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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

8,478

Version

0.8.0

License

MIT + file LICENSE

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Maintainer

Richard Iannone

Last Published

July 25th, 2021

Functions in pointblank (0.8.0)

activate_steps

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

Put the current date-time into a file name
action_levels

Set action levels: failure thresholds and functions to invoke
col_exists

Do one or more columns actually exist?
col_is_date

Do the columns contain R Date objects?
col_is_factor

Do the columns contain R factor objects?
all_passed

Did all of the validations fully pass?
affix_date

Put the current date into a file name
col_is_character

Do the columns contain character/string data?
col_is_integer

Do the columns contain integer values?
col_is_posix

Do the columns contain POSIXct dates?
col_vals_gt

Are column data greater than a fixed value or data in another column?
col_vals_expr

Do column data agree with a predicate expression?
col_schema

Generate a table column schema manually or with a reference table
col_schema_match

Do columns in the table (and their types) match a predefined schema?
col_vals_between

Do column data lie between two specified values or data in other columns?
col_is_numeric

Do the columns contain numeric values?
col_is_logical

Do the columns contain logical values?
col_vals_equal

Are column data equal to a fixed value or data in another column?
col_vals_decreasing

Are column data decreasing by row?