diff --git a/DESCRIPTION b/DESCRIPTION
index b723e20..cbb453e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -46,8 +46,6 @@ Suggests:
VignetteBuilder:
knitr,
rmarkdown
-Remotes:
- insightsengineering/rtables@981_cran_v0.6.11
Config/Needs/verdepcheck: insightsengineering/formatters,
insightsengineering/rtables, tidyverse/magrittr, mllg/checkmate,
rstudio/htmltools, gagolews/stringi, tidymodels/broom, cran/car,
diff --git a/README.Rmd b/README.Rmd
index 1bf4ace..a52f494 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -12,146 +12,50 @@ knitr::opts_chunk$set(
comment = "#>",
fig.path = "man/figures/README-"
)
+suppressPackageStartupMessages(library(rtables.officer))
suppressPackageStartupMessages(library(rtables))
suppressPackageStartupMessages(library(dplyr))
```
-# rtables 
+# rtables.officer
-[](https://github.com/insightsengineering/rtables/actions/workflows/check.yaml)
-[](https://insightsengineering.github.io/rtables/)
-[](https://raw.githubusercontent.com/insightsengineering/rtables/_xml_coverage_reports/data/main/coverage.xml)
-
-
-
-
-
-
-
-
-
-
+[](https://github.com/insightsengineering/rtables.officer/actions/workflows/check.yaml)
+[](https://insightsengineering.github.io/rtables.officer/)
+[](https://raw.githubusercontent.com/insightsengineering/rtables.officer/_xml_coverage_reports/data/main/coverage.xml)
+
+
+
+
+
+
+
+
+
+
[](https://www.repostatus.org/#active)
-[](https://github.com/insightsengineering/rtables/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc)
+[](https://github.com/insightsengineering/rtables.officer/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc)
-[](https://CRAN.R-project.org/package=rtables)
-[](https://github.com/insightsengineering/rtables/tree/main)
+[](https://github.com/insightsengineering/rtables.officer/tree/main)
## Reporting Tables with R
The `rtables` R package was designed to create and display complex tables with R. The cells in an `rtable` may contain
any high-dimensional data structure which can then be displayed with cell-specific formatting instructions. Currently,
-`rtables` can be outputted in `ascii` `html`, and `pdf`, as well Power Point (via conversion to `flextable` objects). `rtf` support is in development and will be in a future release.
+`rtables` can be outputted in `ascii` `html`, and `pdf`, as well Power Point (via conversion to `flextable` objects). This package `rtables.officer` is designed to support the exporting outputs relate Microsoft office software such as `word` and `powerpoint`.
-`rtables` is developed and copy written by `F. Hoffmann-La Roche` and it is released open source under Apache
+`rtables` and `rtables.officer` is developed and copy written by `F. Hoffmann-La Roche` and it is released open source under Apache
License Version 2.
-`rtables` development is driven by the need to create regulatory ready tables for health authority review. Some of the key requirements for this undertaking are listed below:
-
-* cell values and their visualization separate (i.e. no string based tables)
- - values need to be programmatically accessible in their non-rounded state for cross-checking
-* multiple values displayed within a cell
-* flexible tabulation framework
-* flexible formatting (cell spans, rounding, alignment, etc.)
-* multiple output formats (html, ascii, latex, pdf, xml)
-* flexible pagination in both horizontal and vertical directions
-* distinguish between name and label in the data structure to work with `CDISC` standards
-* title, footnotes, cell cell/row/column references
-
-`rtables` currently covers virtually all of these requirements, and further advances remain under active development.
## Installation
-`rtables` is available on CRAN and you can install the latest released version with:
-
-```r
-install.packages("rtables")
-```
-
-or you can install the latest development version directly from GitHub with:
+`rtables.officer` can be installed with the latest development version directly from GitHub with:
```r
# install.packages("pak")
-pak::pak("insightsengineering/rtables")
+pak::pak("insightsengineering/rtables.officer")
```
-Packaged releases (both those on CRAN and those between official CRAN releases) can be
-found in the [releases list](https://github.com/insightsengineering/rtables/releases).
