trellis layered plots in altair/Vega-Lite

Question

I would like to compare multiple conditions of an altair (ultimately vega-lite) layered plot. The perfect solution would be to facet/trellis the plot so I can see the different conditions side by side. Unfortunately I cannot figure out how to give the command to plot the different conditions.

Here is my attempt to implement my idea based on the example for layered plots: (https://github.com/ellisonbg/altair/blob/master/altair/notebooks/07-LayeredCharts.ipynb)

import pandas as pd
import numpy as np

data = pd.DataFrame({'x':np.random.rand(10), 'y':np.random.rand(10), 'z':['a', 'b']*5})

chart = LayeredChart(data)
chart += Chart().mark_line().encode(x='x:Q', y='y:Q', column='z:Q')
chart += Chart().mark_point().encode(x='x:Q', y='y:Q', column='z:Q')    
chart

When compared with the example I added the column 'z' with the two conditions, and the two column statements in the Chart definitions. This solution generates seemingly good Vega-lite code, but no plot. Alternatively I tried "chart = LayeredChart(data).encode(column='z:Q')" but I then got the error 'LayeredChart' object has no attribute 'encode'

I am wondering whether it is possible to facet (trellis) layered plots at all and whether it will be possible in future Vega-Lite releases.

I am using jupyter with Anaconda

jakevdp jakevdp · Accepted Answer · 2017-03-29T20:27:38

Layering is only experimentally supported in the current release of Vega-Lite and Altair, and I believe you've hit one of the unsupported aspects. This should be addressed in the Vega-Lite 2.0 release (and associated Altair release) later this spring.

trellis layered plots in altair/Vega-Lite

1 Answers