Spending Patterns Dataset

Dataset Overview

The Spending Patterns Dataset provides a synthetic representation of consumer spending behavior across various categories. This dataset is ideal for exploratory data analysis, statistical modeling, and machine learning applications related to financial forecasting, customer segmentation, or consumer behavior analysis.

Dataset Features

The dataset contains 10,000 transactions for 200 unique customers. Each transaction is associated with detailed information, including category, item, quantity, price, payment method, and transaction date.

Columns

Column Name	Description
`Customer ID`	Unique identifier for each customer (e.g., `CUST_0001`).
`Category`	The spending category (e.g., Groceries, Shopping, Travel).
`Item`	The specific item purchased within the category (e.g., Milk, Plane Ticket).
`Quantity`	Number of units purchased. For specific categories (e.g., Subscriptions, Housing and Utilities, Transportation, Medical/Dental, Travel), this is always `1`.
`Price Per Unit`	The price of one unit of the item (in USD).
`Total Spent`	Total expenditure for the transaction (`Quantity` × `Price Per Unit`).
`Payment Method`	The payment method used (e.g., Credit Card, Cash).
`Location`	Where the transaction occurred (e.g., Online, In-store, Mobile App).
`Transaction Date`	The date of the transaction (YYYY-MM-DD format).

Categories and Items

The dataset includes the following spending categories with example items:

Groceries: Milk, Bread, Fruits, Vegetables, Meat, etc.
Shopping: Clothes, Shoes, Electronics, Car.
Subscriptions: Streaming Service, Gym Membership (Quantity always 1).
Housing and Utilities: Rent, Electricity Bill, Gas Bill (Quantity always 1).
Transportation: Gas, Public Transit, Car Repair (Quantity always 1).
Food: Restaurant Meal, Fast Food, Coffee.
Medical/Dental: Doctor Visit, Dentist Visit, Medicine (Quantity always 1).
Personal Hygiene: Toothpaste, Shampoo, Soap.
Fitness: Yoga Class, Personal Trainer, Workout Equipment.
Travel: Plane Ticket, Hotel Stay, Taxi/Uber (Plane Ticket and Hotel Stay have Quantity always 1).
Hobbies: Books, Art Supplies, Video Games.
Friend Activities: Movie Tickets, Concert Tickets, Dinner with Friends.
Gifts: Flowers, Gift Cards, Jewelry.

Usage Examples

Example 1: Total Spending by Category

Example 2: Spending Habits of Each Customer

Example 13 Price Change Over Time

Tables

Spending Patterns Detailed

@kaggle.ahmedmohamed2003_spending_habits.spending_patterns_detailed

166.73 KB
10000 rows
9 columns


CREATE TABLE spending_patterns_detailed (
  "customer_id" VARCHAR,
  "category" VARCHAR,
  "item" VARCHAR,
  "quantity" BIGINT,
  "price_per_unit" DOUBLE,
  "total_spent" DOUBLE,
  "payment_method" VARCHAR,
  "location" VARCHAR,
  "transaction_date" TIMESTAMP
);