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Support transformed_data for Layered and Concatenated charts #313

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May 13, 2023
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Original file line number Diff line number Diff line change
@@ -1,5 +1,3 @@
# https://altair-viz.github.io/gallery/seattle_weather_interactive.html

import altair as alt
from vega_datasets import data

Expand All @@ -13,7 +11,7 @@
# - a brush that is active on the top panel
# - a multi-click that is active on the bottom panel
brush = alt.selection_interval(encodings=['x'])
click = alt.selection_multi(encodings=['color'])
click = alt.selection_point(encodings=['color'])

# Top panel is scatter plot of temperature vs time
points = alt.Chart().mark_point().encode(
Expand All @@ -27,7 +25,7 @@
).properties(
width=550,
height=300
).add_selection(
).add_params(
brush
).transform_filter(
click
Expand All @@ -42,7 +40,7 @@
brush
).properties(
width=550,
).add_selection(
).add_params(
click
)

Expand All @@ -51,4 +49,4 @@
bars,
data=source,
title="Seattle Weather: 2012-2015"
)
)
Original file line number Diff line number Diff line change
@@ -1,15 +1,14 @@
# https://altair-viz.github.io/gallery/us_population_pyramid_over_time.html

import altair as alt
from vega_datasets import data

source = data.population.url

slider = alt.binding_range(min=1850, max=2000, step=10)
select_year = alt.selection_single(name='year', fields=['year'],
bind=slider, init={'year': 2000})
select_year = alt.selection_point(name='year', fields=['year'],
bind=slider, value={'year': 2000})

base = alt.Chart(source).add_selection(
base = alt.Chart(source).add_params(
select_year
).transform_filter(
select_year
Expand Down Expand Up @@ -46,4 +45,4 @@
color=alt.Color('gender:N', scale=color_scale, legend=None)
).mark_bar().properties(title='Male')

alt.concat(left, middle, right, spacing=5)
alt.concat(left, middle, right, spacing=5)
Original file line number Diff line number Diff line change
@@ -1,12 +1,9 @@
# https://altair-viz.github.io/gallery/interactive_cross_highlight.html
# - Selection count legend removed to keep from shifting bar chart

import altair as alt
from vega_datasets import data

source = data.movies.url

pts = alt.selection(type="single", encodings=['x'])
pts = alt.selection_point(encodings=['x'])

rect = alt.Chart(data.movies.url).mark_rect().encode(
alt.X('IMDB_Rating:Q', bin=True),
Expand All @@ -15,34 +12,30 @@
scale=alt.Scale(scheme='greenblue'),
legend=alt.Legend(title='Total Records')
)
).properties(
width=500,
height=250
)

circ = rect.mark_point().encode(
alt.ColorValue('grey'),
alt.Size('count()', legend=None)
alt.Size('count()',
legend=alt.Legend(title='Records in Selection')
)
).transform_filter(
pts
).properties(
width=500,
height=250
)

bar = alt.Chart(source).mark_bar().encode(
x='Major_Genre:N',
y='count()',
color=alt.condition(pts, alt.ColorValue("steelblue"), alt.ColorValue("grey"))
).properties(
width=500,
height=100
).add_selection(pts)
width=550,
height=200
).add_params(pts)

alt.vconcat(
rect + circ,
bar
).resolve_legend(
color="independent",
size="independent"
)
)
Original file line number Diff line number Diff line change
@@ -1,12 +1,10 @@
# https://altair-viz.github.io/gallery/multiline_highlight.html

import altair as alt
from vega_datasets import data

source = data.stocks()

highlight = alt.selection(type='single', on='mouseover',
fields=['symbol'], nearest=True)
highlight = alt.selection_point(on='mouseover',
fields=['symbol'], nearest=True)

base = alt.Chart(source).encode(
x='date:T',
Expand All @@ -16,14 +14,14 @@

points = base.mark_circle().encode(
opacity=alt.value(0)
).add_selection(
).add_params(
highlight
).properties(
width=500
width=600
)

lines = base.mark_line().encode(
size=alt.condition(~highlight, alt.value(1), alt.value(3))
)

points + lines
points + lines
Original file line number Diff line number Diff line change
@@ -1,5 +1,3 @@
# https://altair-viz.github.io/gallery/multiline_tooltip.html

import altair as alt
import pandas as pd
import numpy as np
Expand All @@ -10,8 +8,8 @@
source = source.reset_index().melt('x', var_name='category', value_name='y')

