Data Quality Reporting for Temporal Datasets
Aggregate source data
Close any active log file
Create a data quality report from a data frame
daiquiri: Data Quality Reporting for Temporal Datasets
Export aggregated data
Create field_types_advanced specification
Types of data fields available for specification
Create field_types specification
Initialise a log file
Prepare source data
Read delimited data for optimal use with daiquiri
Generate report from existing objects
Print a template field_types() specification to console
Generate reports that enable quick visual review of temporal shifts in record-level data. Time series plots showing aggregated values are automatically created for each data field (column) depending on its contents (e.g. min/max/mean values for numeric data, no. of distinct values for categorical data), as well as overviews for missing values, non-conformant values, and duplicated rows. The resulting reports are shareable and can contribute to forming a transparent record of the entire analysis process. It is designed with Electronic Health Records in mind, but can be used for any type of record-level temporal data (i.e. tabular data where each row represents a single "event", one column contains the "event date", and other columns contain any associated values for the event).
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