Progress Telerik 教程（五）：图表与数据可视化完全指南

Progress Telerik Ultimate Collection 2025 Q2下载地址 https://soft51.cc/software/175792580241152290

1. 图表控件概述

Telerik Chart 是功能强大的数据可视化控件，支持多种图表类型和丰富的交互功能。它能够将复杂的数据转化为直观的可视化图表，帮助用户更好地理解数据趋势和模式。

1.1 主要特性

丰富的图表类型：支持30+种图表类型
高性能渲染：基于SVG和Canvas的高效渲染
响应式设计：自适应不同屏幕尺寸
实时数据：支持动态数据更新和实时刷新
交互功能：缩放、平移、工具提示、选择等
主题支持：多种内置主题和自定义样式

1.2 适用场景

销售报表和业务仪表板
数据分析和统计展示
实时监控系统
财务报表和趋势分析
用户行为分析

1.3 支持的图表类型

| 分类 | 图表类型 | 适用场景 | |------|----------|----------| | 基础图表 | 柱状图、条形图、折线图、面积图 | 数据对比、趋势展示 | | 统计图表 | 饼图、环形图、漏斗图 | 占比分析、流程分析 | | 高级图表 | 散点图、气泡图、雷达图 | 多维数据分析 | | 金融图表 | K线图、股票图 | 金融数据分析 |

2. 常见图表类型实现

2.1 柱状图（Column Chart）

基础柱状图

@(Html.Kendo().Chart<SalesData>()
    .Name("columnChart")
    .Title("月度销售统计")
    .Legend(legend => legend.Position(ChartLegendPosition.Top))
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetMonthlySales", "Chart"))
    )
    .Series(series =>
    {
        series.Column(model => model.Sales)
              .Name("销售额")
              .Color("#3498db");
    })
    .CategoryAxis(axis => axis
        .Categories(model => model.Month)
        .MajorGridLines(lines => lines.Visible(false))
    )
    .ValueAxis(axis => axis
        .Numeric()
        .Labels(labels => labels.Format("{0:C}"))
        .Line(line => line.Visible(false))
    )
    .Tooltip(tooltip => tooltip
        .Visible(true)
        .Template("月份: #= category #<br/>销售额: #= kendo.format('{0:C}', value) #")
    )
)

对应的数据模型和控制器：

public class SalesData
{
    public string Month { get; set; }
    public decimal Sales { get; set; }
    public decimal Target { get; set; }
}

[HttpPost]
public IActionResult GetMonthlySales()
{
    var data = new List<SalesData>
    {
        new SalesData { Month = "1月", Sales = 120000, Target = 100000 },
        new SalesData { Month = "2月", Sales = 135000, Target = 110000 },
        new SalesData { Month = "3月", Sales = 98000, Target = 120000 },
        new SalesData { Month = "4月", Sales = 156000, Target = 130000 },
        new SalesData { Month = "5月", Sales = 189000, Target = 140000 },
        new SalesData { Month = "6月", Sales = 201000, Target = 150000 }
    };
    
    return Json(data);
}

多系列柱状图

@(Html.Kendo().Chart<SalesData>()
    .Name("multiColumnChart")
    .Title("销售额与目标对比")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetMonthlySales", "Chart"))
    )
    .Series(series =>
    {
        series.Column(model => model.Sales)
              .Name("实际销售")
              .Color("#3498db")
              .Tooltip(tooltip => tooltip.Template("实际: #= kendo.format('{0:C}', value) #"));
              
        series.Column(model => model.Target)
              .Name("销售目标")
              .Color("#e74c3c")
              .Tooltip(tooltip => tooltip.Template("目标: #= kendo.format('{0:C}', value) #"));
    })
    .CategoryAxis(axis => axis.Categories(model => model.Month))
    .ValueAxis(axis => axis
        .Numeric()
        .Labels(labels => labels.Format("{0:C}"))
    )
    .Legend(legend => legend.Position(ChartLegendPosition.Bottom))
)

