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# Wheat Price Data Visualization Project
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This project demonstrates how to create sophisticated, interactive data visualizations for wheat price analysis using AI-assisted development. Without writing code manually, I used Claude 3.7 Sonnet to generate a complete visualization suite that includes heatmaps, parallel coordinates plots, and an executive summary dashboard. The visualizations feature responsive design, interactive filtering, dark/light themes, and contextual information about global events affecting wheat markets.
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A fenti gabonás vizuaizációkat teljességgel kódolás nélkül készítettem (bár kellet hozzá egy pár próbálkozás.. :sweat_smile:)
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Itt megtaláljátok az összes promptot amit használtam (`clause-sonnet-3.7`):
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# [Prompt 1](https://github.com/denesdata/denesdata.github.io/blob/main/ADV%202025/5/prompts%201.md) - Wheat Price Data Visualization Development Journey
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This conversation documents the iterative development of interactive visualizations for wheat price data. The process began with a simple Vega-Lite specification for line charts and evolved into multiple sophisticated visualizations including:
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1. **Line charts** showing price trends over time for different wheat types
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2. **Interactive dashboard** with multiple chart types (bar charts, box plots, heatmaps)
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3. **Violin plot** showing price distributions by wheat type
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4. **D3.js carpet plot** with:
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- Color-coded price visualization
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- Year separators
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- Global event markers
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- Multiselect filtering options
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- Enhanced tooltips
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- Wheat/grain themed styling
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Throughout the development, several improvements were made:
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- Adding company logos to visualizations
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- Fixing technical issues (like Chart.js width calculation errors)
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- Switching from Chart.js to D3.js for better control
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- Enhancing user experience with better tooltips and filters
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- Adding contextual information about global events affecting wheat prices
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- Implementing a grain-themed design with gradients and icons
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The final product is a comprehensive, interactive data exploration tool that allows users to analyze wheat price trends across different types, countries, and time periods while providing context through global events that impacted the market.
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### Screenshot 1
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![Screenshot 1](https://raw.githubusercontent.com/denesdata/denesdata.github.io/refs/heads/main/ADV%202025/5/Screenshot%201.png)
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# [Prompt 2](https://github.com/denesdata/denesdata.github.io/blob/main/ADV%202025/5/prompts%202.md) - Adding a second plot, interactions and styling
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Key developments:
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1. **Initial Restructuring**
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- Breaking a monolithic file into smaller functional components
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- Organizing code into a subfolder structure
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- Implementing proper separation of concerns (HTML, CSS, JS)
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2. **Visual Enhancements**
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- Adding gradients and wheat-themed styling
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- Incorporating FontAwesome icons
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- Fixing tooltip positioning issues
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- Removing drop shadows from logos
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3. **Adding Parallel Coordinates Plot**
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- Creating a second visualization type below the heatmap
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- Implementing interactive brushing and filtering
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- Fixing issues with categorical axes and year labels
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- Changing coloring from price-based to country-based
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4. **Style Refinements**
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- Aligning legends consistently
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- Using pastel colors inspired by Information is Beautiful and Airbnb ViSX
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- Implementing modern typography with the Inter font family
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- Reducing spline curvature to prevent data distortion
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5. **Theme Implementation**
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- Creating a dark theme with pink and green color scheme
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- Adding a theme toggle with sun/moon icons
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- Implementing persistent theme preferences
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- Adding top-left to bottom-right gradients on containers
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The final product is a sophisticated data visualization tool that combines a heatmap/carpet plot with a parallel coordinates plot, allowing users to explore wheat price data through multiple perspectives while enjoying a visually pleasing, professionally designed interface with both light and dark themes.
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### Screenshot 2
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![Screenshot 2](Screenshot%202.png)
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# [Prompt 3](https://github.com/denesdata/denesdata.github.io/blob/main/ADV%202025/5/prompts%202.md) - Final touches and Executive Summary
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Key developments:
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1. **Standardizing Chart Formatting**
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- Aligning titles, margins, and legends across both visualizations
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- Creating consistent container styling and spacing
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- Implementing uniform header and legend designs
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2. **Code Cleanup**
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- Eliminating duplicate function declarations
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- Standardizing function styles
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- Resolving global variable conflicts
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- Centralizing tooltip content generation
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3. **Event Visualization Improvements**
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- Fixing event dot tooltips and label alignments
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- Resolving issues with event markers moving on hover
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- Implementing consistent tooltip behavior
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4. **Navigation Enhancements**
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- Adding a navigation bar to the main page
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- Implementing smooth scrolling between sections
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- Adding appropriate spacing when scrolling to sections
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5. **Parallel Coordinates Refinements**
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- Implementing default price range highlighting (450-550)
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- Fixing cross-filtering functionality across multiple axes
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The final product features a cohesive design with consistent styling across all elements, proper cross-filtering functionality, and smooth navigation between different sections of the visualization.
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### Screenshot 3
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![Screenshot 3](Screenshot%203.gif)
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