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---
dataset_info:
features:
- name: Beverage type
dtype: string
- name: Category
dtype: string
- name: Added sugar (g)
dtype: float64
- name: Calories
dtype: float64
- name: Volume
dtype: string
- name: Energy rating (1-5)
dtype: int64
- name: Is high sugar?
dtype: int64
splits:
- name: original
num_bytes: 2590
num_examples: 30
- name: augmented
num_bytes: 25900
num_examples: 300
download_size: 13298
dataset_size: 28490
configs:
- config_name: default
data_files:
- split: original
path: data/original-*
- split: augmented
path: data/augmented-*
license: cc
language:
- en
task_categories:
- tabular-classification
tags:
- beverage
- energy
pretty_name: Beverage Energy Tracker
size_categories:
- 10K<n<100K
---
# Dataset Card for Beverage Energy Tracker
This dataset card documents the **Beverage Energy Tracker** dataset.
It contains nutritional and energy-related features of 30 unique beverages, with an augmented split expanding to 300 rows.
---
## Dataset Details
**Dataset Description**
- **Curated by:** Bareethul Kader (Carnegie Mellon University, EST&P program)
- **Language(s):** English (column labels, beverage names)
- **License:** CC BY 4.0
- **Repository:** [bareethul/beverage-energy-tracker](https://huggingface.co/datasets/bareethul/beverage-energy-tracker)
---
## Uses
**Direct Use**
- Educational practice in data collection, preprocessing, and augmentation.
- Demonstration of label-preserving jitter augmentation for tabular datasets.
- Binary classification task: predict whether a beverage is **high sugar** or not.
**Out-of-Scope Use**
- Not intended for clinical, nutritional, or health policy decision-making.
- Values are approximate and curated manually - not to be used for dietary guidance.
---
## Dataset Structure
- **Original split:** 30 manually curated beverages.
- **Augmented split:** 300 rows, generated with Gaussian jitter (for continuous features) and ±1 step encoding (for ordinal features).
**Features:**
- `Beverage type` (string)
- `Added sugar (g)` (float)
- `Calories` (float)
- `Volume (mL)` (integer)
- `Energy rating (1–5)` (ordinal)
- `is_high_sugar` (binary target: `1 = sugar ≥ 20g`, `0 = sugar < 20g`)
---
## Dataset Creation
**Curation Rationale**
To study how nutritional features (sugar, calories, volume) can relate to **sugar content classification** (high vs low).
**Data Collection and Processing**
- Data manually collected from: Starbucks, ALDI USA, MarketDistrict, Amazon, Walmart product pages.
- Manual preprocessing and type formatting were applied (e.g., ensuring numeric columns, clipping noise to avoid negative values).
- Binary target `is_high_sugar` was derived using a threshold of **20g sugar**.
**Source Data Producers**
- Original producers: beverage manufacturers and retailers (nutritional info posted publicly).
- Dataset curated by Bareethul Kader for educational purposes.
---
## Annotations
- **Annotation Process:** Binary target derived from numeric sugar values.
- **Annotators:** Dataset creator.
---
## Personal and Sensitive Information
- No personal or sensitive data included.
---
## Bias, Risks, and Limitations
- Limited to 30 beverages (not representative of all products).
- `Energy rating` and `is_high_sugar` are simplified labels, not standardized nutrition metrics.
- Augmentation may create unrealistic numeric combinations.
---
## Recommendations
Users should be aware of the risks, biases, and limitations of the dataset.
It is intended only for **educational demonstrations** of dataset creation, preprocessing, and augmentation.
Do not generalize results to real nutrition/health applications.
---
## Citation
**BibTeX:**
```bibtex
@dataset{bareethul_beverage_energy_tracker,
author = {Kader, Bareethul},
title = {Beverage Energy Tracker},
year = {2025},
publisher = {Hugging Face Datasets},
url = {https://huggingface.co/datasets/bareethul/beverage-energy-tracker}
}
|