Validate data in data frames, 'tibble' objects, 'Spark' 'DataFrames', and database tables. Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions. Many other workflows are available including an information management workflow, where the aim is to record, collect, and generate useful information on data tables.
Version: 0.12.2 Depends: R (≥ 3.5.0) Imports: base64enc (≥ 0.1-3), blastula (≥ 0.3.3), cli (≥ 3.6.0), DBI (≥ 1.1.0), digest (≥ 0.6.27), dplyr (≥ 1.0.10), dbplyr (≥ 2.3.0), fs (≥ 1.6.0), glue (≥ 1.6.2), gt (≥ 0.9.0), htmltools (≥ 0.5.4), knitr (≥ 1.42), rlang (≥ 1.0.3), magrittr, scales (≥ 1.2.1), testthat (≥ 3.1.6), tibble (≥ 3.1.8), tidyr (≥ 1.3.0), tidyselect (≥ 1.2.0), yaml (≥ 2.3.7) Suggests: arrow, bigrquery, data.table, duckdb, ggforce, ggplot2, jsonlite, log4r, lubridate, RSQLite, RMySQL, RPostgres, readr, rmarkdown, sparklyr, dittodb, odbc Published: 2024-10-23 DOI: 10.32614/CRAN.package.pointblank Author: Richard Iannone [aut, cre], Mauricio Vargas [aut], June Choe [aut] Maintainer: Richard Iannone <rich at posit.co> BugReports: https://github.com/rstudio/pointblank/issues License: MIT + file LICENSE URL: https://rstudio.github.io/pointblank/, https://github.com/rstudio/pointblank NeedsCompilation: no Materials: NEWS In views: Databases CRAN checks: pointblank results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=pointblank to link to this page.
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