堆叠柱状图

@(Html.Kendo().Chart<ProductSalesData>()
    .Name("stackedColumnChart")
    .Title("产品分类销售构成")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetProductSales", "Chart"))
    )
    .Series(series =>
    {
        series.Column(model => model.Electronics)
              .Name("电子产品")
              .Stack(true)
              .Color("#3498db");
              
        series.Column(model => model.Clothing)
              .Name("服装")
              .Stack(true)
              .Color("#e74c3c");
              
        series.Column(model => model.Books)
              .Name("图书")
              .Stack(true)
              .Color("#2ecc71");
    })
    .CategoryAxis(axis => axis.Categories(model => model.Quarter))
    .ValueAxis(axis => axis
        .Numeric()
        .Labels(labels => labels.Format("{0:C}"))
    )
)

2.2 折线图（Line Chart）

基础折线图

@(Html.Kendo().Chart<TrendData>()
    .Name("lineChart")
    .Title("网站流量趋势")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetTrafficTrend", "Chart"))
    )
    .Series(series =>
    {
        series.Line(model => model.PageViews)
              .Name("页面浏览量")
              .Color("#3498db")
              .Width(3)
              .Markers(markers => markers
                  .Type(ChartMarkerShape.Circle)
                  .Size(6)
              );
    })
    .CategoryAxis(axis => axis
        .Categories(model => model.Date)
        .Labels(labels => labels.Format("{0:MM/dd}"))
        .MajorGridLines(lines => lines.Visible(false))
    )
    .ValueAxis(axis => axis
        .Numeric()
        .Labels(labels => labels.Format("{0:N0}"))
        .Title("访问量")
    )
    .Tooltip(tooltip => tooltip
        .Visible(true)
        .Template("日期: #= category #<br/>访问量: #= kendo.format('{0:N0}', value) #")
    )
)

多系列折线图

@(Html.Kendo().Chart<WebAnalyticsData>()
    .Name("multiLineChart")
    .Title("网站分析数据")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetWebAnalytics", "Chart"))
    )
    .Series(series =>
    {
        series.Line(model => model.PageViews)
              .Name("页面浏览量")
              .Color("#3498db")
              .Width(2);
              
        series.Line(model => model.UniqueVisitors)
              .Name("独立访客")
              .Color("#e74c3c")
              .Width(2);
              
        series.Line(model => model.BounceRate)
              .Name("跳出率 (%)")
              .Color("#f39c12")
              .Width(2)
              .Axis("bounceRateAxis");
    })
    .CategoryAxis(axis => axis
        .Categories(model => model.Date)
        .Labels(labels => labels.Format("{0:MM/dd}"))
    )
    .ValueAxis(axis => axis
        .Numeric()
        .Labels(labels => labels.Format("{0:N0}"))
        .Title("访问量")
    )
    .ValueAxis(axis => axis
        .Numeric()
        .Name("bounceRateAxis")
        .Labels(labels => labels.Format("{0}%"))
        .Title("跳出率")
        .Position(ChartAxisPosition.Right)
    )
)

2.3 饼图（Pie Chart）

基础饼图

@(Html.Kendo().Chart<CategoryData>()
    .Name("pieChart")
    .Title("销售分类占比")
    .Legend(legend => legend
        .Position(ChartLegendPosition.Right)
        .Labels(labels => labels.Template("#= text # (#= kendo.format('{0:P}', percentage)#)"))
    )
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetCategorySales", "Chart"))
    )
    .Series(series =>
    {
        series.Pie(model => model.Value, model => model.Category)
              .Labels(labels => labels
                  .Visible(true)
                  .Template("#= category #: #= kendo.format('{0:P}', percentage) #")
                  .Position(ChartPieLabelsPosition.OutsideEnd)
              )
              .Tooltip(tooltip => tooltip
                  .Visible(true)
                  .Template("#= category #<br/>金额: #= kendo.format('{0:C}', value) #<br/>占比: #= kendo.format('{0:P}', percentage) #")
              );
    })
    .Tooltip(tooltip => tooltip.Visible(true))
)

环形图（Donut Chart）

@(Html.Kendo().Chart<CategoryData>()
    .Name("donutChart")
    .Title("市场份额分布")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetMarketShare", "Chart"))
    )
    .Series(series =>
    {
        series.Pie(model => model.Value, model => model.Category)
              .StartAngle(150)
              .HoleSize(80)
              .Labels(labels => labels
                  .Visible(true)
                  .Template("#= category #")
                  .Position(ChartPieLabelsPosition.Center)
              );
    })
    .Tooltip(tooltip => tooltip
        .Visible(true)
        .Template("#= category #: #= kendo.format('{0:P}', percentage) #")
    )
)

