.us_10m.url

Is there a way to establish a connection between them?

Answer 1

Working from the US Airports example plot and adding an accompanying scatter plot, you can do something like this:

import altair as alt
from vega_datasets import data

airports = data.airports()
states = alt.topo_feature(data.us_10m.url, feature='states')
selection = alt.selection_interval()

# US states background
background = alt.Chart(states).mark_geoshape(
    fill='lightgray',
    stroke='white'
).properties(
    width=500,
    height=300
).project('albersUsa')

# airport positions on background
points = alt.Chart(airports).mark_circle(
    size=10,
).encode(
    longitude='longitude:Q',
    latitude='latitude:Q',
    tooltip=['name', 'city', 'state'],
    color=alt.condition(selection, alt.value('steelblue'), alt.value('lightgray'))
)

#lat/lon scatter
scatter = alt.Chart(airports).mark_point().encode(
    x='longitude:Q',
    y='latitude:Q',
    color=alt.condition(selection, alt.value('steelblue'), alt.value('lightgray'))   
).add_selection(
    selection
)

scatter | (background + points)

Note that interval selections are currently not supported on geographic projections, so it will not be possible to select points on the map itself.