R Provider Tutorial

Referencing the provider

In order to use the R provider, you need to reference the RDotNet.dll library (which is a .NET connector for R) and the RProvider.dll itself. For this tutorial, we use open to reference a number of packages including stats, tseries and zoo:

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#I "../packages/RProvider.1.0.3/lib"
#r "RDotNet.dll"
#r "RDotNet.FSharp.dll"
#r "RDotNet.NativeLibrary.dll"
#r "RProvider.dll"
#r "RProvider.Runtime.dll"
 
open RDotNet
open RProvider
open RProvider.graphics
open RProvider.stats
open RProvider.tseries
open RProvider.zoo

open System
open System.Net

If either of the namespaces above are unrecognized, you need to install the package in R using install.packages("stats").

Obtaining data

In this tutorial, we use F# Data to access stock prices from the Yahoo Finance portal. For more information, see the documentation for the CSV type provider.

The following snippet uses the CSV type provider to generate a type Stocks that can be used for parsing CSV data from Yahoo. Then it defines a function getStockPrices that returns array with prices for the specified stock and a specified number of days:

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#r "FSharp.Data.dll"
open FSharp.Data

type Stocks = CsvProvider<"http://ichart.finance.yahoo.com/table.csv?s=SPX">
 
/// Returns prices of a given stock for a specified number 
/// of days (starting from the most recent)
let getStockPrices stock count =
  let url = "http://ichart.finance.yahoo.com/table.csv?s="
  [| for r in Stocks.Load(url + stock).Take(count).Rows -> float r.Open |] 
  |> Array.rev

/// Get opening prices for MSFT for the last 255 days
let msftOpens = getStockPrices "MSFT" 255

Calling R functions

Now, we're ready to call R functions using the type provider. The following snippet takes msftOpens, calculates logarithm of the values using R.log and then calculates the differences of the resulting vector using R.diff:

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// Retrieve stock price time series and compute returns
let msft = msftOpens |> R.log |> R.diff

If you want to see the resulting values, you can call msft.AsVector() in F# Interactive. Next, we use the acf function to display the atuo-correlation and call adf_test to see if the msft returns are stationary/non-unit root:

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let a = R.acf(msft)
let adf = R.adf_test(msft)

After running the first snippet, a window similar to the following should appear (note that it might not appear as a top-most window).

Finally, we can obtain data for multiple different indicators and use the R.pairs function to produce a matrix of scatter plots:

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// Build a list of tickers and get diff of logs of prices for each one
let tickers = 
  [ "MSFT"; "AAPL"; "X"; "VXX"; "SPX"; "GLD" ]
let data =
  [ for t in tickers -> 
      printfn "got one!"
      t, getStockPrices t 255 |> R.log |> R.diff ]

// Create an R data frame with the data and call 'R.pairs'
let df = R.data_frame(namedParams data)
R.pairs(df)

As a result, you should see a window showing results similar to these:

namespace RDotNet

namespace RProvider

namespace RProvider.graphics

namespace RProvider.stats

namespace RProvider.zoo

namespace System

namespace System.Net

namespace FSharp

namespace FSharp.Data

type Stocks = obj

Full name: Tutorial.Stocks

type CsvProvider

Full name: FSharp.Data.CsvProvider

<summary>Typed representation of a CSV file.</summary>
       <param name='Sample'>Location of a CSV sample file or a string containing a sample CSV document.</param>
       <param name='Separators'>Column delimiter(s). Defaults to `,`.</param>
       <param name='InferRows'>Number of rows to use for inference. Defaults to `1000`. If this is zero, all rows are used.</param>
       <param name='Schema'>Optional column types, in a comma separated list. Valid types are `int`, `int64`, `bool`, `float`, `decimal`, `date`, `guid`, `string`, `int?`, `int64?`, `bool?`, `float?`, `decimal?`, `date?`, `guid?`, `int option`, `int64 option`, `bool option`, `float option`, `decimal option`, `date option`, `guid option` and `string option`.
       You can also specify a unit and the name of the column like this: `Name (type<unit>)`, or you can override only the name. If you don't want to specify all the columns, you can reference the columns by name like this: `ColumnName=type`.</param>
       <param name='HasHeaders'>Whether the sample contains the names of the columns as its first line.</param>
       <param name='IgnoreErrors'>Whether to ignore rows that have the wrong number of columns or which can't be parsed using the inferred or specified schema. Otherwise an exception is thrown when these rows are encountered.</param>
       <param name='SkipRows'>SKips the first n rows of the CSV file.</param>
       <param name='AssumeMissingValues'>When set to true, the type provider will assume all columns can have missing values, even if in the provided sample all values are present. Defaults to false.</param>
       <param name='PreferOptionals'>When set to true, inference will prefer to use the option type instead of nullable types, `double.NaN` or `""` for missing values. Defaults to false.</param>
       <param name='Quote'>The quotation mark (for surrounding values containing the delimiter). Defaults to `"`.</param>
       <param name='MissingValues'>The set of strings recogized as missing values. Defaults to `NaN,NA,N/A,#N/A,:,-,TBA,TBD`.</param>
       <param name='CacheRows'>Whether the rows should be caches so they can be iterated multiple times. Defaults to true. Disable for large datasets.</param>
       <param name='Culture'>The culture used for parsing numbers and dates. Defaults to the invariant culture.</param>
       <param name='Encoding'>The encoding used to read the sample. You can specify either the character set name or the codepage number. Defaults to UTF8 for files, and to ISO-8859-1 the for HTTP requests, unless `charset` is specified in the `Content-Type` response header.</param>
       <param name='ResolutionFolder'>A directory that is used when resolving relative file references (at design time and in hosted execution).</param>
       <param name='EmbeddedResource'>When specified, the type provider first attempts to load the sample from the specified resource
          (e.g. 'MyCompany.MyAssembly, resource_name.csv'). This is useful when exposing types generated by the type provider.</param>