-
-To understand how to use this package, please refer to the [Introduction to `rtables`](https://insightsengineering.github.io/rtables/main/articles/rtables.html) article, which provides multiple examples of code implementation.
-
-## Cheatsheet
-
-
-
-## Usage
-
-We first demonstrate with a demographic table-like example and then show the creation of a more complex table.
-
-```{r, message=FALSE}
-library(rtables)
-
-lyt <- basic_table() %>%
- split_cols_by("ARM") %>%
- analyze(c("AGE", "BMRKR1", "BMRKR2"), function(x, ...) {
- if (is.numeric(x)) {
- in_rows(
- "Mean (sd)" = c(mean(x), sd(x)),
- "Median" = median(x),
- "Min - Max" = range(x),
- .formats = c("xx.xx (xx.xx)", "xx.xx", "xx.xx - xx.xx")
- )
- } else if (is.factor(x) || is.character(x)) {
- in_rows(.list = list_wrap_x(table)(x))
- } else {
- stop("type not supported")
- }
- })
-
-build_table(lyt, ex_adsl)
-```
-
-```{r, message=FALSE}
-library(rtables)
-library(dplyr)
-
-## for simplicity grab non-sparse subset
-ADSL <- ex_adsl %>% filter(RACE %in% levels(RACE)[1:3])
-
-biomarker_ave <- function(x, ...) {
- val <- if (length(x) > 0) round(mean(x), 2) else "no data"
- in_rows(
- "Biomarker 1 (mean)" = rcell(val)
- )
-}
-
-basic_table(show_colcounts = TRUE) %>%
- split_cols_by("ARM") %>%
- split_cols_by("BMRKR2") %>%
- split_rows_by("RACE", split_fun = trim_levels_in_group("SEX")) %>%
- split_rows_by("SEX") %>%
- summarize_row_groups() %>%
- analyze("BMRKR1", biomarker_ave) %>%
- build_table(ADSL)
-```
-
-# Acknowledgments
-
-We would like to thank everyone who has made `rtables` a better project by providing feedback and improving examples & vignettes. The following list of contributors is alphabetical:
-
-Maximo Carreras, Francois Collins, Saibah Chohan, Tadeusz Lewandowski, Nick Paszty, Nina Qi, Jana Stoilova, Heng Wang, Godwin Yung
-
-## Presentations
-- R in Pharma 2023
- - Generating Tables, Listings, and Graphs using NEST / [cardinal](https://pharmaverse.github.io/cardinal/) [[Video](https://www.youtube.com/watch?v=YPmbLPSYFYM)]
- - BBS Session on Regulatory Submissions of Clinical Trials [[Video](https://www.youtube.com/watch?v=yZS4OBuJe_Q)]
-- R Medicine Virtual Conference 2023 [[Video](https://www.youtube.com/watch?v=sxFsavKI7s4)]
-- Advanced rtables Training 2023 [[Part 1 Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/Advanced_rtables_part1.pdf)] [[Part 2 Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/Advances_rtables_part2.pdf)]
-- R in Pharma 2022 - Creating Submission-Quality Clinical Trial Reporting Tables in R with rtables [[Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/Clinical_Trial_Reporting_Tables_in_R.pdf)] [[Video](https://www.youtube.com/watch?v=zBm_NZ0VtKs)]
-- R Consortium 2022
- - R Adoption Series - Reporting Table Creation in R [[Video](https://www.youtube.com/watch?v=1i6vOId2h4A)] [[Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/r_adoption_slides.pdf)]
- - Tables in Clinical Trials with R [[Book](https://rconsortium.github.io/rtrs-wg/)]
-- useR! 2020 - rtables Layouting and Tabulation Framework [[Video](https://www.youtube.com/watch?v=CBQzZ8ZhXLA)]
diff --git a/README.md b/README.md
index 5293da6..db9e42e 100644
--- a/README.md
+++ b/README.md
@@ -1,44 +1,42 @@
-# rtables
+# rtables.officer
[](https://github.com/insightsengineering/rtables/actions/workflows/check.yaml)
+🛠](https://github.com/insightsengineering/rtables.officer/actions/workflows/check.yaml/badge.svg)](https://github.com/insightsengineering/rtables.officer/actions/workflows/check.yaml)
[](https://insightsengineering.github.io/rtables/)
+📚](https://github.com/insightsengineering/rtables.officer/actions/workflows/docs.yaml/badge.svg)](https://insightsengineering.github.io/rtables.officer/)
[](https://raw.githubusercontent.com/insightsengineering/rtables/_xml_coverage_reports/data/main/coverage.xml)