2.4 混合图表

@(Html.Kendo().Chart<MixedData>()
    .Name("mixedChart")
    .Title("销售额与利润率分析")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetMixedData", "Chart"))
    )
    .Series(series =>
    {
        // 柱状图显示销售额
        series.Column(model => model.Sales)
              .Name("销售额")
              .Color("#3498db")
              .Tooltip(tooltip => tooltip.Template("销售额: #= kendo.format('{0:C}', value) #"));
              
        // 折线图显示利润率
        series.Line(model => model.ProfitMargin)
              .Name("利润率")
              .Color("#e74c3c")
              .Width(3)
              .Axis("profitAxis")
              .Markers(markers => markers.Size(8))
              .Tooltip(tooltip => tooltip.Template("利润率: #= value #%"));
    })
    .CategoryAxis(axis => axis.Categories(model => model.Period))
    .ValueAxis(axis => axis
        .Numeric()
        .Labels(labels => labels.Format("{0:C}"))
        .Title("销售额")
    )
    .ValueAxis(axis => axis
        .Numeric()
        .Name("profitAxis")
        .Labels(labels => labels.Format("{0}%"))
        .Title("利润率")
        .Position(ChartAxisPosition.Right)
    )
)

3. 实时数据刷新与动态交互

3.1 实时数据刷新

SignalR 实时数据推送

// SignalR Hub
public class ChartHub : Hub
{
    public async Task JoinGroup(string groupName)
    {
        await Groups.AddToGroupAsync(Context.ConnectionId, groupName);
    }
}

// 数据服务
public class RealTimeDataService
{
    private readonly IHubContext<ChartHub> _hubContext;
    private readonly Timer _timer;

    public RealTimeDataService(IHubContext<ChartHub> hubContext)
    {
        _hubContext = hubContext;
        _timer = new Timer(SendRealTimeData, null, TimeSpan.Zero, TimeSpan.FromSeconds(5));
    }

    private async void SendRealTimeData(object state)
    {
        var data = GenerateRealTimeData();
        await _hubContext.Clients.All.SendAsync("UpdateChartData", data);
    }

    private object GenerateRealTimeData()
    {
        var random = new Random();
        return new
        {
            timestamp = DateTime.Now,
            value = random.Next(50, 200),
            category = "实时数据"
        };
    }
}

客户端实时更新

@(Html.Kendo().Chart<RealTimeData>()
    .Name("realTimeChart")
    .Title("实时数据监控")
    .DataSource(dataSource => dataSource
        .SignalR()
        .Transport(transport => transport
            .Promise("hubStart")
            .Hub("chartHub")
            .Client(client => client
                .Read("updateChartData")
            )
        )
        .Schema(schema => schema
            .Model(model => {
                model.Id("timestamp");
            })
        )
    )
    .Series(series =>
    {
        series.Line(model => model.Value)
              .Name("实时值")
              .Color("#3498db")
              .Width(2);
    })
    .CategoryAxis(axis => axis
        .Categories(model => model.Timestamp)
        .Labels(labels => labels.Format("{0:HH:mm:ss}"))
        .MajorGridLines(lines => lines.Visible(false))
    )
)

<script src="~/lib/signalr/signalr.min.js"></script>
<script>
// SignalR 连接
var connection = new signalR.HubConnectionBuilder()
    .withUrl("/charthub")
    .build();

var hubStart = connection.start();

// 接收实时数据
connection.on("updateChartData", function(data) {
    var chart = $("#realTimeChart").data("kendoChart");
    var dataSource = chart.dataSource;
    
    // 添加新数据点
    dataSource.add(data);
    
    // 保持最近50个数据点
    var items = dataSource.data();
    if (items.length > 50) {
        dataSource.remove(items[0]);
    }
});
</script>

