bokeh.models Interfacebokeh.models.annotationsbokeh.models.axesbokeh.models.callbacksbokeh.models.formattersbokeh.models.glyphsbokeh.models.gridsbokeh.models.map_plotsbokeh.models.mappersbokeh.models.markersbokeh.models.plotsbokeh.models.rangesbokeh.models.renderersbokeh.models.sourcesbokeh.models.tickersbokeh.models.toolsbokeh.models.widgetbokeh.models.widgets.buttonsbokeh.models.widgets.dialogsbokeh.models.widgets.groupsbokeh.models.widgets.iconsbokeh.models.widgets.inputsbokeh.models.widgets.layoutsbokeh.models.widgets.markupsbokeh.models.widgets.panelsbokeh.models.widgets.tablesbokeh.validation Package
bokeh.plotting Interfacebokeh.charts Interface
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from bokeh.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)