pip install bokeh

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

# 準(zhǔn)備數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y = [6, 7, 2, 4, 5]

# 創(chuàng)建繪圖對(duì)象
p = figure(title="簡(jiǎn)單散點(diǎn)圖", x_axis_label='X軸', y_axis_label='Y軸')

# 繪制散點(diǎn)圖
p.circle(x, y, size=10, color="navy", alpha=0.5)

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

# 添加軸標(biāo)簽
p.xaxis.axis_label_standoff = 15
p.yaxis.axis_label_standoff = 15

# 添加圖例
p.legend.label_text_font_size = "12pt"
p.legend.location = "top_left"

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

import yfinance as yf

# 獲取股票數(shù)據(jù)
stock_data = yf.download("AAPL", start="2023-01-01", end="2024-01-01")

# 創(chuàng)建繪圖對(duì)象
p = figure(title="AAPL股票走勢(shì)", x_axis_label='日期', y_axis_label='股價(jià)（美元）', x_axis_type="datetime")

# 繪制線圖
p.line(stock_data.index, stock_data['Close'], line_width=2, color="orange", legend_label="收盤價(jià)")

# 添加圖例和軸標(biāo)簽
p.legend.location = "top_left"
p.xaxis.axis_label_standoff = 15
p.yaxis.axis_label_standoff = 15

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

from bokeh.models import HoverTool

# 創(chuàng)建繪圖對(duì)象
p = figure(title="交互式散點(diǎn)圖", x_axis_label='X軸', y_axis_label='Y軸', tools="pan,box_zoom,reset,save")

# 添加懸停工具
hover = HoverTool(tooltips=[("數(shù)值", "@x, @y")])
p.add_tools(hover)

# 繪制散點(diǎn)圖
p.circle(x, y, size=10, color="navy", alpha=0.5)

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

# 創(chuàng)建繪圖對(duì)象
p = figure(title="矩形和橢圓示例", x_axis_label='X軸', y_axis_label='Y軸')

# 繪制矩形
p.rect(x=[1, 2, 3], y=[4, 5, 6], width=0.2, height=0.2, color="green", alpha=0.7)

# 繪制橢圓
p.ellipse(x=[4, 5, 6], y=[7, 8, 9], width=0.2, height=0.1, color="blue", alpha=0.7)

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

from bokeh.models import Slider
from bokeh.layouts import column

# 創(chuàng)建繪圖對(duì)象
p = figure(title="動(dòng)態(tài)散點(diǎn)圖", x_axis_label='X軸', y_axis_label='Y軸')

# 創(chuàng)建滑塊
slider = Slider(start=1, end=10, step=1, value=1, title="選擇散點(diǎn)大小")

# 回調(diào)函數(shù)，根據(jù)滑塊值更新散點(diǎn)大小
def update_size(attr, old, new):
    p.circle(x, y, size=new, color="navy", alpha=0.5)

slider.on_change('value', update_size)

# 將圖形和滑塊組合在一起
layout = column(p, slider)

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(layout)

import pandas as pd

# 創(chuàng)建一個(gè)Pandas DataFrame
data = pd.DataFrame({'x': [1, 2, 3, 4, 5], 'y': [6, 7, 2, 4, 5]})

# 使用Bokeh繪制散點(diǎn)圖
p = figure(title="Pandas整合示例", x_axis_label='X軸', y_axis_label='Y軸')
p.circle('x', 'y', size=10, color="navy", alpha=0.5, source=data)

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

from bokeh.plotting import figure, show
from bokeh.io import output_notebook
from bokeh.plotting import from_bokeh

# 創(chuàng)建Bokeh繪圖對(duì)象
p = figure(title="Bokeh與Matplotlib整合示例", x_axis_label='X軸', y_axis_label='Y軸')
p.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=10, color="navy", alpha=0.5)

# 在Jupyter Notebook中顯示Bokeh圖形
output_notebook()
show(p)

# 轉(zhuǎn)換為Matplotlib圖形
mpl_fig = from_bokeh(p)

# 在Matplotlib中顯示圖形
import matplotlib.pyplot as plt
plt.show(mpl_fig)

from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Slider
from bokeh.layouts import column
from bokeh.io import curdoc

# 創(chuàng)建繪圖對(duì)象和數(shù)據(jù)源
source = ColumnDataSource(data={'x': [1, 2, 3, 4, 5], 'y': [6, 7, 2, 4, 5]})
p = figure(title="動(dòng)態(tài)散點(diǎn)圖", x_axis_label='X軸', y_axis_label='Y軸')
p.circle('x', 'y', size=10, color="navy", alpha=0.5, source=source)

# 創(chuàng)建滑塊和回調(diào)函數(shù)
slider = Slider(start=1, end=10, step=1, value=1, title="選擇散點(diǎn)大小")

def update_size(attr, old, new):
    source.data = {'x': [1, 2, 3, 4, 5], 'y': [6, 7, 2, 4, 5], 'size': [new]*5}

slider.on_change('value', update_size)

# 將圖形和滑塊組合在一起
layout = column(p, slider)

# 將布局添加到文檔
curdoc().add_root(layout)

from bokeh.themes import built_in_themes

# 創(chuàng)建繪圖對(duì)象
p = figure(title="主題定制示例", x_axis_label='X軸', y_axis_label='Y軸')

# 選擇主題
p.theme = built_in_themes['dark_minimal']

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

# 創(chuàng)建繪圖對(duì)象
p = figure(title="樣式定制示例", x_axis_label='X軸', y_axis_label='Y軸')

# 繪制線圖
p.line([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], line_width=2, line_color="green", line_dash="dashed")

# 設(shè)置字體樣式
p.title.text_font = "times"
p.title.text_font_style = "italic"

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)

from bokeh.models import HoverTool

# 創(chuàng)建繪圖對(duì)象
p = figure(title="自定義工具提示示例", x_axis_label='X軸', y_axis_label='Y軸')

# 繪制散點(diǎn)圖
scatter = p.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=10, color="navy", alpha=0.5)

# 自定義工具提示
hover = HoverTool(tooltips=[("數(shù)值", "@x, @y"), ("額外信息", "自定義信息")], renderers=[scatter])
p.add_tools(hover)

# 在Jupyter Notebook中顯示圖形
output_notebook()
show(p)