Web tech » History » Version 11
jun chen, 02/12/2025 10:51 AM
| 1 | 1 | jun chen | # Web tech |
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| 3 | 3 | jun chen | {{toc}} |
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| 5 | 1 | jun chen | |
| 6 | 4 | jun chen | ## How to visualize data: |
| 7 | |||
| 8 | D3 ref: https://observablehq.com/@d3/gallery , https://johan.github.io/d3/ex/ |
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| 9 | Plotly ref: https://plotly.com/javascript/ |
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| 10 | |||
| 11 | 5 | jun chen | ### js d3 内嵌数据显示折线 |
| 12 | 4 | jun chen | |
| 13 | 6 | jun chen | {{collapse(show code...) |
| 14 | |||
| 15 | 1 | jun chen | ``` |
| 16 | <!DOCTYPE html> |
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| 17 | <html lang="en"> |
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| 18 | <head> |
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| 19 | <meta charset="UTF-8"> |
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| 20 | <meta name="viewport" content="width=device-width, initial-scale=1.0"> |
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| 21 | <title>分段填充折线图</title> |
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| 22 | <script src="https://d3js.org/d3.v7.min.js"></script> |
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| 23 | <style> |
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| 24 | .tooltip { |
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| 25 | position: absolute; |
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| 26 | background-color: rgba(255, 255, 255, 0.9); |
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| 27 | border: 1px solid #ccc; |
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| 28 | padding: 5px; |
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| 29 | font-size: 12px; |
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| 30 | pointer-events: none; |
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| 31 | opacity: 0; |
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| 32 | } |
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| 33 | .line { |
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| 34 | fill: none; |
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| 35 | stroke: black; |
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| 36 | stroke-width: 2; |
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| 37 | } |
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| 38 | </style> |
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| 39 | </head> |
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| 40 | <body> |
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| 41 | <div id="chart"></div> |
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| 42 | <div class="tooltip" id="tooltip"></div> |
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| 43 | |||
| 44 | <script> |
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| 45 | // 示例数据 |
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| 46 | const data = [ |
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| 47 | { time: "2025-01-01", value: 10, description: "说明1" }, |
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| 48 | { time: "2025-01-02", value: 15, description: "说明2" }, |
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| 49 | { time: "2025-01-03", value: 20, description: "说明3" }, |
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| 50 | { time: "2025-01-04", value: 25, description: "说明4" }, |
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| 51 | { time: "2025-01-05", value: 30, description: "说明5" }, |
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| 52 | { time: "2025-01-06", value: 35, description: "说明6" }, |
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| 53 | { time: "2025-01-07", value: 40, description: "说明7" }, |
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| 54 | { time: "2025-01-08", value: 45, description: "说明8" }, |
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| 55 | { time: "2025-01-09", value: 50, description: "说明9" }, |
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| 56 | { time: "2025-01-10", value: 55, description: "说明10" }, |
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| 57 | { time: "2025-01-11", value: 60, description: "说明11" }, |
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| 58 | { time: "2025-01-12", value: 65, description: "说明12" }, |
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| 59 | { time: "2025-01-13", value: 70, description: "说明13" }, |
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| 60 | { time: "2025-01-14", value: 75, description: "说明14" }, |
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| 61 | { time: "2025-01-15", value: 80, description: "说明15" }, |
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| 62 | { time: "2025-01-16", value: 85, description: "说明16" }, |
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| 63 | { time: "2025-01-17", value: 90, description: "说明17" }, |
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| 64 | { time: "2025-01-18", value: 95, description: "说明18" }, |
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| 65 | { time: "2025-01-19", value: 100, description: "说明19" }, |
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| 66 | { time: "2025-01-20", value: 105, description: "说明20" } |
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| 67 | ]; |
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| 68 | |||
| 69 | // 设置图表尺寸 |
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| 70 | const margin = { top: 20, right: 30, bottom: 30, left: 40 }; |
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| 71 | const width = 800 - margin.left - margin.right; |
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| 72 | const height = 400 - margin.top - margin.bottom; |
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| 73 | |||
| 74 | // 创建 SVG 容器 |
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| 75 | const svg = d3.select("#chart") |
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| 76 | .append("svg") |
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| 77 | .attr("width", width + margin.left + margin.right) |
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| 78 | .attr("height", height + margin.top + margin.bottom) |
