π§π· PortuguΓͺs (clique para expandir)
Nomes de Pastas e DescriΓ§Γ΅es (PT/EN):
dashboards/
β Dashboards interativos (Interactive dashboards)docs/
β DocumentaΓ§Γ£o e guias (Documentation and guides)error_reports/
β RelatΓ³rios de erros e liΓ§Γ΅es aprendidas (Error reports and lessons learned)ai_learning_guides/
β InstruΓ§Γ΅es para IA e aprendizado de mΓ‘quina (AI and ML learning guides)assets/
β Imagens, screenshots e arquivos de referΓͺncia (Images, screenshots, reference files)requirements.txt
β DependΓͺncias do projeto (Project dependencies)README.md
β DocumentaΓ§Γ£o principal (Main documentation)
Uma jornada completa do desenvolvimento de dashboards Plotly/Dash: desde visualizaΓ§Γ΅es simples atΓ© anΓ‘lises complexas com Machine Learning
Este repositΓ³rio documenta a evoluΓ§Γ£o completa de um projeto de dashboards interativos, comeΓ§ando com um aplicativo Dash problemΓ‘tico e culminando em trΓͺs versΓ΅es funcionais progressivamente mais sofisticadas:
- V1: Dashboard simples com grΓ‘fico Sunburst
- V2: Dashboard de construΓ§Γ£o com filtros avanΓ§ados
- V3: Dashboard complexo com ML, mapas e mΓΊltiplas visualizaΓ§Γ΅es
O projeto foi guiado por referΓͺncias visuais profissionais que definiram nossos padrΓ΅es de qualidade:
Sunburst HierΓ‘rquico | AnΓ‘lise CientΓfica | Dashboard Comercial |
---|---|---|
![]() |
![]() |
![]() |
Estrutura hierΓ‘rquica complexa | CorrelaΓ§Γ£o e heatmap | Vendas por categoria |
Porta: 8052 | Foco: Fundamentos
- β GrΓ‘fico Sunburst hierΓ‘rquico
- β Dados extraΓdos de HTML funcional
- β Interface limpa e responsiva
- β MΓ©tricas financeiras bΓ‘sicas
Porta: 8050 | Foco: Filtros & Interatividade
- β Filtros em cascata (Pillar β Area β Service)
- β Tooltips detalhados com variΓ’ncias
- β AnΓ‘lise de custos de construΓ§Γ£o
- β Interface profissional
Porta: 8053 | Foco: ML & AnΓ‘lise AvanΓ§ada
- β 4 VisualizaΓ§Γ΅es: Sunburst + Mapa + Scatter + ML
- β Machine Learning: AnΓ‘lise preditiva de economia de energia
- β Mapas GeogrΓ‘ficos: Coordenadas reais dos EUA
- β Design Moderno: Cards responsivos com styling avanΓ§ado
git clone https://github.com/Genovese-Felipe/Python-Data-Driven-Visualization-Journey.git
cd Python-Data-Driven-Visualization-Journey
pip install -r requirements.txt
# V1 - Sunburst Simples
python dashboards/v1_simple/sunburst_cost_explorer_funcional.py
# Acesse: http://localhost:8052
# V2 - ConstruΓ§Γ£o AvanΓ§ada
python dashboards/v2_construction/V2_script.py
# Acesse: http://localhost:8050
# V3 - Smart Home Complexo
python dashboards/v3_smart_home/Plan_V3_funcional.py
# Acesse: http://localhost:8053
Python-Data-Driven-Visualization-Journey/
βββ π dashboards/
β βββ π v1_simple/ # Dashboard bΓ‘sico com Sunburst
β βββ ποΈ v2_construction/ # Dashboard de construΓ§Γ£o com filtros
β βββ π‘ v3_smart_home/ # Dashboard complexo com ML
βββ π docs/ # DocumentaΓ§Γ£o e guias
βββ π΄ error_reports/ # RelatΓ³rios de erros e liΓ§Γ΅es aprendidas
βββ π€ ai_learning_guides/ # InstruΓ§Γ΅es para futuros modelos de IA
βββ π¨ assets/ # Arquivos de referΓͺncia e recursos
β βββ πΌοΈ reference_images/ # Imagens que inspiraram o projeto
β βββ πΈ screenshots/ # Capturas de tela da evoluΓ§Γ£o
β βββ π HTML files # Arquivos funcionais para extraΓ§Γ£o de dados
βββ π requirements.txt # DependΓͺncias do projeto
βββ π README.md # Este arquivo
Categoria | Tecnologia | VersΓ£o | Uso |
---|---|---|---|
Backend | Python | 3.12+ | Linguagem principal |
Web Framework | Dash | 2.x | AplicaΓ§Γ΅es web interativas |
VisualizaΓ§Γ£o | Plotly | 5.x | GrΓ‘ficos e visualizaΓ§Γ΅es |
Machine Learning | Scikit-Learn | 1.x | AnΓ‘lise preditiva |
Data Processing | Pandas | 2.x | ManipulaΓ§Γ£o de dados |
Scientific Computing | NumPy | 1.x | ComputaΓ§Γ£o numΓ©rica |
Baseamo-nos em referΓͺncias visuais profissionais para definir o padrΓ£o de qualidade:
Exemplo de Sunburst hierΓ‘rquico complexo usado como inspiraΓ§Γ£o
- App Dash com mΓΊltiplos erros de callback
- Estrutura hierΓ‘rquica mal construΓda
- Interface nΓ£o responsiva
- Status: β NΓ£o funcional
- AnΓ‘lise de arquivos HTML funcionais
- ExtraΓ§Γ£o de dados estruturados
- IdentificaΓ§Γ£o de padrΓ΅es funcionais
- Status: π Em desenvolvimento
- Dashboard simples e funcional
- Dados reais extraΓdos de HTML
- GrΓ‘fico Sunburst perfeitamente renderizado
- Status: β Funcional
- Sistema de filtros em cascata
- Tooltips informativos
- AnΓ‘lise de variΓ’ncias de custos
- Status: β Funcional
- 4 tipos de visualizaΓ§Γ£o integrados
- Machine Learning para anΓ‘lise preditiva
- Mapas geogrΓ‘ficos interativos
- Status: β Funcional
Screenshot dos trΓͺs dashboards rodando simultaneamente: V1 (Sunburst), V2 (Construction), V3 (Smart Home)
- AnΓ‘lise de cΓ³digo funcional existente
- ExtraΓ§Γ£o de dados estruturados de HTML
- Desenvolvimento incremental (V1 β V2 β V3)
- Foco na funcionalidade antes da complexidade
- Uso de referΓͺncias visuais profissionais
- DocumentaΓ§Γ£o visual completa da jornada
- Callbacks complexos demais
- Estruturas hierΓ‘rquicas mal planejadas
- Tentativa de corrigir cΓ³digo quebrado vs. recriar
- Falta de dados estruturados adequados
- Desenvolvimento sem referΓͺncias visuais claras
Todo o processo foi documentado visualmente:
- π¨ Jornada Visual Completa
- πΌοΈ Imagens de ReferΓͺncia
- πΈ Screenshots da EvoluΓ§Γ£o
Este projeto serve como:
- Template para dashboards Plotly/Dash
- Guia de boas prΓ‘ticas para visualizaΓ§Γ£o de dados
- Exemplo de evoluΓ§Γ£o de projeto de dados
- ReferΓͺncia de debugging para aplicaΓ§Γ΅es Dash
Este projeto estΓ‘ licenciado sob a MIT License.
Felipe Genovese
- GitHub: @Genovese-Felipe
- Projeto: Python Data Driven Visualization Journey
Para dΓΊvidas, problemas ou sugestΓ΅es:
- Consulte a documentaΓ§Γ£o
- Verifique os relatΓ³rios de erro
- Abra uma Issue
π Projeto ConcluΓdo com Sucesso! π
De um app quebrado para trΓͺs dashboards funcionais com ML
πΊπΈ English (click to expand)
Folder Names and Descriptions (EN/PT):
dashboards/
β Interactive dashboards (Dashboards interativos)docs/
β Documentation and guides (DocumentaΓ§Γ£o e guias)error_reports/
β Error reports and lessons learned (RelatΓ³rios de erros e liΓ§Γ΅es aprendidas)ai_learning_guides/
β AI and ML learning guides (InstruΓ§Γ΅es para IA e aprendizado de mΓ‘quina)assets/
β Images, screenshots, reference files (Imagens, screenshots, arquivos de referΓͺncia)requirements.txt
β Project dependencies (DependΓͺncias do projeto)README.md
β Main documentation (DocumentaΓ§Γ£o principal)
A complete journey in Plotly/Dash dashboard development: from simple visualizations to complex Machine Learning analytics
This repository documents the full evolution of an interactive dashboard project, starting from a problematic Dash app and culminating in three progressively more sophisticated functional versions:
- V1: Simple dashboard with Sunburst chart
- V2: Construction dashboard with advanced filters
- V3: Complex dashboard with ML, maps, and multiple visualizations
The project was guided by professional visual references that set our quality standards:
Hierarchical Sunburst | Scientific Analysis | Business Dashboard |
---|---|---|
![]() |
![]() |
![]() |
Complex hierarchical structure | Correlation and heatmap | Sales by category |
Port: 8052 | Focus: Fundamentals
- β Hierarchical Sunburst chart
- β Data extracted from functional HTML
- β Clean and responsive interface
- β Basic financial metrics
Port: 8050 | Focus: Filters & Interactivity
- β Cascading filters (Pillar β Area β Service)
- β Detailed tooltips with variances
- β Construction cost analysis
- β Professional interface
