{
  "format": "dataset-manifest/1",
  "slug": "coffee-recipe-app",
  "version": 2,
  "seed": "coffee-recipe-app:1",
  "spec": {
    "format": "dataset/1",
    "slug": "coffee-recipe-app",
    "name": "Coffee Crafting Data",
    "tagline": "Recipes and user interactions for various coffee brewing techniques and bean reviews from diverse roasters.",
    "description": "Coffee enthusiasts share their passion for brewing by exploring diverse coffee recipes that highlight the unique characteristics of beans sourced from various roasters. Users engage with these recipes by detailing the steps involved, the specific equipment used, and their personal reviews of the beans. This interaction fosters a community where individuals can discuss techniques, compare results, and experiment with different brewing methods that cater to a range of tastes and preferences. Popular recipes often cluster around well-known brewing methods, while niche recipes might focus on specific water profiles or unique equipment that appeal to dedicated aficionados.\n\nThe primary table in this dataset, coffee_recipes, contains detailed records of each recipe shared within the community. Each row represents a unique coffee recipe, including attributes such as the ingredients required, the brewing techniques employed, and user ratings. This information allows for connections between various brewing methods and the preferences of coffee drinkers, revealing trends in user engagement with specific recipes and roasters. Users may also leave reviews for the different beans, which are indirectly linked to the recipes they appear in, offering insights into how the quality of beans impacts the overall brewing process.\n\nQuestions that this data can help answer include: What are the most popular brewing methods among users? How do reviews of beans affect recipe ratings? What types of equipment correlate with successful brewing outcomes? The dataset is particularly useful for practicing data analysis, as it offers opportunities to explore user behavior, recipe performance, and the influence of different brewing techniques. Keep in mind that the data is synthetic, designed for educational purposes, allowing developers to enhance their skills in data manipulation and analysis without using real user information.",
    "domain": "restaurants",
    "shape": "graph-edges",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "coffee",
      "recipes",
      "brewing techniques",
      "user interactions",
      "reviews",
      "roasters",
      "data analysis"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "coffee_recipes": {
        "description": "Each row represents a unique coffee recipe, detailing the brewing method, ingredients, and user interactions. It captures the relationships between different recipes, equipment, and user reviews.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each coffee recipe."
          },
          "recipe_name": {
            "kind": "words",
            "max": 3,
            "description": "Name of the coffee recipe.",
            "pool": [
              "espresso",
              "latte",
              "cappuccino",
              "mocha",
              "americano",
              "flatwhite",
              "affogato",
              "macchiato",
              "breve",
              "ristretto",
              "turmeric",
              "iced",
              "vanilla",
              "hazelnut",
              "caramel",
              "café",
              "caféau",
              "cafécon",
              "cafécrema",
              "cafélatte"
            ],
            "min": 1
          },
          "brewing_method": {
            "kind": "enum",
            "values": [
              "French Press",
              "Espresso",
              "Pour Over",
              "Cold Brew",
              "AeroPress"
            ],
            "description": "The method used to brew the coffee."
          },
          "bean_type": {
            "kind": "words",
            "max": 3,
            "description": "Type of coffee bean used in the recipe.",
            "pool": [
              "arabica",
              "robusta",
              "liberica",
              "excelsa",
              "brazilian",
              "ethiopian",
              "colombian",
              "sumatra",
              "kenyan",
              "guatemalan",
              "peruvian",
              "jamaican",
              "sumatran",
              "kona",
              "panama",
              "nicaraguan",
              "honduran",
              "mexican",
              "indonesian",
              "vietnamese"
            ],
            "min": 1
          },
          "equipment_used": {
            "kind": "words",
            "max": 3,
            "description": "Equipment used to prepare the coffee.",
            "pool": [
              "espresso_machine",
              "french_press",
              "pour_over",
              "aeropress",
              "drip_coffee",
              "cold_brew",
              "moka_pot",
              "syphon",
              "percolator",
              "coffee_grinder",
              "milk_frother",
              "coffee_scale",
              "thermometer",
              "coffee_filter",
              "stovetop",
              "vacuum_pot",
              "nitro_cold_brew",
              "espresso_cup",
              "coffee_carafe",
              "coffee_siphon"
            ],
            "min": 1
          },
          "user_interactions": {
            "kind": "int",
            "min": 0,
            "max": 1000,
            "description": "Number of user interactions with the recipe, such as views or favorites.",
            "distribution": "long-tail"
          },
          "average_rating": {
            "kind": "decimal",
            "min": 0,
            "max": 5,
            "scale": 1,
            "description": "Average user rating for the recipe.",
            "distribution": "high"
          },
          "review_count": {
            "kind": "int",
            "min": 0,
            "max": 500,
            "description": "Number of reviews submitted for this recipe.",
            "distribution": "long-tail"
          },
          "created_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date and time when the recipe was created.",
            "dayProfile": "business"
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "categorical",
      "timestamped",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most popular brewing methods among users?",
      "How do different coffee bean types affect user ratings?",
      "Which recipes have the highest number of user interactions and why?",
      "What is the relationship between equipment used and recipe ratings?",
      "How do user reviews vary across different brewing techniques?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Coffee Recipes with User Ratings",
        "sql": "SELECT recipe_name, average_rating FROM coffee_recipes ORDER BY average_rating DESC;",
        "dialect": "postgres"
      },
      {
        "title": "Count of Recipes by Brewing Method",
        "sql": "SELECT brewing_method, COUNT(*) FROM coffee_recipes GROUP BY brewing_method;",
        "dialect": "postgres"
      },
      {
        "title": "Average Rating for Each Bean Type",
        "sql": "SELECT bean_type, AVG(average_rating) FROM coffee_recipes GROUP BY bean_type;",
        "dialect": "postgres"
      },
      {
        "title": "Top 5 Recipes with User Interactions",
        "sql": "SELECT recipe_name, user_interactions FROM coffee_recipes ORDER BY user_interactions DESC LIMIT 5;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Culinary Educators",
        "body": "Using this dataset, culinary educators can teach students about data analysis in the food industry, focusing on coffee recipes and user engagement trends. By practicing SQL queries, students can learn how to extract meaningful insights from user-generated data."
      },
      {
        "title": "Coffee Enthusiasts",
        "body": "Coffee enthusiasts looking to refine their brewing skills can use this dataset to explore popular recipes and brewing methods. By analyzing user interactions, they can identify trends and preferences within the coffee community, helping them to choose recipes that resonate with other coffee lovers."
      },
      {
        "title": "Data Analysts in Restaurants",
        "body": "Data analysts working in restaurants can utilize this dataset to evaluate the performance of different coffee recipes. By examining average ratings and user interactions, they can make informed decisions about which recipes to feature on their menu."
      }
    ]
  },
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    "coffee_recipes": 200
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          "min": "2020-01-17 14:07:20",
          "max": "2023-12-24 15:04:38"
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    }
  },
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