val getStockPrices : stock:'a -> count:'b -> float []

Full name: Tutorial.getStockPrices

Returns prices of a given stock for a specified number
of days (starting from the most recent)

val stock : 'a

val count : 'b

val url : string

val r : obj

Multiple items
val float : value:'T -> float (requires member op_Explicit)

Full name: Microsoft.FSharp.Core.Operators.float

--------------------
type float = Double

Full name: Microsoft.FSharp.Core.float

--------------------
type float<'Measure> = float

Full name: Microsoft.FSharp.Core.float<_>

type Array =
  member Clone : unit -> obj
  member CopyTo : array:Array * index:int -> unit + 1 overload
  member GetEnumerator : unit -> IEnumerator
  member GetLength : dimension:int -> int
  member GetLongLength : dimension:int -> int64
  member GetLowerBound : dimension:int -> int
  member GetUpperBound : dimension:int -> int
  member GetValue : params indices:int[] -> obj + 7 overloads
  member Initialize : unit -> unit
  member IsFixedSize : bool
  ...

Full name: System.Array

val rev : array:'T [] -> 'T []

Full name: Microsoft.FSharp.Collections.Array.rev

val msftOpens : float []

Full name: Tutorial.msftOpens

Get opening prices for MSFT for the last 255 days

val msft : SymbolicExpression

Full name: Tutorial.msft

type R =
  static member ! : ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member != : ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member !_hexmode : ?a: obj -> SymbolicExpression + 1 overload
  static member !_octmode : ?a: obj -> SymbolicExpression + 1 overload
  static member $ : ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member $<- : ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member $<-_data_frame : ?x: obj * ?name: obj * ?value: obj -> SymbolicExpression + 1 overload
  static member $_DLLInfo : ?x: obj * ?name: obj -> SymbolicExpression + 1 overload
  static member $_data_frame : ?x: obj * ?name: obj -> SymbolicExpression + 1 overload
  static member $_package__version : ?x: obj * ?name: obj -> SymbolicExpression + 1 overload
  ...

Full name: RProvider.R

Base R functions.

R.log(paramsByName: Collections.Generic.IDictionary<string,obj>) : SymbolicExpression
R.log(?paramArray: obj []) : SymbolicExpression

Logarithms and Exponentials

R.diff(paramsByName: Collections.Generic.IDictionary<string,obj>) : SymbolicExpression
R.diff(?x: obj, ?___: obj, ?paramArray: obj []) : SymbolicExpression

Lagged Differences

val a : SymbolicExpression

Full name: Tutorial.a

type R =
  static member AIC : ?object: obj * ?___: obj * ?k: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member ARMAacf : ?ar: obj * ?ma: obj * ?lag_max: obj * ?pacf: obj -> SymbolicExpression + 1 overload
  static member ARMAtoMA : ?ar: obj * ?ma: obj * ?lag_max: obj -> SymbolicExpression + 1 overload
  static member BIC : ?object: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member Box_test : ?x: obj * ?lag: obj * ?type: obj * ?fitdf: obj -> SymbolicExpression + 1 overload
  static member C : ?object: obj * ?contr: obj * ?how_many: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member D : ?expr: obj * ?name: obj -> SymbolicExpression + 1 overload
  static member Gamma : ?link: obj -> SymbolicExpression + 1 overload
  static member HoltWinters : ?x: obj * ?alpha: obj * ?beta: obj * ?gamma: obj * ?seasonal: obj * ?start_periods: obj * ?l_start: obj * ?b_start: obj * ?s_start: obj * ?optim_start: obj * ?optim_control: obj -> SymbolicExpression + 1 overload
  static member IQR : ?x: obj * ?na_rm: obj * ?type: obj -> SymbolicExpression + 1 overload
  ...

