Dataset research report
Haberman research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Haberman The Haberman dataset from the UCI ML repository. Has the patient survived surgery? Configurations and tasks Configuration Task Description sruvival Binary classification Has the patient survived surgery? Usage from datasets import load_dataset dataset = load_dataset("mstz/haberman", "survival")["train"]
Research Context
Haberman: 306 rows by 4 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.
age vs year_of_operation
Relationship between age and year_of_operation.
Open and export this chartCorrelation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartFollow-Up Queries
Preview Rows
| # | ageinteger | year_of_operationinteger | number_of_axillary_nodesinteger | has_survived_5_yearsinteger |
|---|---|---|---|---|
| 1 | 30 | 1964 | 1 | 1 |
| 2 | 30 | 1962 | 3 | 1 |
| 3 | 30 | 1965 | 0 | 1 |
| 4 | 31 | 1959 | 2 | 1 |
| 5 | 31 | 1965 | 4 | 1 |
| 6 | 33 | 1958 | 10 | 1 |
Data Dictionary
- age numeric
- year_of_operation datetime
- number_of_axillary_nodes numeric
- has_survived_5_years datetime
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.