+📔](https://raw.githubusercontent.com/insightsengineering/rtables.officer/_xml_coverage_reports/data/main/badge.svg)](https://raw.githubusercontent.com/insightsengineering/rtables.officer/_xml_coverage_reports/data/main/coverage.xml)
+forks](https://img.shields.io/github/forks/insightsengineering/rtables.officer?style=social)
+stars](https://img.shields.io/github/stars/insightsengineering/rtables.officer?style=social)
+activity](https://img.shields.io/github/commit-activity/m/insightsengineering/rtables.officer)
+contributors](https://img.shields.io/github/contributors/insightsengineering/rtables.officer)
+commit](https://img.shields.io/github/last-commit/insightsengineering/rtables.officer)
+requests](https://img.shields.io/github/issues-pr/insightsengineering/rtables.officer)
+size](https://img.shields.io/github/repo-size/insightsengineering/rtables.officer)
+count](https://img.shields.io/github/languages/count/insightsengineering/rtables.officer)
[](https://www.repostatus.org/#active)
[](https://github.com/insightsengineering/rtables/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc)
+Issues](https://img.shields.io/github/issues-raw/insightsengineering/rtables.officer?color=red&label=open%20issues)](https://github.com/insightsengineering/rtables.officer/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc)
-[](https://CRAN.R-project.org/package=rtables)
[](https://github.com/insightsengineering/rtables/tree/main)
+Version](https://img.shields.io/github/r-package/v/insightsengineering/rtables.officer/main?color=purple&label=Development%20Version)](https://github.com/insightsengineering/rtables.officer/tree/main)
## Reporting Tables with R
@@ -48,186 +46,20 @@ tables with R. The cells in an `rtable` may contain any high-dimensional
data structure which can then be displayed with cell-specific formatting
instructions. Currently, `rtables` can be outputted in `ascii` `html`,
and `pdf`, as well Power Point (via conversion to `flextable` objects).
-`rtf` support is in development and will be in a future release.
+This package `rtables.officer` is designed to support the exporting
+outputs relate Microsoft office software such as `word` and
+`powerpoint`.
-`rtables` is developed and copy written by `F. Hoffmann-La Roche` and it
-is released open source under Apache License Version 2.
-
-`rtables` development is driven by the need to create regulatory ready
-tables for health authority review. Some of the key requirements for
-this undertaking are listed below:
-
-- cell values and their visualization separate (i.e. no string based
- tables)
- - values need to be programmatically accessible in their non-rounded
- state for cross-checking
-- multiple values displayed within a cell
-- flexible tabulation framework
-- flexible formatting (cell spans, rounding, alignment, etc.)
-- multiple output formats (html, ascii, latex, pdf, xml)
-- flexible pagination in both horizontal and vertical directions
-- distinguish between name and label in the data structure to work with
- `CDISC` standards
-- title, footnotes, cell cell/row/column references
-
-`rtables` currently covers virtually all of these requirements, and
-further advances remain under active development.
+`rtables` and `rtables.officer` is developed and copy written by
+`F. Hoffmann-La Roche` and it is released open source under Apache
+License Version 2.
## Installation
-`rtables` is available on CRAN and you can install the latest released
-version with:
-
-``` r
-install.packages("rtables")
-```
-
-or you can install the latest development version directly from GitHub
-with:
+`rtables.officer` can be installed with the latest development version
+directly from GitHub with:
``` r
# install.packages("pak")
-pak::pak("insightsengineering/rtables")
+pak::pak("insightsengineering/rtables.officer")
```
-
-Packaged releases (both those on CRAN and those between official CRAN
-releases) can be found in the [releases
-list](https://github.com/insightsengineering/rtables/releases).
