1. Define the query explicitly | 2. Retrieve the project table | 3. Choose project identifiers | 4. Retrieve related records | 5. Join project attributes to related records | 6. Preserve provenance

1. Discover available resources | 2. Inspect filters before querying | 3. Retrieve a small first page | 4. Inspect pagination metadata | 5. Retrieve related resources | 6. Record the source update timestamp | Portuguese aliases | Client configuration | Next steps

Retrieve one page first | Collect a controlled number of pages | Understand nested relationships | Normalize one nested relationship | Work across collected pages | Save data with retrieval context

The convenience layer: tnt_index_df() | Searching | Filtering | Highlighting and ordering | Counting | The explicit layer: schemas and persistence | Incremental updates and deletes | Reopening an index | Where to go next

1. Convert and chunk | 2. Attach embeddings | 3. Retrieve | 4. Persist | Scaling to many documents

The Python backend | OCR | Table structure: accurate vs. fast | Hardware acceleration | Images and figures | Batch conversion | A pragmatic recipe

The basics | Accurate vs. fast table structure | Working with the extracted tables | Tips

Overview | One-time setup | Converting a document | Exporting structure | Tables as tibbles | Figures | Chunking for retrieval | From chunks to embeddings | Where to go next

Travel-time service areas from a facility | Nearest facility for each origin | On real data | References

Tag filters | From a bounding box | A tidy result | Combining features with a network | References

A single diagram | Comparing network form | Your own places | References

What is osmnxr? | A real network | Network statistics | Routing | Where to next

sf | sfnetworks and tidygraph | dodgr | GeoJSON and MapLibre | GraphML round-trip

Shortest path by distance | Travel time instead of distance | Route alternatives | Isochrones (service areas) | Many-to-many distances | References

A real first network | Comparing cities | On your own city | References

Basic statistics | Circuity | Centrality: finding chokepoints | References

1. Crawl and collect text | 2. Chunk | 3. Embed | 4. Export for retrieval | End to end

The model | Your first crawler | Following links | Controlling scope | Routing different page types | Crawling from a sitemap | Rendering JavaScript pages | Where next

The mental model | A minimal crawl | The handler context | Controlling link discovery | Reproducibility

Being a good web citizen | Going faster | Fixed-concurrency batches — cr_parallel() | Adaptive batches — cr_autoscale() | Continuous streaming pool — cr_stream() | Choosing an engine | Combining with persistence

The dataset | The key-value store | The request queue and reproducibility | One-call setup: cr_persist() | Resuming

What is specific about Big Data PE | Defining the profile | Storing a token and fetching | Note on language

Overview | Saving as SVG | Converting to PNG | Standard conversion (rsvg) | Chrome-based conversion (recommended for fonts) | Installing Chrome support | Background options | PNG with margin | Converting to PDF | Chrome-based conversion | Multiple formats | Batch processing | Displaying in R Markdown / Quarto | Choosing the rendering engine | Inline SVG display | PNG display (better compatibility) | Save for knitr | Custom knitr engine | Integration with grid/ggplot2 | Quality settings | DPI recommendations | DPI and Chrome scaling | File size considerations | Comparing engines | Error handling | Troubleshooting | Fonts not rendering correctly with rsvg | Chrome not found | Slow Chrome conversion | Timeout errors

A single diagram | Comparing network form | Your own places | References

Travel-time service areas from a facility | Nearest facility for each origin | On real data | References

Tag filters | From a bounding box | A tidy result | Combining features with a network | References

What is osmnxr? | A real network | Network statistics | Routing | Where to next

sf | sfnetworks and tidygraph | dodgr | GeoJSON and MapLibre | GraphML round-trip

Shortest path by distance | Travel time instead of distance | Route alternatives | Isochrones (service areas) | Many-to-many distances | References

A real first network | Comparing cities | On your own city | References

Basic statistics | Circuity | Centrality: finding chokepoints | References

The convenience layer: tnt_index_df() | Searching | Filtering | Highlighting and ordering | Counting | The explicit layer: schemas and persistence | Incremental updates and deletes | Reopening an index | Where to go next

A first CVRP | Stopping criteria | Time windows (VRPTW) | Heterogeneous fleet | Multiple depots (MDVRP) | Prize-collecting | Reading standard instances | Other variants

