Dataset research report
Student Alcohol Consumption research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Student Alcohol Consumption Dataset A dataset on social, gender and study data from secondary school students. Following was retrieved from UCI machine learning repository. Context: The data were obtained in a survey of students math and portuguese language courses in secondary school. It contains a lot of interesting social, gender and study information about students. You can use it for some EDA or try to predict students final grade. Content: Attributes for both… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/student-alcohol-consumption.
Research Context
Student Alcohol Consumption: 500 rows by 33 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
| # | schooltext | sextext | ageinteger | addresstext | famsizetext | Pstatustext | Meduinteger | Feduinteger |
|---|---|---|---|---|---|---|---|---|
| 1 | GP | F | 18 | U | GT3 | A | 4 | 4 |
| 2 | GP | F | 17 | U | GT3 | T | 1 | 1 |
| 3 | GP | F | 15 | U | LE3 | T | 1 | 1 |
| 4 | GP | F | 15 | U | GT3 | T | 4 | 2 |
| 5 | GP | F | 16 | U | GT3 | T | 3 | 3 |
| 6 | GP | M | 16 | U | LE3 | T | 4 | 3 |
Data Dictionary
- school categorical
- sex categorical
- age numeric
- address categorical
- famsize categorical
- Pstatus categorical
- Medu numeric
- Fedu numeric
- Mjob categorical
- Fjob categorical
- reason categorical
- guardian categorical
- traveltime datetime
- studytime datetime
- failures numeric
- schoolsup categorical
- famsup categorical
- paid categorical
- activities categorical
- nursery categorical
- higher categorical
- internet categorical
- romantic categorical
- famrel numeric
- freetime datetime
- goout numeric
- Dalc numeric
- Walc numeric
- health numeric
- absences numeric
- G1 numeric
- G2 numeric
- G3 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.