"""
Ridgeline plot (Joyplot) Example
--------------------------------
A `Ridgeline plot <https://serialmentor.com/blog/2017/9/15/goodbye-joyplots>`_
chart is a chart that lets you visualize distribution of a numeric value for 
several groups.

Such a chart can be created in Altair by first transforming the data into a
suitable representation.

"""
# category: other charts
import altair as alt
from vega_datasets import data

source = data.seattle_weather.url

step = 20
overlap = 1

ridgeline = alt.Chart(source).transform_timeunit(
    Month='month(date)'
).transform_joinaggregate(
    mean_temp='mean(temp_max)', groupby=['Month']
).transform_bin(
    ['bin_max', 'bin_min'], 'temp_max'
).transform_aggregate(
    value='count()', groupby=['Month', 'mean_temp', 'bin_min', 'bin_max']
).transform_impute(
    impute='value', groupby=['Month', 'mean_temp'], key='bin_min', value=0
).mark_line(
    interpolate='monotone',
    fillOpacity=0.8,
    stroke='lightgray',
    strokeWidth=0.5
).encode(
    alt.X('bin_min:Q', bin='binned', title='Maximum Daily Temperature (C)'),
    alt.Y(
        'value:Q',
        scale=alt.Scale(range=[step, -step * overlap]),
        axis=None
    ),
    alt.Fill(
        'mean_temp:Q',
        legend=None,
        scale=alt.Scale(domain=[30, 5], scheme='redyellowblue')
    ),
    alt.Row(
        'Month:T',
        title=None,
        header=alt.Header(labelAngle=0, labelAlign='right', format='%B')
    )
).properties(
    bounds='flush', title='Seattle Weather', height=step
).configure_facet(
    spacing=0
).configure_view(
    stroke=None
).configure_title(
    anchor='end'
)
ridgeline


"""
Ridgeline plot (Joyplot) Example
--------------------------------
A `Ridgeline plot <https://serialmentor.com/blog/2017/9/15/goodbye-joyplots>`_
chart is a chart that lets you visualize distribution of a numeric value for 
several groups.

Such a chart can be created in Altair by first transforming the data into a
suitable representation.

"""
# category: other charts
import altair as alt
from vega_datasets import data

source = data.seattle_weather.url

step = 20
overlap = 1

ridgeline = alt.Chart(source).transform_timeunit(
    Month='month(date)'
).transform_joinaggregate(
    mean_temp='mean(temp_max)', groupby=['Month']
).transform_bin(
    ['bin_max', 'bin_min'], 'temp_max'
).transform_aggregate(
    value='count()', groupby=['Month', 'mean_temp', 'bin_min', 'bin_max']
).transform_impute(
    impute='value', groupby=['Month', 'mean_temp'], key='bin_min', value=0
).mark_area(
    interpolate='monotone',
    fillOpacity=0.8,
    stroke='lightgray',
    strokeWidth=0.5
).encode(
    alt.X('bin_min:Q', bin='binned', title='Maximum Daily Temperature (C)'),
    alt.Y(
        'value:Q',
        scale=alt.Scale(range=[step, -step * overlap]),
        axis=None
    ),
    alt.Fill(
        'mean_temp:Q',
        legend=None,
        scale=alt.Scale(domain=[30, 5], scheme='redyellowblue')
    ),
    alt.Row(
        'Month:T',
        title=None,
        header=alt.Header(labelAngle=0, labelAlign='right', format='%B')
    )
).properties(
    bounds='flush', title='Seattle Weather', height=step
).configure_facet(
    spacing=0
).configure_view(
    stroke=None
).configure_title(
    anchor='end'
)
ridgeline


Use mark_area in ridgeline plot example