Dataset research report
Breast research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Breast cancer The Breast cancer dataset from the UCI ML repository. Classify cancerousness of the given cell. Configurations and tasks Configuration Task Description cancer Binary classification Is the cell clump cancerous? Usage from datasets import load_dataset dataset = load_dataset("mstz/breast", "cancer")["train"] Features Name Type Description clump_thickness int8 Thickness of the clump… See the full description on the dataset page: https://huggingface.co/datasets/mstz/breast.
Research Context
Breast: 500 rows by 10 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.
clump_thickness vs uniformity_of_cell_size
Relationship between clump_thickness and uniformity_of_cell_size.
Open and export this chartDistribution of clump_thickness
Histogram of clump_thickness values.
Open and export this chartCorrelation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartFollow-Up Queries
Preview Rows
| # | clump_thicknessinteger | uniformity_of_cell_sizeinteger | uniformity_of_cell_shapeinteger | marginal_adhesioninteger | single_epithelial_cell_sizeinteger | bare_nucleiinteger | bland_chromatininteger | normal_nucleoliinteger |
|---|---|---|---|---|---|---|---|---|
| 1 | 5 | 1 | 1 | 1 | 2 | 1 | 3 | 1 |
| 2 | 5 | 4 | 4 | 5 | 7 | 10 | 3 | 2 |
| 3 | 3 | 1 | 1 | 1 | 2 | 2 | 3 | 1 |
| 4 | 6 | 8 | 8 | 1 | 3 | 4 | 3 | 7 |
| 5 | 4 | 1 | 1 | 3 | 2 | 1 | 3 | 1 |
| 6 | 8 | 10 | 10 | 8 | 7 | 10 | 9 | 7 |
Data Dictionary
- clump_thickness numeric
- uniformity_of_cell_size numeric
- uniformity_of_cell_shape numeric
- marginal_adhesion numeric
- single_epithelial_cell_size numeric
- bare_nuclei numeric
- bland_chromatin numeric
- normal_nucleoli numeric
- mitoses numeric
- is_cancer 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.