Brushing Scatter Plot to Show Data on a Table

A scatter plot of the cars dataset, with data tables for horsepower, MPG, and origin. The tables update to reflect the selection on the scatter plot.

Method syntax

import altair as alt
from vega_datasets import data

source = data.cars()

# Brush for selection
brush = alt.selection_interval()

# Scatter Plot
points = alt.Chart(source).mark_point().encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
    color=alt.condition(brush, alt.value('steelblue'), alt.value('grey'))
).add_params(brush)

# Base chart for data tables
ranked_text = alt.Chart(source).mark_text(align='right').encode(
    y=alt.Y('row_number:O').axis(None)
).transform_filter(
    brush
).transform_window(
    row_number='row_number()'
).transform_filter(
    'datum.row_number < 15'
)

# Data Tables
horsepower = ranked_text.encode(text='Horsepower:N').properties(
    title=alt.TitleParams(text='Horsepower', align='right')
)
mpg = ranked_text.encode(text='Miles_per_Gallon:N').properties(
    title=alt.TitleParams(text='MPG', align='right')
)
origin = ranked_text.encode(text='Origin:N').properties(
    title=alt.TitleParams(text='Origin', align='right')
)
text = alt.hconcat(horsepower, mpg, origin) # Combine data tables

# Build chart
alt.hconcat(
    points,
    text
).resolve_legend(
    color="independent"
).configure_view(
    stroke=None
)

Attribute syntax

import altair as alt
from vega_datasets import data

source = data.cars()

# Brush for selection
brush = alt.selection_interval()

# Scatter Plot
points = alt.Chart(source).mark_point().encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
    color=alt.condition(brush, 'Cylinders:O', alt.value('grey'))
).add_params(brush)

# Base chart for data tables
ranked_text = alt.Chart(source).mark_text().encode(
    y=alt.Y('row_number:O',axis=None)
).transform_window(
    row_number='row_number()'
).transform_filter(
    brush
).transform_window(
    rank='rank(row_number)'
).transform_filter(
    alt.datum.rank<20
)

# Data Tables
horsepower = ranked_text.encode(text='Horsepower:N').properties(title='Horsepower')
mpg = ranked_text.encode(text='Miles_per_Gallon:N').properties(title='MPG')
origin = ranked_text.encode(text='Origin:N').properties(title='Origin')
text = alt.hconcat(horsepower, mpg, origin) # Combine data tables

# Build chart
alt.hconcat(
    points,
    text
).resolve_legend(
    color="independent"
)