heatmap_unemployment

使用失业数据创建分类热力图。此示例演示如何向绘图中添加ColorBar。

详情

示例数据：

bokeh.sampledata.unemployment1948

Bokeh API：

figure.rect，bokeh.models.ColorBar

更多信息：

颜色条

关键词：

分类，颜色条，热力图，悬停，工具提示

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)