Dataset research report
Auto Mpg research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Auto Miles per Gallon (MPG) Dataset Following description was taken from UCI machine learning repository. Source: This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. The dataset was used in the 1983 American Statistical Association Exposition. Data Set Information: This dataset is a slightly modified version of the dataset provided in the StatLib library. In line with the use by Ross Quinlan (1993) in predicting the attribute… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/auto-mpg.
Research Context
Auto Mpg: 398 rows by 9 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
| # | mpgfloat | cylindersinteger | displacementfloat | horsepowertext | weightinteger | accelerationfloat | model yearinteger | origininteger |
|---|---|---|---|---|---|---|---|---|
| 1 | 18 | 8 | 307 | 130 | 3504 | 12 | 70 | 1 |
| 2 | 15 | 8 | 350 | 165 | 3693 | 11.5 | 70 | 1 |
| 3 | 18 | 8 | 318 | 150 | 3436 | 11 | 70 | 1 |
| 4 | 16 | 8 | 304 | 150 | 3433 | 12 | 70 | 1 |
| 5 | 17 | 8 | 302 | 140 | 3449 | 10.5 | 70 | 1 |
| 6 | 15 | 8 | 429 | 198 | 4341 | 10 | 70 | 1 |
Data Dictionary
- mpg numeric
- cylinders numeric
- displacement numeric
- horsepower text
- weight numeric
- acceleration numeric
- model year datetime
- origin numeric
- car name text
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.