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| 79 | .append("g") |
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| 80 | .attr("transform", `translate(${margin.left},${margin.top})`); |
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| 81 | |||
| 82 | // 解析时间格式 |
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| 83 | const parseTime = d3.timeParse("%Y-%m-%d"); |
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| 84 | |||
| 85 | // 格式化数据 |
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| 86 | data.forEach(d => { |
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| 87 | d.time = parseTime(d.time); |
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| 88 | d.value = +d.value; |
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| 89 | }); |
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| 90 | |||
| 91 | // 设置比例尺 |
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| 92 | const x = d3.scaleTime() |
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| 93 | .domain(d3.extent(data, d => d.time)) |
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| 94 | .range([0, width]); |
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| 95 | |||
| 96 | const y = d3.scaleLinear() |
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| 97 | .domain([0, d3.max(data, d => d.value)]) |
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| 98 | .range([height, 0]); |
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| 99 | |||
| 100 | // 添加 X 轴 |
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| 101 | svg.append("g") |
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| 102 | .attr("transform", `translate(0,${height})`) |
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| 103 | .call(d3.axisBottom(x)); |
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| 104 | |||
| 105 | // 添加 Y 轴 |
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| 106 | svg.append("g") |
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| 107 | .call(d3.axisLeft(y)); |
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| 108 | |||
| 109 | // 创建折线生成器 |
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| 110 | const line = d3.line() |
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| 111 | .x(d => x(d.time)) |
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| 112 | .y(d => y(d.value)); |
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| 113 | |||
| 114 | // 绘制折线 |
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| 115 | svg.append("path") |
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| 116 | .datum(data) |
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| 117 | .attr("class", "line") |
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| 118 | .attr("d", line); |
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| 119 | |||
| 120 | // 分段填充颜色 |
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| 121 | const first10 = data.slice(0, 10); |
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| 122 | const last10 = data.slice(-10); |
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| 123 | const middle = data.slice(10, -10); |
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| 124 | |||
| 125 | // 填充前十个时间段的绿色区域 |
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| 126 | svg.append("path") |
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| 127 | .datum(first10) |
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| 128 | .attr("fill", "green") |
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| 129 | .attr("opacity", 0.3) |
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| 130 | .attr("d", d3.area() |
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| 131 | .x(d => x(d.time)) |
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| 132 | .y0(height) |
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| 133 | .y1(d => y(d.value)) |
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| 134 | ); |
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| 135 | |||
| 136 | // 填充中间时间段的蓝色区域 |
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| 137 | svg.append("path") |
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| 138 | .datum(middle) |
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| 139 | .attr("fill", "blue") |
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| 140 | .attr("opacity", 0.3) |
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| 141 | .attr("d", d3.area() |
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| 142 | .x(d => x(d.time)) |
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| 143 | .y0(height) |
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| 144 | .y1(d => y(d.value)) |
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| 145 | ); |
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| 146 | |||
| 147 | // 填充后十个时间段的红色区域 |
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| 148 | svg.append("path") |
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| 149 | .datum(last10) |
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| 150 | .attr("fill", "red") |
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| 151 | .attr("opacity", 0.3) |
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| 152 | .attr("d", d3.area() |
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| 153 | .x(d => x(d.time)) |
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| 154 | .y0(height) |
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| 155 | .y1(d => y(d.value)) |
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| 156 | ); |
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| 157 | |||
| 158 | // 添加悬停交互 |
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| 159 | const tooltip = d3.select("#tooltip"); |
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| 160 | |||
| 161 | svg.selectAll(".dot") |
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| 162 | .data(data) |
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| 163 | .enter() |
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| 164 | .append("circle") |
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| 165 | .attr("class", "dot") |
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| 166 | .attr("cx", d => x(d.time)) |
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| 167 | .attr("cy", d => y(d.value)) |
