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daiquiri
View on CRAN: Click
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Download and install daiquiri package within the R console
Install from CRAN:
install.packages("daiquiri")
Install from Github:
library("remotes")
install_github("cran/daiquiri") Install by package version:
library("remotes")
install_version("daiquiri", "1.2.1") Attach the package and use:
library("daiquiri")
Maintained by
T. Phuong Quan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-11-11
Latest Update: 2025-06-24
Description:
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).
How to cite:
T. Phuong Quan (2022). daiquiri: Data Quality Reporting for Temporal Datasets. R package version 1.2.1, https://cran.r-project.org/web/packages/daiquiri. Accessed 04 Jun. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for daiquiri
Functions, R codes and Examples using
the daiquiri R package
Some associated functions: aggregate_data . close_log . daiquiri-package . daiquiri_report . export_aggregated_data . field_types . field_types_available . initialise_log . prepare_data . read_data . report_data . template_field_types .
Some associated R codes: aggregate_data.R . aggregation_functions.R . daiquiri-package.R . field_types.R . main.R . reports.R . source_data.R . utilities.R . zzz.R . Full daiquiri package functions and examples
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