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import pandas as pd
import numpy as np
import time
from datetime import datetime
def generate_realtime_data(num_rows=1):
"""Generates simulated sales data."""
products = ['Electronics', 'Clothing', 'Books', 'Home Goods']
payment_methods = ['Credit Card', 'Debit Card', 'UPI', 'Net Banking']
data = []
for _ in range(num_rows):
timestamp = datetime.now()
product_type = np.random.choice(products)
price = round(np.random.uniform(10, 500), 2)
num_clicks = np.random.randint(1, 100)
payment_method = np.random.choice(payment_methods)
customer_id = np.random.randint(1000, 9999)
data.append([timestamp, product_type, price, num_clicks, payment_method, customer_id])
df = pd.DataFrame(data, columns=['timestamp', 'product_type', 'price', 'num_clicks', 'payment_method', 'customer_id'])
return df
if __name__ == "__main__":
while True:
new_data = generate_realtime_data()
print(new_data)
# In a real application, you would likely append this to a larger DataFrame
# or stream it to your dashboard.
time.sleep(1) # Simulate data generation every 1 second |