dlookr: R Package for Data Diagnosis, Exploration, and Transformation

A collection of R tools for data diagnosis, exploration, and transformation created by Choonghyun Ryu. The package provides automated reports and visualizations for tasks like missing value detection, outlier identification, normality testing, and variable correlation analysis. It supports binning, imputation, and skewness resolution for data transformation.

Use Cases

• Diagnose data quality issues based on missing value and outlier visualizations mentioned in the description
• Explore variable relationships based on correlation analysis and target-predictor relationship tools
• Transform skewed or problematic data based on binning and imputation functions
• Generate automated diagnostic reports based on the package's reporting capabilities

Strengths

• Provides integrated tools for three key data preparation stages: diagnosis, exploration, and transformation
• Includes automated reporting functionality for diagnostic tasks
• Offers specific visualizations for outliers, missing values, and variable relationships

Limitations

• Row count, column names, and file formats are unknown; dataset scale cannot be assessed
• Column-level documentation is absent; field semantics must be inferred after download
• Last update date is unknown; freshness unverified

Provenance

Source

Choonghyun Ryu

Collection Method

Software package development for data analysis