heatmap_unemployment

A categorical heatmap using unemployment data. This example demonstrates adding a ColorBar to a plot.

Details

Sampledata:

bokeh.sampledata.unemployment1948

Bokeh APIs:

figure.rect, bokeh.models.ColorBar

More info:

Color bars

Keywords:

categorical, colorbar, heatmap, hover, tooltip

from math import pi

import pandas as pd

from bokeh.models import BasicTicker, PrintfTickFormatter
from bokeh.plotting import figure, show
from bokeh.sampledata.unemployment1948 import data
from bokeh.transform import linear_cmap

data['Year'] = data['Year'].astype(str)
data = data.set_index('Year')
data.drop('Annual', axis=1, inplace=True)
data.columns.name = 'Month'

years = list(data.index)
months = list(reversed(data.columns))

# reshape to 1D array or rates with a month and year for each row.
df = pd.DataFrame(data.stack(), columns=['rate']).reset_index()

# this is the colormap from the original NYTimes plot
colors = ["#75968f", "#a5bab7", "#c9d9d3", "#e2e2e2", "#dfccce", "#ddb7b1", "#cc7878", "#933b41", "#550b1d"]

TOOLS = "hover,save,pan,box_zoom,reset,wheel_zoom"

p = figure(title=f"US Unemployment ({years[0]} - {years[-1]})",
           x_range=years, y_range=months,
           x_axis_location="above", width=900, height=400,
           tools=TOOLS, toolbar_location='below',
           tooltips=[('date', '@Month @Year'), ('rate', '@rate%')])

p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_text_font_size = "7px"
p.axis.major_label_standoff = 0
p.xaxis.major_label_orientation = pi / 3

r = p.rect(x="Year", y="Month", width=1, height=1, source=df,
           fill_color=linear_cmap("rate", colors, low=df.rate.min(), high=df.rate.max()),
           line_color=None)

p.add_layout(r.construct_color_bar(
    major_label_text_font_size="7px",
    ticker=BasicTicker(desired_num_ticks=len(colors)),
    formatter=PrintfTickFormatter(format="%d%%"),
    label_standoff=6,
    border_line_color=None,
    padding=5
), 'right')

show(p)