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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NEWS

Peer review:

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

On CRAN:

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

20 exports 35 stars 2.85 score 66 dependencies 733 downloads

Last updated 2 months agofrom:9f3828e087 (on master)

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