-
-To understand how to use this package, please refer to the [Introduction
-to
-`rtables`](https://insightsengineering.github.io/rtables/main/articles/rtables.html)
-article, which provides multiple examples of code implementation.
-
-## Cheatsheet
-
-
-
-## Usage
-
-We first demonstrate with a demographic table-like example and then show
-the creation of a more complex table.
-
-``` r
-library(rtables)
-
-lyt <- basic_table() %>%
- split_cols_by("ARM") %>%
- analyze(c("AGE", "BMRKR1", "BMRKR2"), function(x, ...) {
- if (is.numeric(x)) {
- in_rows(
- "Mean (sd)" = c(mean(x), sd(x)),
- "Median" = median(x),
- "Min - Max" = range(x),
- .formats = c("xx.xx (xx.xx)", "xx.xx", "xx.xx - xx.xx")
- )
- } else if (is.factor(x) || is.character(x)) {
- in_rows(.list = list_wrap_x(table)(x))
- } else {
- stop("type not supported")
- }
- })
-
-build_table(lyt, ex_adsl)
-#> A: Drug X B: Placebo C: Combination
-#> ————————————————————————————————————————————————————————————
-#> AGE
-#> Mean (sd) 33.77 (6.55) 35.43 (7.90) 35.43 (7.72)
-#> Median 33.00 35.00 35.00
-#> Min - Max 21.00 - 50.00 21.00 - 62.00 20.00 - 69.00
-#> BMRKR1
-#> Mean (sd) 5.97 (3.55) 5.70 (3.31) 5.62 (3.49)
-#> Median 5.39 4.81 4.61
-#> Min - Max 0.41 - 17.67 0.65 - 14.24 0.17 - 21.39
-#> BMRKR2
-#> LOW 50 45 40
-#> MEDIUM 37 56 42
-#> HIGH 47 33 50
-```
-
-``` r
-library(rtables)
-library(dplyr)
-
-## for simplicity grab non-sparse subset
-ADSL <- ex_adsl %>% filter(RACE %in% levels(RACE)[1:3])
-
-biomarker_ave <- function(x, ...) {
- val <- if (length(x) > 0) round(mean(x), 2) else "no data"
- in_rows(
- "Biomarker 1 (mean)" = rcell(val)
- )
-}
-
-basic_table(show_colcounts = TRUE) %>%
- split_cols_by("ARM") %>%
- split_cols_by("BMRKR2") %>%
- split_rows_by("RACE", split_fun = trim_levels_in_group("SEX")) %>%
- split_rows_by("SEX") %>%
- summarize_row_groups() %>%
- analyze("BMRKR1", biomarker_ave) %>%
- build_table(ADSL)
-#> A: Drug X B: Placebo C: Combination
-#> LOW MEDIUM HIGH LOW MEDIUM HIGH LOW MEDIUM HIGH
-#> (N=45) (N=35) (N=46) (N=42) (N=48) (N=31) (N=40) (N=39) (N=47)
-#> ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
-#> ASIAN
-#> F 13 (28.9%) 9 (25.7%) 19 (41.3%) 9 (21.4%) 18 (37.5%) 9 (29.0%) 13 (32.5%) 9 (23.1%) 17 (36.2%)
-#> Biomarker 1 (mean) 5.23 6.17 5.38 5.64 5.55 4.33 5.46 5.48 5.19
-#> M 8 (17.8%) 7 (20.0%) 10 (21.7%) 12 (28.6%) 10 (20.8%) 8 (25.8%) 5 (12.5%) 11 (28.2%) 16 (34.0%)
-#> Biomarker 1 (mean) 6.77 6.06 5.54 4.9 4.98 6.81 6.53 5.47 4.98
-#> U 1 (2.2%) 1 (2.9%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (3.2%) 0 (0.0%) 1 (2.6%) 1 (2.1%)
-#> Biomarker 1 (mean) 4.68 7.7 no data no data no data 6.97 no data 11.93 9.01
-#> BLACK OR AFRICAN AMERICAN
-#> F 6 (13.3%) 3 (8.6%) 9 (19.6%) 6 (14.3%) 8 (16.7%) 2 (6.5%) 7 (17.5%) 4 (10.3%) 3 (6.4%)
