from math import pi
import pandas as pd
from bokeh.io import show
from bokeh.models import LinearColorMapper, BasicTicker, PrintfTickFormatter, ColorBar
from bokeh.plotting import figure
from bokeh.sampledata.unemployment1948 import data
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(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"]
mapper = LinearColorMapper(palette=colors, low=df.rate.min(), high=df.rate.max())
TOOLS = "hover,save,pan,box_zoom,reset,wheel_zoom"
p = figure(title="US Unemployment ({0} - {1})".format(years[0], years[-1]),
x_range=years, y_range=list(reversed(months)),
x_axis_location="above", plot_width=900, plot_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 = "5pt"
p.axis.major_label_standoff = 0
p.xaxis.major_label_orientation = pi / 3
p.rect(x="Year", y="Month", width=1, height=1,
source=df,
fill_color={'field': 'rate', 'transform': mapper},
line_color=None)
color_bar = ColorBar(color_mapper=mapper, major_label_text_font_size="5pt",
ticker=BasicTicker(desired_num_ticks=len(colors)),
formatter=PrintfTickFormatter(format="%d%%"),
label_standoff=6, border_line_color=None, location=(0, 0))
p.add_layout(color_bar, 'right')
show(p) # show the plot
