Much training in quantitative social science focuses on data analysis and fails to equip researchers with the skills to prepare the data required for this. This book is a comprehensive introduction to simple and advanced tools for data management, drawing on established concepts and techniques from computer science.
Much training in quantitative social science focuses on data analysis and fails to equip researchers with the skills to prepare the data required for this. This book is a comprehensive introduction to simple and advanced tools for data management, drawing on established concepts and techniques from computer science.
Nils B. Weidmann is Professor of Political Science at the University of Konstanz.
Inhaltsangabe
Part I. Introduction: 1. Motivation 2. Gearing up 3. Data = content + structure Part II. Data in Files: 4. Storing data in files 5. Managing data in spreadsheets 6. Basic data management in R 7. R and the tidyverse Part III. Data in Databases: 8. Introduction to relational databases 9. Relational databases and multiple tables 10. Database fine-tuning Part IV. Special Types of Data: 11. Spatial data 12. Text data 13. Network data Part V. Conclusion: 14. Best practices in data management.
Part I. Introduction: 1. Motivation 2. Gearing up 3. Data = content + structure Part II. Data in Files: 4. Storing data in files 5. Managing data in spreadsheets 6. Basic data management in R 7. R and the tidyverse Part III. Data in Databases: 8. Introduction to relational databases 9. Relational databases and multiple tables 10. Database fine-tuning Part IV. Special Types of Data: 11. Spatial data 12. Text data 13. Network data Part V. Conclusion: 14. Best practices in data management.
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