商品明細

TeeChart for .NET 圖表開發

    商品簡述

    TeeChart 帶有地圖和儀表的圖表組件套件供開發人員使用

      商品介紹

      本產品出貨為最新版本。
      如需購買或了解內容請來電(2749-1909)或來信(sales@ahasoft.com.tw)業務部
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      Flexible data visualisation

      for WinForms, WPF, UWP and Xamarin

      The chart component for .NET handles your data, creating informative and attractive charts, seamlessly across a variety of platforms including: Windows Forms, WPF, ASP.NET (& ASP.NET Core, NET5/NET6) with HTML5 /Javascript rendering and Universal Windows Platform (UWP).

      TeeChart for .NET C# code may be reused with Steema's mobile TeeChart products for Xamarin to reach Windows Phone, Android and iOS directly or via Xamarin's Forms PCL platform.

      .NET Chart Control

      Tracking financial data

      Many mathematical indicators, statistical functions and more

      The .NET chart control is packed with functionality to produce high-class financial charting applications. Functions and indicators include: Open-High-Low-Close Series, Candle, Volume and Moving Average Convergence/Divergence (MACD), ADX, Stochastic, Bollinger Bands, Renko, Kagi, Momentum, Moving Average and many more statistical functions.
       

      .NET Financial Charts

      Web charts - Blazor - MVC

      ASP.NET Core, .NET 5 MVC & Blazor charts as HTML5 Javascript
      The ASP.NET Web chart component may be placed on the WebForm panel for full in-place editing or be used within an MVC Blazor project. You can render your web charts either as static or ajax enhanced images or take advantage of TeeChart's comprehensive, client-side HTML5 Javascript library to render fully interactive .NET charts for MVC & ASP.NET.

      Predictive & Anomaly Detection

      Machine Learning algorithm interface for TeeChart
      We have prepared a module to link directly to Microsoft's ML.Net Machine-Learning framework with prepared and optimised predictive and anomaly detection algorithms. See the blog article. Save valuable learning-curve time delivering data insight to your customers.

      .NET Anomaly Detection