Generate reports that enable quick visual review of temporal shifts in record-level data. Time series plots showing aggregated values are automatically created for each data field (column) depending on its contents (e.g. min/max/mean values for numeric data, no. of distinct values for categorical data), as well as overviews for missing values, non-conformant values, and duplicated rows. The resulting reports are shareable and can contribute to forming a transparent record of the entire analysis process. It is designed with Electronic Health Records in mind, but can be used for any type of record-level temporal data (i.e. tabular data where each row represents a single "event", one column contains the "event date", and other columns contain any associated values for the event).
Version: 1.2.0 Imports: data.table (≥ 1.12.8), readr (≥ 2.0.0), ggplot2 (≥ 3.1.0), scales (≥ 1.1.0), cowplot (≥ 0.9.3), rmarkdown, reactable (≥ 0.2.3), utils, stats, xfun (≥ 0.15) Suggests: covr, knitr, testthat (≥ 3.0.0), codemetar Published: 2025-06-24 DOI: 10.32614/CRAN.package.daiquiri Author: T. Phuong Quan [aut, cre], Jack Cregan [ctb], University of Oxford [cph], National Institute for Health Research (NIHR) [fnd], Brad Cannell [rev] Maintainer: T. Phuong Quan <phuong.quan at ndm.ox.ac.uk> BugReports: https://github.com/ropensci/daiquiri/issues License: GPL (≥ 3) URL: https://github.com/ropensci/daiquiri, https://ropensci.github.io/daiquiri/ NeedsCompilation: no Citation: daiquiri citation info Materials: README, NEWS CRAN checks: daiquiri results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=daiquiri to link to this page.
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