clickR: Semi-automatic pre-processing of messy data with change tracking for integral dataset cleaning
Year: 2024
Type: software-paper
Abstract: In this contribution, we present clickR , an R package intended for data cleaning following a semi-automatic and supervised procedure. Few packages and commercial software with cleaning capacities are available. In all cases, their functionalities just cover part of the overall data pre-processing and do not follow an integral approach to cleaning up the data. In contrast, clickR brings together all functions needed for correcting the main structural, variable-assignment and typographical errors found in databases and allows researchers to have a strict control on the suggested changes. This is possible because the package creates a data frame that keeps track of all the implemented data modifications. To prove its capacity for detecting and fixing errors, we clean a messy database that exhibits multiple types of errors within date, numeric and factor variables.
Source: SoftwareX
Authors: David Hervas, David Fuente
Institution: Universitat Politècnica de València
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $970
OpenAlex ID: W4401871378