# spicy 0.8.0

## New features

* `table_continuous_lm()` adds APA-style bivariate linear-model tables for continuous outcomes. It acts as the model-based companion to `table_continuous()` for reporting fitted mean comparisons or slopes in an `lm` framework, with one predictor per model, model-based means for categorical predictors, optional case weights, classical or HC0-HC5 variance estimators, multiple output formats (ASCII, tinytable, gt, flextable, Excel, clipboard, and Word), `output = "data.frame"` for the wide raw table, `output = "long"` for the analytic long table, and configurable display of tests, confidence intervals, fit statistics, and effect sizes.

## Minor improvements

* Installed package vignettes now avoid embedding heavy HTML table and codebook widgets during CRAN builds, reducing package size while preserving rich pkgdown article rendering.

* Website and vignette coverage now includes `table_continuous_lm()`, using the bundled `sochealth` data throughout and adding a dedicated article for model-based continuous summary tables.

* `table_continuous()` and `table_continuous_lm()` now support dedicated display precision for effect-size columns, and `table_continuous_lm()` also supports separate precision for `R²` columns, so model fit and effect sizes can be formatted independently from descriptive values and test statistics.

* `table_continuous_lm()` now keeps `n` as the unweighted analytic sample size in wide and rendered outputs, and can optionally add a separate `Weighted n` column reporting the sum of case weights.

# spicy 0.7.0

## New features

* `table_continuous()` is a new helper for continuous summary tables. It computes descriptive statistics (mean, SD, min, max, confidence interval of the mean, and n) for numeric variables, with tidyselect column selection, optional grouping via `by`, and multiple output formats (ASCII, tinytable, gt, flextable, Excel, clipboard, and Word).

* `table_continuous()` gains `effect_size` and `effect_size_ci` arguments. When `by` is used, `effect_size = TRUE` adds an "ES" column with the appropriate measure (Hedges' g, eta-squared, rank-biserial `r_rb`, or epsilon-squared) chosen automatically based on the test method and number of groups, and `effect_size_ci = TRUE` appends the confidence interval in brackets.

* `table_continuous()` gains a `test` argument (`"welch"`, `"student"`, or `"nonparametric"`) to choose the group-comparison method, along with independent `p_value` and `statistic` display toggles so users can request either or both outputs when `by` is used.

* ASCII console tables now split oversized outputs into stacked horizontal panels, repeating the left-most identifier columns so wide `freq()`, `cross_tab()`, `table_categorical()`, and `table_continuous()` prints stay readable in narrow consoles.

## Breaking changes

* `table_categorical()` replaces `table_apa()` as the public helper for categorical summary tables. It uses `select` and `by`, supports grouped cross-tabulation or one-way frequency-style tables when `by = NULL`, and consolidates output formats under a single `output` argument. Migrate existing `table_apa()` calls to `table_categorical()`, use `output = "default"` for ASCII tables and `output = "data.frame"` for plain data frames, and replace former `output = "wide"` / `style = "report"` paths with the formatted output engines.

* Excel export now uses `openxlsx2` instead of `openxlsx` for a lighter dependency footprint (no Rcpp compilation required).

## Minor improvements

* Package citation metadata now uses the current package title and CRAN DOI, so `citation("spicy")` matches `DESCRIPTION` and points to the package DOI.

* `table_categorical()` and `table_continuous()` now print shorter ASCII titles without appending the input data frame name, and no longer require `officer` for `output = "flextable"` alone; `officer` is now required only for Word export paths that actually write `.docx` files.

* `table_continuous()` now accepts tidyselect syntax in `exclude` in addition to character vectors, and no longer warns that `test` is ignored when it is still needed to compute effect sizes.

# spicy 0.6.0

## New features

* New family of association measure functions for contingency tables: `assoc_measures()`, `contingency_coef()`, `gamma_gk()`, `goodman_kruskal_tau()`, `kendall_tau_b()`, `kendall_tau_c()`, `lambda_gk()`, `phi()`, `somers_d()`, `uncertainty_coef()`, and `yule_q()`. Each returns a numeric scalar by default; pass `detail = TRUE` for a named vector with estimate, confidence interval, and p-value.

