Dataset research report
Pol research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Pol The Pol dataset from the OpenML repository. Configurations and tasks Configuration Task Description pol Binary classification Has the pol cost gone up? Usage from datasets import load_dataset dataset = load_dataset("mstz/pol", "pol")["train"]
Research Context
Pol: 500 rows by 49 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
| # | f1integer | f2integer | f3integer | f4integer | f5integer | f6integer | f7integer | f8integer |
|---|---|---|---|---|---|---|---|---|
| 1 | 110 | 100 | 100 | 100 | 60 | 108 | 76 | 71 |
| 2 | 110 | 100 | 100 | 100 | 130 | 77 | 76 | 71 |
| 3 | 110 | 100 | 100 | 100 | 110 | 89 | 76 | 71 |
| 4 | 110 | 100 | 100 | 100 | 13 | 126 | 89 | 72 |
| 5 | 110 | 100 | 100 | 100 | 15 | 119 | 78 | 71 |
| 6 | 110 | 100 | 100 | 100 | 50 | 113 | 100 | 143 |
Data Dictionary
- f1 numeric
- f2 numeric
- f3 numeric
- f4 numeric
- f5 numeric
- f6 numeric
- f7 numeric
- f8 numeric
- f9 numeric
- f10 numeric
- f11 numeric
- f12 numeric
- f13 numeric
- f14 numeric
- f15 numeric
- f16 numeric
- f17 numeric
- f18 numeric
- f19 numeric
- f20 numeric
- f21 numeric
- f22 numeric
- f23 numeric
- f24 numeric
- f25 numeric
- f26 numeric
- f27 numeric
- f28 numeric
- f29 numeric
- f30 numeric
- f31 numeric
- f32 numeric
- f33 numeric
- f34 numeric
- f35 numeric
- f36 numeric
- f37 numeric
- f38 numeric
- f39 numeric
- f40 numeric
- f41 numeric
- f42 numeric
- f43 numeric
- f44 numeric
- f45 numeric
- f46 numeric
- f47 numeric
- f48 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.