Principal Component Analysis Loadings, Eigenvalues, and Variance

Ana Caroline Bini de Lima published a dataset containing loading values, eigenvalues, and variance from a principal component analysis on figshare in April 2026. The 5.5 KB Excel file includes results where loadings greater than 0.40 or less than -0.40 indicate a variable's association with a principal component. The dataset is licensed under CC-BY-4.0.

Use Cases

• Interpreting variable associations with principal components based on loading values.
• Assessing the variance explained by each principal component using the eigenvalues and variance data.
• Teaching or demonstrating PCA results and their presentation in a tabular format.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Loadings are clearly marked (values in bold) for associations greater than 0.40 or less than -0.40.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Ana Caroline Bini de Lima via figshare

Collection Method

Likely contains calculated results from a statistical analysis.

Time Range

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Freshness

Last updated 2026-04-20 17:38:34; freshness should be verified.

Geography

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