naniar: Data Structures and Visualizations for Missing Data Analysis

The 'naniar' package provides data structures and functions for exploring and visualizing missing values in data. It facilitates the plotting of missing values and the examination of imputations, integrating with the 'ggplot2' and tidy data workflows. The work is discussed in Tierney & Cook (2023).

Use Cases

• Visualize missing data patterns based on the plotting functions mentioned in the description
• Explore dependencies in missing values based on the data structures provided
• Examine the effects of data imputation based on the package's imputation examination tools
• Integrate missing data analysis into a 'ggplot2' workflow based on the minimal deviation from common patterns

Strengths

• Provides specialized data structures for missing data, as described
• Integrates with the widely-used 'ggplot2' and tidy data workflows
• The methodology is peer-reviewed and published in the Journal of Statistical Software (2023)

Limitations

• Row count, column names, and file formats are unknown; scale and structure are unverified
• Description metadata is limited; actual data quality requires manual inspection after download
• The package is designed for R users; practitioners using other languages cannot use it directly

Provenance

Source

Nicholas Tierney

Collection Method

Developed as an R software package for data analysis.

Time Range

Associated publication from 2023.

Freshness

Last update date is unknown; freshness unverified.

Geography

Spatial coverage is unknown.