LEADER 03900nam  22005895  450 
001 9910483059603321
005 20250610110437.0
010   $a3-030-36826-2
024 7 $a10.1007/978-3-030-36826-5
035   $a(CKB)4920000000496078
035   $a(DE-He213)978-3-030-36826-5
035   $a(MiAaPQ)EBC6184653
035   $a(PPN)243762852
035   $a(MiAaPQ)EBC29090547
035   $a(EXLCZ)994920000000496078
100   $a20200422d2020      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aComputational Frameworks for Political and Social Research with Python /$fby Josh Cutler, Matt Dickenson
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (XV, 209 p. 18 illus.) 
225 1 $aTextbooks on Political Analysis,$x2522-0373
311 08$a3-030-36825-4 
327   $aChapter 1. Getting Started With Python -- Chapter 2. Building Software -- Chapter 3. Object-Oriented Programming -- Chapter 4. Introduction to Algorithms -- Chapter 5. Introduction to Data Structures -- Chapter 6. Input, Output, and the Web -- Chapter 7. Application Programming Interfaces -- Chapter 8. Databases -- Chapter 9. NoSQL Databases -- Chapter 10. Introduction to Machine Learning with Python -- Chapter 11. Linear Programming -- Chapter 12. Practical Programming -- Chapter 13. Case Study: Image Processing -- Chapter 14. Case Study: Natural Language Processing -- Chapter 15. Conclusion.
330   $aThis book is intended to serve as the basis for a first course in Python programming for graduate students in political science and related fields. The book introduces core concepts of software development and computer science such as basic data structures (e.g. arrays, lists, dictionaries, trees, graphs), algorithms (e.g. sorting), and analysis of computational efficiency. It then demonstrates how to apply these concepts to the field of political science by working with structured and unstructured data, querying databases, and interacting with application programming interfaces (APIs). Students will learn how to collect, manipulate, and exploit large volumes of available data and apply them to political and social research questions. They will also learn best practices from the field of software development such as version control and object-oriented programming. Instructors will be supplied with in-class example code, suggested homework assignments (with solutions), and material for practical lab sessions.
410  0$aTextbooks on Political Analysis,$x2522-0373
606   $aStatistics
606   $aPolitical science
606   $aSocial sciences
606   $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040
606   $aPolitical Science and International Relations, general$3https://scigraph.springernature.com/ontologies/product-market-codes/900000
606   $aMethodology of the Social Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/X17000
615  0$aStatistics.
615  0$aPolitical science.
615  0$aSocial sciences.
615 14$aStatistics for Social Sciences, Humanities, Law.
615 24$aPolitical Science and International Relations, general.
615 24$aMethodology of the Social Sciences.
676   $a005.133
700   $aCutler$b Josh$4aut$4http://id.loc.gov/vocabulary/relators/aut$01013802
702   $aDickenson$b Matt$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483059603321
996   $aComputational Frameworks for Political and Social Research with Python$92359379
997   $aUNINA