snapedautilityR is an open-source library that generate useful function to kickstart EDA (Exploratory Data Analysis) with just a few lines of code. The system is built around quickly analyzing the whole dataset and providing a detailed report with visualization. Its goal is to help quick analysis of feature characteristics, detecting outliers from the observations and other such data characterization tasks.
Features
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plot_histograms: Plots the distribution for numerical, categorical and text features -
detect_outliers: Generate a violin plot that indicates the outliers that deviate from other observations on data. -
plot_corr: Generates Correlation Plots for numerical (Pearson’s correlation), categorical (uncertainty coefficient) and categorical-numerical (correlation ratio) datatypes seamlessly for all data types.
Installation
You can install the released version of snapedautilityR from CRAN with:
install.packages("snapedautilityR")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("UBC-MDS/snapedautilityR")Documentation & Usage
Documentation and usage examples for snapedautilityR can be found here.
Usage
library(snapedautilityR)
library(palmerpenguins)
## basic example code for each utility function
# detect_outliers function
detect_outliers(c(1, 1, 2, 3, 4, 5, 6, 9, 10, 13, 40))
# plot_corr function
numerical_features <- c("bill_length_mm", "body_mass_g", "bill_depth_mm")
plot_corr(penguins, features = numerical_features)
# plot_histograms function
df <- penguins
plot <- plot_histograms(df, c("species", "bill_length_mm", "island"), 2, 100, 100)Contributors
| Core contributor | Github.com username |
|---|---|
| Kyle Ahn | @AraiYuno |
| Harry Chan | @harryyikhchan |
| Dongxiao Li | @dol23asuka |
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
Similar Work
We recognize EDA (exploratory data analysis) and preprocessing packages are common in the R open source ecosystem. Our package aims to do a few things very well, and be light weight. A non exhaustive list of EDA helper packages in R include:
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- This package includes handful tools to diagnose, explore and transform the data.
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- This package provides an easy to generate report, visualization and feature engineering functions for data analysis/predictive modeling.