Port: 8053 | Focus: ML & Advanced Analytics
- β 4 Visualizations: Sunburst + Map + Scatter + ML
- β Machine Learning: Predictive energy savings analysis
- β Geographic Maps: Real US coordinates
- β Modern Design: Responsive cards with advanced styling
git clone https://github.com/Genovese-Felipe/Python-Data-Driven-Visualization-Journey.git
cd Python-Data-Driven-Visualization-Journey
pip install -r requirements.txt
# V1 - Simple Sunburst
python dashboards/v1_simple/sunburst_cost_explorer_funcional.py
# Access: http://localhost:8052
# V2 - Advanced Construction
python dashboards/v2_construction/V2_script.py
# Access: http://localhost:8050
# V3 - Complex Smart Home
python dashboards/v3_smart_home/Plan_V3_funcional.py
# Access: http://localhost:8053
Python-Data-Driven-Visualization-Journey/
βββ π dashboards/
β βββ π v1_simple/ # Basic Sunburst dashboard
β βββ ποΈ v2_construction/ # Construction dashboard with filters
β βββ π‘ v3_smart_home/ # Complex dashboard with ML
βββ π docs/ # Documentation and guides
βββ π΄ error_reports/ # Error reports and lessons learned
βββ π€ ai_learning_guides/ # Instructions for future AI models
βββ π¨ assets/ # Reference files and resources
β βββ πΌοΈ reference_images/ # Images that inspired the project
β βββ πΈ screenshots/ # Screenshots of the evolution
β βββ π HTML files # Functional files for data extraction
βββ π requirements.txt # Project dependencies
βββ π README.md # This file
Category | Technology | Version | Usage |
---|---|---|---|
Backend | Python | 3.12+ | Main language |
Web Framework | Dash | 2.x | Interactive web apps |
Visualization | Plotly | 5.x | Charts and visualizations |
Machine Learning | Scikit-Learn | 1.x | Predictive analytics |
Data Processing | Pandas | 2.x | Data manipulation |
Scientific Computing | NumPy | 1.x | Numeric computation |
We based our standards on professional visual references:
Example of a complex hierarchical Sunburst used as inspiration
- Dash app with multiple callback errors
- Poorly built hierarchical structure
- Non-responsive interface
- Status: β Not functional
- Analysis of functional HTML files
- Extraction of structured data
- Identification of functional patterns
- Status: π In development
- Simple and functional dashboard
- Real data extracted from HTML
- Perfectly rendered Sunburst chart
- Status: β Functional
- Cascading filter system
- Informative tooltips
- Cost variance analysis
- Status: β Functional
- 4 integrated visualization types
- Machine Learning for predictive analysis
- Interactive geographic maps
- Status: β Functional
Screenshot of the three dashboards running simultaneously: V1 (Sunburst), V2 (Construction), V3 (Smart Home)
- Analysis of existing functional code
- Extraction of structured data from HTML
- Incremental development (V1 β V2 β V3)
- Focus on functionality before complexity
- Use of professional visual references
- Complete visual documentation of the journey
- Overly complex callbacks
- Poorly planned hierarchical structures
- Trying to fix broken code vs. recreating
- Lack of adequate structured data
- Development without clear visual references
The entire process was visually documented:
- π¨ Full Visual Journey
- πΌοΈ Reference Images
- πΈ Evolution Screenshots
This project serves as:
- Template for Plotly/Dash dashboards
- Best practices guide for data visualization
- Example of project evolution in data projects
- Debugging reference for Dash applications
This project is licensed under the MIT License.
Felipe Genovese
- GitHub: @Genovese-Felipe
- Project: Python Data Driven Visualization Journey
For questions, issues, or suggestions:
- Check the documentation
- See the error reports
- Open an Issue
π Project Successfully Completed! π
From a broken app to three functional dashboards with ML