Data Quality Assessment for Process-Oriented Data


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Documentation for package ‘daqapo’ version 0.3.1

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daqapo daqapo - Data Quality Assessment for Process-oriented Data
detect_activity_frequency_violations Check activity frequencies
detect_activity_order_violations Detect activity order violations
detect_activity_order_violations.activitylog Detect activity order violations
detect_attribute_dependencies Detect dependency violations between attributes
detect_case_id_sequence_gaps Detect gaps in case_id
detect_conditional_activity_presence Detect conditional activity presence violations
detect_duration_outliers Detect activity duration outliers
detect_inactive_periods Detect inactive periods
detect_incomplete_cases Detect incomplete cases
detect_incorrect_activity_names Detect incorrect activity names
detect_missing_values Detect missing values
detect_multiregistration Detect multi-registration
detect_overlaps Detect overlapping acitivity instances
detect_related_activities Detect missing related activities
detect_similar_labels Search for similar labels in a column
detect_time_anomalies Detect time anomalies
detect_unique_values Search for unique values / distinct combinations
detect_value_range_violations Detect value range violations
domain_categorical Define allowable range of values
domain_numeric Define allowable range of values
domain_time Define allowable time range
duration_within Define bounds for activity duration
filter_anomalies Filter anomalies from the activity log
fix Fix problems
hospital An activity log of 20 patients in a hospital (data frame)
hospital_actlog An activity log of 20 patients in a hospital (activity log object)
hospital_events An event log of 20 patients in a hospital