Python 交互式可视化的利器Bokeh的使用

pip install bokeh

from bokeh.plotting import figure, show
from bokeh.io import output_file

output_file("test.html")  # 生成 HTML 文件
p = figure(title="示例图", x_axis_label="X 轴", y_axis_label="Y 轴")
p.line([1, 2, 3, 4], [10, 20, 30, 40], line_width=2)
show(p)  # 在浏览器中显示图表

from bokeh.plotting import figure, show

p = figure(title="折线图示例", x_axis_label="X", y_axis_label="Y")
p.line([1, 2, 3, 4, 5], [5, 7, 2, 3, 6], line_width=2, color="blue")
show(p)

p = figure(title="散点图示例", x_axis_label="X", y_axis_label="Y")
p.circle([1, 2, 3, 4, 5], [5, 7, 2, 3, 6], size=10, color="red", alpha=0.5)
show(p)

from bokeh.io import show
from bokeh.plotting import figure
from bokeh.transform import factor_cmap
from bokeh.models import ColumnDataSource

fruits = ["苹果", "香蕉", "橙子", "葡萄"]
values = [10, 20, 15, 30]

source = ColumnDataSource(data=dict(fruits=fruits, values=values))
p = figure(x_range=fruits, title="水果销量", toolbar_location=None, tools="")
p.vbar(x="fruits", top="values", width=0.4, source=source)
show(p)

from bokeh.models import HoverTool

p = figure(title="悬停提示示例", x_axis_label="X", y_axis_label="Y")
p.circle([1, 2, 3, 4], [10, 20, 30, 40], size=10, color="navy", alpha=0.5)

hover = HoverTool(tooltips=[("X 轴", "$x"), ("Y 轴", "$y")])
p.add_tools(hover)
show(p)

p = figure(title="选择和缩放示例", tools="box_select,pan,wheel_zoom,reset")
p.circle([1, 2, 3, 4], [10, 20, 30, 40], size=10, color="green", alpha=0.5)
show(p)

from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, curdoc
import numpy as np

source = ColumnDataSource(data=dict(x=[], y=[]))
p = figure(title="动态数据流", x_axis_label="X", y_axis_label="Y")
p.line("x", "y", source=source, line_width=2)

def update():
    new_data = dict(x=[np.random.random()], y=[np.random.random()])
    source.stream(new_data, rollover=50)

curdoc().add_root(p)
curdoc().add_periodic_callback(update, 1000)  # 每秒更新一次

import pandas as pd
data = pd.DataFrame({"x": [1, 2, 3, 4], "y": [10, 20, 30, 40]})
source = ColumnDataSource(data)

p = figure(title="Pandas 数据绘图")
p.line("x", "y", source=source, line_width=2)
show(p)

from flask import Flask, render_template
from bokeh.embed import components

app = Flask(__name__)

@app.route("/")
def index():
    p = figure(title="Flask 集成示例")
    p.line([1, 2, 3, 4], [10, 20, 30, 40])
    script, div = components(p)
    return render_template("index.html", script=script, div=div)

if __name__ == "__main__":
    app.run(debug=True)