1. Convert and chunk | 2. Attach embeddings | 3. Retrieve | 4. Persist | Scaling to many documents

The Python backend | OCR | Table structure: accurate vs. fast | Hardware acceleration | Images and figures | Batch conversion | A pragmatic recipe

The basics | Accurate vs. fast table structure | Working with the extracted tables | Tips

Overview | One-time setup | Converting a document | Exporting structure | Tables as tibbles | Figures | Chunking for retrieval | From chunks to embeddings | Where to go next

1. Crawl and collect text | 2. Chunk | 3. Embed | 4. Export for retrieval | End to end

Being a good web citizen | Going faster | Fixed-concurrency batches — cr_parallel() | Adaptive batches — cr_autoscale() | Continuous streaming pool — cr_stream() | Choosing an engine | Combining with persistence

The dataset | The key-value store | The request queue and reproducibility | One-call setup: cr_persist() | Resuming

The model | Your first crawler | Following links | Controlling scope | Routing different page types | Crawling from a sitemap | Rendering JavaScript pages | Where next

The mental model | A minimal crawl | The handler context | Controlling link discovery | Reproducibility

What is specific about Big Data PE | Defining the profile | Storing a token and fetching | Note on language

Overview | Installation | Quick examples | Caching | Bilingual interface | Debugging with verbose | Controlling page size | Column names | API Reference | SICONFI — Fiscal Reports | CUSTOS — Federal Government Costs | SADIPEM — Public Debt | Transferências Constitucionais | SIORG — Organizational Structure | SIOPE — Education Spending | Common features (all APIs)

The problem: RREO labels drift across years | The bundled layout reference | Step 1 — Normalize column labels | Step 2 — Tidy by topic | Multi-regime in one call | Adding new topics | See also

About | Available functions | Parameter mapping | Examples | Entity lookup | RREO – Budget Execution | RGF – Fiscal Management | DCA – Annual Accounts | MSC – Accounting Balances Matrix

About | Available functions | Required parameters | Period mapping | Performance tip: use filter to reduce downloads | Filtering by entity type (tipo / type) | Filtering by municipality | OData filter syntax | Selecting specific columns | Sorting results | Compensation data with filters | Examples | Quick test with max_rows | Combining states | How the OData URL works

Configuração | Consultar um processo | Consultar vários processos | Documentos e publicações | Listagens | Tratamento de erros | Operações de escrita

Visão geral do fluxo | Dados a enviar no pedido | 1. Sigla do sistema (SiglaSistema) | 2. IPs de saída (liberação de firewall) | 3. Tipos de operação (métodos) | A IdentificacaoServico (chave de acesso) | Endpoints (treinamento e produção) | Configurando o rsei com o que foi liberado | Boas práticas de privacidade e segurança (LGPD)

Visão geral do fluxo | Dados a enviar no pedido | 1. Sigla do sistema (SiglaSistema) | 2. IPs de saída (liberação de firewall) | 3. Tipos de operação (métodos) | A IdentificacaoServico (chave de acesso) | Endpoints (treinamento e produção) | Configurando o rsei com o que foi liberado | Boas práticas de privacidade e segurança (LGPD)

Configuração | Consultar um processo | Consultar vários processos | Documentos e publicações | Listagens | Tratamento de erros | Operações de escrita

Overview | Number Formatting | Abbreviated Numbers | Date/Time Formatting | Relative Time | Custom JS Renderers | HTML Templates | Orthogonal Rendering | Named Renderers (Reuse Across Tables)

Overview | Responsive Tables | Styling | Inline overrides | Theme presets | Reusable themes | CSS class override | Table Layout | Layout positions | Default layout | Rearranging elements | Removing elements | Multiple elements in one position | Search box placeholder | Buttons (Export / Copy / Print) | Quick setup | Using the helper | Buttons + search together | Grouped buttons with dropdown | Separated button groups with spacer | Bottom buttons | Button styling | Pagination styling | Quick reference | Infinite Scrolling (Scroller) | Column Formatting | Abbreviated numbers (k/M/B) | DataTables Options | Saving as HTML | Keeping Libraries Up to Date | Complete Example: Custom Renderers, Flags, and ColumnControl | Next Steps

How to use this reference | Example: inspect and query Contratos

Discover endpoints with tce_catalog() | Inspect one endpoint | Input parameters | Output fields | Query using snake_case arguments | Parameter validation | Working with cache

