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Datasets:
SDMN2001
/
recipe_difficulties

Tasks:
Text Classification
Text Retrieval
Other
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
Tags:
recipes
cooking
food
difficulty-prediction
nlp
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
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recipe_difficulties / README.md
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metadata
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
  • 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 

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} }