datacheck-package: Check a table against a set of constraints or rules defined...

In datacheck: Tools for Checking Data Consistency

Description

The rules can be written in standard R syntax. A rule must contain the names of 'columns' or variables present in the table and use R operators or simple functions. If not, the rule will simply be ignored. Each line must 'test' one rule and return a vector of boolean values as many as the table has rows. Rules must not contain an assignment. The set of rules is simply defined as a set of R statements and can be mixed with empty lines and comments. Comments after a rule will be used for summarizing rule check results in a table and should therefore be short - usually short names. This allows to visually organize rules in a file and also document them. One may put more extensive comments just before the rule and add a short name or comment on the same line after it. This also allows to use standard R editors for development of the rules.

Details

A simple score is calculated based on the number of rules a datapoint (= table cell) complies with. Like in a school test only the number of correct answers (or rule compliances) are counted. Summaries of scores by row (record) and column (variable) are added to a score data frame.

The table itself must be a simple dataframe or .csv file.

The package includes a simple graphical user interface as a web page. This can be started with run_datacheck(). This interface shows summaries of the checks by rule and by record. The score table can be 'downloaded'. The user interface is meant as an easy way to get to know the package. All results can be also created using the command line interface of R.

The main function and the principal example can be found under datadict_profile.

Several helper functions like is_proper_name or is_only_lowers are for convenience and illustration on how to express rules more clearly or succinct.

datacheck documentation built on May 2, 2019, 4:52 a.m.