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"""
Stacked Density Estimates
-------------------------
To plot a stacked graph of estimates, use a shared ``extent`` and a fixed
number of subdivision ``steps`` to ensure that the points for each area align
well. Density estimates of measurements for each iris flower feature are plot
in a stacked method. In addition, setting ``counts`` to true multiplies the
densities by the number of data points in each group, preserving proportional
differences.
"""
# category: distributions
import altair as alt
from vega_datasets import data
source = data.iris()
alt.Chart(source).transform_fold(
['petalWidth',
'petalLength',
'sepalWidth',
'sepalLength'],
as_ = ['Measurement_type', 'value']
).transform_density(
density='value',
bandwidth=0.3,
groupby=['Measurement_type'],
extent= [0, 8],
counts = True,
steps=200
).mark_area().encode(
alt.X('value:Q'),
alt.Y('density:Q', stack='zero'),
alt.Color('Measurement_type:N')
).properties(width=400, height=100)
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