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--- |
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datasets: |
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- processed_recipes |
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language: |
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- en |
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tags: |
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- recipes |
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- cooking |
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- food |
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- difficulty-prediction |
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- nlp |
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license: other |
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task_categories: |
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- text-classification |
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- text-retrieval |
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- other |
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pretty_name: Processed Recipes Dataset |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Processed Recipes Dataset |
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## Dataset Description |
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- **Source**: Scraped from [Food Network](https://www.foodnetwork.com/) |
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- **Processed by**: Cleaned and parsed for use in recipe difficulty prediction |
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- **Format**: Parquet (`.parquet`) |
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- **Size**: 1 file (`processed_recipes.parquet`) |
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This dataset contains structured recipe information scraped from Food Network. |
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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: |
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- Ingredient analysis |
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- Cooking time prediction |
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- Recipe recommendation systems |
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- Natural language processing on cooking instructions |
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--- |
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## Dataset Structure |
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### Columns |
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- **title** *(string)*: Recipe title |
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- **level** *(string)*: Difficulty level (e.g., Easy, Intermediate, Advanced) |
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- **clean_ingredients** *(string)*: Comma-separated list of cleaned ingredients |
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- **ingredients_count** *(int)*: Number of ingredients in the recipe |
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- **directions_count** *(int)*: Number of steps in the recipe directions |
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- **unique_techniques** *(string)*: Comma-separated list of unique cooking techniques detected |
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- **equipment** *(string)*: Comma-separated list of equipment mentioned |
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- **has_precise_timing** *(bool)*: Whether the recipe specifies precise timing (True/False) |
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- **total_minutes** *(int)*: Total time in minutes (0 if not specified) |
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- **active_minutes** *(int)*: Active cooking time in minutes (0 if not specified) |
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- **prep_minutes** *(int)*: Preparation time in minutes |
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- **cook_minutes** *(int)*: Cooking time in minutes |
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--- |
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### Example Row |
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```text |
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title: 100-Calorie Ham and Cheese Individual Frittatas |
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level: Easy |
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clean_ingredients: nonstick cooking spray, olive oil, ham steak, sliced mushrooms, ... |
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ingredients_count: 9 |
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directions_count: 5 |
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unique_techniques: preheat, reduce, beat, come, insert, scoop, set, heat |
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equipment: center, large bowl, large nonstick skillet medium |
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has_precise_timing: True |
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total_minutes: 0 |
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active_minutes: 0 |
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prep_minutes: 15 |
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cook_minutes: 45 |
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``` |
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--- |
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## Intended Uses |
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- **Primary use**: Training models for recipe difficulty prediction |
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- **Other possible uses**: |
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- Ingredient-based clustering |
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- Cooking time estimation |
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- Recipe recommendation |
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- NLP tasks on cooking instructions |
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--- |
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## Limitations |
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- Recipes are scraped from Food Network and may not represent all cuisines or cooking styles. |
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- Some time values (`total_minutes`, `active_minutes`) may be missing or set to `0` if not provided. |
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- Ingredient and equipment parsing may not be perfect. |
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--- |
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## License |
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⚠️ **Note**: The dataset is derived from Food Network content. Please ensure compliance with their terms of service before using this dataset for commercial purposes. |
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--- |
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## Citation |
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If you use this dataset in your research or project, please cite it as: |
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@dataset{processed_recipes, |
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title = {Processed Recipes Dataset}, |
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author = {Saadman Rahman}, |
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year = {2025}, |
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url = {https://huggingface.co/datasets/SDMN2001/recipe_difficulties} |
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} |
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