Overview | Installation | Load the package | Explore endpoints before querying | List endpoints | Inspect input parameters | Inspect output fields | Quick queries | Municipalities | Contracts | Suppliers | Verbose mode (recommended while exploring) | Keeping original output field names | Handling the 100,000-record limit | Direct access to any endpoint | Cache

1. Look up the state code | 2. Build the query parameters | 3. Fetch exports and imports | 4. Cast metrics and add a date column | 5. Monthly trade balance | 6. Top municipalities by flow | 7. Top products (HS4) | 8. Top trading partners (countries) | 9. Cross-cuts (country × product, city × product) | 10. Year-over-year comparison | 11. Adapt to any state

Countries and economic blocs | Countries | Economic blocs | Geographic tables | States (UF) | Cities | Transport modes | Customs units (URF) | Product nomenclatures | NCM — Mercosur Common Nomenclature (1997–present) | NBM — Brazilian Nomenclature of Goods (historical, 1989–1996) | HS — Harmonized System | Classification tables | CGCE — Classification by Broad Economic Categories (BEC) | SITC — Standard International Trade Classification (CUCI) | ISIC — International Standard Industrial Classification | Using table codes in queries | Pagination | Runtime discovery

What the city endpoint exposes | 1. Headline totals (FOB and net weight) | 2. Top trading partners | 3. Top economic blocs | 4. Top products (HS4 / heading) | 5. Monthly time series | 6. Year-over-year comparison | 7. Cross-cutting query: top destinations by product | Looking up the city code from a name | Tips

Overview | Installation | Quick start | 1. Check what data is available | 2. Run a simple export query | 3. Add filters and multiple details | 4. Look up auxiliary tables | Available detail names | Language support | Next steps

Basic queries | Exports by country | Imports with CIF value | Monthly breakdown | Multiple grouping fields | Applying filters | The generic comex_query() | City-level queries | Historical data (1989–1996) | Working with results | Tips and best practices

Introdução | Pacotes | 1. Obtendo os dados | 2. Categorização das transferências | 3. Preparação dos dados geográficos | 4. Paleta e tema | 5. Composição e séries históricas | 5.1 Composição anual por categoria | 5.2 Séries mensais das principais categorias | 5.3 Top 10 municípios por volume absoluto | 6. Análise per capita | 6.1 Top 10 e Bottom 10 per capita | 6.2 Evolução per capita ao longo do tempo | 6.3 Mapas: absoluto vs per capita | 6.4 Mapa de referência: Regiões de Desenvolvimento | 7. Análise por Região de Desenvolvimento | 7.1 Série temporal por RD | 7.2 Composição por categoria dentro de cada RD | 7.3 Per capita por RD | 7.4 Evolução per capita por RD | 7.5 Mapa per capita por RD | 8. Mapas por categoria de transferência | Considerações finais | Próximos passos | Referências

About | Performance warning | Available functions | Parameter mapping | Examples | Response columns

How caching works | Configuring the cache directory | Inspecting the cache | Forcing a re-download | Pruning and clearing the cache

TL;DR — when to use what | Feature comparison | Reading DBC files | API ergonomics | Caching and parallelism | Variable labelling | Composing the packages | Summary

Overview | 1. Basic String Distances | Levenshtein Distance | Comparing Multiple Metrics | 2. Fuzzy Matching with Fuzz Ratios | New in v1.1.0: Partial Token Ratios | 3. Matching Against a List of Choices | Using US State Names | Extract Top-N Matches | Extract All Matches Above a Threshold | 4. Choosing the Right Scorer | 5. String Preprocessing | 6. Edit Operations | 7. Prefix and Postfix Matching | 8. Practical Example: Record Linkage | 9. Performance Comparison with Base R | Summary

Introduction | Running Pikchr Scripts | Viewing Pikchr Script Source Code For This Document | About Pikchr Scripts | Pikchr Statements | Layout | Controlling Layout Using Attributes | The Advantage Of Relative Layout | Single-Pass Design | Labeling Objects | Layout Of Block Objects | Automatic Layout Of Block Objects | Adjusting The Size Of Block Objects | Default Sizes | Setting Sizes Using Attributes | Automatic Sizing To Fit Text Annotations | Attributes For Stroke Width And Drawing Colors | Filled Polygons | Text Annotations | Text Attributes | Position Text Above Or Below The Center Of The Object | Justify Text Left Or Right | Text Attribute "center" | Bold And Italic Font Styles | Monospace Font Family | Aligned Text | Adjusting The Font Size | Text Is Positioned Around The Center Of The Object | Containers | Object Stacking Order | Summary And Conclusion

