{
  "format": "dataset-manifest/1",
  "slug": "customizable-diet-and-nutrition-planner",
  "version": 3,
  "seed": "customizable-diet-and-nutrition-planner:1",
  "spec": {
    "format": "dataset/1",
    "slug": "customizable-diet-and-nutrition-planner",
    "name": "Personalized Nutrition Insights",
    "tagline": "Tailor your meal plans to achieve your health goals and preferences.",
    "description": "Individuals create tailored meal plans that align with their health goals and personal preferences. This customizable diet and nutrition planner allows users to explore various meal options, food types, and exercise activities while considering their unique dietary restrictions or preferences. Users engage with the platform by selecting meals and incorporating an assortment of foods and supplements to curate their ideal nutrition profile, leading to a variety of simple yet balanced meal plans that emphasize core food categories. The straightforward nature of most meal plans ensures that users can easily manage their dietary choices without the complexity of multi-ingredient dishes.\n\nThe primary table in this dataset is the meal_plans table. Each row represents a distinct meal plan created by a user, detailing their selected meals, dietary restrictions, and the nutritional profile associated with each plan. By understanding this table, developers can practice querying user-specific preferences, dietary habits, and nutritional outcomes. Users can join this table with other potential data sources, such as user profiles and exercise activities, to build comprehensive insights into the relationship between diet and health, even though other tables are not currently included in this dataset.\n\nThis data set helps answer key questions related to personalized nutrition, such as: What meal combinations work best for different dietary goals? How do users with specific dietary restrictions create their meal plans? What are the most popular meal choices among various user demographics? Practicing queries with this synthetic dataset can enhance skills in data manipulation, user behavior analysis, and nutrition insights, making it an ideal resource for developers looking to strengthen their expertise in data analytics within the restaurant domain.",
    "domain": "restaurants",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "nutrition",
      "meal planning",
      "diet",
      "exercise",
      "user profiles",
      "food types",
      "customizable meals",
      "health goals"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "meal_plans": {
        "description": "Each row represents a user's personalized meal plan, detailing their selected meals, food types, and exercise activities. The table includes user profiles that specify dietary restrictions or preferences, enabling a tailored nutrition experience.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each meal plan."
          },
          "user_id": {
            "kind": "int",
            "min": 1,
            "max": 100,
            "description": "Identifier for the user creating the meal plan."
          },
          "meal_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the selected meal.",
            "pool": [
              "salad",
              "pasta",
              "chicken",
              "quinoa",
              "smoothie",
              "soup",
              "tacos",
              "bowl",
              "wrap",
              "curry",
              "stirfry",
              "sandwich",
              "omelette",
              "pizza",
              "burger",
              "toast",
              "sushi",
              "pancake",
              "cereal",
              "dessert"
            ]
          },
          "food_type": {
            "kind": "enum",
            "values": [
              "vegetarian",
              "vegan",
              "paleo",
              "keto",
              "gluten-free"
            ],
            "description": "Type of food based on dietary preferences.",
            "weights": [
              6,
              2,
              1,
              1,
              1
            ]
          },
          "calories": {
            "kind": "int",
            "min": 100,
            "max": 1200,
            "description": "Total calories in the meal.",
            "distribution": "normal"
          },
          "protein": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 1,
            "description": "Protein content in grams.",
            "distribution": "normal"
          },
          "carbohydrates": {
            "kind": "decimal",
            "min": 0,
            "max": 200,
            "scale": 1,
            "description": "Carbohydrate content in grams.",
            "distribution": "normal"
          },
          "fats": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 1,
            "description": "Fat content in grams.",
            "distribution": "normal"
          },
          "exercise_activity": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Type of exercise activity associated with the meal plan.",
            "pool": [
              "running",
              "yoga",
              "cycling",
              "swimming",
              "weightlifting",
              "hiking",
              "dancing",
              "boxing",
              "pilates",
              "aerobics",
              "stretching",
              "walking",
              "jumping",
              "climbing",
              "skating",
              "surfing",
              "crossfit",
              "martialarts",
              "zumba",
              "kickboxing"
            ]
          },
          "dietary_restrictions": {
            "kind": "words",
            "nullable": true,
            "description": "User's dietary restrictions, if any.",
            "pool": [
              "vegan",
              "glutenfree",
              "nutfree",
              "dairyfree",
              "lowcarb",
              "paleo",
              "keto",
              "vegetarian",
              "lowfat",
              "sugarfree",
              "halal",
              "kosher",
              "lowcalorie",
              "highprotein",
              "raw",
              "mediterranean",
              "whole30",
              "FODMAP",
              "antiinflammatory",
              "clean"
            ],
            "min": 1,
            "max": 3
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "categorical",
      "monetary",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most common dietary restrictions among users?",
      "How do meal choices vary by food type?",
      "What is the average calorie intake per meal plan?",
      "Which exercise activities are most frequently paired with meal plans?",
      "What meal types contribute the highest protein content?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all meal plans for a specific user",
        "sql": "SELECT * FROM meal_plans WHERE user_id = 1;",
        "dialect": "postgres"
      },
      {
        "title": "Calculate average calories per food type",
        "sql": "SELECT food_type, AVG(calories) FROM meal_plans GROUP BY food_type;",
        "dialect": "postgres"
      },
      {
        "title": "Find meal plans with dietary restrictions",
        "sql": "SELECT * FROM meal_plans WHERE dietary_restrictions IS NOT NULL;",
        "dialect": "postgres"
      },
      {
        "title": "Count meal plans by exercise activity",
        "sql": "SELECT exercise_activity, COUNT(*) FROM meal_plans GROUP BY exercise_activity;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Nutritionist Application",
        "body": "Nutritionists can utilize this dataset to create user-specific meal plans, helping clients meet their dietary goals based on personal preferences and medical needs. By analyzing the data, they can identify popular meal choices and nutritional trends among their clientele."
      },
      {
        "title": "Fitness Tracker Integration",
        "body": "Developers of fitness tracking applications can leverage this dataset to integrate meal planning features, allowing users to log their food intake alongside exercise routines. This enhances the user experience by providing a holistic view of their health journey."
      },
      {
        "title": "Health Research Studies",
        "body": "Researchers in the field of nutrition can analyze this dataset to study the correlation between dietary restrictions and meal preferences. This insight can drive better understanding in dietary choices and their implications for health outcomes."
      }
    ]
  },
  "counts": {
    "meal_plans": 200
  },
  "stats": {
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      "columns": {
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          "nulls": 0,
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          "min": 1,
          "max": 200
        },
        "user_id": {
          "nulls": 0,
          "distinct": 86,
          "min": 1,
          "max": 100
        },
        "meal_name": {
          "nulls": 0,
          "distinct": 160
        },
        "food_type": {
          "nulls": 0,
          "distinct": 5,
          "min": "gluten-free",
          "max": "vegetarian"
        },
        "calories": {
          "nulls": 0,
          "distinct": 175,
          "min": 190,
          "max": 1104
        },
        "protein": {
          "nulls": 0,
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          "min": 14.4,
          "max": 89.2
        },
        "carbohydrates": {
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          "distinct": 183,
          "min": 32.2,
          "max": 177.9
        },
        "fats": {
          "nulls": 0,
          "distinct": 163,
          "min": 15.3,
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        },
        "exercise_activity": {
          "nulls": 0,
          "distinct": 152
        },
        "dietary_restrictions": {
          "nulls": 30,
          "distinct": 134
        }
      }
    }
  },
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