Package: daiquiri 1.1.1.9000

T. Phuong Quan

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).

Authors:T. Phuong Quan [aut, cre], Jack Cregan [ctb], University of Oxford [cph], National Institute for Health Research [fnd], Brad Cannell [rev]

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daiquiri/json (API)
NEWS

# Install 'daiquiri' in R:
install.packages('daiquiri', repos = c('https://packages.ropensci.org', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ropensci/daiquiri/issues

On CRAN:

data-qualityinitial-data-analysisreproducible-researchtemporal-datatime-series

20 exports 35 stars 5.89 score 66 dependencies 11 scripts 799 downloads

Last updated 1 months agofrom:25a7b05a58 (on master). Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 02 2024
R-4.5-winOKOct 02 2024
R-4.5-linuxOKOct 02 2024
R-4.4-winOKOct 02 2024
R-4.4-macOKOct 02 2024
R-4.3-winOKOct 02 2024
R-4.3-macOKOct 02 2024

Exports:aggregate_dataclose_logdaiquiri_reportexport_aggregated_datafield_typesfield_types_advancedft_categoricalft_datetimeft_freetextft_ignoreft_numericft_simpleft_strataft_timepointft_uniqueidentifierinitialise_logprepare_dataread_datareport_datatemplate_field_types

Dependencies:base64encbitbit64bslibcachemclicliprcolorspacecowplotcpp11crayondata.tabledigestevaluatefansifarverfastmapfontawesomefsggplot2gluegtablehighrhmshtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigprettyunitsprogressR6rappdirsRColorBrewerreactablereactRreadrrlangrmarkdownsassscalestibbletidyselecttinytextzdbutf8vctrsviridisLitevroomwithrxfunyaml

Walkthrough for the daiquiri package

Rendered fromdaiquiri.Rmdusingknitr::rmarkdownon Oct 02 2024.

Last update: 2024-04-04
Started: 2022-06-08

Readme and manuals

Help Manual

Help pageTopics
Aggregate source dataaggregate_data
Close any active log fileclose_log
Create a data quality report from a data framedaiquiri_report
Export aggregated dataexport_aggregated_data
Create field_types specificationfield_types
Create field_types_advanced specificationfield_types_advanced
Types of data fields available for specificationfield_types_available ft_categorical ft_datetime ft_freetext ft_ignore ft_numeric ft_simple ft_strata ft_timepoint ft_uniqueidentifier
Initialise a log fileinitialise_log
Prepare source dataprepare_data
Read delimited data for optimal use with daiquiriread_data
Generate report from existing objectsreport_data
Print a template field_types() specification to consoletemplate_field_types