Yes. The records fall into three natural groups, and the `species` column already defines them: setosa, versicolor and virginica, with 50 specimens each (from `iris_by_species`). **Petal size separates the groups best.** - **Setosa** is clearly distinct. Its petal length ranges from 1.0 to 1.9 cm (median 1.5) and its petal width from 0.1 to 0.6 cm. The other two species never go below 3.0 cm in petal length or 1.0 cm in petal width, so setosa can be separated with a single threshold. - **Versicolor and virginica** form two adjacent groups. Average petal length is 4.26 cm for versicolor and 5.55 cm for virginica. Average petal width is 1.33 cm and 2.03 cm. - **Those two groups overlap slightly.** In petal length, versicolor reaches 5.1 and virginica starts at 4.5. In petal width, versicolor reaches 1.8 and virginica starts at 1.4. A few specimens therefore sit in a boundary zone, but the medians are well apart (4.35 vs 5.55 cm length, 1.3 vs 2.0 cm width). **Sepal measurements separate the groups less well.** - Sepal length averages 5.01 for setosa, 5.94 for versicolor and 6.59 for virginica. The ranges overlap heavily: versicolor runs 4.9–7.0 and virginica 4.9–7.9. - Sepal width is the weakest separator. Setosa is slightly wider (average 3.43) but its 2.3–4.4 range overlaps both other species. **Practical takeaway:** segment by species, and use petal length and petal width as the features if you need to classify or cluster new specimens. Expect a clean split for setosa and a small amount of confusion between versicolor and virginica. A clustering method such as k-means would likely recover setosa perfectly, but it could misassign a few specimens at the versicolor–virginica boundary. I did not run a clustering or check the overlapping specimens row by row; the overlap comes from the per-species min and max values. The other columns (`_batch_id`, `_source_file`, `_ingestion_timestamp`) are ingestion metadata, not meaningful segmentation dimensions.