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daiquiri: Data Quality Reporting for Temporal Datasets

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: 1.1.1
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: 2023-07-18
DOI: 10.32614/CRAN.package.daiquiri
Author: T. Phuong Quan ORCID iD [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:

Reference manual: daiquiri.pdf
Vignettes: Walkthrough for the daiquiri package

Downloads:

Package source: daiquiri_1.1.1.tar.gz
Windows binaries: r-devel: daiquiri_1.1.1.zip, r-release: daiquiri_1.1.1.zip, r-oldrel: daiquiri_1.1.1.zip
macOS binaries: r-release (arm64): daiquiri_1.1.1.tgz, r-oldrel (arm64): daiquiri_1.1.1.tgz, r-release (x86_64): daiquiri_1.1.1.tgz, r-oldrel (x86_64): daiquiri_1.1.1.tgz
Old sources: daiquiri archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=daiquiri to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.