Introduction | Setup | 1. Storing the access token | 2. Fetching data | Basic query | Using query parameters | 3. Fetching data in chunks | 4. Exploring the data | Distribution by sex | Notifications by year | Most frequent symptoms | Distribution by neighbourhood (top 10) | Hospitalisations | 5. Managing tokens | Retrieve a stored token | Remove a token | Data dictionary (key variables) | References

Source catalog overview | Hospital information (SIH) | Outpatient information (SIA) | Mortality (SIM) | Live births (SINASC) | Health facilities (CNES) | Hospital and outpatient reporting (CIHA / CIH) | Notifiable diseases (SINAN) | Other disease surveillance | Oncology panel | Schistosomiasis control (PCE) | Discontinued and replaced systems | Territorial reference tables | Documentation and data dictionaries | Connectivity check | Cleaning up

The fastest way: datasus_fetch() | Reading a local DBC file | Selecting columns | Controlling column types | Exploring available data | Step-by-step workflow | Territorial data (municipalities, regions) | Finding documentation and data dictionaries | Next steps

Column selection | Type inference | Explicit types | Date parsing | Benchmarking example | Memory

About | Available functions | Typical workflow | PVL processing status | Parameter mapping | get_pvl() / get_debt_requests() | Detail functions

Overview | Looking up organization codes | Step 1: List top-level organizations (N1) | Step 2: Browse sub-units (N2, N3) | Step 3: Use in CUSTOS queries | Step 4: Get details of a single unit | Functions | Parameter mapping | get_siorg_orgaos() / get_siorg_organizations() | get_siorg_estrutura() / get_siorg_structure() | SIORG codes in CUSTOS | Response columns

About | Available functions | Examples | Step 1: Lookup codes | State-level transfers | Municipality-level transfers | Parameter mapping

Colors | Background color | Gradient backgrounds | Text colors | Fonts | Font sizes | Dimensions | Card width | Padding and corners | Custom footer | Custom logos | Complete example | Displaying in documents

What is cardargus? | Installation | Creating your first card | Displaying cards in R Markdown / Quarto | Saving cards | As SVG | As PNG | Chrome rendering (recommended) | Using bundled logos | Custom cards | Next steps

How Extensions Work | Listing Available Extensions | Buttons (Export / Copy / Print) | Grouped Buttons with Labels | Select (Row Selection) | Responsive | ColumnControl | FixedHeader | Combining Extensions | Adding New Plugins | Updating Library Versions

Basic Usage | Reading Table State | Proxy: Server-Side Manipulation | Buttons with Custom Style | Infinite Scrolling (Scroller) | Custom Layout | Pagination Types | Inline Inputs (Checkboxes and Buttons) | Server-Side Processing | Dataset Switcher with bslib | Shared Theme Across Tables | Complete Example: Custom Renderers, Flags, and ColumnControl

The 1:1 Mapping Principle | Translation Rules | Example: JS to R | Layout — The Complete Guide | Position grid | Available elements | Default layout | Rearranging | Removing elements | Multiple elements in one position | Full-width rows | Buttons in layout | Customized search box | Complete custom layout | Migrating from dom | Using htmlwidgets::JS() for Callbacks | Common Callbacks | Column Renderers | Built-in DataTables Renderers | Custom Render Function | Internationalization (i18n) | Inline language object | CDN language URL | Debugging

Introduction | Core concepts | Aggregates | Variables | Classifications and categories | Geographic levels and localities | Periods and periodicities | Request limits | View modes | How ibger maps to the API | Further reading

Overview | Installation | A typical workflow | Step 1 — Find an aggregate | Step 2 — Inspect the metadata | Step 3 — Retrieve data | Specifying localities | Specifying periods | Filtering with classifications | Automatic validation | Browsing the survey catalog | API limits and special values

Introduction | Step 1 — Explore the aggregate | Step 2 — Monthly IPCA for Brazil | Plot the monthly variation | Step 3 — Compare accumulation measures | Step 4 — Breakdown by product group | Step 5 — Metropolitan area comparison | Step 6 — Building a complete dataset | Tips for large queries | Handling special values

