Notebook

This notebook reproduces a visualization by the Wall Street Journal about the incidence of measles over time, which the brilliant Brian Granger adapted into an example for the Altair library.

Most examples work across multiple plotting backends, this example is also available for:

Matplotlib measles_example

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import numpy as np
import holoviews as hv
from holoviews import opts
import pandas as pd
hv.extension('bokeh')

Declaring data¶

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url = 'https://raw.githubusercontent.com/blmoore/blogR/master/data/measles_incidence.csv'
data = pd.read_csv(url, skiprows=2, na_values='-')

yearly_data = data.drop('WEEK', axis=1).groupby('YEAR').sum().reset_index()
measles = pd.melt(yearly_data, id_vars=['YEAR'], var_name='State', value_name='Incidence')

heatmap = hv.HeatMap(measles, label='Measles Incidence')
aggregate = hv.Dataset(heatmap).aggregate('YEAR', np.mean, np.std)

vline = hv.VLine(1963)
marker = hv.Text(1964, 800, 'Vaccine introduction', halign='left')

agg = hv.ErrorBars(aggregate) * hv.Curve(aggregate)

Plot¶

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overlay = (heatmap + agg * vline * marker).cols(1)
overlay.opts(
    opts.HeatMap(width=900, height=500, tools=['hover'], logz=True, 
                 invert_yaxis=True, labelled=[], toolbar='above',
                 xaxis=None, colorbar=True, clim=(1, np.nan)),
    opts.VLine(line_color='black'),
    opts.Overlay(width=900, height=200, show_title=False, xrotation=90))