Dataset research report
Vertebral Column research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Vertebral Column The Vertebral Column dataset from the UCI ML repository. Configurations and tasks Configuration Task Description abnormal Binary classification Is the spine abnormal? Usage from datasets import load_dataset dataset = load_dataset("mstz/vertebral_column")["train"]
Research Context
Vertebral Column: 310 rows by 7 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.
Data Profile
Chart Evidence
These views are generated from the dataset profile. Each chart is paired with a Helix query so it can be opened, adjusted, and exported.
pelvic_incidence vs pelvic_tilt
Relationship between pelvic_incidence and pelvic_tilt.
Open and export this chartDistribution of pelvic_incidence
Histogram of pelvic_incidence values.
Open and export this chartCorrelation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartFollow-Up Queries
Preview Rows
| # | pelvic_incidencefloat | pelvic_tiltfloat | lumbar_lordosis_anglefloat | sacral_slopefloat | pelvic_radiusfloat | degree_spondylolisthesisfloat | is_abnormalinteger |
|---|---|---|---|---|---|---|---|
| 1 | 63.03 | 22.55 | 39.61 | 40.48 | 98.67 | -0.2544 | 1 |
| 2 | 39.06 | 10.06 | 25.02 | 29 | 114.4 | 4.564 | 1 |
| 3 | 68.83 | 22.22 | 50.09 | 46.61 | 106 | -3.53 | 1 |
| 4 | 69.3 | 24.65 | 44.31 | 44.64 | 101.9 | 11.21 | 1 |
| 5 | 49.71 | 9.652 | 28.32 | 40.06 | 108.2 | 7.919 | 1 |
| 6 | 40.25 | 13.92 | 25.12 | 26.33 | 130.3 | 2.231 | 1 |
Data Dictionary
- pelvic_incidence numeric
- pelvic_tilt numeric
- lumbar_lordosis_angle numeric
- sacral_slope numeric
- pelvic_radius numeric
- degree_spondylolisthesis numeric
- is_abnormal numeric
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.