Data Views

import pandasai as pai

# Create source datasets for an e-commerce analytics system
# Orders dataset
orders_df = pai.read_csv("orders.csv")
orders_dataset = pai.create(
    "myorg/orders",
    orders_df,
    description="Customer orders and transaction data"
)

# Products dataset
products_df = pai.read_csv("products.csv")
products_dataset = pai.create(
    "myorg/products",
    products_df,
    description="Product catalog with categories and pricing"
)

# Customer dataset
customers_df = pai.read_csv("customers.csv")
customers_dataset = pai.create(
    "myorg/customers",
    customers_df,
    description="Customer demographics and preferences"
)

# Define relationships between datasets
view_relations = [
    {
        "name": "order_to_product",
        "description": "Links orders to their products",
        "from": "orders.product_id",
        "to": "products.id"
    },
    {
        "name": "order_to_customer",
        "description": "Links orders to customer profiles",
        "from": "orders.customer_id",
        "to": "customers.id"
    }
]

# Select relevant columns for the sales analytics view
view_columns = [
    # Order details
    {"name": "orders.id", "type": "integer"},
    {"name": "orders.order_date", "type": "date"},
    {"name": "orders.total_amount", "type": "float"},
    {"name": "orders.status", "type": "string"},

    # Product information
    {"name": "products.name", "type": "string"},
    {"name": "products.category", "type": "string"},
    {"name": "products.unit_price", "type": "float"},
    {"name": "products.stock_level", "type": "integer"},

    # Customer information
    {"name": "customers.segment", "type": "string"},
    {"name": "customers.country", "type": "string"},
    {"name": "customers.join_date", "type": "date"},
]

# Create a comprehensive sales analytics view
sales_view = pai.create(
    "myorg/sales-analytics",
    description="Unified view of sales data combining orders, products, and customer information",
    relations=view_relations,
    columns=view_columns,
    view=True
)

# This view enables powerful analytics queries like:
# - Sales trends by customer segment and product category
# - Customer purchase history and preferences
# - Inventory management based on order patterns
# - Geographic sales distribution

name: table_heart
columns:
  - name: parents.id
  - name: parents.name
  - name: parents.age
  - name: children.name
  - name: children.age
relations:
  - name: parent_to_children
    description: Relation linking the parent to its children
    from: parents.id
    to: children.id