add instructions for R programming language (#346)

* add instructions for R programming language

* copilot review updates

* applyTo syntax update

* copilot nitpicks

README.instructions.md

@@ -97,6 +97,7 @@ Team and project-specific instructions to enhance GitHub Copilot's behavior for
 | [Python MCP Server Development](instructions/python-mcp-server.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fpython-mcp-server.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fpython-mcp-server.instructions.md) | Instructions for building Model Context Protocol (MCP) servers using the Python SDK |
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+| [R Programming Language Instructions](instructions/r.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fr.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fr.instructions.md) | R language and document formats (R, Rmd, Quarto): coding standards and Copilot guidance for idiomatic, safe, and consistent code generation. |
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 | [Ruby on Rails](instructions/ruby-on-rails.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fruby-on-rails.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fruby-on-rails.instructions.md) | Ruby on Rails coding conventions and guidelines |

instructions/r.instructions.md

@@ -0,0 +1,116 @@
+---
+description: 'R language and document formats (R, Rmd, Quarto): coding standards and Copilot guidance for idiomatic, safe, and consistent code generation.'
+applyTo: '**/*.R, **/*.r, **/*.Rmd, **/*.rmd, **/*.qmd'
+---
+
+# R Programming Language Instructions
+
+## Purpose
+
+Help GitHub Copilot generate idiomatic, safe, and maintainable R code across projects.
+
+## Core Conventions
+
+- **Match the project’s style.** If the file shows a preference (tidyverse vs. base R, `%>%` vs. `|>`), follow it.
+- **Prefer clear, vectorized code.** Keep functions small and avoid hidden side effects.
+- **Qualify non-base functions in examples/snippets**, e.g., `dplyr::mutate()`, `stringr::str_detect()`. In project code, using `library()` is acceptable when that’s the repo norm.
+- **Naming:** `lower_snake_case` for objects/files; avoid dots in names.
+- **Side effects:** Never call `setwd()`; prefer project-relative paths (e.g., `here::here()`).
+- **Reproducibility:** Set seeds locally around stochastic operations using `withr::with_seed()`.
+- **Validation:** Validate and constrain user inputs; use typed checks and allowlists where possible.
+- **Safety:** Avoid `eval(parse())`, unvalidated shell calls, and unparameterized SQL.
+
+### Pipe Operators
+
+- **Native pipe `|>` (R ≥ 4.1.0):** Prefer in R ≥ 4.1 (no extra dependency).
+- **Magrittr pipe `%>%`:** Continue using in projects already committed to magrittr or when you need features like `.`, `%T>%`, or `%$%`.
+- **Be consistent:** Don't mix `|>` and `%>%` within the same script unless there's a clear technical reason.
+
+## Performance Considerations
+
+- **Large datasets:** consider `data.table`; benchmark with your workload.
+- **dplyr compatibility:** Use `dtplyr` to write dplyr syntax that translates to data.table operations automatically for performance gains.
+- **Profiling:** Use `profvis::profvis()` to identify performance bottlenecks in your code. Profile before optimizing.
+- **Caching:** Use `memoise::memoise()` to cache expensive function results. Particularly useful for repeated API calls or complex computations.
+- **Vectorization:** Prefer vectorized operations over loops. Use `purrr::map_*()` family or `apply()` family for remaining iteration needs.
+
+## Tooling & Quality
+
+- **Formatting:** `styler` (tidyverse style), two-space indents, ~100-char lines.
+- **Linting:** `lintr` configured via `.lintr`.
+- **Pre-commit:** consider `precommit` hooks to lint/format automatically.
+- **Docs:** roxygen2 for exported functions (`@param`, `@return`, `@examples`).
