![]() Summarizing, the basic workflow in validate is to create a rule set, confrontĪ data set with the rules in the rule set, and then analyze or use the resultsįurther. Negatives caused machine rounding issues. That validate left a bit of slack when executing the rule, to avoid false We see that in record 1, rule V1, was satisfied (the result is TRUE), and We can extract all individual resuls results using for example as.ame. We select only the first three results because the last rule can Using the function violating we can select the records that violate one or Hence there are 151 validation results in total. Three rules yield 50 results each, while the last rule yields a single result. Passes and Missings, summed over all checks. The table in the legend lists the total number of Fails, In this plot each horizontal bar indicates the percentage of Failing, Passing,Īnd Missing cases. The same information can be summarized graphically as follows The expression that was actually evaluated to perform the check.Whether the check resulted in an error (could not be performed) or gave an warning.How many items passed, failed or resulted in NA. ![]()
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