* `cross_tab()` gains `assoc_measure` and `assoc_ci` arguments. When both variables are ordered factors, it automatically selects Kendall's Tau-b instead of Cramer's V. The note format changes from `Chi-2: 18.0 (df = 4)` to `Chi-2(4) = 18.0`. Numeric attributes (`chi2`, `df`, `p_value`, `assoc_measure`, `assoc_value`, `assoc_result`) are now attached to the output data frame.

* `table_apa()` now dynamically labels the association measure column based on the measure used, instead of always showing "Cramer's V". New `assoc_measure` and `assoc_ci` arguments are passed through to `cross_tab()`.

* `table_apa()` gains `output = "gt"` to produce a `gt_tbl` object with APA-style formatting, column spanners, and alignment.

* `table_apa()` now correctly centers spanner labels over their column pairs in `tinytable` and `flextable` output.

* All association measure functions and `assoc_measures()` gain a `digits` argument (default 3) that controls the number of decimal places when printed. The p-value always uses 3 decimal places or `< 0.001`.

* `detail = TRUE` results now print with formatted output (aligned columns, fixed decimal places) via a new `print.spicy_assoc_detail()` method. `assoc_measures()` output uses a new `print.spicy_assoc_table()` method with the same formatting.

* New bundled dataset `sochealth`: a simulated social-health survey (n = 1200, 24 variables) with variable labels, ordered factors, survey weights, and missing values. Includes four Likert-scaled life satisfaction items (`life_sat_health`, `life_sat_work`, `life_sat_relationships`, `life_sat_standard`) for demonstrating `mean_n()`, `sum_n()`, and `count_n()`.

## Bug fixes

* `count_n()` now correctly counts `NA` values when `count = NA` and `strict = TRUE` are both used. List columns are now reported in verbose mode instead of causing silent errors.

* `cross_tab()` rescale logic now operates on complete cases only, so the weighted total N matches the unweighted N when missing values are present (consistent with Stata behavior).

* `freq()` now uses true `NA` consistently (instead of the `"<NA>"` string) in both weighted and unweighted paths. `cum_valid_prop` is now correctly `NA` for missing rows. Invalid `digits` and `sort` values are rejected with clear error messages.

* `mean_n()` and `sum_n()` now validate `min_valid` and `digits` arguments, rejecting non-numeric, negative, or multi-element values.

* `mean_n()`, `sum_n()`, and `count_n()` no longer trigger a tidyselect deprecation warning when `select` receives a character vector. Character vectors are now automatically wrapped with `all_of()`.

* `table_apa()` now preserves the original factor level order in row variables instead of sorting alphabetically. When `drop_na = FALSE`, the `(Missing)` category is placed at the bottom of each variable's levels. `percent_digits`, `p_digits`, and `v_digits` are now validated.

* `table_apa()` p-values no longer wrap across lines in `tinytable` HTML output.

## Breaking changes

* `cramer_v()` now accepts a `detail` argument. By default it returns a numeric scalar (as before). Pass `detail = TRUE` to get a 4-element named vector (`estimate`, `ci_lower`, `ci_upper`, `p_value`), or `detail = TRUE, conf_level = NULL` for a 2-element vector (`estimate`, `p_value`) without CI.

# spicy 0.5.0

## New features

* New `table_apa()` helper to build APA-ready cross-tab reports with multiple output formats (`wide`, `long`, `tinytable`, `flextable`, `excel`, `clipboard`, `word`).
* `table_apa()` exposes key `cross_tab()` controls for weighting and inference (`weights`, `rescale`, `correct`, `simulate_p`, `simulate_B`) and now handles missing values explicitly when `drop_na = FALSE`.

