Python 数据可视化之Bokeh详解

# 导入模块
from bokeh.plotting import figure, output_file, show
from bokeh.palettes import magma
import pandas as pd

# 实例化图形对象
graph = figure(title = "Bokeh Scatter Graph")
# 读取数据库
data = pd.read_csv("tips.csv")
color = magma(256)
# 绘制图形
graph.scatter(data['total_bill'], data['tip'], color=color)
# 展示模型
show(graph)

# 导入模块
from bokeh.plotting import figure, output_file, show
import pandas as pd

# 实例化图形对象
graph = figure(title = "Bokeh Bar Chart")
# 读取数据库
data = pd.read_csv("tips.csv")
# 绘制图形
graph.vbar(data['total_bill'], top=data['tip'],
		legend_label = "Bill VS Tips", color='green')
graph.vbar(data['tip'], top=data['size'],
		legend_label = "Tips VS Size", color='red')
graph.legend.click_policy = "hide"
# 展示模型
show(graph)

from bokeh.io import show
from bokeh.models import Button, CheckboxGroup, RadioGroup, CustomJS
button = Button(label="GFG")
button.js_on_click(CustomJS(
	code="console.log('button: click!', this.toString())"))
# 复选框和单选按钮的标签
L = ["First", "Second", "Third"]
# 活动参数集默认检查选定的值
checkbox_group = CheckboxGroup(labels=L, active=[0, 2])
checkbox_group.js_on_click(CustomJS(code="""
	console.log('checkbox_group: active=' + this.active, this.toString())
"""))
# 活动参数集默认检查选定的值
radio_group = RadioGroup(labels=L, active=1)
radio_group.js_on_click(CustomJS(code="""
	console.log('radio_group: active=' + this.active, this.toString())
"""))
show(button)
show(checkbox_group)
show(radio_group)

from bokeh.io import show
from bokeh.models import CustomJS, Slider
slider = Slider(start=1, end=20, value=1, step=2, title="Slider")
slider.js_on_change("value", CustomJS(code="""
	console.log('slider: value=' + this.value, this.toString())
"""))
show(slider)