Student Spending Habits Dataset.

- Title: Student Spending Habits Dataset
Description:
This dataset contains fictional data representing the spending habits of 1000 students across various demographic groups and academic backgrounds.
The dataset includes information such as age, gender, year in school, major, monthly income, financial aid received, and expenses in different spending categories.
Spending categories include tuition, housing, food, transportation, books & supplies, entertainment, personal care, technology, health & wellness, and miscellaneous expenses.
Additionally, the dataset includes the preferred payment method for each student.
Columns:

1. Age: Age of the student (in years)
2. Gender: Gender of the student (Male, Female, Non-binary)
3. Year in School: Year of study (Freshman, Sophomore, Junior, Senior)
4. Major: Field of study or major
5. Monthly Income: Monthly income of the student (in dollars)
6. Financial Aid: Financial aid received by the student (in dollars)
7. Tuition: Expenses for tuition (in dollars)
8. Housing: Expenses for housing (in dollars)
9. Food: Expenses for food (in dollars)
10. Transportation: Expenses for transportation (in dollars)
11. Books & Supplies: Expenses for books and supplies (in dollars)
12. Entertainment: Expenses for entertainment (in dollars)
13. Personal Care: Expenses for personal care items (in dollars)
14. Technology: Expenses for technology (in dollars)
15. Health & Wellness: Expenses for health and wellness (in dollars)
16. Miscellaneous: Miscellaneous expenses (in dollars)
17. Preferred Payment Method: Preferred payment method (Cash, Credit/Debit Card, Mobile Payment App)
    Usage:
    This dataset can be used for various analyses related to student spending habits, financial literacy, budgeting strategies, and payment preferences.
    Researchers, educators, and students can utilize this dataset for exploratory data analysis, predictive modeling, and developing insights into the financial behaviors of students.
    Acknowledgements:
    This dataset was generated for educational and research purposes, and all data is entirely fictional.