Global Food Nutrition Dataset

Global Food Nutrition Dataset

Datasets

Global Food Nutrition Dataset

File

Global Food Nutrition Dataset

Use Case

Global Food Nutrition Dataset

Description

Explore our extensive Global Food Nutrition Dataset for detailed macro and micronutrient content. Ideal for dietary planning

Global Food Nutrition Dataset

Description:

This dataset offers an extensive range of nutritional information for various globally consumed food items. It is designed to assist with dietary planning, nutritional analysis, and educational purposes, detailing macro and micronutrient content.

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Data Format:
The dataset is provided as a CSV file, facilitating easy import into data analysis tools.

Column Descriptions:

  1. Food: Name of the food item.
  2. Caloric Value: Energy in kcal per 100 grams.
  3. Fat (g): Total fats per 100 grams.
  4. Saturated Fats (g): Saturated fats per 100 grams.
  5. Monounsaturated Fats (g): Monounsaturated fats per 100 grams.
  6. Polyunsaturated Fats (g): Polyunsaturated fats per 100 grams.
  7. Carbohydrates (g): Total carbohydrates per 100 grams.
  8. Sugars (g): Sugars per 100 grams.
  9. Protein (g): Protein per 100 grams.
  10. Dietary Fiber (g): Fiber content per 100 grams.
  11. Cholesterol (mg): Cholesterol per 100 grams.
  12. Sodium (mg): Sodium per 100 grams.
  13. Water (g): Water content per 100 grams.
  14. Vitamin A (µg): Vitamin A per 100 grams.
  15. Vitamin B1 (Thiamine) (mg): Thiamine per 100 grams.
  16. Vitamin B11 (Folic Acid) (µg): Folic Acid per 100 grams.
  17. Vitamin B12 (µg): Vitamin B12 per 100 grams.
  18. Vitamin B2 (Riboflavin) (mg): Riboflavin per 100 grams.
  19. Vitamin B3 (Niacin) (mg): Niacin per 100 grams.
  20. Vitamin B5 (Pantothenic Acid) (mg): Pantothenic Acid per 100 grams.
  21. Vitamin B6 (mg): Vitamin B6 per 100 grams.
  22. Vitamin C (mg): Vitamin C per 100 grams.
  23. Vitamin D (µg): Vitamin D per 100 grams.
  24. Vitamin E (mg): Vitamin E per 100 grams.
  25. Vitamin K (µg): Vitamin K per 100 grams.
  26. Calcium (mg): Calcium per 100 grams.
  27. Copper (mg): Copper per 100 grams.
  28. Iron (mg): Iron per 100 grams.
  29. Magnesium (mg): Magnesium per 100 grams.
  30. Manganese (mg): Manganese per 100 grams.
  31. Phosphorus (mg): Phosphorus per 100 grams.
  32. Potassium (mg): Potassium per 100 grams.
  33. Selenium (µg): Selenium per 100 grams.
  34. Zinc (mg): Zinc per 100 grams.
  35. Nutrition Density: Nutrient richness per calorie.

Use Cases:

  1. Nutritional Pattern Analysis: Identify patterns in food consumption and nutritional impacts using machine learning.
  2. Diet Recommendation Systems: Suggest dietary adjustments integrating broader dietary data.
  3. Predictive Health Modeling: Forecast health impacts based on food consumption patterns.
  4. Ingredient Optimization: Formulate new recipes predicting nutritional content based on ingredients.
  5. Consumer Behavior Analysis: Predict preferences based on nutritional information and demographics.
  6. Quality Control: Ensure quality and consistency in food manufacturing.
  7. Text Analysis for Marketing: Extract consumer sentiments related to nutritional aspects from reviews.
  8. Supply Chain Optimization: Optimize supply chains by predicting demand based on health trends.
  9. Educational Tools: Develop interactive applications to teach nutrition.
  10. Integration with Fitness Apps: Provide insights into dietary goals by integrating consumption data into fitness apps.

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