Package: daiquiri 1.1.1.9000
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:
daiquiri_1.1.1.9000.tar.gz
daiquiri_1.1.1.9000.zip(r-4.5)daiquiri_1.1.1.9000.zip(r-4.4)daiquiri_1.1.1.9000.zip(r-4.3)
daiquiri_1.1.1.9000.tgz(r-4.4-any)daiquiri_1.1.1.9000.tgz(r-4.3-any)
daiquiri_1.1.1.9000.tar.gz(r-4.5-noble)daiquiri_1.1.1.9000.tar.gz(r-4.4-noble)
daiquiri_1.1.1.9000.tgz(r-4.4-emscripten)daiquiri_1.1.1.9000.tgz(r-4.3-emscripten)
daiquiri.pdf |daiquiri.html✨
daiquiri/json (API)
NEWS
# Install 'daiquiri' in R: |
install.packages('daiquiri', repos = c('https://ropensci.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ropensci/daiquiri/issues
Pkgdown:https://docs.ropensci.org
data-qualityinitial-data-analysisreproducible-researchtemporal-datatime-series
Last updated 4 months agofrom:25a7b05a58 (on master). Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 01 2024 |
R-4.5-win | OK | Dec 01 2024 |
R-4.5-linux | OK | Dec 01 2024 |
R-4.4-win | OK | Dec 01 2024 |
R-4.4-mac | OK | Dec 01 2024 |
R-4.3-win | OK | Dec 01 2024 |
R-4.3-mac | OK | Dec 01 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
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Aggregate source data | aggregate_data |
Close any active log file | close_log |
Create a data quality report from a data frame | daiquiri_report |
Export aggregated data | export_aggregated_data |
Create field_types specification | field_types |
Create field_types_advanced specification | field_types_advanced |
Types of data fields available for specification | field_types_available ft_categorical ft_datetime ft_freetext ft_ignore ft_numeric ft_simple ft_strata ft_timepoint ft_uniqueidentifier |
Initialise a log file | initialise_log |
Prepare source data | prepare_data |
Read delimited data for optimal use with daiquiri | read_data |
Generate report from existing objects | report_data |
Print a template field_types() specification to console | template_field_types |