## Bug fixes

* `count_n()` no longer crashes when `special = "NaN"` is used with non-numeric columns. Passing `count = NA` now errors with a message directing to `special = "NA"`.
* `cross_tab()` fixes a spurious rescale warning for explicit all-ones weights and aligns the Cramer's V formula with `cramer_v()`.
* `table_apa()` no longer leaks global options on error. The `simulate_p` default is aligned to `FALSE`.
* `varlist()` title generation no longer crashes on unrecognizable expressions.

## Minor improvements

* `copy_clipboard()` parameter `message` renamed to `show_message`.
* `freq()` now dispatches printing correctly via S3.
* Removed unused `collapse` and `stringi` from `Imports`.


# spicy 0.4.2

* `cross_tab()` hardening: improved vector-mode detection (including labelled vectors), stricter weight validation, safer rescaling, and clearer early errors (e.g., explicit `y = NULL`).
* `cross_tab()` statistics are now computed on non-empty margins in grouped tables, avoiding spurious `NA` results; internal core path refactored to remove `dplyr`/`tibble` from computation while preserving user-facing behavior.
* `freq()` now errors clearly when `x` is missing for data.frame input and validates rescaling when weight sums are zero/non-finite.
* `count_n()`, `mean_n()`, and `sum_n()` regex mode is hardened (`regex = TRUE` now validates/defaults `select` safely).
* `mean_n()` and `sum_n()` now return `NA` (with warning) when no numeric columns are selected.
* `label_from_names()` now validates input type (`data.frame`/tibble required).
* `cramer_v()` now returns `NA` with warning for degenerate tables.
* Dependency optimization: `DT` and `clipr` moved to `Suggests`; optional runtime checks added in `code_book()` and `copy_clipboard()`.
* Tests expanded with regression coverage for all the above edge cases.


# spicy 0.4.1

* Fixed CRAN incoming check notes by removing non-standard top-level files.

# spicy 0.4.0

* Print methods have been fully redesigned to produce clean, aligned ASCII tables inspired by Stata's layout. The new implementation improves formatting, adds optional color support, and provides more consistent handling of totals and column spacing.

* Output from `freq()` and `cross_tab()` now benefits from the enhanced
  `print.spicy()` formatting, offering clearer, more readable summary tables.

* Documentation and internal tests were updated for clarity and consistency.

* `cross_tab()` gains an explicit `correct` argument to control the use of
  Yates' continuity correction for Chi-squared tests in 2x2 tables. The default
  behavior remains unchanged.

* The documentation of `cross_tab()` was refined and harmonized, with a clearer
  high-level description, improved parameter wording, and expanded examples.

* Minor cosmetic improvements were made to `varlist()` output: the title prefix
  now uses `vl:` instead of `VARLIST`, and the column name `Ndist_val` was renamed
  to `N_distinct` for improved readability and consistency.

* Minor cosmetic improvement: ASCII table output no longer includes a closing
  bottom rule by default.


# spicy 0.3.0

* New function `code_book()`, which generates a comprehensive variable
  codebook that can be viewed interactively and exported to multiple
  formats (copy, print, CSV, Excel, PDF).

# spicy 0.2.1

* `label_from_names()` now correctly handles edge cases when the
  separator appears in the label or is missing.

# spicy 0.2.0

* New function `label_from_names()` to derive and assign variable labels
  from headers of the form `"name<sep>label"` (e.g. `"name. label"`).
  Especially useful for LimeSurvey CSV exports (*Export results* ->
  *CSV* -> *Headings: Question code & question text*), where the default
  separator is `". "`.

# spicy 0.1.0

## Initial release

* Introduces a collection of tools for variable inspection, descriptive
  summaries, and data exploration.
* Provides functions to:
  - Extract variable metadata and display compact summaries (`varlist()`).
  - Compute frequency tables (`freq()`), cross-tabulations (`cross_tab()`),
    and Cramer's V for categorical associations (`cramer_v()`).
  - Generate descriptive statistics such as means (`mean_n()`), sums
    (`sum_n()`), and counts (`count_n()`) with automatic handling of
    missing data.
  - Copy data (`copy_clipboard()`) directly to the clipboard for quick export.
