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# tabular <a href="https://vthanik.github.io/tabular/"><img src="man/figures/logo.png" align="right" height="139" alt="tabular website" /></a>

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**tabular** turns a pre-summarised data frame into a submission-grade clinical table and emits it natively to **RTF, PDF, HTML, LaTeX, and DOCX** — no Java, no LibreOffice, no Word automation. One short pipeline gives you decimal alignment via real font metrics, multi-level column headers, predicate-targeted styling, and group-aware pagination, built for CDISC ADaM workflows and FDA / EMA / PMDA submissions.

It is the only R table package that pairs a **live HTML preview** with a **paginated print deliverable**: the same spec you eyeball in a notebook is the one that paginates into the RTF you ship.

> **Scope.** `tabular` renders the full set of clinical outputs – **tables, listings, and figures** (the “T”, “L”, and “F” of TFL) – to RTF, LaTeX, HTML, PDF, and DOCX from one verb pipeline. A zero-row table renders an empty-data placeholder (“No data available to report”) in the body, with the page chrome and column headers intact.

## Installation

Install the released version from CRAN:

``` r
install.packages("tabular")
```

Or the development version from GitHub:

``` r
# install.packages("pak")
pak::pak("vthanik/tabular")
# or
remotes::install_github("vthanik/tabular")
```

R dependencies install automatically. The five backends differ in what *else* they need:

| Backend | Extra requirement |
|----|:---|
| RTF, DOCX, HTML, Markdown | none — pure R, no Java, no `pandoc`, no Office |
| LaTeX (`.tex` source) | none — `tabular` writes the fragment |
| PDF | a TeX install (xelatex) with `tabularray` + `ninecolors` |

PDF is the only backend that shells out. Install [`tinytex`](https://yihui.org/tinytex/) once per machine and `tabular` compiles with `xelatex` thereafter:

``` r
install.packages("tinytex")
tinytex::install_tinytex() # one-time TeX setup
tinytex::tlmgr_install(c("tabularray", "ninecolors", "siunitx", "tex-gyre"))
```

`check_latex()` reports which LaTeX packages are present and prints the exact `tlmgr_install()` line for anything missing; `check_fonts(spec)` does the same for the fonts a spec asks for, per backend.

``` r
tabular::check_latex()   # PDF readiness, with the install remedy
```

> **TeX Live on a managed OS.** If TeX Live came from the system package manager (RHEL `dnf`, Debian/Ubuntu `apt`), its `tlmgr` is usually locked and `tlmgr_install()` fails on permissions. Install user-space TinyTeX alongside it rather than fighting the system copy — and never reach for `--ignore-warning` to force it.

## A table in one pipeline

The pipeline starts from a pre-summarised wide data frame (one row in = one display row — `tabular` does no aggregation) and chains one verb per concern. Every verb returns an updated, immutable `tabular_spec`; the engine resolves it at render time.

``` r
library(tabular)

# BigN denominators, keyed by arm
n <- stats::setNames(cdisc_saf_n$n, cdisc_saf_n$arm_short)

# columns render in data-frame order, so put them in dose order first;
# subset to Age / Sex / Race for a compact display
keep <- c("Age (years)", "Sex, n (%)", "Race, n (%)")
demo <- cdisc_saf_demo[
  cdisc_saf_demo$variable %in% keep,
  c("variable", "stat_label", "placebo", "drug_50", "drug_100", "Total")
]

tab <- tabular(
  demo,
  titles = c(
    "Table 14.1.1",
    "Demographic and Baseline Characteristics",
    "Safety Population"
  ),
  footnotes = "Percentages are based on the number of subjects per treatment group."
) |>
  cols(
    variable = col_spec(usage = "group", label = "Characteristic"),
    stat_label = col_spec(label = "Statistic"),
    placebo = col_spec(
      label = "Placebo (N={n['placebo']})",
      align = "decimal"
    ),
    drug_50 = col_spec(
      label = "Drug 50 (N={n['drug_50']})",
      align = "decimal"
    ),
    drug_100 = col_spec(
      label = "Drug 100 (N={n['drug_100']})",
      align = "decimal"
    ),
    Total = col_spec(label = "Total (N={n['Total']})", align = "decimal")
  )

# render to any backend by file extension (or format = "...")
path <- emit(tab, tempfile(fileext = ".rtf")) # submission deliverable
```

