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: |
0.12.1 |
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, covr, crayon, data.table, duckdb, ggforce, ggplot2, jsonlite, log4r, lubridate, RSQLite, RMySQL, RPostgres, readr, rmarkdown, sparklyr, dittodb, odbc |
Published: |
2024-03-25 |
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 |