3.2 定时数据刷新

@(Html.Kendo().Chart<SystemMetrics>()
    .Name("systemMetricsChart")
    .Title("系统性能监控")
    .DataSource(dataSource => dataSource
        .Ajax()
        .Transport(transport => transport
            .Read(read => read.Action("GetSystemMetrics", "Monitoring"))
        )
        .ServerOperation(false)
    )
    .Series(series =>
    {
        series.Line(model => model.CpuUsage)
              .Name("CPU使用率 (%)")
              .Color("#e74c3c");
              
        series.Line(model => model.MemoryUsage)
              .Name("内存使用率 (%)")
              .Color("#3498db");
              
        series.Line(model => model.DiskUsage)
              .Name("磁盘使用率 (%)")
              .Color("#f39c12");
    })
    .CategoryAxis(axis => axis
        .Categories(model => model.Timestamp)
        .Labels(labels => labels.Format("{0:HH:mm}"))
    )
    .ValueAxis(axis => axis
        .Numeric()
        .Min(0)
        .Max(100)
        .Labels(labels => labels.Format("{0}%"))
    )
)

<script>
$(document).ready(function() {
    // 每30秒刷新一次数据
    setInterval(function() {
        var chart = $("#systemMetricsChart").data("kendoChart");
        chart.dataSource.read();
    }, 30000);
    
    // 添加手动刷新按钮
    $("#refreshButton").click(function() {
        var chart = $("#systemMetricsChart").data("kendoChart");
        chart.dataSource.read();
        
        // 显示刷新动画
        showRefreshAnimation();
    });
});

function showRefreshAnimation() {
    var chart = $("#systemMetricsChart").data("kendoChart");
    
    // 添加加载指示器
    chart.surface.draw(chart._createLoadingIndicator());
    
    setTimeout(function() {
        chart.redraw();
    }, 1000);
}
</script>

3.3 交互式图表功能

缩放和平移

@(Html.Kendo().Chart<HistoricalData>()
    .Name("zoomableChart")
    .Title("历史数据分析（支持缩放）")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetHistoricalData", "Chart"))
    )
    .Series(series =>
    {
        series.Line(model => model.Value)
              .Name("数据值")
              .Color("#3498db");
    })
    .CategoryAxis(axis => axis
        .Categories(model => model.Date)
        .Labels(labels => labels.Format("{0:yyyy-MM-dd}"))
    )
    .Pannable(pannable => pannable.Lock(ChartAxisLock.Y))
    .Zoomable(zoomable => zoomable.MouseWheel(mouseWheel => mouseWheel.Lock(ChartAxisLock.Y)))
    .Navigator(navigator => navigator
        .Visible(true)
        .Series(series => series.Line(model => model.Value))
    )
)

钻取功能

@(Html.Kendo().Chart<DrillDownData>()
    .Name("drillDownChart")
    .Title("销售数据钻取分析")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetDrillDownData", "Chart"))
    )
    .Series(series =>
    {
        series.Column(model => model.Value)
              .Name("销售额")
              .Color("#3498db");
    })
    .CategoryAxis(axis => axis.Categories(model => model.Category))
    .SeriesClick("onSeriesClick")
)

<script>
function onSeriesClick(e) {
    var category = e.category;
    var value = e.value;
    
    // 弹出详细数据窗口
    showDrillDownDetails(category, value);
}

function showDrillDownDetails(category, value) {
    // 创建详细数据图表
    $.post('/Chart/GetDrillDownDetails', { category: category }, function(data) {
        $("#drillDownModal").modal('show');
        
        $("#detailChart").kendoChart({
            title: { text: category + " 详细数据" },
            dataSource: data,
            series: [{
                type: "pie",
                field: "value",
                categoryField: "subcategory"
            }]
        });
    });
}
</script>

3.4 数据导出功能

@(Html.Kendo().Chart<ExportData>()
    .Name("exportChart")
    .Title("数据报表")
    .DataSource(dataSource => dataSource
        .Read(read => read.Action("GetReportData", "Chart"))
    )
    .Series(series =>
    {
        series.Column(model => model.Value)
              .Name("数据值");
    })
    .CategoryAxis(axis => axis.Categories(model => model.Category))
    .Pdf(pdf => pdf
        .FileName("chart-report.pdf")
        .ProxyURL(Url.Action("Pdf_Export_Save", "Chart"))
    )
)

