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pointblank (version 0.12.1)

Data Validation and Organization of Metadata for Local and Remote Tables

Description

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.

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install.packages('pointblank')

Monthly Downloads

12,086

Version

0.12.1

License

MIT + file LICENSE

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Last Published

March 25th, 2024

Functions in pointblank (0.12.1)

affix_datetime

Put the current datetime into a file name
col_is_date

Do the columns contain R Date objects?
all_passed

Did all of the validations fully pass?
action_levels

Set action levels: failure thresholds and functions to invoke
col_is_factor

Do the columns contain R factor objects?
affix_date

Put the current date into a file name
activate_steps

Activate one or more of an agent's validation steps
col_exists

Do one or more columns actually exist?
col_is_character

Do the columns contain character/string data?
col_count_match

Does the column count match that of a different table?