Dataset research report
Ozone research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Ozone The Ozone dataset from the UCI ML repository. Configurations and tasks Configuration Task Description 8hr Binary classification Is there an ozone layer? 1hr Binary classification Is there an ozone layer? Usage from datasets import load_dataset dataset = load_dataset("mstz/ozone", "8hr")["train"]
Research Context
Ozone: 500 rows by 73 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.
Correlation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartFollow-Up Queries
Preview Rows
| # | WSR0float | WSR1float | WSR2float | WSR3float | WSR4float | WSR5float | WSR6float | WSR7float |
|---|---|---|---|---|---|---|---|---|
| 1 | 0.8 | 1.8 | 2.4 | 2.1 | 2 | 2.1 | 1.5 | 1.7 |
| 2 | 2.8 | 3.2 | 3.3 | 2.7 | 3.3 | 3.2 | 2.9 | 2.8 |
| 3 | 2.9 | 2.8 | 2.6 | 2.1 | 2.2 | 2.5 | 2.5 | 2.7 |
| 4 | 4.7 | 3.8 | 3.7 | 3.8 | 2.9 | 3.1 | 2.8 | 2.5 |
| 5 | 3.7 | 3.2 | 3.8 | 5.1 | 6 | 7 | 6.3 | 6.4 |
| 6 | 2.2 | 2.9 | 3.4 | 4.2 | 4.7 | 4.7 | 5.3 | 4.9 |
Data Dictionary
- WSR0 numeric
- WSR1 numeric
- WSR2 numeric
- WSR3 numeric
- WSR4 numeric
- WSR5 numeric
- WSR6 numeric
- WSR7 numeric
- WSR8 numeric
- WSR9 numeric
- WSR10 numeric
- WSR11 numeric
- WSR12 numeric
- WSR13 numeric
- WSR14 numeric
- WSR15 numeric
- WSR16 numeric
- WSR17 numeric
- WSR18 numeric
- WSR19 numeric
- WSR20 numeric
- WSR21 numeric
- WSR22 numeric
- WSR23 numeric
- WSR_PK numeric
- WSR_AV numeric
- T0 numeric
- T1 numeric
- T2 numeric
- T3 numeric
- T4 numeric
- T5 numeric
- T6 numeric
- T7 numeric
- T8 numeric
- T9 numeric
- T10 numeric
- T11 numeric
- T12 numeric
- T13 numeric
- T14 numeric
- T15 numeric
- T16 numeric
- T17 numeric
- T18 numeric
- T19 numeric
- T20 numeric
- T21 numeric
- T22 numeric
- T23 numeric
- T_PK numeric
- T_AV numeric
- T85 numeric
- RH85 numeric
- U85 numeric
- V85 numeric
- HT85 numeric
- T70 numeric
- RH70 numeric
- U70 numeric
- V70 numeric
- HT70 numeric
- T50 numeric
- RH50 numeric
- U50 numeric
- V50 numeric
- HT50 numeric
- KI numeric
- TT numeric
- SLP numeric
- SLP_ numeric
- Precp numeric
- Class 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.