<div class="chart-controls mt-3">
    <button type="button" class="btn btn-primary" onclick="exportToPdf()">
        <i class="fa fa-file-pdf"></i> 导出PDF
    </button>
    <button type="button" class="btn btn-success" onclick="exportToImage()">
        <i class="fa fa-image"></i> 导出图片
    </button>
    <button type="button" class="btn btn-info" onclick="exportToSVG()">
        <i class="fa fa-vector-square"></i> 导出SVG
    </button>
</div>

<script>
function exportToPdf() {
    var chart = $("#exportChart").data("kendoChart");
    chart.exportPDF({
        paperSize: "A4",
        margin: { top: "1cm", bottom: "1cm", right: "1cm", left: "1cm" }
    }).done(function(data) {
        saveAs(dataURItoBlob(data), "chart-report.pdf");
    });
}

function exportToImage() {
    var chart = $("#exportChart").data("kendoChart");
    chart.exportImage({
        width: 800,
        height: 600
    }).done(function(data) {
        saveAs(dataURItoBlob(data), "chart-report.png");
    });
}

function exportToSVG() {
    var chart = $("#exportChart").data("kendoChart");
    chart.exportSVG().done(function(data) {
        var blob = new Blob([data], { type: "image/svg+xml" });
        saveAs(blob, "chart-report.svg");
    });
}

function dataURItoBlob(dataURI) {
    var byteString = atob(dataURI.split(',')[1]);
    var mimeString = dataURI.split(',')[0].split(':')[1].split(';')[0];
    var ab = new ArrayBuffer(byteString.length);
    var ia = new Uint8Array(ab);
    
    for (var i = 0; i < byteString.length; i++) {
        ia[i] = byteString.charCodeAt(i);
    }
    
    return new Blob([ab], { type: mimeString });
}
</script>

4. 综合实例：业务仪表板

<div class="container-fluid">
    <div class="row mb-4">
        <div class="col">
            <h2>销售业绩仪表板</h2>
            <p class="text-muted">实时销售数据监控与分析</p>
        </div>
        <div class="col-auto">
            <div class="btn-group" role="group">
                <button type="button" class="btn btn-outline-primary" onclick="refreshAllCharts()">
                    <i class="fa fa-refresh"></i> 刷新数据
                </button>
                <button type="button" class="btn btn-outline-secondary" onclick="exportDashboard()">
                    <i class="fa fa-download"></i> 导出报告
                </button>
            </div>
        </div>
    </div>

    <div class="row mb-4">
        <div class="col-md-8">
            @(Html.Kendo().Chart<MonthlySalesData>()
                .Name("salesTrendChart")
                .Title("月度销售趋势")
                .DataSource(dataSource => dataSource
                    .Read(read => read.Action("GetSalesTrend", "Dashboard"))
                )
                .Series(series =>
                {
                    series.Line(model => model.ActualSales)
                          .Name("实际销售")
                          .Color("#3498db")
                          .Width(3);
                          
                    series.Line(model => model.TargetSales)
                          .Name("销售目标")
                          .Color("#e74c3c")
                          .DashType(ChartDashType.Dash)
                          .Width(2);
                })
                .CategoryAxis(axis => axis.Categories(model => model.Month))
                .ValueAxis(axis => axis
                    .Numeric()
                    .Labels(labels => labels.Format("{0:C}"))
                )
                .Height(300)
            )
        </div>
        
        <div class="col-md-4">
            @(Html.Kendo().Chart<RegionSalesData>()
                .Name("regionChart")
                .Title("区域销售分布")
                .DataSource(dataSource => dataSource
                    .Read(read => read.Action("GetRegionSales", "Dashboard"))
                )
                .Series(series =>
                {
                    series.Pie(model => model.Sales, model => model.Region)
                          .HoleSize(40)
                          .Labels(labels => labels
                              .Visible(true)
                              .Template("#= category #")
                          );
                })
                .Height(300)
            )
        </div>
    </div>

