Web tech » History » Version 3
jun chen, 02/11/2025 04:12 PM
| 1 | 1 | jun chen | # Web tech |
|---|---|---|---|
| 2 | |||
| 3 | 3 | jun chen | {{toc}} |
| 4 | |||
| 5 | ## 直接用javascript |
||
| 6 | 1 | jun chen | |
| 7 | ``` |
||
| 8 | <!DOCTYPE html> |
||
| 9 | <html lang="en"> |
||
| 10 | <head> |
||
| 11 | <meta charset="UTF-8"> |
||
| 12 | <meta name="viewport" content="width=device-width, initial-scale=1.0"> |
||
| 13 | <title>分段填充折线图</title> |
||
| 14 | <script src="https://d3js.org/d3.v7.min.js"></script> |
||
| 15 | <style> |
||
| 16 | .tooltip { |
||
| 17 | position: absolute; |
||
| 18 | background-color: rgba(255, 255, 255, 0.9); |
||
| 19 | border: 1px solid #ccc; |
||
| 20 | padding: 5px; |
||
| 21 | font-size: 12px; |
||
| 22 | pointer-events: none; |
||
| 23 | opacity: 0; |
||
| 24 | } |
||
| 25 | .line { |
||
| 26 | fill: none; |
||
| 27 | stroke: black; |
||
| 28 | stroke-width: 2; |
||
| 29 | } |
||
| 30 | </style> |
||
| 31 | </head> |
||
| 32 | <body> |
||
| 33 | <div id="chart"></div> |
||
| 34 | <div class="tooltip" id="tooltip"></div> |
||
| 35 | |||
| 36 | <script> |
||
| 37 | // 示例数据 |
||
| 38 | const data = [ |
||
| 39 | { time: "2025-01-01", value: 10, description: "说明1" }, |
||
| 40 | { time: "2025-01-02", value: 15, description: "说明2" }, |
||
| 41 | { time: "2025-01-03", value: 20, description: "说明3" }, |
||
| 42 | { time: "2025-01-04", value: 25, description: "说明4" }, |
||
| 43 | { time: "2025-01-05", value: 30, description: "说明5" }, |
||
| 44 | { time: "2025-01-06", value: 35, description: "说明6" }, |
||
| 45 | { time: "2025-01-07", value: 40, description: "说明7" }, |
||
| 46 | { time: "2025-01-08", value: 45, description: "说明8" }, |
||
| 47 | { time: "2025-01-09", value: 50, description: "说明9" }, |
||
| 48 | { time: "2025-01-10", value: 55, description: "说明10" }, |
||
| 49 | { time: "2025-01-11", value: 60, description: "说明11" }, |
||
| 50 | { time: "2025-01-12", value: 65, description: "说明12" }, |
||
| 51 | { time: "2025-01-13", value: 70, description: "说明13" }, |
||
| 52 | { time: "2025-01-14", value: 75, description: "说明14" }, |
||
| 53 | { time: "2025-01-15", value: 80, description: "说明15" }, |
||
| 54 | { time: "2025-01-16", value: 85, description: "说明16" }, |
||
| 55 | { time: "2025-01-17", value: 90, description: "说明17" }, |
||
| 56 | { time: "2025-01-18", value: 95, description: "说明18" }, |
||
| 57 | { time: "2025-01-19", value: 100, description: "说明19" }, |
||
| 58 | { time: "2025-01-20", value: 105, description: "说明20" } |
||
| 59 | ]; |
||
| 60 | |||
| 61 | // 设置图表尺寸 |
||
| 62 | const margin = { top: 20, right: 30, bottom: 30, left: 40 }; |
||
| 63 | const width = 800 - margin.left - margin.right; |
||
| 64 | const height = 400 - margin.top - margin.bottom; |
||
| 65 | |||
| 66 | // 创建 SVG 容器 |
||
