- Follow ES6+ conventions
- Avoid using 'var' keyword

- Follow Django style guide
- Avoid using raw queries
- Prefer the Django REST Framework for API development
- Prefer Celery for background tasks
- Prefer Redis for caching and task queues
- Prefer PostgreSQL for production databases

You are an experienced data scientist who specializes in Python-based
data science and machine learning. You use the following tools:
- Python 3 as the primary programming language
- PyTorch for deep learning and neural networks
- NumPy for numerical computing and array operations
- Pandas for data manipulation and analysis
- Jupyter for interactive development and visualization
- Conda for environment and package management
- Matplotlib for data visualization and plotting

- Follow Next.js patterns, use app router and correctly use server and client components.
- Use Tailwind CSS for styling.
- Use Shadcn UI for components.
- Use TanStack Query (react-query) for frontend data fetching.
- Use React Hook Form for form handling.
- Use Zod for validation.
- Use React Context for state management.
- Use Prisma for database access.
- Follow AirBnB style guide for code formatting.
- Use PascalCase when creating new React files. UserCard, not user-card.
- Use named exports when creating new react components.
- DO NOT TEACH ME HOW TO SET UP THE PROJECT, JUMP STRAIGHT TO WRITING COMPONENTS AND CODE.

- Follow Nuxt.js 3 patterns and correctly use server and client components.
- Use Nuxt UI for components and styling (built on top of Tailwind CSS).
- Use VueUse for utility composables.
- Use Pinia for state management.
- Use Vee-Validate + Zod for form handling and validation.
- Use Nuxt DevTools for debugging.
- Use Vue Query (TanStack) for complex data fetching scenarios.
- Use Prisma for database access.
- Follow Vue.js Style Guide for code formatting.
- Use script setup syntax for components.
- DO NOT TEACH ME HOW TO SET UP THE PROJECT, JUMP STRAIGHT TO WRITING COMPONENTS AND CODE.

## Build & Development Commands
- codeigniter, laravel, grunt, composer, npm

## Testing Guidelines
- 

## Code Style & Guidelines 
- 

## Documentation Guidelines 
- 

Use Cargo to write a comprehensive suite of unit tests for this function

Create a new Next.js page based on the following description.

Review this API route for security vulnerabilities. Ask questions about the context, data flow, and potential attack vectors. Be thorough in your investigation.

Create a client component with the following functionality. If writing this as a server component is not possible, explain why.

Create an exploratory data analysis workflow that includes:

Data Overview:
- Basic statistics (mean, median, std, quartiles)
- Missing values and data types
- Unique value distributions

Visualizations:
- Numerical: histograms, box plots
- Categorical: bar charts, frequency plots
- Relationships: correlation matrices
- Temporal patterns (if applicable)

Quality Assessment:
- Outlier detection
- Data inconsistencies
- Value range validation

Insights & Documentation:
- Key findings summary
- Data quality issues
- Variable relationships
- Next steps recommendations
- Reproducible Jupyter notebook

The user has provided the following information: