---
datasets:
- processed_recipes
language:
- en
tags:
- recipes
- cooking
- food
- difficulty-prediction
- nlp
license: other
task_categories:
- text-classification
- text-retrieval
- other
pretty_name: Processed Recipes Dataset
size_categories:
- 10K<n<100K
---


# Processed Recipes Dataset

## Dataset Description

- **Source**: Scraped from [Food Network](https://www.foodnetwork.com/)  
- **Processed by**: Cleaned and parsed for use in recipe difficulty prediction  
- **Format**: Parquet (`.parquet`)  
- **Size**: 1 file (`processed_recipes.parquet`)  

This dataset contains structured recipe information scraped from Food Network.  
It was originally collected and processed to train a model for **recipe difficulty prediction**, but it can also be used for other tasks such as:

- Ingredient analysis  
- Cooking time prediction  
- Recipe recommendation systems  
- Natural language processing on cooking instructions  

---

## Dataset Structure

### Columns

- **title** *(string)*: Recipe title  
- **level** *(string)*: Difficulty level (e.g., Easy, Intermediate, Advanced)  
- **clean_ingredients** *(string)*: Comma-separated list of cleaned ingredients  
- **ingredients_count** *(int)*: Number of ingredients in the recipe  
- **directions_count** *(int)*: Number of steps in the recipe directions  
- **unique_techniques** *(string)*: Comma-separated list of unique cooking techniques detected  
- **equipment** *(string)*: Comma-separated list of equipment mentioned  
- **has_precise_timing** *(bool)*: Whether the recipe specifies precise timing (True/False)  
- **total_minutes** *(int)*: Total time in minutes (0 if not specified)  
- **active_minutes** *(int)*: Active cooking time in minutes (0 if not specified)  
- **prep_minutes** *(int)*: Preparation time in minutes  
- **cook_minutes** *(int)*: Cooking time in minutes  

---

### Example Row

```text
title:                100-Calorie Ham and Cheese Individual Frittatas
level:                Easy
clean_ingredients:    nonstick cooking spray, olive oil, ham steak, sliced mushrooms, ...
ingredients_count:    9
directions_count:     5
unique_techniques:    preheat, reduce, beat, come, insert, scoop, set, heat
equipment:            center, large bowl, large nonstick skillet medium
has_precise_timing:   True
total_minutes:        0
active_minutes:       0
prep_minutes:         15
cook_minutes:         45
```

---

## Intended Uses

- **Primary use**: Training models for recipe difficulty prediction  
- **Other possible uses**:  
  - Ingredient-based clustering  
  - Cooking time estimation  
  - Recipe recommendation  
  - NLP tasks on cooking instructions  

---

## Limitations

- Recipes are scraped from Food Network and may not represent all cuisines or cooking styles.  
- Some time values (`total_minutes`, `active_minutes`) may be missing or set to `0` if not provided.  
- Ingredient and equipment parsing may not be perfect.  

---

## License

⚠️ **Note**: The dataset is derived from Food Network content. Please ensure compliance with their terms of service before using this dataset for commercial purposes.  

---

## Citation

If you use this dataset in your research or project, please cite it as:

@dataset{processed_recipes,
title        = {Processed Recipes Dataset},
author       = {Saadman Rahman},
year         = {2025},
url          = {https://huggingface.co/datasets/SDMN2001/recipe_difficulties}
}