categorical_heatmap_unemployment.py — Anaconda Enterprise 4.4 documentation

Anaconda Enterprise: Documentation

# categorical_heatmap_unemployment.py

    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, location=(0, 0),
                         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 = "5pt"
    p.axis.major_label_standoff = 0
    p.xaxis.major_label_orientation = 1.0

    show(p)