Data Preparation and Producing Analysis-Ready Data with R
Covers, through hands-on practice, importing data from different sources into the R environment, cleaning and standardising it, and documenting it with a data dictionary to make it ready for analysis.
Training content
- Importing data from data sources (CSV/Excel/SQL)
- Data types
- Missing value and duplicate record management
- Data transformation
- Standardization
- Data dictionary (codebook) logic
- Producing an analysis-ready data package
At the end of this training, participants
- Will be able to import data from different sources into the R environment using the correct method.
- Will be able to detect missing, erroneous and duplicate records in datasets and correct them appropriately.
- Will be able to build a data structure suitable for analysis processes by correctly defining variable types.
- Will be able to make data quality traceable at an institutional scale by producing a data dictionary using standardization and coding logic.
- Will be able to institutionalise the difference between raw data and analysis-ready data in terms of process and documentation.
As a result, participants will be able to apply a repeatable and auditable “analysis preparation” workflow.