RRF: Interfaces for RRF package for data science pipelines.

In intubate: Interface to Popular R Functions for Data Science Pipelines

Description

Interfaces to RRF functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_RRF(data, ...)
ntbt_rrfImpute(data, ...)

Arguments

data	data frame, tibble, list, ...
...	Other arguments passed to the corresponding interfaced function.

Details

Interfaces call their corresponding interfaced function.

Value

Object returned by interfaced function.

Author(s)

Roberto Bertolusso

Examples

## Not run: 
library(intubate)
library(magrittr)
library(RRF)


data(iris)
set.seed(111)
ind <- sample(2, nrow(iris), replace = TRUE, prob=c(0.8, 0.2))

## Original function to interface
RRF(Species ~ ., data=iris[ind == 1,])

## The interface puts data as first parameter
ntbt_RRF(iris[ind == 1,], Species ~ .)

## so it can be used easily in a pipeline.
iris[ind == 1,] %>%
  ntbt_RRF(Species ~ .)


## ntbt_rrfImpute: Missing Value Imputations by RRF
data(iris)
iris.na <- iris
set.seed(111)
for (i in 1:4) iris.na[sample(150, sample(20)), i] <- NA

## Original function to interface
set.seed(222)
rrfImpute(Species ~ ., iris.na)

## The interface puts data as first parameter
set.seed(222)
ntbt_rrfImpute(iris.na, Species ~ .)

## so it can be used easily in a pipeline.
set.seed(222)
iris.na %>%
  ntbt_rrfImpute(Species ~ .)

## End(Not run)

intubate documentation built on May 2, 2019, 2:46 p.m.