fruits = { 'fruit': [ 'apples', 'apples', 'apples', 'apples', 'apples', 'pears', 'pears', 'pears', 'pears', 'pears', 'bananas', 'bananas', 'bananas', 'bananas', 'bananas' ], 'fruit_count': [4, 5, 8, 12, 4, 6, 5, 4, 8, 7, 1, 2, 4, 8, 12], 'year': [ 2009, 2010, 2011, 2012, 2013, 2009, 2010, 2011, 2012, 2013, 2009, 2010, 2011, 2012, 2013 ] } fruits['year'] = [str(yr) for yr in fruits['year']] hm1 = HeatMap(autompg, x=bins('mpg'), y=bins('displ')) hm2 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), values='cyl', stat='mean') hm3 = HeatMap(autompg, x=bins('mpg'), y=bins('displ', bins=15), values='cyl', stat='mean') hm4 = HeatMap(autompg, x=bins('mpg'), y='cyl', values='displ', stat='mean')
from bokeh.sampledata.unemployment1948 import data # setup data sources data = data.copy() data['Year'] = data['Year'].astype(str) unempl = pd.melt(data, var_name='Month', value_name='Unemployment', id_vars=['Year']) fruits = {'fruit': ['apples', 'apples', 'apples', 'apples', 'apples', 'pears', 'pears', 'pears', 'pears', 'pears', 'bananas', 'bananas', 'bananas', 'bananas', 'bananas'], 'fruit_count': [4, 5, 8, 12, 4, 6, 5, 4, 8, 7, 1, 2, 4, 8, 12], 'year': [2009, 2010, 2011, 2012, 2013, 2009, 2010, 2011, 2012, 2013, 2009, 2010, 2011, 2012, 2013]} fruits['year'] = [str(yr) for yr in fruits['year']] hm1 = HeatMap(autompg, x=bins('mpg'), y=bins('displ')) hm2 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), values='cyl', stat='mean') hm3 = HeatMap(autompg, x=bins('mpg'), y=bins('displ', bins=15), values='cyl', stat='mean') hm4 = HeatMap(autompg, x=bins('mpg'), y='cyl', values='displ', stat='mean') hm5 = HeatMap(autompg, y=bins('displ'), x=bins('mpg'), values='cyl', stat='mean', spacing_ratio=0.9) hm6 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), stat='mean', values='cyl', palette=RdYlGn6) hm7 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), stat='mean', values='cyl',
from bokeh.sampledata.unemployment1948 import data # setup data sources del data['Annual'] data['Year'] = data['Year'].astype(str) unempl = pd.melt(data, var_name='Month', value_name='Unemployment', id_vars=['Year']) fruits = {'fruit': ['apples', 'apples', 'apples', 'apples', 'apples', 'pears', 'pears', 'pears', 'pears', 'pears', 'bananas', 'bananas', 'bananas', 'bananas', 'bananas'], 'fruit_count': [4, 5, 8, 12, 4, 6, 5, 4, 8, 7, 1, 2, 4, 8, 12], 'year': [2009, 2010, 2011, 2012, 2013, 2009, 2010, 2011, 2012, 2013, 2009, 2010, 2011, 2012, 2013]} fruits['year'] = [str(yr) for yr in fruits['year']] hm1 = HeatMap(autompg, x=bins('mpg'), y=bins('displ')) hm2 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), values='cyl', stat='mean') hm3 = HeatMap(autompg, x=bins('mpg'), y=bins('displ', bins=15), values='cyl', stat='mean') hm4 = HeatMap(autompg, x=bins('mpg'), y='cyl', values='displ', stat='mean') hm5 = HeatMap(autompg, y=bins('displ'), x=bins('mpg'), values='cyl', stat='mean', spacing_ratio=0.9) hm6 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), stat='mean', values='cyl', palette=RdYlGn6) hm7 = HeatMap(autompg, x=bins('mpg'), y=bins('displ'), stat='mean', values='cyl',
from bokeh.charts import HeatMap, bins, output_file, show import pandas as pd DATA_FILE = '../../samples/GSM188012.CEL' dtype = {'x': int, 'y': int, 'lux': float} dataset = pd.read_csv(DATA_FILE, sep='\t', dtype=dtype) hm = HeatMap(dataset, x=bins('x'), y=bins('y'), values='lux', title='Expression', stat='mean') output_file("heatmap7.html", title="heatmap.py example") show(hm)