bokeh.models
Interfacebokeh.models.annotations
bokeh.models.axes
bokeh.models.callbacks
bokeh.models.formatters
bokeh.models.glyphs
bokeh.models.grids
bokeh.models.map_plots
bokeh.models.mappers
bokeh.models.markers
bokeh.models.plots
bokeh.models.ranges
bokeh.models.renderers
bokeh.models.sources
bokeh.models.tickers
bokeh.models.tools
bokeh.models.widget
bokeh.models.widgets.buttons
bokeh.models.widgets.dialogs
bokeh.models.widgets.groups
bokeh.models.widgets.icons
bokeh.models.widgets.inputs
bokeh.models.widgets.layouts
bokeh.models.widgets.markups
bokeh.models.widgets.panels
bokeh.models.widgets.tables
bokeh.validation
Package
bokeh.plotting
Interfacebokeh.charts
Interface
< boxplot_chart | back to Gallery | donut_chart >
from bokeh._legacy_charts import HeatMap, output_file, show
from bokeh.palettes import YlOrRd9 as palette
from bokeh.sampledata.unemployment1948 import data
# pandas magic
df = data[data.columns[:-1]]
df2 = df.set_index(df[df.columns[0]].astype(str))
df2.drop(df.columns[0], axis=1, inplace=True)
df3 = df2.transpose()
output_file("cat_heatmap.html")
palette = palette[::-1] # Reverse the color order so dark red is highest unemployment
hm = HeatMap(df3, title="categorical heatmap", width=800, palette=palette)
show(hm)