import pandas as pd

from bokeh.io import output_file, show
from bokeh.models import (BasicTicker, ColorBar, ColumnDataSource,
                          LinearColorMapper, PrintfTickFormatter,)
from bokeh.plotting import figure
from bokeh.sampledata.unemployment1948 import data
from bokeh.transform import transform

output_file("unemploymemt.html")

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

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

source = ColumnDataSource(df)

# 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())

p = figure(plot_width=800, plot_height=300, title="US unemployment 1948—2016",
           x_range=list(data.index), y_range=list(reversed(data.columns)),
           toolbar_location=None, tools="", x_axis_location="above")

p.rect(x="Year", y="Month", width=1, height=1, source=source,
       line_color=None, fill_color=transform('rate', mapper))

color_bar = ColorBar(color_mapper=mapper,
                     ticker=BasicTicker(desired_num_ticks=len(colors)),
                     formatter=PrintfTickFormatter(format="%d%%"))

p.add_layout(color_bar, 'right')

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 = 1.0

show(p)