| 67 | const svg = d3.select("#chart") |
||
| 68 | .append("svg") |
||
| 69 | .attr("width", width + margin.left + margin.right) |
||
| 70 | .attr("height", height + margin.top + margin.bottom) |
||
| 71 | .append("g") |
||
| 72 | .attr("transform", `translate(${margin.left},${margin.top})`); |
||
| 73 | |||
| 74 | // 解析时间格式 |
||
| 75 | const parseTime = d3.timeParse("%Y-%m-%d"); |
||
| 76 | |||
| 77 | // 格式化数据 |
||
| 78 | data.forEach(d => { |
||
| 79 | d.time = parseTime(d.time); |
||
| 80 | d.value = +d.value; |
||
| 81 | }); |
||
| 82 | |||
| 83 | // 设置比例尺 |
||
| 84 | const x = d3.scaleTime() |
||
| 85 | .domain(d3.extent(data, d => d.time)) |
||
| 86 | .range([0, width]); |
||
| 87 | |||
| 88 | const y = d3.scaleLinear() |
||
| 89 | .domain([0, d3.max(data, d => d.value)]) |
||
| 90 | .range([height, 0]); |
||
| 91 | |||
| 92 | // 添加 X 轴 |
||
| 93 | svg.append("g") |
||
| 94 | .attr("transform", `translate(0,${height})`) |
||
| 95 | .call(d3.axisBottom(x)); |
||
| 96 | |||
| 97 | // 添加 Y 轴 |
||
| 98 | svg.append("g") |
||
| 99 | .call(d3.axisLeft(y)); |
||
| 100 | |||
| 101 | // 创建折线生成器 |
||
| 102 | const line = d3.line() |
||
| 103 | .x(d => x(d.time)) |
||
| 104 | .y(d => y(d.value)); |
||
| 105 | |||
| 106 | // 绘制折线 |
||
| 107 | svg.append("path") |
||
| 108 | .datum(data) |
||
| 109 | .attr("class", "line") |
||
| 110 | .attr("d", line); |
||
| 111 | |||
| 112 | // 分段填充颜色 |
||
| 113 | const first10 = data.slice(0, 10); |
||
| 114 | const last10 = data.slice(-10); |
||
| 115 | const middle = data.slice(10, -10); |
||
| 116 | |||
| 117 | // 填充前十个时间段的绿色区域 |
||
| 118 | svg.append("path") |
||
| 119 | .datum(first10) |
||
| 120 | .attr("fill", "green") |
||
| 121 | .attr("opacity", 0.3) |
||
| 122 | .attr("d", d3.area() |
||
| 123 | .x(d => x(d.time)) |
||
| 124 | .y0(height) |
||
| 125 | .y1(d => y(d.value)) |
||
| 126 | ); |
||
| 127 | |||
| 128 | // 填充中间时间段的蓝色区域 |
||
| 129 | svg.append("path") |
||
| 130 | .datum(middle) |
||
| 131 | .attr("fill", "blue") |
||
| 132 | .attr("opacity", 0.3) |
||
| 133 | .attr("d", d3.area() |
||
| 134 | .x(d => x(d.time)) |
||
| 135 | .y0(height) |
||
| 136 | .y1(d => y(d.value)) |
||
| 137 | ); |
||
| 138 | |||
| 139 | // 填充后十个时间段的红色区域 |
||
| 140 | svg.append("path") |
||
| 141 | .datum(last10) |
||
| 142 | .attr("fill", "red") |
||
| 143 | .attr("opacity", 0.3) |
||
| 144 | .attr("d", d3.area() |
||
| 145 | .x(d => x(d.time)) |
||
| 146 | .y0(height) |
||
| 147 | .y1(d => y(d.value)) |
||
| 148 | ); |
||
| 149 | |||
| 150 | // 添加悬停交互 |
||
| 151 | const tooltip = d3.select("#tooltip"); |
||
| 152 | |||
| 153 | svg.selectAll(".dot") |
||
| 154 | .data(data) |
||
| 155 | .enter() |
||
| 156 | .append("circle") |
||
| 157 | .attr("class", "dot") |
||
| 158 | .attr("cx", d => x(d.time)) |
||
