Data cleaning for statistical purpose
Repositories
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errorlocate
Find and replace erroneous fields in data using validation rules
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ValidatReport
Standard validation report structure for the ESS
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lintools
Tools for manipulating systems of linear (in)equalities
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ISM2020_tutorial
Data Cleaning for Official Statistics
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book
Resources for Statistical Data Cleaning with Applications in R
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useR2020_tutorial
Materials for the useR2020 tutorial on Statistical Data Cleaning with R
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EESW2019_tutorial
Materials for the short course at the European Establishment Statistics Workshop 2019
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useR2019_tutorial
Tutorial for useR2019
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uRos2019_tutorial
Tutorial materials for uRos 2019
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validatereport
Create attractive validation reports, export validation results to ESS json reporting standard
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dirtyharry
Make your data dirty
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Madrid2019
Slides and exercises for Mark's visit to the Complutense University of Madrid and INE
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dcmodify
Modify data records using separately defined modification rules
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editrules
R package for handling, checking and enforcing data rules
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uRos2018_tutorial
Data-Cleaning tutorial for Use of R in Official Statistics
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drat
Beta versions of data-cleaning packages
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datacleaning
Load and install multiple R packages for data cleaning
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ValidatPoC
Rules and data for the PoC of the ESSnet on Validation
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graphics
Some graphics and logos to use in presentations
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deducorrect
An R package for rule-based record correction and imputation
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data.log Archived
Logging framework for data cleaning
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validate.adjust
Adjust numerical records to satisfy linear (in)equality restrictions
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validate.viz
visualisations for the R package validate