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).

Package details

AuthorT. Phuong Quan [aut, cre] (ORCID: <https://orcid.org/0000-0001-8566-1817>), Jack Cregan [ctb], University of Oxford [cph], National Institute for Health Research (NIHR) [fnd], Brad Cannell [rev]
MaintainerT. Phuong Quan <phuong.quan@ndm.ox.ac.uk>
LicenseGPL (>= 3)
Version1.2.0
URL https://github.com/ropensci/daiquiri https://ropensci.github.io/daiquiri/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("daiquiri")

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daiquiri documentation built on June 25, 2025, 1:07 a.m.