DevOps

# Web tech

{{toc}}

## How to visualize data:

D3 ref: https://observablehq.com/@d3/gallery  ,  https://johan.github.io/d3/ex/

Plotly ref: https://plotly.com/javascript/

---

### **交互功能对比**

| **功能**               | **JavaScript/Plotly** | **Python/Plotly** |   **JavaScript/d3**  |

|------------------------|-----------------------|-------------------|----------------------|

| 缩放/平移              | ✔️                    | ✔️               | ✔️                  |

| 悬停显示数值           | ✔️                    | ✔️               | ✔️                  |

| 数据点高亮             | ✔️                    | ✔️               | ✔️                  |

| 导出为图片（PNG/JPEG） | ✔️                    | ✔️               |✔️                  | 

| 动态更新数据           | ✔️（需额外代码）      | ❌               | ✔️                  |

| 旧firefox支持          | ❌（globalthis）      | ?                | ✔️                  |

---

### button

// 设置图表的尺寸和边距

const margin = {top: 20, right: 30, bottom: 30, left: 40},

      width = 960 - margin.left - margin.right,

      height = 500 - margin.top - margin.bottom;

// 设置SVG的尺寸

const svg = d3.select("#chart").append("svg")

    .attr("width", width + margin.left + margin.right)

    .attr("height", height + margin.top + margin.bottom)

  .append("g")

    .attr("transform", `translate(${margin.left},${margin.top})`);

// 设置比例尺

const x = d3.scaleLinear().range([0, width]);

const y = d3.scaleLinear().range([height, 0]);

// 定义折线生成器

const line = d3.line()

    .x(d => x(d.index)) // 使用第一列（index）作为X轴

    .y(d => y(d.observation)); // 使用观测值作为Y轴

// 初始化Y轴数据为第二列（observation1）

let currentY = "observation1";

// 读取CSV文件

d3.csv("data.csv").then(data => {

    // 转换数据类型

    data.forEach(d => {

        d.index = +d.index; // 第一列转换为数值

        d.observation1 = +d.observation1; // 第二列转换为数值

        d.observation2 = +d.observation2; // 第三列转换为数值

    });

    // 设置比例尺的域

    x.domain(d3.extent(data, d => d.index)); // X轴范围为第一列的最小值和最大值

    y.domain([0, d3.max(data, d => Math.max(d.observation1, d.observation2))]); // Y轴范围为0到观测值的最大值

    // 绘制初始折线图（使用observation1）

    drawChart(data);

    // 添加按钮点击事件

    d3.select("#toggleButton").on("click", function() {

        // 切换Y轴数据

        currentY = currentY === "observation1" ? "observation2" : "observation1";

        // 更新按钮文本

        d3.select(this).text(currentY === "observation1" ? "Switch to Observation 2" : "Switch to Observation 1");

        // 重新绘制折线图

        drawChart(data);

    });

});

// 绘制折线图的函数

function drawChart(data) {

    // 移除旧的折线和点

    svg.selectAll(".line").remove();

    svg.selectAll(".dot").remove();

    // 更新折线生成器的Y值

    line.y(d => y(d[currentY]));

    // 添加折线

    svg.append("path")

        .datum(data)

        .attr("class", `line ${currentY === "observation1" ? "line1" : "line2"}`)

        .attr("d", line);

    // 添加点

    svg.selectAll(".dot")

        .data(data)

      .enter().append("circle")

        .attr("class", "dot")

        .attr("cx", d => x(d.index)) // 使用第一列（index）作为X轴

        .attr("cy", d => y(d[currentY])) // 使用当前观测值作为Y轴

        .attr("r", 5)

        .on("mouseover", function(event, d) {

            tooltip.transition()

                .duration(200)

                .style("opacity", .9);

            tooltip.html(`Index: ${d.index}<br>Observation: ${d[currentY]}<br>Label: ${d.label}`)

                .style("left", (event.pageX + 5) + "px")

                .style("top", (event.pageY - 28) + "px");

        })

        .on("mouseout", function(d) {

            tooltip.transition()

                .duration(500)

                .style("opacity", 0);

        });

    // 添加X轴

    svg.select(".x-axis").remove(); // 移除旧的X轴

    svg.append("g")

        .attr("class", "x-axis")