Full name: RProvider.stats.R

R statistical functions.

R.acf(paramsByName: Collections.Generic.IDictionary<string,obj>) : SymbolicExpression
R.acf(?x: obj, ?lag_max: obj, ?type: obj, ?plot: obj, ?na_action: obj, ?demean: obj, ?___: obj, ?paramArray: obj []) : SymbolicExpression

Auto- and Cross- Covariance and -Correlation Function Estimation

val adf : obj

Full name: Tutorial.adf

type R =
  static member MATCH : ?x: obj * ?table: obj * ?nomatch: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member MATCH_default : ?x: obj * ?table: obj * ?nomatch: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member MATCH_times : ?x: obj * ?table: obj * ?nomatch: obj * ?units: obj * ?eps: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member ORDER : ?x: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member ORDER_default : ?x: obj * ?___: obj * ?na_last: obj * ?decreasing: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member Sys_yearmon : ?NULL: obj -> SymbolicExpression + 1 overload
  static member Sys_yearqtr : ?NULL: obj -> SymbolicExpression + 1 overload
  static member as_Date : ?x: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member as_Date_numeric : ?x: obj * ?origin: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member as_Date_ts : ?x: obj * ?offset: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  ...

Full name: RProvider.zoo.R

An S3 class with methods for totally ordered indexed
             observations. It is particularly aimed at irregular time series
             of numeric vectors/matrices and factors. zoo's key design goals
             are independence of a particular index/date/time class and
             consistency with ts and base R by providing methods to extend
             standard generics.

val tickers : string list

Full name: Tutorial.tickers

val data : (string * SymbolicExpression) list

Full name: Tutorial.data

val t : string

val printfn : format:Printf.TextWriterFormat<'T> -> 'T

Full name: Microsoft.FSharp.Core.ExtraTopLevelOperators.printfn

val df : SymbolicExpression

Full name: Tutorial.df

R.data_frame(paramsByName: Collections.Generic.IDictionary<string,obj>) : SymbolicExpression
R.data_frame(?___: obj, ?row_names: obj, ?check_rows: obj, ?check_names: obj, ?stringsAsFactors: obj, ?paramArray: obj []) : SymbolicExpression

Data Frames

val namedParams : s:seq<string * 'a> -> Collections.Generic.IDictionary<string,obj>

Full name: RProvider.Helpers.namedParams

type R =
  static member Axis : ?x: obj * ?at: obj * ?___: obj * ?side: obj * ?labels: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member abline : ?a: obj * ?b: obj * ?h: obj * ?v: obj * ?reg: obj * ?coef: obj * ?untf: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member arrows : ?x0: obj * ?y0: obj * ?x1: obj * ?y1: obj * ?length: obj * ?angle: obj * ?code: obj * ?col: obj * ?lty: obj * ?lwd: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member assocplot : ?x: obj * ?col: obj * ?space: obj * ?main: obj * ?xlab: obj * ?ylab: obj -> SymbolicExpression + 1 overload
  static member axTicks : ?side: obj * ?axp: obj * ?usr: obj * ?log: obj * ?nintLog: obj -> SymbolicExpression + 1 overload
  static member axis : ?side: obj * ?at: obj * ?labels: obj * ?tick: obj * ?line: obj * ?pos: obj * ?outer: obj * ?font: obj * ?lty: obj * ?lwd: obj * ?lwd_ticks: obj * ?col: obj * ?col_ticks: obj * ?hadj: obj * ?padj: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member axis_Date : ?side: obj * ?x: obj * ?at: obj * ?format: obj * ?labels: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member axis_POSIXct : ?side: obj * ?x: obj * ?at: obj * ?format: obj * ?labels: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member barplot : ?height: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  static member barplot_default : ?height: obj * ?width: obj * ?space: obj * ?names_arg: obj * ?legend_text: obj * ?beside: obj * ?horiz: obj * ?density: obj * ?angle: obj * ?col: obj * ?border: obj * ?main: obj * ?sub: obj * ?xlab: obj * ?ylab: obj * ?xlim: obj * ?ylim: obj * ?xpd: obj * ?log: obj * ?axes: obj * ?axisnames: obj * ?cex_axis: obj * ?cex_names: obj * ?inside: obj * ?plot: obj * ?axis_lty: obj * ?offset: obj * ?add: obj * ?args_legend: obj * ?___: obj * ?paramArray: obj [] -> SymbolicExpression + 1 overload
  ...

Full name: RProvider.graphics.R

R functions for base graphics.

R.pairs(paramsByName: Collections.Generic.IDictionary<string,obj>) : SymbolicExpression
R.pairs(?x: obj, ?___: obj, ?paramArray: obj []) : SymbolicExpression

Scatterplot Matrices

R Type Provider

R Provider Tutorial

Referencing the provider

Obtaining data

Calling R functions