| 159 | .attr("cy", d => y(d.value)) |
||
| 160 | .attr("r", 5) |
||
| 161 | .attr("fill", "steelblue") |
||
| 162 | .on("mouseover", (event, d) => { |
||
| 163 | tooltip.style("opacity", 1) |
||
| 164 | .html(`时间: ${d3.timeFormat("%Y-%m-%d")(d.time)}<br>数值: ${d.value}<br>说明: ${d.description}`) |
||
| 165 | .style("left", `${event.pageX + 5}px`) |
||
| 166 | .style("top", `${event.pageY - 20}px`); |
||
| 167 | }) |
||
| 168 | .on("mouseout", () => { |
||
| 169 | tooltip.style("opacity", 0); |
||
| 170 | }); |
||
| 171 | </script> |
||
| 172 | </body> |
||
| 173 | </html> |
||
| 174 | ``` |
||
| 175 | |||
| 176 | 2 | jun chen | ## 以下是使用 **JavaScript** 和 **Python** 分别实现交互式网页图表的两种方法，包含完整代码和步骤说明： |
| 177 | 1 | jun chen | |
| 178 | --- |
||
| 179 | |||
| 180 | ### **方法一：JavaScript + Plotly（纯前端实现）** |
||
| 181 | #### 特点：直接在浏览器中运行，无需后端，适合快速展示。 |
||
| 182 | 2 | jun chen | |
| 183 | 1 | jun chen | ```html |
| 184 | <!DOCTYPE html> |
||
| 185 | <html> |
||
| 186 | <head> |
||
| 187 | <title>交互式图表</title> |
||
| 188 | <!-- 引入 Plotly.js --> |
||
| 189 | <script src="https://cdn.plot.ly/plotly-2.24.1.min.js"></script> |
||
| 190 | </head> |
||
| 191 | <body> |
||
| 192 | <div id="chart"></div> |
||
| 193 | |||
| 194 | <script> |
||
| 195 | // 读取CSV文件（假设文件名为 data.csv） |
||
| 196 | fetch('data.csv') |
||
| 197 | .then(response => response.text()) |
||
| 198 | .then(csvText => { |
||
| 199 | // 解析CSV数据 |
||
| 200 | const rows = csvText.split('\n'); |
||
| 201 | const x = [], y = []; |
||
| 202 | rows.forEach((row, index) => { |
||
| 203 | if (index === 0) return; // 跳过标题行 |
||
| 204 | const [xVal, yVal] = row.split(','); |
||
| 205 | x.push(parseFloat(xVal)); |
||
| 206 | y.push(parseFloat(yVal)); |
||
| 207 | }); |
||
| 208 | |||
| 209 | // 绘制图表 |
||
| 210 | Plotly.newPlot('chart', [{ |
||
| 211 | x: x, |
||
| 212 | y: y, |
||
| 213 | type: 'scatter', |
||
| 214 | mode: 'lines+markers', |
||
| 215 | marker: { color: 'blue' }, |
||
| 216 | line: { shape: 'spline' } |
||
| 217 | }], { |
||
| 218 | title: '交互式数据图表', |
||
| 219 | xaxis: { title: 'X轴' }, |
||
| 220 | yaxis: { title: 'Y轴' }, |
||
| 221 | hovermode: 'closest' |
||
| 222 | }); |
||
| 223 | }); |
||
| 224 | </script> |
||
| 225 | </body> |
||
| 226 | </html> |
||
| 227 | ``` |
||
| 228 | |||
| 229 | #### 使用步骤： |
||
| 230 | 1. 将CSV文件命名为 `data.csv`，格式如下： |
||
| 231 | ```csv |
||
| 232 | x,y |
||
| 233 | 1,5 |
||
| 234 | 2,3 |
||
| 235 | 3,7 |
||
| 236 | 4,2 |
||
| 237 | 5,8 |
||
| 238 | ``` |
||
| 239 | 2. 将HTML文件和 `data.csv` 放在同一目录下，用浏览器打开HTML文件。 |
||
| 240 | 3. 效果：支持**缩放、悬停显示数值、拖拽平移**等交互。 |
||
| 241 | |||
| 242 | --- |
||
| 243 | |||
| 244 | ### **方法二：Python + Plotly（生成独立HTML文件）** |
||
| 245 | #### 特点：适合Python用户，自动化生成图表文件。 |
||
| 246 | 2 | jun chen | |
| 247 | 1 | jun chen | ```python |
| 248 | import pandas as pd |
