ManagedCode.TimeSeries 0.0.17

Prefix Reserved
There is a newer version of this package available.
See the version list below for details.
dotnet add package ManagedCode.TimeSeries --version 0.0.17                
NuGet\Install-Package ManagedCode.TimeSeries -Version 0.0.17                
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="ManagedCode.TimeSeries" Version="0.0.17" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add ManagedCode.TimeSeries --version 0.0.17                
#r "nuget: ManagedCode.TimeSeries, 0.0.17"                
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install ManagedCode.TimeSeries as a Cake Addin
#addin nuget:?package=ManagedCode.TimeSeries&version=0.0.17

// Install ManagedCode.TimeSeries as a Cake Tool
#tool nuget:?package=ManagedCode.TimeSeries&version=0.0.17                

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TimeSeries

.NET Coverage Status nuget CodeQL

Version Package Description
NuGet Package ManagedCode.TimeSeries Core

Motivation

Time series data is a common type of data in many applications, such as finance, physics, and engineering. It is often necessary to store and manipulate large amounts of time series data efficiently in order to perform analysis and make predictions.

Our C# library, TimeSeries, provides convenient tools for working with time series data in C#. It includes classes for accumulating and summarizing data in time frames, as well as storing and compressing the data efficiently. This makes it easy to add and manage time series data in your C# projects.

Features

  • Accumulators for adding data to time frames.
  • Summers for summarizing data in time frames.
  • Efficient storage and compression of time series data.

Example

Here's an example of how you might use the TimeSeries library to accumulate and summarize data in a time frame:

using ManagedCode.TimeSeries;

var series = new IntTimeSeriesAccumulator(TimeSpan.FromSeconds(5)); // step
for (int i = 0; i < count; i++)
{
    series.AddNewData(i);
}
using ManagedCode.TimeSeries;

var series = new IntTimeSeriesAccumulator(TimeSpan.FromSeconds(0.1));
for (var i = 0; i < 1000; i++)
{
    await Task.Delay(new Random().Next(1, 5));
    series.AddNewData(i);
}

series.DataCount; // 1000

Installation

To install the TimeSeries library, you can use NuGet:

dotnet add package ManagedCode.TimeSeries

Conclusion In summary, the TimeSeries library provides convenient tools for working with time series data in C#. Its accumulators and summers make it easy to add and summarize data in time frames, and its efficient storage and compression capabilities ensure.

Product Compatible and additional computed target framework versions.
.NET net7.0 is compatible.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
  • net7.0

    • No dependencies.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on ManagedCode.TimeSeries:

Package Downloads
ManagedCode.Keda.Orleans.Scaler.Client

Keda

ManagedCode.Keda.Orleans.Scaler

Keda

ManagedCode.TimeSeries.Orleans

TimeSeries

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
0.0.18 558 5/17/2023
0.0.17 10,330 12/9/2022
0.0.16 309 12/9/2022
0.0.15 296 12/9/2022
0.0.12 1,791 10/11/2022
0.0.11 389 10/11/2022
0.0.10 654 10/10/2022
0.0.9 1,086 10/10/2022
0.0.8 639 10/10/2022
0.0.7 628 10/10/2022
0.0.6 1,138 10/10/2022
0.0.5 657 10/10/2022
0.0.4 1,658 10/3/2022
0.0.3 2,643 9/23/2022
0.0.2 2,501 9/19/2022
0.0.1 450 9/19/2022