        .attr("transform", `translate(0,${height})`)

        .call(d3.axisBottom(x));

    // 添加Y轴

    svg.select(".y-axis").remove(); // 移除旧的Y轴

    svg.append("g")

        .attr("class", "y-axis")

        .call(d3.axisLeft(y));

}

// 添加提示工具

const tooltip = d3.select("body").append("div")

    .attr("class", "tooltip")

    .style("opacity", 0);

### js d3 读入 csv 并绘制折线交互

{{collapse(show code...)

``` 

// 设置图表的尺寸和边距

const margin = {top: 20, right: 30, bottom: 30, left: 40},

      width = 960 - margin.left - margin.right,

      height = 500 - margin.top - margin.bottom;

// 设置SVG的尺寸

const svg = d3.select("#chart").append("svg")

    .attr("width", width + margin.left + margin.right)

    .attr("height", height + margin.top + margin.bottom)

  .append("g")

    .attr("transform", `translate(${margin.left},${margin.top})`);

// 设置比例尺

const x = d3.scaleLinear().range([0, width]);

const y = d3.scaleLinear().range([height, 0]);

// 定义折线生成器

const line = d3.line()

    .x((d, i) => x(i))

    .y(d => y(d.observation));

// 读取CSV文件

d3.csv("data.csv").then(data => {

    // 转换数据类型

    data.forEach((d, i) => {

        d.observation = +d.observation;

        d.index = i;

    });

    // 设置比例尺的域

    x.domain([0, data.length - 1]);

    y.domain([0, d3.max(data, d => d.observation)]);

    // 添加折线

    svg.append("path")

        .datum(data)

        .attr("class", "line")

        .attr("d", line);

    // 添加点

    svg.selectAll(".dot")

        .data(data)

      .enter().append("circle")

        .attr("class", "dot")

        .attr("cx", (d, i) => x(i))

        .attr("cy", d => y(d.observation))

        .attr("r", 5)

        .on("mouseover", function(event, d) {

            tooltip.transition()

                .duration(200)

                .style("opacity", .9);

            tooltip.html(`Observation: ${d.observation}<br>Label: ${d.label}`)

                .style("left", (event.pageX + 5) + "px")

                .style("top", (event.pageY - 28) + "px");

        })

        .on("mouseout", function(d) {

            tooltip.transition()

                .duration(500)

                .style("opacity", 0);

        });

    // 添加X轴

    svg.append("g")

        .attr("transform", `translate(0,${height})`)

        .call(d3.axisBottom(x));

    // 添加Y轴

    svg.append("g")

        .call(d3.axisLeft(y));

});

// 添加提示工具

const tooltip = d3.select("body").append("div")

    .attr("class", "tooltip")

    .style("opacity", 0);

```

``` 

<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="UTF-8">

    <title>D3.js Line Chart</title>

    <script src="https://d3js.org/d3.v7.min.js"></script>

    <style>

        .line {

            fill: none;

            stroke: steelblue;

            stroke-width: 2px;

        }

        .dot {

            fill: steelblue;

            stroke: #fff;

        }

        .tooltip {

            position: absolute;

            text-align: center;

            width: 120px;

            height: auto;

            padding: 5px;

            font: 12px sans-serif;

            background: lightsteelblue;

            border: 0px;

            border-radius: 8px;

            pointer-events: none;

        }

    </style>

</head>

<body>

    <div id="chart"></div>

    <script src="script.js"></script>

</body>

</html>