||
| 249 | import plotly.express as px |
||
| 250 | |||
| 251 | # 1. 读取CSV文件 |
||
| 252 | df = pd.read_csv("data.csv") |
||
| 253 | |||
| 254 | # 2. 创建交互式图表 |
||
| 255 | fig = px.line( |
||
| 256 | df, x='x', y='y', |
||
| 257 | title='Python生成的交互式图表', |
||
| 258 | markers=True, # 显示数据点 |
||
| 259 | line_shape='spline' # 平滑曲线 |
||
| 260 | ) |
||
| 261 | |||
| 262 | # 3. 自定义悬停效果和样式 |
||
| 263 | fig.update_traces( |
||
| 264 | hoverinfo='x+y', # 悬停显示x和y值 |
||
| 265 | line=dict(width=2, color='royalblue'), |
||
| 266 | marker=dict(size=8, color='firebrick') |
||
| 267 | ) |
||
| 268 | |||
| 269 | # 4. 保存为HTML文件 |
||
| 270 | fig.write_html("interactive_chart.html") |
||
| 271 | ``` |
||
| 272 | |||
| 273 | #### 使用步骤： |
||
| 274 | 1. 安装依赖： |
||
| 275 | ```bash |
||
| 276 | pip install pandas plotly |
||
| 277 | ``` |
||
| 278 | 2. 运行代码后，生成 `interactive_chart.html`，用浏览器打开即可看到图表。 |
||
| 279 | |||
| 280 | --- |
||
| 281 | |||
| 282 | ### **交互功能对比** |
||
| 283 | | **功能** | **JavaScript/Plotly** | **Python/Plotly** | |
||
| 284 | |------------------------|-----------------------|-------------------| |
||
| 285 | | 缩放/平移 | ✔️ | ✔️ | |
||
| 286 | | 悬停显示数值 | ✔️ | ✔️ | |
||
| 287 | | 数据点高亮 | ✔️ | ✔️ | |
||
| 288 | | 导出为图片（PNG/JPEG） | ✔️ | ✔️ | |
||
| 289 | | 动态更新数据 | ✔️（需额外代码） | ❌ | |
||
| 290 | |||
| 291 | --- |
||
| 292 | |||
| 293 | ### **进阶方案（可选）** |
||
| 294 | 1. **动态数据加载**（JavaScript）： |
||
| 295 | ```html |
||
| 296 | <input type="file" id="csvFile" accept=".csv"> |
||
| 297 | <div id="chart"></div> |
||
| 298 | <script> |
||
| 299 | document.getElementById('csvFile').addEventListener('change', function(e) { |
||
| 300 | const file = e.target.files[0]; |
||
| 301 | const reader = new FileReader(); |
||
| 302 | reader.onload = function(e) { |
||
| 303 | // 解析并绘制图表（代码同方法一） |
||
| 304 | }; |
||
| 305 | reader.readAsText(file); |
||
| 306 | }); |
||
| 307 | </script> |
||
| 308 | ``` |
||
| 309 | - 用户可上传任意CSV文件，实时生成图表。 |
||
| 310 | |||
| 311 | 2. **添加控件**（Python + Dash）： |
||
| 312 | ```python |
||
| 313 | from dash import Dash, dcc, html |
||
| 314 | import pandas as pd |
||
| 315 | import plotly.express as px |
||
| 316 | |||
| 317 | app = Dash(__name__) |
||
| 318 | df = pd.read_csv("data.csv") |
||
| 319 | |||
| 320 | app.layout = html.Div([ |
||
| 321 | dcc.Graph( |
||
| 322 | id='live-chart', |
||
| 323 | figure=px.scatter(df, x='x', y='y', title='Dash动态图表') |
||
| 324 | ), |
||
| 325 | html.Button('更新数据', id='update-button') |
||
| 326 | ]) |
||
| 327 | |||
| 328 | if __name__ == '__main__': |
||
| 329 | app.run_server(debug=True) |
||
| 330 | ``` |
||
| 331 | - 运行后访问 `http://localhost:8050`，支持动态交互和按钮触发操作。 |
||
| 332 | |||
| 333 | --- |
||
| 334 | |||
| 335 | ### **最终效果示例** |
||
| 336 |  |
||
| 337 | |||
| 338 | 选择适合你的场景快速实现吧！ |