Ridgeline plot

joy_division.py

import altair as alt
from vega_datasets import data

source = data.seattle_weather.url
step = 20
overlap = 1

alt.Chart(source, height=step).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'))
).facet(
    row=alt.Row('Month:T',title=None,header=alt.Header(labelAngle=0, labelAlign='right', format='%B'))
).properties(title='Seattle Weather',bounds='flush'
).configure_facet(spacing=0).configure_view(stroke=None).configure_title(anchor='end')