knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

routliersutils

codecov ci-cd

Overview

As data rarely comes ready to be used and analyzed for machine learning right away, this package aims to help speed up the process of cleaning and doing initial exploratory data analysis specific to outliers. The package focuses on the tasks of identifying univariate outliers, providing summary of outliers like count, range of outliers, visualize them and giving functionality to remove them from data.

Installation

You can install then development version from GitHub with:

# install.packages("devtools") # run this line first if `devtools` package is not installed in your local.
devtools::install_github("UBC-MDS/r_outliers_utils")

Functions

The three functions contained in this package are as follows:

Our Place in the R Ecosystem

While R packages with similar functionalities exist, this package aims to provide summary, visualization of outliers in a single package with an additional functionality to generate outlier-free dataset. Few packages with similar functionality are as follows:

Usage

The routliersutils package help you to build exploratory data analysis.

routliersutils includes multiple functions to perform initial EDA specific to outliers. The generated output for outliers can be obtained in the form of dataframe objects and graphical form.

The routliersutils is capable of :

Documentation

Please find the detailed documentation in the vignette.

Example usage to load package
library(routliersutils)

Contributing

This package is authored by Karanpreet Kaur, Linhan Cai, Qingqing Song as part of the course project in DSCI-524 (UBC-MDS program). You can see the list of all contributors in the contributors tab.

We welcome and recognize all contributions. If you wish to participate, please review our Contributing guidelines

License

routliersutils is licensed under the terms of the MIT license.



UBC-MDS/r_outliers_utils documentation built on Feb. 7, 2022, 9:12 a.m.