- 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.

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

- Optimize indexes to improve query execution speed.
- Avoid N+1 queries and suggest more efficient alternatives.
- Recommend normalization or denormalization strategies based on use cases.
- Implement transaction management where necessary to ensure data consistency.
- Suggest methods for monitoring database performance.

- Follow NestJS's modular architecture to ensure scalability and
maintainability.
- Use DTOs (Data Transfer Objects) to validate and type API requests.
- Implement Dependency Injection for better service management.
- Use the Repository pattern to separate data access logic from the rest of the application.
- Ensure that all REST APIs are well-documented with Swagger.
- Implement caching strategies to reduce database load.
- Suggest optimizations to improve PostgreSQL query performance.

## Core Principles:
  - Optimize for Hydrogens **streaming and caching** model to enhance performance.
  - Use **Shopifys Storefront API** effectively, following best practices for queries and mutations.
  - Ensure all components are **server-first** but leverage **client-side hydration** where needed.
  - Use **Tailwind CSS** efficiently with Hydrogens best practices for styling.
  - Prioritize **authentication and session handling** for Shopify customers.

## Routing & Layout in Remix
  - Use `loader` functions for **server-side data fetching**.
  - Prefer **nested routes** for modular page structures.
  - Use `useLoaderData()` instead of client-side fetching where possible.
  - Optimize Remixs **deferred loading** to improve perceived performance.

## Shopify Storefront API Usage
  - Always fetch data using **GraphQL queries** in `loader` functions.
  - Minimize API requests by batching queries efficiently.
  - Cache queries where appropriate to **reduce unnecessary API calls**.
  - Avoid over-fetching request **only the necessary fields**.
  - Use Shopifys **recommended pagination techniques** (`cursor`-based pagination).

## Hydrogen & Performance Optimizations
  - Utilize **Hydrogens streaming API** to improve time-to-first-byte (TTFB).
  - Use `CacheNone()` or `CacheLong()` selectively to control caching behavior.
  - Edge caching Ensure frequently accessed data is cached at the CDN level.
  - Prefer `useShopQuery()` over manual API calls for **consistent data fetching**.
  - Offload **expensive computations to server-side** where possible.

## Styling & Tailwind CSS
  - Use **Hydrogens built-in Tailwind setup** for consistency.
  - Avoid excessive utility classes by leveraging **Tailwinds theme and variants**.
  - Structure styles efficiently to **minimize CSS bloat**.
  - Use **Tailwinds responsive utilities** to ensure a mobile-first approach.

## Authentication & Session Handling
  - Implement Shopifys **customer authentication** using `customerAccessToken`.
  - Store authentication tokens securely in **server-side sessions**.
  - Use Remix loaders and actions to **handle login and logout server-side**.
  - Ensure **session expiry is handled gracefully** to prevent errors.
  - Implement **SSR-friendly authentication checks** to avoid hydration mismatches.

## Deployment on Shopify Oxygen
  - Follow **Shopifys guidelines for edge deployment**.
  - Ensure **Remix server handlers** are optimized for Oxygen.
  - Use `@shopify/hydrogen` utilities for **seamless integration with Shopify's infrastructure**.
  - Test deployments using Shopifys **Oxygen preview environment** before production.

## Component & Code Best Practices
  - Prefer **server components** whenever possible to reduce client-side JavaScript.
  - Use **lazy loading** (`React.lazy()`, `Suspense`) for non-critical UI components.
  - Keep components **small, modular, and reusable**.
  - Avoid excessive **client-side state management**; leverage Remix loaders instead.
  - Use **React Error Boundaries** for graceful error handling.

## Key Conventions:
  - Always **fetch data in loaders**; minimize client-side API calls.
  - Structure routes **to take full advantage of Remixs nested routing**.
  - Use **server caching strategies** to reduce redundant Storefront API calls.
  - Optimize **Hydrogens streaming features** for a fast user experience.
  - Follow **Shopifys best practices for deployment on Oxygen**.

Refer to Shopifys Hydrogen and Remix documentation for additional best practices.

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

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

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 new Next.js page based on the following description.

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:

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