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:
-
outlier_identifier: A function to identify outliers in the dataset and provide their summary as an output -
visualize_outliers: A function to generate the eda plots highlighting outliers providing additional functionality to visualize them -
trim_outliers: A function to generate outlier free dataset by imputing them with mean, median or trim entire row with outlier from dataset.
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 :
- Summarizing outliers and identify them in dataset
- Visualize them in boxplot and violin plot
- Trim or impute outliers with mean , median in dataset
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