```

}}

### js d3 内嵌数据显示折线

{{collapse(show code...)

``` 

<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="UTF-8">

    <meta name="viewport" content="width=device-width, initial-scale=1.0">

    <title>分段填充折线图</title>

    <script src="https://d3js.org/d3.v7.min.js"></script>

    <style>

        .tooltip {

            position: absolute;

            background-color: rgba(255, 255, 255, 0.9);

            border: 1px solid #ccc;

            padding: 5px;

            font-size: 12px;

            pointer-events: none;

            opacity: 0;

        }

        .line {

            fill: none;

            stroke: black;

            stroke-width: 2;

        }

    </style>

</head>

<body>

    <div id="chart"></div>

    <div class="tooltip" id="tooltip"></div>

    <script>

        // 示例数据

        const data = [

            { time: "2025-01-01", value: 10, description: "说明1" },

            { time: "2025-01-02", value: 15, description: "说明2" },

            { time: "2025-01-03", value: 20, description: "说明3" },

            { time: "2025-01-04", value: 25, description: "说明4" },

            { time: "2025-01-05", value: 30, description: "说明5" },

            { time: "2025-01-06", value: 35, description: "说明6" },

            { time: "2025-01-07", value: 40, description: "说明7" },

            { time: "2025-01-08", value: 45, description: "说明8" },

            { time: "2025-01-09", value: 50, description: "说明9" },

            { time: "2025-01-10", value: 55, description: "说明10" },

            { time: "2025-01-11", value: 60, description: "说明11" },

            { time: "2025-01-12", value: 65, description: "说明12" },

            { time: "2025-01-13", value: 70, description: "说明13" },

            { time: "2025-01-14", value: 75, description: "说明14" },

            { time: "2025-01-15", value: 80, description: "说明15" },

            { time: "2025-01-16", value: 85, description: "说明16" },

            { time: "2025-01-17", value: 90, description: "说明17" },

            { time: "2025-01-18", value: 95, description: "说明18" },

            { time: "2025-01-19", value: 100, description: "说明19" },

            { time: "2025-01-20", value: 105, description: "说明20" }

        ];

        // 设置图表尺寸

        const margin = { top: 20, right: 30, bottom: 30, left: 40 };

        const width = 800 - margin.left - margin.right;

        const height = 400 - margin.top - margin.bottom;

        // 创建 SVG 容器

        const svg = d3.select("#chart")

            .append("svg")

            .attr("width", width + margin.left + margin.right)

            .attr("height", height + margin.top + margin.bottom)

            .append("g")

            .attr("transform", `translate(${margin.left},${margin.top})`);

        // 解析时间格式

        const parseTime = d3.timeParse("%Y-%m-%d");

        // 格式化数据

        data.forEach(d => {

            d.time = parseTime(d.time);

            d.value = +d.value;

        });

        // 设置比例尺

        const x = d3.scaleTime()

            .domain(d3.extent(data, d => d.time))

            .range([0, width]);

        const y = d3.scaleLinear()

            .domain([0, d3.max(data, d => d.value)])

            .range([height, 0]);

        // 添加 X 轴

        svg.append("g")

            .attr("transform", `translate(0,${height})`)

            .call(d3.axisBottom(x));

        // 添加 Y 轴

        svg.append("g")

            .call(d3.axisLeft(y));

        // 创建折线生成器

        const line = d3.line()

            .x(d => x(d.time))

            .y(d => y(d.value));

        // 绘制折线

        svg.append("path")

            .datum(data)

            .attr("class", "line")

            .attr("d", line);

        // 分段填充颜色

        const first10 = data.slice(0, 10);

        const last10 = data.slice(-10);

        const middle = data.slice(10, -10);

        // 填充前十个时间段的绿色区域

        svg.append("path")

            .datum(first10)

            .attr("fill", "green")

            .attr("opacity", 0.3)

            .attr("d", d3.area()

                .x(d => x(d.time))

                .y0(height)

                .y1(d => y(d.value))

            );

        // 填充中间时间段的蓝色区域

        svg.append("path")

            .datum(middle)

            .attr("fill", "blue")

            .attr("opacity", 0.3)

            .attr("d", d3.area()

                .x(d => x(d.time))

                .y0(height)

                .y1(d => y(d.value))

            );

        // 填充后十个时间段的红色区域

        svg.append("path")

            .datum(last10)

            .attr("fill", "red")

            .attr("opacity", 0.3)

            .attr("d", d3.area()

                .x(d => x(d.time))

                .y0(height)

                .y1(d => y(d.value))

            );

        // 添加悬停交互

        const tooltip = d3.select("#tooltip");

        svg.selectAll(".dot")

            .data(data)

            .enter()

            .append("circle")

            .attr("class", "dot")

            .attr("cx", d => x(d.time))

            .attr("cy", d => y(d.value))

            .attr("r", 5)

            .attr("fill", "steelblue")

            .on("mouseover", (event, d) => {

                tooltip.style("opacity", 1)

                    .html(`时间: ${d3.timeFormat("%Y-%m-%d")(d.time)}<br>数值: ${d.value}<br>说明: ${d.description}`)

                    .style("left", `${event.pageX + 5}px`)

                    .style("top", `${event.pageY - 20}px`);

            })

            .on("mouseout", () => {

                tooltip.style("opacity", 0);

            });

    </script>

</body>

</html>

