
from math import pi

from bokeh.models import HoverTool
from bokeh.plotting import ColumnDataSource, figure, show, output_file
from bokeh.sampledata.unemployment1948 import data

data['Year'] = [str(x) for x in data['Year']]

years = list(data['Year'])
months = ["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]

data = data.set_index('Year')

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

# Set up the data for plotting. We will need to have values for every
# pair of year/month names. Map the rate to a color.
month = []
year = []
color = []
rate = []
for y in years:
    for m in months:
        month.append(m)
        year.append(y)
        monthly_rate = data[m][y]
        rate.append(monthly_rate)
        color.append(colors[min(int(monthly_rate)-2, 8)])

source = ColumnDataSource(
    data=dict(month=month, year=year, color=color, rate=rate)
)

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

p = figure(title="US Unemployment (1948 - 2013)",
           x_range=years, y_range=list(reversed(months)),
           x_axis_location="above", plot_width=900, plot_height=400,
           toolbar_location="left", tools=TOOLS)

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("year", "month", 1, 1, source=source,
       color="color", line_color=None)

p.select_one(HoverTool).tooltips = [
    ('date', '@month @year'),
    ('rate', '@rate'),
]

output_file('unemployment.html', title="unemployment.py example")

show(p)      # show the plot