-#> Biomarker 1 (mean) 5.01 7.2 6.79 6.15 5.26 8.57 5.72 5.76 4.58
-#> M 5 (11.1%) 5 (14.3%) 2 (4.3%) 3 (7.1%) 5 (10.4%) 4 (12.9%) 4 (10.0%) 5 (12.8%) 5 (10.6%)
-#> Biomarker 1 (mean) 6.92 5.82 11.66 4.46 6.14 8.47 6.16 5.25 4.83
-#> U 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (2.5%) 1 (2.6%) 0 (0.0%)
-#> Biomarker 1 (mean) no data no data no data no data no data no data 2.79 9.82 no data
-#> UNDIFFERENTIATED 1 (2.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 2 (5.0%) 0 (0.0%) 0 (0.0%)
-#> Biomarker 1 (mean) 9.48 no data no data no data no data no data 6.46 no data no data
-#> WHITE
-#> F 6 (13.3%) 7 (20.0%) 4 (8.7%) 5 (11.9%) 6 (12.5%) 6 (19.4%) 6 (15.0%) 3 (7.7%) 2 (4.3%)
-#> Biomarker 1 (mean) 4.43 7.83 4.52 6.42 5.07 7.83 6.71 5.87 10.7
-#> M 4 (8.9%) 3 (8.6%) 2 (4.3%) 6 (14.3%) 1 (2.1%) 1 (3.2%) 2 (5.0%) 5 (12.8%) 3 (6.4%)
-#> Biomarker 1 (mean) 5.81 7.23 1.39 4.72 4.58 12.87 2.3 5.1 5.98
-#> U 1 (2.2%) 0 (0.0%) 0 (0.0%) 1 (2.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
-#> Biomarker 1 (mean) 3.94 no data no data 3.77 no data no data no data no data no data
-```
-
-# Acknowledgments
-
-We would like to thank everyone who has made `rtables` a better project
-by providing feedback and improving examples & vignettes. The following
-list of contributors is alphabetical:
-
-Maximo Carreras, Francois Collins, Saibah Chohan, Tadeusz Lewandowski,
-Nick Paszty, Nina Qi, Jana Stoilova, Heng Wang, Godwin Yung
-
-## Presentations
-
-- R in Pharma 2023
- - Generating Tables, Listings, and Graphs using NEST /
- [cardinal](https://pharmaverse.github.io/cardinal/)
- \[[Video](https://www.youtube.com/watch?v=YPmbLPSYFYM)\]
- - BBS Session on Regulatory Submissions of Clinical Trials
- \[[Video](https://www.youtube.com/watch?v=yZS4OBuJe_Q)\]
-- R Medicine Virtual Conference 2023
- \[[Video](https://www.youtube.com/watch?v=sxFsavKI7s4)\]
-- Advanced rtables Training 2023 \[[Part 1
- Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/Advanced_rtables_part1.pdf)\]
- \[[Part 2
- Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/Advances_rtables_part2.pdf)\]
-- R in Pharma 2022 - Creating Submission-Quality Clinical Trial
- Reporting Tables in R with rtables
- \[[Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/Clinical_Trial_Reporting_Tables_in_R.pdf)\]
- \[[Video](https://www.youtube.com/watch?v=zBm_NZ0VtKs)\]
-- R Consortium 2022
- - R Adoption Series - Reporting Table Creation in R
- \[[Video](https://www.youtube.com/watch?v=1i6vOId2h4A)\]
- \[[Slides](https://github.com/insightsengineering/rtables/blob/main/inst/extdata/r_adoption_slides.pdf)\]
- - Tables in Clinical Trials with R
- \[[Book](https://rconsortium.github.io/rtrs-wg/)\]
-- useR! 2020 - rtables Layouting and Tabulation Framework
- \[[Video](https://www.youtube.com/watch?v=CBQzZ8ZhXLA)\]