Digital Wallet Transactions

Digital Wallet Transactions Dataset
Overview
This dataset simulates transactions from a digital wallet platform similar to popular services like PayTm in India or Khalti in Nepal. It contains 5000 synthetic records of various financial transactions across multiple categories, providing a rich source for analysis of digital payment behaviors and trends.

Dataset Description
The dataset includes the following features:

idx: Unique index for each record
*transaction_id:*Unique identifier for each transaction (UUID)
user_id: Unique identifier for each user
transaction_date: Date and time of the transaction
product_category: Category of the product or service
product_name: Specific product or service name
merchant_name: Name of the merchant or service provider
product_amount: Transaction amount in local currency
transaction_fee: Fee charged for the transaction
cashback: Cashback amount received for the transaction
loyalty_points: Loyalty points earned from the transaction
payment_method: Method used for payment
transaction_status: Status of the transaction (Successful, Failed, Pending)
merchant_id: Unique identifier for each merchant
device_type: Type of device used for the transaction
location: Broad location category of the transaction

Key Features

• Realistic product and service names across various categories
• Dynamic transaction dates spanning the last year
• Variety of payment methods and transaction statuses
• Inclusion of cashback and loyalty points to reflect modern digital wallet features

Potential Use Cases

• Analyzing spending patterns across different product categories
• Studying the effectiveness of cashback and loyalty programs
• Investigating the relationship between payment methods and transaction success rates
• Exploring seasonal trends in digital wallet usage
• Developing fraud detection models based on transaction patterns
• Segmenting users based on their spending behavior
• Analyzing the popularity of different merchants and services

Notes

This is a synthetic dataset created for educational and analytical purposes.
While it aims to mimic real-world patterns, it does not represent actual transactions or real individuals.
The dataset can be used for various data science projects, including but not limited to exploratory data analysis, machine learning model development, and data visualization exercises.