This book is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work.

I Introduction to R
1. Basic R
2. Data Management
3. Data Visualization
4. Data Loading

II Models
5. Linear Models
6. Case Selection Based on Regressions
7. Panel Data
8. Logistic Models
9. Survival Models
10. Causal Inference

III Applications
11. Advanced Political Data Management
12. Web Mining
13. Quantitative Analysis of Political Texts
14. Networks
15. Principal Component Analysis
16. Maps and Spatial Data

This book is edited by Francisco Urdinez, Assistant Professor at the Institute of Political Science of the Pontifical Catholic University of Chile, and Andrés Cruz, Adjunct Instructor at the same institution. Most of the authors who contributed with chapters to this volume are political scientists affiliated to the Institute of Political Science of the Pontifical Catholic University of Chile, and many are researchers and collaborators of the Millennium Data Foundation Institute, an institution that aims at gathering, cleaning and analyzing public data to support public policy. Andrew Heiss is affiliated to Georgia State University Andrew Young School of Policy Studies and he joined this project contributing with a chapter on causal inference. Above all, all the authors are keen users of R.