Deedle implements an efficient and robust frame and series data structures for manipulating with structured data. It supports handling of missing values, aggregations, grouping, joining, statistical functions and more. For frames and series with ordered indices (such as time series), automatic alignment is also available. This package installs core Deedle package, together with an R type provider plugin which makes it possible to pass data frames and time series between R and Deedle

F#, fsharp, deedle, dataframe, series, statistics, data, science, R, RProvider
Install-Package Deedle.RPlugin -Version 2.1.0


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Deedle is an easy to use library for data and time series manipulation and for scientific programming. It supports working with structured data frames, ordered and unordered data, as well as time series. Deedle is designed to work well for exploratory programming using F# and C# interactive console, but can be also used in efficient compiled .NET code.

The library implements a wide range of operations for data manipulation including advanced indexing and slicing, joining and aligning data, handling of missing values, grouping and aggregation, statistics and more.


More information can be found in the documentation.

  • Quick start tutorial shows how to use the most important features of Deedle. Start here for a 10 minute intro!
  • Data frame features provides more examples of using data frames including slicing, joining, grouping and aggregation.
  • Time series features discusses data and time-series manipulation, such as sliding windows, sampling and statistics.
  • Using Deedle from C# shows the idiomatic C# API for working with Deedle.

Automatically generated documentation for all types, modules and functions in the library is available in the API Reference:

More functions related to linear algebra, statistical analysis and financial analysis can be found in Deedle.Math extension. Deedle.Math has dependency on MathNet.Numerics.

  • Linear Algebra module provides linear algebra operations and functions on frame, series, matrix and vector.
  • Stats module provides extra statistical functions on frame and series by applying existing functions in MathNet.Numerics.
  • Finance module provides statistical functions specific to finance domain.


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