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| 168 | .attr("r", 5) |
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| 169 | .attr("fill", "steelblue") |
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| 170 | .on("mouseover", (event, d) => { |
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| 171 | tooltip.style("opacity", 1) |
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| 172 | .html(`时间: ${d3.timeFormat("%Y-%m-%d")(d.time)}<br>数值: ${d.value}<br>说明: ${d.description}`) |
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| 173 | .style("left", `${event.pageX + 5}px`) |
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| 174 | .style("top", `${event.pageY - 20}px`); |
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| 175 | }) |
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| 176 | .on("mouseout", () => { |
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| 177 | tooltip.style("opacity", 0); |
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| 178 | }); |
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| 179 | </script> |
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| 180 | </body> |
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| 181 | </html> |
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| 182 | ``` |
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| 183 | 6 | jun chen | |
| 184 | }} |
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| 185 | 1 | jun chen | |
| 186 | 8 | jun chen | ### JavaScript + Plotly（纯前端实现）** |
| 187 | 1 | jun chen | |
| 188 | 8 | jun chen | {{collapse(show code...) |
| 189 | |||
| 190 | 1 | jun chen | ```html |
| 191 | <!DOCTYPE html> |
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| 192 | <html> |
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| 193 | <head> |
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| 194 | <title>交互式图表</title> |
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| 195 | <!-- 引入 Plotly.js --> |
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| 196 | <script src="https://cdn.plot.ly/plotly-2.24.1.min.js"></script> |
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| 197 | </head> |
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| 198 | <body> |
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| 199 | <div id="chart"></div> |
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| 200 | |||
| 201 | <script> |
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| 202 | // 读取CSV文件（假设文件名为 data.csv） |
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| 203 | fetch('data.csv') |
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| 204 | .then(response => response.text()) |
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| 205 | .then(csvText => { |
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| 206 | // 解析CSV数据 |
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| 207 | const rows = csvText.split('\n'); |
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| 208 | const x = [], y = []; |
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| 209 | rows.forEach((row, index) => { |
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| 210 | if (index === 0) return; // 跳过标题行 |
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| 211 | const [xVal, yVal] = row.split(','); |
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| 212 | x.push(parseFloat(xVal)); |
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| 213 | y.push(parseFloat(yVal)); |
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| 214 | }); |
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| 215 | |||
| 216 | // 绘制图表 |
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| 217 | Plotly.newPlot('chart', [{ |
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| 218 | x: x, |
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| 219 | y: y, |
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| 220 | type: 'scatter', |
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| 221 | mode: 'lines+markers', |
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| 222 | marker: { color: 'blue' }, |
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| 223 | line: { shape: 'spline' } |
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| 224 | }], { |
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| 225 | title: '交互式数据图表', |
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| 226 | xaxis: { title: 'X轴' }, |
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| 227 | yaxis: { title: 'Y轴' }, |
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| 228 | hovermode: 'closest' |
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| 229 | }); |
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| 230 | }); |
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| 231 | </script> |
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| 232 | </body> |
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| 233 | </html> |
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| 234 | ``` |
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| 235 | 8 | jun chen | }} |
| 236 | 1 | jun chen | |
| 237 | #### 使用步骤： |
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| 238 | 1. 将CSV文件命名为 `data.csv`，格式如下： |
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| 239 | ```csv |
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| 240 | x,y |
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| 241 | 1,5 |
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| 242 | 2,3 |
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| 243 | 3,7 |
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| 244 | 4,2 |
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| 245 | 5,8 |
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| 246 | ``` |
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| 247 | 2. 将HTML文件和 `data.csv` 放在同一目录下，用浏览器打开HTML文件。 |
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| 248 | 3. 效果：支持**缩放、悬停显示数值、拖拽平移**等交互。 |
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| 249 | |||
| 250 | --- |
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| 251 | |||
| 252 | 9 | jun chen | ### Python + Plotly（生成独立HTML文件）** |
| 253 | 1 | jun chen | #### 特点：适合Python用户，自动化生成图表文件。 |
| 254 | |||
| 255 | 9 | jun chen | {{collapse(show code...) |
| 256 | 1 | jun chen | ```python |
