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Data Validation and Organization of Metadata for Local and Remote Tables

Installation

About

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.

rstudio.github.io/pointblank/
github.com/rstudio/pointblank
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Key Metrics

Version 0.12.1
R ≥ 3.5.0
Published 2024-03-25 24 days ago
Needs compilation? no
License MIT
License File
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Maintainer

Maintainer

Richard Iannone

rich@posit.co

Authors

Richard Iannone

aut / cre

Mauricio Vargas

aut

June Choe

aut

Material

NEWS
Reference manual
Package source

In Views

Databases

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

pointblank archive

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

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