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)
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)