Overview | Setup | Helper: convert period codes to dates | 1) IPCA (7060) — Health insurance | 1.1 Discovering the right IDs | 1.2 Fetching the data | 1.3 Wide format for inspection | 1.4 Plot | 2) IPCA (7060) — Vehicle insurance | 3) PMS (8693) — Transportation and postal services | 4) PNAD Contínua (5434) — Accommodation and food services | 5) PMS (8693) — Professional and administrative services | 6) PNAD Contínua (5434) — Domestic services | 7) PIM-PF (8888) — Industrial production (selected CNAE sectors) | 8) Construction (8886) — Typical construction inputs | 9) PMC (8884 / 8757 / 8880) — Retail trade indices | 9.1 Vehicles, motorcycles, parts and accessories (8884) | 9.2 Construction materials (8757) | 9.3 Retail trade (8880) | Next steps

Overview | Quick Setup | Check Availability | Register Google Fonts | Install Fonts Locally | Using Custom Fonts | CSS for SVG | Font Cache | Access Package Resources | Troubleshooting | Font not rendering correctly | PNG export with rsvg | PNG export with Chrome (recommended) | Fonts on servers | Recommended Fonts | Dependencies

Built-in Icons | Using icons in fields | Customizing icons | Bundled Logos | Using logos in cards | Loading external SVGs | Creating logo rows | Custom SVG logos | Summary: How to use icons and logos

Overview | Creating a single badge | Badge colors | Automatic text color | Badge rows | Badges in cards | Uniform badge height | Customizing badge appearance | Saving badges | Badge in R Markdown

Setup | Example 1: PIX Keys Market Share | Example 2: Key Type Distribution | Example 3: Regional Transaction Analysis | Example 4: State-Level Analysis | Example 5: Transaction Nature Analysis | Example 6: Filtering Transactions by State | Example 7: Comparing Regions with Filters | Example 8: P2P vs P2B Analysis | Example 9: Multiple Months Analysis | Example 10: Initiation Method Analysis | Example 11: Creating a Summary Report | Example 12: Exporting Data | Tips for Large-Scale Analysis | See Also

Overview | Installation | Getting Started | API Endpoints | Quick Examples | Retrieve PIX Keys Data | Retrieve Transaction Data by Municipality | Retrieve Transaction Statistics | Retrieve Fraud Statistics | OData Filter and OrderBy | Common Filter Examples | Working with the Data | Configuration | Timeout | Verbose Output | Debugging | Next Steps | References

What is PIX? | The PIX Ecosystem | System Components | PIX Key Types | Data Available Through pixr | 1. PIX Keys Stock (ChavesPix) | Column Descriptions | 2. Transactions by Municipality (TransacoesPixPorMunicipio) | 3. Transaction Statistics (EstatisticasTransacoesPix) | Transaction Nature Codes | Initiation Methods | 4. Fraud Statistics (EstatisticasFraudesPix) | API Parameters Summary | OData Filter Examples | Data Quality Notes | Coverage | Exclusions | Geographic Data | Working with Dates | Currency Formatting | Understanding Participant Identifiers | See Also | References

Introduction to OData | API Endpoints and Parameters | Filtering with $filter | Basic Filter Syntax | Comparison Operators | Logical Operators | String Functions | Ordering with $orderby | Basic Ordering | Combining Filter and OrderBy | Selecting Columns with $select | Pagination with $top and $skip | Iterating Through All Data | Custom Queries with pix_query() | Building and Debugging URLs | Practical Examples | Top 10 States by Transaction Volume | P2P vs P2B Transactions by Region | Market Share by Key Type | Performance Tips | Filter Reference by Endpoint | ChavesPix (PIX Keys) | TransacoesPixPorMunicipio (Transactions by Municipality) | EstatisticasTransacoesPix (Transaction Statistics) | See Also | References

Functions | 1. Creating a WebDAV Request | 2. Copying Files | 3. Creating a Directory | 4. Deleting a File or Directory | 5. Listing Files in a Directory | 6. Uploading a File | 7. Download a file | Conclusion

Example 1 | Example 2 | Example 3 | Example 4 | Example 5 | Example 6 | Example 7 | Example 8 | Example 9 | Example 10 | Example 11 | Example 12 | Example 13 | Example 14 | Example 15 | Example 16 | Example 17 | Example 18

Step 1: Setting Up Environment Variables | macOS and Linux Folks: You’re Basically Already There | Windows Users: You've Got This Too! | Pro Tip: Use .Renviron for Project-Specific Vars | Step 2: Accessing Environment Variables in Your Code | Step 3: Don’t Forget .gitignore