```

}}

### JavaScript + Plotly（纯前端实现）

{{collapse(show code...)

```html

<!DOCTYPE html>

<html>

<head>

    <title>交互式图表</title>

    <!-- 引入 Plotly.js -->

    <script src="https://cdn.plot.ly/plotly-2.24.1.min.js"></script>

</head>

<body>

    <div id="chart"></div>

    <script>

        // 读取CSV文件（假设文件名为 data.csv）

        fetch('data.csv')

            .then(response => response.text())

            .then(csvText => {

                // 解析CSV数据

                const rows = csvText.split('\n');

                const x = [], y = [];

                rows.forEach((row, index) => {

                    if (index === 0) return; // 跳过标题行

                    const [xVal, yVal] = row.split(',');

                    x.push(parseFloat(xVal));

                    y.push(parseFloat(yVal));

                });

                // 绘制图表

                Plotly.newPlot('chart', [{

                    x: x,

                    y: y,

                    type: 'scatter',

                    mode: 'lines+markers',

                    marker: { color: 'blue' },

                    line: { shape: 'spline' }

                }], {

                    title: '交互式数据图表',

                    xaxis: { title: 'X轴' },

                    yaxis: { title: 'Y轴' },

                    hovermode: 'closest'

                });

            });

    </script>

</body>

</html>

```

}}

#### 使用步骤：

1. 将CSV文件命名为 `data.csv`，格式如下：

   ```csv

   x,y

   1,5

   2,3

   3,7

   4,2

   5,8

   ```

2. 将HTML文件和 `data.csv` 放在同一目录下，用浏览器打开HTML文件。

3. 效果：支持**缩放、悬停显示数值、拖拽平移**等交互。

---

### Python + Plotly（生成独立HTML文件）

#### 特点：适合Python用户，自动化生成图表文件。

{{collapse(show code...)

```python

import pandas as pd

import plotly.express as px

# 1. 读取CSV文件

df = pd.read_csv("data.csv")

# 2. 创建交互式图表

fig = px.line(

    df, x='x', y='y',

    title='Python生成的交互式图表',

    markers=True,  # 显示数据点

    line_shape='spline'  # 平滑曲线

)

# 3. 自定义悬停效果和样式

fig.update_traces(

    hoverinfo='x+y',  # 悬停显示x和y值

    line=dict(width=2, color='royalblue'),

    marker=dict(size=8, color='firebrick')

)

# 4. 保存为HTML文件

fig.write_html("interactive_chart.html")

```

}}

#### 使用步骤：

1. 安装依赖：

   ```bash

   pip install pandas plotly

   ```

2. 运行代码后，生成 `interactive_chart.html`，用浏览器打开即可看到图表。

### **进阶方案（可选）**

1. **动态数据加载**（JavaScript）：

{{collapse(View details...)

   ```html

   <input type="file" id="csvFile" accept=".csv">

   <div id="chart"></div>

   <script>

     document.getElementById('csvFile').addEventListener('change', function(e) {

       const file = e.target.files[0];

       const reader = new FileReader();

       reader.onload = function(e) {

         // 解析并绘制图表（代码同方法一）

       };

       reader.readAsText(file);

     });

   </script>

   ```

}}

   - 用户可上传任意CSV文件，实时生成图表。

2. **添加控件**（Python + Dash）：

{{collapse(View details...)

   ```python

   from dash import Dash, dcc, html

   import pandas as pd

   import plotly.express as px

   app = Dash(__name__)

   df = pd.read_csv("data.csv")

   app.layout = html.Div([

       dcc.Graph(

           id='live-chart',

           figure=px.scatter(df, x='x', y='y', title='Dash动态图表')

       ),

       html.Button('更新数据', id='update-button')

   ])

   if __name__ == '__main__':

       app.run_server(debug=True)

   ```

}}

   - 运行后访问 `http://localhost:8050`，支持动态交互和按钮触发操作。

---