pip install plotly

import plotly.express as px
import pandas as pd

# 創(chuàng)建示例數(shù)據(jù)
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5],
    'y': [10, 11, 12, 13, 14],
    'category': ['A', 'B', 'A', 'B', 'A']
})

# 創(chuàng)建散點(diǎn)圖
fig = px.scatter(df, x='x', y='y', color='category', title='互動(dòng)散點(diǎn)圖')

# 顯示圖表
fig.show()

import plotly.graph_objects as go

# 創(chuàng)建示例數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y = [10, 11, 12, 13, 14]

# 創(chuàng)建折線圖
fig = go.Figure()

fig.add_trace(go.Scatter(x=x, y=y, mode='lines+markers', name='數(shù)據(jù)線'))

# 更新布局
fig.update_layout(
    title='互動(dòng)折線圖',
    xaxis_title='X 軸',
    yaxis_title='Y 軸',
    hovermode='closest'
)

# 顯示圖表
fig.show()

import plotly.express as px
import pandas as pd

# 創(chuàng)建示例數(shù)據(jù)
df = pd.DataFrame({
    'x': range(1, 11),
    'y': [i**2 for i in range(1, 11)],
    'category': ['A', 'B'] * 5
})

# 創(chuàng)建圖表
fig = px.scatter(df, x='x', y='y', color='category', title='交互式數(shù)據(jù)選擇圖')

# 更新圖表以啟用選擇功能
fig.update_layout(
    dragmode='select',
    selectmode='event+select'
)

# 顯示圖表
fig.show()

import plotly.graph_objects as go

# 創(chuàng)建示例數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y = [10, 11, 12, 13, 14]

# 創(chuàng)建折線圖
fig = go.Figure()

fig.add_trace(go.Scatter(x=x, y=y, mode='lines+markers', name='數(shù)據(jù)線'))

# 添加注釋
fig.add_annotation(
    x=3,
    y=12,
    text="關(guān)鍵點(diǎn)",
    showarrow=True,
    arrowhead=2,
    ax=0,
    ay=-40
)

# 更新布局
fig.update_layout(
    title='添加注釋和標(biāo)記的折線圖',
    xaxis_title='X 軸',
    yaxis_title='Y 軸',
    hovermode='closest'
)

# 顯示圖表
fig.show()

from plotly.subplots import make_subplots
import plotly.graph_objects as go

# 創(chuàng)建子圖布局
fig = make_subplots(rows=1, cols=2, subplot_titles=('子圖 1', '子圖 2'))

# 添加數(shù)據(jù)到子圖 1
fig.add_trace(go.Scatter(x=[1, 2, 3, 4], y=[10, 11, 12, 13], mode='lines+markers', name='子圖 1 數(shù)據(jù)'),
              row=1, col=1)

# 添加數(shù)據(jù)到子圖 2
fig.add_trace(go.Bar(x=['A', 'B', 'C'], y=[5, 10, 15], name='子圖 2 數(shù)據(jù)'),
              row=1, col=2)

# 更新布局
fig.update_layout(
    title='包含子圖的圖表',
    xaxis_title='X 軸',
    yaxis_title='Y 軸',
    xaxis2_title='類(lèi)別',
    yaxis2_title='值',
    showlegend=False
)

# 顯示圖表
fig.show()

import dash
from dash import dcc, html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np

# 創(chuàng)建 Dash 應(yīng)用
app = dash.Dash(__name__)

# 定義布局
app.layout = html.Div([
    dcc.Graph(id='interactive-graph'),
    dcc.Slider(
        id='data-slider',
        min=1,
        max=100,
        step=1,
        value=10,
        marks={i: str(i) for i in range(1, 101, 10)}
    )
])

# 定義回調(diào)函數(shù)
@app.callback(
    Output('interactive-graph', 'figure'),
    Input('data-slider', 'value')
)
def update_graph(slider_value):
    x = np.linspace(0, 10, 100)
    y = np.sin(x) * slider_value

    fig = go.Figure()
    fig.add_trace(go.Scatter(x=x, y=y, mode='lines', name='動(dòng)態(tài)數(shù)據(jù)'))
    fig.update_layout(title='動(dòng)態(tài)更新的圖表')
    
    return fig

# 運(yùn)行應(yīng)用
if __name__ == '__main__':
    app.run_server(debug=True)

import plotly.express as px
import pandas as pd

# 創(chuàng)建示例數(shù)據(jù)
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5],
    'y': [10, 11, 12, 13, 14],
    'category': ['A', 'B', 'A', 'B', 'A']
})

# 創(chuàng)建交互式散點(diǎn)圖
fig = px.scatter(df, x='x', y='y', color='category', title='Jupyter Notebook中的交互式散點(diǎn)圖')

# 在 Jupyter Notebook 中顯示圖表
fig.show()

import dash
from dash import dcc, html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import pandas as pd

# 創(chuàng)建示例數(shù)據(jù)
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5],
    'y': [10, 11, 12, 13, 14],
    'category': ['A', 'B', 'A', 'B', 'A']
})

# 創(chuàng)建 Dash 應(yīng)用
app = dash.Dash(__name__)

# 定義布局
app.layout = html.Div([
    dcc.Graph(id='scatter-plot'),
    dcc.Slider(
        id='data-slider',
        min=1,
        max=5,
        step=1,
        value=1,
        marks={i: str(i) for i in range(1, 6)}
    )
])

# 定義回調(diào)函數(shù)
@app.callback(
    Output('scatter-plot', 'figure'),
    Input('data-slider', 'value')
)
def update_figure(slider_value):
    filtered_df = df[df['x'] <= slider_value]
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=filtered_df['x'], y=filtered_df['y'], mode='markers', color=filtered_df['category']))
    fig.update_layout(title='Dash 應(yīng)用中的交互式散點(diǎn)圖')
    return fig

# 運(yùn)行應(yīng)用
if __name__ == '__main__':
    app.run_server(debug=True)

import plotly.express as px
import pandas as pd

# 創(chuàng)建示例數(shù)據(jù)
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5],
    'y': [10, 11, 12, 13, 14],
    'category': ['A', 'B', 'A', 'B', 'A']
})

# 創(chuàng)建交互式散點(diǎn)圖
fig = px.scatter(df, x='x', y='y', color='category', title='保存為 HTML 文件的散點(diǎn)圖')

# 保存圖表為 HTML 文件
fig.write_html('scatter_plot.html')

<!DOCTYPE html>
<html>
<head>
    <title>Plotly 圖表</title>
</head>
<body>
    <h1>我的 Plotly 圖表</h1>
    <iframe src="scatter_plot.html" width="800" height="600"></iframe>
</body>
</html>

import plotly.express as px
import pandas as pd

# 創(chuàng)建大量示例數(shù)據(jù)
df = pd.DataFrame({
    'x': range(1, 10001),
    'y': [i ** 0.5 for i in range(1, 10001)]
})

# 創(chuàng)建散點(diǎn)圖，使用數(shù)據(jù)降采樣
fig = px.scatter(df, x='x', y='y', render_mode='webgl')

# 顯示圖表
fig.show()

import plotly.graph_objects as go
import numpy as np

# 創(chuàng)建數(shù)據(jù)
x = np.linspace(0, 100, 1000)
y = np.sin(x)

# 創(chuàng)建圖表
fig = go.Figure()

# 添加多層數(shù)據(jù)
for i in range(1, 6):
    fig.add_trace(go.Scatter(x=x[x < i * 20], y=y[x < i * 20], mode='markers', name=f'層 {i}'))

# 更新布局
fig.update_layout(title='分層渲染的圖表')

# 顯示圖表
fig.show()