# Create a selection that chooses the nearest point & selects based on x-value
nearest = alt.selection(type='single', nearest=True, on='mouseover',
fields=['x'], empty='none')
nearest = alt.selection_point(nearest=True, on='mouseover',
fields=['x'], empty=False)

# The basic line
line = alt.Chart(source).mark_line(interpolate='basis').encode(
Expand All @@ -25,7 +23,7 @@
selectors = alt.Chart(source).mark_point().encode(
x='x:Q',
opacity=alt.value(0),
).add_selection(
).add_params(
nearest
)

Expand All @@ -50,5 +48,5 @@
alt.layer(
line, selectors, points, rules, text
).properties(
width=500, height=300
width=600, height=300
)
Original file line number Diff line number Diff line change
@@ -1,19 +1,17 @@
# https://altair-viz.github.io/gallery/scatter_linked_table.html

import altair as alt
from vega_datasets import data

source = data.cars()

# Brush for selection
brush = alt.selection(type='interval')
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_selection(brush)
).add_params(brush)

# Base chart for data tables
ranked_text = alt.Chart(source).mark_text().encode(
Expand Down
Original file line number Diff line number Diff line change
@@ -1,6 +1,3 @@
# https://altair-viz.github.io/gallery/scatter_with_minimap.html
# with smaller subplots

import altair as alt
from vega_datasets import data

Expand All @@ -10,33 +7,34 @@

minimap = (
alt.Chart(source)
.mark_point()
.add_selection(zoom)
.encode(
.mark_point()
.add_params(zoom)
.encode(
x="date:T",
y="temp_max:Q",
color=alt.condition(zoom, "weather", alt.value("lightgray")),
)
.properties(
.properties(
width=200,
height=200,
title="Minimap -- click and drag to zoom in the detail view",
)
).properties(width=250, height=300)
)

detail = (
alt.Chart(source)
.mark_point()
.encode(
.mark_point()
.encode(
x=alt.X(
"date:T", scale=alt.Scale(domain={"selection": zoom.name, "encoding": "x"})
"date:T", scale=alt.Scale(domain={"param": zoom.name, "encoding": "x"})
),
y=alt.Y(
"temp_max:Q",
scale=alt.Scale(domain={"selection": zoom.name, "encoding": "y"}),
scale=alt.Scale(domain={"param": zoom.name, "encoding": "y"}),
),
color="weather",
).properties(width=250, height=300, title="Seattle weather -- detail view")
)
.properties(width=600, height=400, title="Seattle weather -- detail view")
)

detail | minimap
detail | minimap
Original file line number Diff line number Diff line change
@@ -1,12 +1,7 @@
# https://altair-viz.github.io/gallery/scatter_with_histogram.html
# With smaller subplots and a random seed

import altair as alt
import pandas as pd
import numpy as np

np.random.seed(1)

x = np.random.normal(size=100)
y = np.random.normal(size=100)

Expand All @@ -15,7 +10,7 @@
source = pd.DataFrame({"x": x, "y":y, "m":m})

# interval selection in the scatter plot
pts = alt.selection(type="interval", encodings=["x"])
pts = alt.selection_interval(encodings=["x"])

# left panel: scatter plot
points = alt.Chart().mark_point(filled=True, color="black").encode(
Expand All @@ -24,7 +19,7 @@
).transform_filter(
pts
).properties(
width=250,
width=300,
height=300
)

Expand All @@ -34,9 +29,9 @@
y="count()",
color=alt.condition(pts, alt.value("black"), alt.value("lightgray"))
).properties(
width=250,
width=300,
height=300
).add_selection(pts)
).add_params(pts)

# build the chart:
alt.hconcat(
Expand All @@ -47,4 +42,4 @@
"mbin",
field="m",
bin=alt.Bin(maxbins=20)
)
)
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