Tap¶

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Title: HeatMap Tap stream example¶

Description: A linked streams example demonstrating how use Tap stream on a HeatMap. The data contains the incidence of measles across US states by year and week (obtained from Project Tycho). The HeatMap represents the mean measles incidence per year. On tap the Histogram on the right will generate a Histogram of the incidences for each week in the selected year and state.

Dependencies: Bokeh

Backends: Bokeh

In [1]:

import pandas as pd
import numpy as np
import holoviews as hv
from holoviews import opts

hv.extension('bokeh', width=90)

In [2]:

# Declare dataset
df = pd.read_csv('http://assets.holoviews.org/data/diseases.csv.gz', compression='gzip')
dataset = hv.Dataset(df, vdims=('measles','Measles Incidence'))

# Declare HeatMap
heatmap = hv.HeatMap(dataset.aggregate(['Year', 'State'], np.mean),
                     label='Measles Incidence').select(Year=(1928, 2002))

# Declare Tap stream with heatmap as source and initial values
posxy = hv.streams.Tap(source=heatmap, x=1951, y='New York')

# Define function to compute histogram based on tap location
def tap_histogram(x, y):
    return hv.Curve(dataset.select(State=y, Year=int(x)), kdims='Week',
                   label='Year: %s, State: %s' % (x, y))

tap_dmap = hv.DynamicMap(tap_histogram, streams=[posxy])

(heatmap + tap_dmap).opts(
    opts.Curve(framewise=True, height=500, line_color='black', width=375, yaxis='right'),
    opts.HeatMap(cmap='RdBu_r', fontsize={'xticks': '6pt'}, height=500,
                 logz=True, tools=['hover'], width=700, xrotation=90)
)

WARNING:param.HeatMapPlot03878: Log color mapper lower bound <= 0 and will not render corrrectly. Ensure you set a positive lower bound on the color dimension or using the `clim` option.

Out[2]:

Download this notebook from GitHub (right-click to download).