Ordination Result #55 — Analysis Report
Contents
- ordination (#55) completed
1. Ordination
2026-09-21 02:18:03 · ordination
The first two PCA axes capture 39.9% of the total variance in the data.
| n_components | 3 |
|---|---|
| method | pca |
| n_rows | 20 |
| n_dropped | 0 |
| color_col | Group |
explained variance
| Axis | Fraction | Cumulative |
|---|---|---|
| Axis 1 | 0.213754 | 0.213754 |
| Axis 2 | 0.1855 | 0.399254 |
| Axis 3 | 0.166912 | 0.566165 |
ordination scatter
scree
loadings
Method & Provenance
- Method
- Ordination — PCA
- Engine
- Python · scikit-learn 1.8.0
- Input dataset
- gallery — example_metabolomics.csv
- Started
- 2026-09-21 02:18:03.435062
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/f39c0418559c409bb880f45913bcdc31
| Parameter | Value |
|---|---|
| ordination_method | pca |
| method | pca |
| feature_cols | Protein_content, Alanine, Glycine, Serine, Threonine, Valine, Leucine, Isoleucine, Proline, Phenylalanine, Tryptophan |
| n_components | 3 |
| color_col | Group |
Command history
# python from sklearn.decomposition import PCA # python from sklearn.preprocessing import StandardScaler # python X_scaled = StandardScaler().fit_transform(X) # python coords = PCA(n_components=3).fit_transform(X_scaled)