#!/usr/bin/env python3
"""
Script to create sample CSV files that can be imported into DuckDB
"""
import csv
from pathlib import Path
def create_sample_csvs():
"""Create sample CSV files for the package"""
data_dir = Path("mcp_visualization/data")
data_dir.mkdir(parents=True, exist_ok=True)
print("Creating sample CSV files...")
# Sales data
sales_data = [
["id", "product_name", "category", "sales_amount", "quantity", "sale_date", "region", "salesperson"],
[1, "Laptop Pro", "Electronics", 1299.99, 2, "2024-01-15", "North", "Alice Johnson"],
[2, "Wireless Mouse", "Electronics", 29.99, 15, "2024-01-16", "South", "Bob Smith"],
[3, "Coffee Maker", "Appliances", 79.99, 8, "2024-01-17", "East", "Carol Davis"],
[4, "Smartphone", "Electronics", 899.99, 12, "2024-01-18", "West", "David Wilson"],
[5, "Desk Chair", "Furniture", 199.99, 5, "2024-01-19", "North", "Alice Johnson"],
[6, "Monitor", "Electronics", 349.99, 7, "2024-01-20", "South", "Eve Brown"],
[7, "Kitchen Blender", "Appliances", 89.99, 4, "2024-01-21", "East", "Frank Miller"],
[8, "Bookshelf", "Furniture", 159.99, 3, "2024-01-22", "West", "Grace Taylor"],
[9, "Tablet", "Electronics", 449.99, 9, "2024-01-23", "North", "Henry Lee"],
[10, "Microwave", "Appliances", 129.99, 6, "2024-01-24", "South", "Ivy Chen"],
[11, "Gaming Keyboard", "Electronics", 79.99, 11, "2024-01-25", "East", "Jack White"],
[12, "Office Desk", "Furniture", 299.99, 4, "2024-01-26", "West", "Kate Green"],
[13, "Smart Watch", "Electronics", 249.99, 8, "2024-01-27", "North", "Liam Black"],
[14, "Air Fryer", "Appliances", 119.99, 7, "2024-01-28", "South", "Mia Gray"],
[15, "Sofa", "Furniture", 799.99, 2, "2024-01-29", "East", "Noah Blue"]
]
with open(data_dir / "sales_data.csv", 'w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerows(sales_data)
# Customer data
customer_data = [
["customer_id", "customer_name", "email", "age", "gender", "city", "state", "signup_date", "total_purchases", "loyalty_tier"],
[1, "John Doe", "john.doe@email.com", 32, "Male", "New York", "NY", "2023-03-15", 2459.97, "Gold"],
[2, "Jane Smith", "jane.smith@email.com", 28, "Female", "Los Angeles", "CA", "2023-05-20", 1879.94, "Silver"],
[3, "Mike Johnson", "mike.j@email.com", 45, "Male", "Chicago", "IL", "2023-01-10", 3299.95, "Platinum"],
[4, "Sarah Wilson", "sarah.w@email.com", 35, "Female", "Houston", "TX", "2023-07-08", 1599.98, "Silver"],
[5, "David Brown", "david.b@email.com", 52, "Male", "Phoenix", "AZ", "2023-02-14", 1049.99, "Bronze"],
[6, "Lisa Davis", "lisa.d@email.com", 29, "Female", "Philadelphia", "PA", "2023-06-25", 2199.96, "Gold"],
[7, "Chris Miller", "chris.m@email.com", 38, "Male", "San Antonio", "TX", "2023-04-12", 899.99, "Bronze"],
[8, "Amy Taylor", "amy.t@email.com", 41, "Female", "San Diego", "CA", "2023-08-30", 1749.97, "Silver"],
[9, "Tom Anderson", "tom.a@email.com", 33, "Male", "Dallas", "TX", "2023-03-22", 1299.99, "Bronze"],
[10, "Emma White", "emma.w@email.com", 26, "Female", "San Jose", "CA", "2023-09-15", 1949.98, "Gold"]
]
with open(data_dir / "customer_data.csv", 'w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerows(customer_data)
# Monthly revenue
monthly_revenue = [
["month", "total_revenue", "orders_count", "avg_order_value", "new_customers", "returning_customers"],
["2023-01-01", 45000.00, 150, 300.00, 45, 105],
["2023-02-01", 52000.00, 173, 300.58, 38, 135],
["2023-03-01", 48000.00, 160, 300.00, 42, 118],
["2023-04-01", 61000.00, 203, 300.49, 55, 148],
["2023-05-01", 58000.00, 193, 300.52, 48, 145],
["2023-06-01", 65000.00, 217, 299.54, 62, 155],
["2023-07-01", 71000.00, 237, 299.58, 68, 169],
["2023-08-01", 69000.00, 230, 300.00, 59, 171],
["2023-09-01", 74000.00, 247, 299.59, 71, 176],
["2023-10-01", 78000.00, 260, 300.00, 75, 185],
["2023-11-01", 85000.00, 283, 300.35, 82, 201],
["2023-12-01", 92000.00, 307, 299.67, 89, 218]
]
with open(data_dir / "monthly_revenue.csv", 'w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerows(monthly_revenue)
# Product categories
product_categories = [
["category", "total_sales", "units_sold", "avg_price", "profit_margin", "customer_rating"],
["Electronics", 234599.88, 1250, 187.68, 22.5, 4.2],
["Furniture", 189799.92, 485, 391.34, 35.2, 4.1],
["Appliances", 145699.95, 823, 177.06, 28.7, 4.3],
["Clothing", 98750.00, 1875, 52.67, 45.3, 3.9],
["Sports", 76890.50, 967, 79.51, 32.1, 4.0],
["Books", 45230.75, 2011, 22.50, 40.8, 4.4],
["Beauty", 67890.25, 1534, 44.26, 55.2, 4.1],
["Toys", 34567.80, 891, 38.79, 38.9, 4.2]
]
with open(data_dir / "product_categories.csv", 'w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerows(product_categories)
print("ā
Sample CSV files created:")
for csv_file in data_dir.glob("*.csv"):
print(f" - {csv_file}")
return True
if __name__ == "__main__":
create_sample_csvs()
print("\nš Sample data creation complete!")
print("š Files are ready for package distribution")