    <div class="row">
        <div class="col-md-6">
            @(Html.Kendo().Chart<ProductPerformanceData>()
                .Name("productChart")
                .Title("产品销售排行")
                .DataSource(dataSource => dataSource
                    .Read(read => read.Action("GetProductPerformance", "Dashboard"))
                )
                .Series(series =>
                {
                    series.Bar(model => model.Sales)
                          .Name("销售额")
                          .Color("#2ecc71");
                })
                .CategoryAxis(axis => axis
                    .Categories(model => model.ProductName)
                    .MajorGridLines(lines => lines.Visible(false))
                )
                .ValueAxis(axis => axis
                    .Numeric()
                    .Labels(labels => labels.Format("{0:C}"))
                )
                .Height(300)
            )
        </div>
        
        <div class="col-md-6">
            @(Html.Kendo().Chart<RealTimeMetrics>()
                .Name("realTimeChart")
                .Title("实时销售监控")
                .DataSource(dataSource => dataSource
                    .Read(read => read.Action("GetRealTimeMetrics", "Dashboard"))
                    .ServerOperation(false)
                )
                .Series(series =>
                {
                    series.Area(model => model.Value)
                          .Name("实时销售")
                          .Color("#9b59b6")
                          .Opacity(0.7);
                })
                .CategoryAxis(axis => axis
                    .Categories(model => model.Time)
                    .Labels(labels => labels.Format("{0:HH:mm}"))
                )
                .Height(300)
            )
        </div>
    </div>
</div>

<script>
$(document).ready(function() {
    // 每分钟刷新实时数据
    setInterval(function() {
        $("#realTimeChart").data("kendoChart").dataSource.read();
    }, 60000);
});

function refreshAllCharts() {
    $("#salesTrendChart").data("kendoChart").dataSource.read();
    $("#regionChart").data("kendoChart").dataSource.read();
    $("#productChart").data("kendoChart").dataSource.read();
    $("#realTimeChart").data("kendoChart").dataSource.read();
    
    showNotification("数据已刷新", "success");
}

function exportDashboard() {
    // 导出所有图表为PDF报告
    var charts = ["salesTrendChart", "regionChart", "productChart", "realTimeChart"];
    var promises = [];
    
    charts.forEach(function(chartName) {
        var chart = $("#" + chartName).data("kendoChart");
        promises.push(chart.exportImage());
    });
    
    Promise.all(promises).then(function(images) {
        generatePDFReport(images);
    });
}

function generatePDFReport(images) {
    // 使用jsPDF生成报告
    var doc = new jsPDF();
    
    doc.setFontSize(20);
    doc.text("销售业绩报告", 20, 30);
    
    doc.setFontSize(12);
    doc.text("生成时间: " + new Date().toLocaleString(), 20, 45);
    
    // 添加图表图片到PDF
    images.forEach(function(image, index) {
        if (index > 0) doc.addPage();
        doc.addImage(image, 'PNG', 10, 60, 190, 120);
    });
    
    doc.save("sales-dashboard-report.pdf");
}

function showNotification(message, type) {
    // 显示通知消息
    var alertClass = type === 'success' ? 'alert-success' : 'alert-info';
    var alert = '<div class="alert ' + alertClass + ' alert-dismissible fade show" role="alert">' +
                message +
                '<button type="button" class="btn-close" data-bs-dismiss="alert"></button>' +
                '</div>';
    
    $("#notifications").html(alert);
    
    setTimeout(function() {
        $(".alert").alert('close');
    }, 3000);
}
</script>

总结

本教程全面介绍了Telerik Chart图表控件的核心功能和应用：

常见图表类型：
- 柱状图：适用于数据对比和分类展示
- 折线图：展示数据趋势和时间序列变化
- 饼图：显示数据占比和构成分析
- 混合图表：多维度数据综合展示
实时数据功能：
- SignalR实时数据推送
- 定时数据刷新机制
- 动态数据更新处理
交互式功能：
- 图表缩放和平移操作
- 数据钻取和详细分析
- 工具提示和选择交互
- 多格式数据导出
实际应用：
- 业务仪表板设计
- 实时监控系统
- 数据分析报表
- 可视化交互界面

通过掌握这些图表技术，您可以构建功能强大、视觉美观的数据可视化应用，有效展示业务数据，帮助用户快速理解数据趋势和做出决策。Telerik Chart的丰富功能和灵活配置使其成为企业级数据可视化的理想选择。

Progress Telerik Ultimate Collection 2025 Q2下载地址 https://soft51.cc/software/175792580241152290