+- **Tests:** prefer small, pure, composable functions that are easy to unit test.
+- **Dependencies:** manage with `renv`; snapshot after adding packages.
+- **Paths:** prefer `fs` and `here` for portability.
+
+## Data Wrangling & I/O
+
+- **Data frames:** prefer tibbles in tidyverse-heavy files; otherwise base `data.frame()` is fine.
+- **Iteration:** use `purrr` in tidyverse code. In base-style code, prefer type-stable, vectorized patterns such as `vapply()`
+   (for atomic outputs) or `Map()` (for elementwise operations) instead of explicit `for` loops when they improve clarity or performance.
+- **Strings & Dates:** use `stringr`/`lubridate` where already present; otherwise use clear base helpers (e.g., `nchar()`, `substr()`, `as.Date()` with explicit format).
+- **I/O:** prefer explicit, typed readers (e.g., `readr::read_csv()`); make parsing assumptions explicit.
+
+## Plotting
+
+- Prefer `ggplot2` for publication-quality plots. Keep layers readable and label axes and units.
+
+## Error Handling
+
+- In tidyverse contexts, use `rlang::abort()` / `rlang::warn()` for structured conditions; in base-only code, use `stop()` / `warning()`.
+- For recoverable operations:
+- Use `purrr::possibly()` when you want a typed fallback value of the same type (simpler).
+- Use `purrr::safely()` when you need to capture both results and errors for later inspection or logging.
+- Use `tryCatch()` in base R for fine-grained control or compatibility with non-tidyverse code.
+- Prefer consistent return structures—typed outputs for normal flows, structured lists only when error details are required.
+
+## Security Best Practices
+
+- **Command execution:** Prefer `processx::run()` or `sys::exec_wait()` over `system()`; validate and sanitize all arguments.
+- **Database queries:** Use parameterized `DBI` queries to prevent SQL injection.
+- **File paths:** Normalize and sanitize user-provided paths (e.g., `fs::path_sanitize()`), and validate against allowlists.
+- **Credentials:** Never hardcode secrets. Use env vars (`Sys.getenv()`), config outside VCS, or `keyring`.
+
+## Shiny
+
+- Modularize UI and server logic for non-trivial apps. Use `eventReactive()` / `observeEvent()` for explicit dependencies.
+- Validate inputs with `req()` and clear, user-friendly messages.
+- Use connection pooling (`pool`) for databases; avoid long-lived global objects.
+- Isolate expensive computations and prefer `reactiveVal()` / `reactiveValues()` for small state.
+
+## R Markdown / Quarto
+
+- Keep chunks focused; prefer explicit chunk options (`echo`, `message`, `warning`).
+- Avoid global state; prefer local helpers. Use `withr::with_seed()` for deterministic chunks.
+
+## Copilot-Specific Guidance
+
+- If the current file uses tidyverse, **suggest tidyverse-first patterns** (e.g., `dplyr::across()` instead of superseded verbs). If base-R style is present, **use base idioms**.
+- Qualify non-base calls in suggestions (e.g., `dplyr::mutate()`).
+- Suggest vectorized or tidy solutions over loops when idiomatic.
+- Prefer small helper functions over long pipelines.
+- When multiple approaches are equivalent, prefer readability and type stability and explain the trade-offs.
+
+---
+
+## Minimal Examples
+
+```r
+# Base R variant
+scores <- data.frame(id = 1:5, x = c(1, 3, 2, 5, 4))
+safe_log <- function(x) tryCatch(log(x), error = function(e) NA_real_)
+scores$z <- vapply(scores$x, safe_log, numeric(1))
+
+# Tidyverse variant (if this file uses tidyverse)
+result <- tibble::tibble(id = 1:5, x = c(1, 3, 2, 5, 4)) |>
+dplyr::mutate(z = purrr::map_dbl(x, purrr::possibly(log, otherwise = NA_real_))) |>
+dplyr::filter(z > 0)
+
+# Example reusable helper with roxygen2 doc
+#' Compute the z-score of a numeric vector
+#' @param x A numeric vector
+#' @return Numeric vector of z-scores
+#' @examples z_score(c(1, 2, 3))
+z_score <- function(x) (x - mean(x, na.rm = TRUE)) / stats::sd(x, na.rm = TRUE)
+```