| 257 | import pandas as pd |
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| 258 | import plotly.express as px |
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| 259 | |||
| 260 | # 1. 读取CSV文件 |
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| 261 | df = pd.read_csv("data.csv") |
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| 262 | |||
| 263 | # 2. 创建交互式图表 |
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| 264 | fig = px.line( |
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| 265 | df, x='x', y='y', |
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| 266 | title='Python生成的交互式图表', |
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| 267 | markers=True, # 显示数据点 |
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| 268 | line_shape='spline' # 平滑曲线 |
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| 269 | ) |
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| 270 | |||
| 271 | # 3. 自定义悬停效果和样式 |
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| 272 | fig.update_traces( |
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| 273 | hoverinfo='x+y', # 悬停显示x和y值 |
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| 274 | line=dict(width=2, color='royalblue'), |
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| 275 | marker=dict(size=8, color='firebrick') |
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| 276 | ) |
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| 277 | |||
| 278 | # 4. 保存为HTML文件 |
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| 279 | fig.write_html("interactive_chart.html") |
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| 280 | ``` |
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| 281 | 9 | jun chen | }} |
| 282 | 1 | jun chen | |
| 283 | #### 使用步骤： |
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| 284 | 1. 安装依赖： |
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| 285 | ```bash |
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| 286 | pip install pandas plotly |
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| 287 | ``` |
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| 288 | 2. 运行代码后，生成 `interactive_chart.html`，用浏览器打开即可看到图表。 |
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| 289 | |||
| 290 | --- |
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| 291 | |||
| 292 | ### **交互功能对比** |
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| 293 | | **功能** | **JavaScript/Plotly** | **Python/Plotly** | |
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| 294 | |------------------------|-----------------------|-------------------| |
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| 295 | | 缩放/平移 | ✔️ | ✔️ | |
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| 296 | | 悬停显示数值 | ✔️ | ✔️ | |
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| 297 | | 数据点高亮 | ✔️ | ✔️ | |
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| 298 | | 导出为图片（PNG/JPEG） | ✔️ | ✔️ | |
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| 299 | | 动态更新数据 | ✔️（需额外代码） | ❌ | |
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| 300 | |||
| 301 | --- |
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| 302 | |||
| 303 | ### **进阶方案（可选）** |
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| 304 | 1. **动态数据加载**（JavaScript）： |
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| 305 | 11 | jun chen | |
| 306 | {{collapse(View details...) |
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| 307 | 1 | jun chen | ```html |
| 308 | <input type="file" id="csvFile" accept=".csv"> |
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| 309 | <div id="chart"></div> |
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| 310 | <script> |
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| 311 | document.getElementById('csvFile').addEventListener('change', function(e) { |
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| 312 | const file = e.target.files[0]; |
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| 313 | const reader = new FileReader(); |
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| 314 | reader.onload = function(e) { |
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| 315 | // 解析并绘制图表（代码同方法一） |
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| 316 | }; |
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| 317 | reader.readAsText(file); |
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| 318 | }); |
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| 319 | </script> |
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| 320 | ``` |
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| 321 | 11 | jun chen | }} |
| 322 | 1 | jun chen | - 用户可上传任意CSV文件，实时生成图表。 |
| 323 | |||
| 324 | 11 | jun chen | |
| 325 | 1 | jun chen | 2. **添加控件**（Python + Dash）： |
| 326 | 11 | jun chen | {{collapse(View details...) |
| 327 | 1 | jun chen | ```python |
| 328 | from dash import Dash, dcc, html |
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| 329 | import pandas as pd |
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| 330 | import plotly.express as px |
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| 331 | |||
| 332 | app = Dash(__name__) |
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| 333 | df = pd.read_csv("data.csv") |
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| 334 | |||
| 335 | app.layout = html.Div([ |
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| 336 | dcc.Graph( |
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| 337 | id='live-chart', |
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| 338 | figure=px.scatter(df, x='x', y='y', title='Dash动态图表') |
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| 339 | ), |
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| 340 | html.Button('更新数据', id='update-button') |
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| 341 | ]) |
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| 342 | |||
| 343 | if __name__ == '__main__': |
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| 344 | app.run_server(debug=True) |
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| 345 | ``` |
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| 346 | 11 | jun chen | }} |
| 347 | |||
| 348 | 1 | jun chen | - 运行后访问 `http://localhost:8050`，支持动态交互和按钮触发操作。 |
| 349 | |||
| 350 | --- |