The same `tab` emits to every backend from the one spec. The table below is tabular’s own HTML render — the identical spec also produces RTF, a paginated PDF, a `tabularray` LaTeX fragment, and native OOXML `.docx`:

<div align="center">

<img src="man/figures/README-hero.png" width="815" alt="Demographic and baseline characteristics table rendered by tabular: decimal-aligned arm columns, a centred multi-line caption, and a single footnote.">

</div>

## Why tabular?

- **Five native backends, one spec.** `emit()` dispatches on the file extension to RTF 1.9.1, PDF (via `tinytex`), self-contained Bootstrap HTML, `tabularray` LaTeX, and native OOXML DOCX. No JVM, no Office round-trip.
- **Decimal alignment that survives the page.** Numbers align on the decimal using the backend’s real font metrics, not guessed padding — so columns stay aligned in print, not just on screen.
- **Submission chrome built in.** Multi-line titles, up to eleven footnote lines, page header/footer slots, and the four-section page layout regulatory reviewers expect.
- **Auto-numbered footnotes.** `footnote()` anchors a marker to any cell, header, or title; the engine assigns the glyph once, in reading order, deduped by `id`, and byte-identical across every backend and page.
- **Group-aware pagination.** Keep a SOC and its preferred terms on one page, repeat titles/headers/footnotes per page, control orphan/widow rows, and split wide tables into horizontal panels.
- **Display-only by design.** `tabular` styles and renders; it never filters, aggregates, or weights. Pair it with `cards` / `gtsummary` / `dplyr` / SAS upstream and feed it a tidy wide frame.
- **A QC trail.** `emit(data_file = ...)` writes the resolved wide data beside the render, and a CDISC ARS audit manifest documents the display.

## Where tabular fits

`tabular` is a *renderer* for pre-summarised clinical tables, not a statistics engine. Compute the summary upstream — with `cards`, `gtsummary`, `dplyr`, or SAS — then hand the finished wide frame to `tabular()`. Reach for `gtsummary` or `rtables` when you want the package to *compute* the summary; reach for `tabular` to *render* a summary you already have to submission-grade output.

The matrix reflects each package’s documented export surface (verified against their namespaces; `via gt` means `gtsummary` renders through `gt`):

|  | tabular | gt | rtables | gtsummary | flextable | huxtable |
|----|:--:|:--:|:--:|:--:|:--:|:--:|
| Computes statistics | — | — | ✓ | ✓ | — | — |
| Live HTML preview | ✓ | ✓ | — | ✓ | ✓ | ✓ |
| Native RTF | ✓ | ✓ | — | via gt | ✓ | ✓ |
| Native DOCX | ✓ | ✓ | — | via gt | ✓ | ✓ |
| LaTeX | ✓ | ✓ | — | via gt | — | ✓ |
| PDF | ✓ | ✓ | ✓ | via gt | — | ✓ |
| Paginated submission output | ✓ | — | ✓ | — | — | — |
| Decimal align via font metrics | ✓ | — | — | — | — | — |
| CDISC ARS audit manifest | ✓ | — | — | — | — | — |

Two notes on the marks:

- **Live HTML preview** means the table renders as HTML *inline* when you print it in a Quarto / R Markdown chunk or the RStudio viewer (a `knit_print` method). `rtables` prints a monospace ASCII table by default and ships no `knit_print` method, so it is `—` here; it can still emit HTML through an explicit `as_html()` call.
- **PDF** is compiled through LaTeX, so it needs a TeX installation — see [Installation](#installation) above. Every other backend is pure R.

## Documentation

- [Get started](https://vthanik.github.io/tabular/articles/tabular.html) — the mental model and your first table
- [Data in](https://vthanik.github.io/tabular/articles/data-in.html) — turn a cards/cardx ARD into the wide frame with `pivot_across()`
- [Structure](https://vthanik.github.io/tabular/articles/structure.html) — columns, headers, BigN, and pagination
- [Presentation](https://vthanik.github.io/tabular/articles/presentation.html) — titles, footnotes, page chrome, and styling
- [Output & qualification](https://vthanik.github.io/tabular/articles/output.html) — backends, requirements, and the CDISC-pilot validation
- [Reference](https://vthanik.github.io/tabular/reference/index.html) — every verb, grouped by role

## License

MIT © Vignesh Thanikachalam
