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References

Published online by Cambridge University Press:  15 September 2017

Jose Manuel Magallanes Reyes
Jose Manuel Magallanes Reyes
Affiliation:
University of Washington and Pontificia Universidad Católica del Perú
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Introduction to Data Science for Social and Policy Research
Collecting and Organizing Data with R and Python
 , pp. 299 - 300
Publisher: Cambridge University Press
Print publication year: 2017

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References

Allison, Paul David. 2002. Missing dat. Sage university papers. Quantitative applications in the social science. nos. 07–136. Thousand Oaks, CA: SAGE.
Allison, Paul Davi. 2014. Event history and survival analysi. Second edition. Quantitative applications in the social science. nos. 07–46. Los Angeles: SAGE.
ANE. 2014. Users guide and codebook for the ANES 2012 Time Series Stud. Ann Arbor, MI and Palo Alto, CA: University of Michigan and Stanford University.
Arel-Bundock, Vincen. 2013 (Aug.). WDI: World Development Indicator. Washington, DC: World Bank.
Arnold, Ti. 2014 (Nov.). Manipulating PDFs with Python | Python.
Bivand, Roge. Pebesma, Edzer J. and Gāmez-Rubio, Virgili. 2013. Applied Spatial data analysis with. Second editio. New York: Springer. OCLC: ocn857289562.
Box-Steffensmeier, Janet M. and Jones, Bradford S. 2004. Event history modeling: A guide for social scientist. New York: Cambridge University Press.
Brunsdon, Chri. and Comber, Le. 2015. An introduction to R for spatial analysis & mappin. Los Angeles: SAGE. OCLC: ocn904424364.
Chrisman, Nicholas R. 1998. Rethinking Levels of Measurement for Cartography. Cartography and geographic information science, 25(4), 231–242.Google Scholar
Danneman, Natha. and Heimann, Richar. 2014. Social media mining with. Birmingham, UK: Packt Publishing.
Davidson-Pilon, Camero. 2015. Lifelines: Survival analysis in Python.
DeBell, Matthe. 2010. How to analyze ANES survey dat. Tech. rep. nes012492. Palo Alto, CA, and Ann Arbor,MI: Stanford University and the University of Michigan.
Duck, Mat. 2013 (Oct.). wbpy. wbpy - Python interface to the World Bank Indicators and Climate APIs. https://github.com/mattduck/wbpy
Elff, Marti. 2015 (Mar.). Tools for management of survey data, graphics, programming, statistics, and simulation. Package ‘memisc’. https://cran.r-project.org/web/packages/memisc/index.html.
European Commission, Organisation for Economic Co-operation and Development, and SourceOECD (Online service) (eds). 2008. Handbook on constructing composite indicators: Methodology and user guid. Paris: OECD.
Feinerer, Ing. Hornik, Kur. and Software, Artifex, and GPL Ghostscript, Inc (pdf_info ps taken from. 2015 (July). tm: Text Mining Package.
Figueroa, Adolf. 2008. Competition and circulation of economic elites: Theory and application to the case of Peru. Quarterly Review of Economics and Finance, 48(2), 263–273.Google Scholar
Forta, Be. 2000. Sams teach yourself regular expressions in 10 minute. Indianapolis, Ind: Sams.
Garrard, Chri. 2016. Geoprocessing with Pytho. Shelter Island, NY: Manning Publications. OCLC: ocn915498655.
Goyvaerts, Ja. and Levithan, Steve. 2012. Regular expressions cookboo. Second editio. Beijing: O'Reilly.
Grolemund, Garret. Spinu, Vitali. and Wickham, Hadle. 2016 (Sept.). Make dealing with dates a little easier [R package lubridate version 1.6.0].
Lawhead, Joe. 2015. Learning geospatial analysis with Python: An effective guide to geographic information system and remote sensing analysis using Python. Birmingham, UK: Packt Publishing. OCLC: 934039792.
Lawson, Richar. 2015.Web scraping with Python..Birmingham, UK: Packt Publishing.
Levenshtein, V. I. 1966. Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet physics doklady, 10(Feb.), 707.Google Scholar
Mitchell, Rya. 2015.Web scraping with Python: Collecting data from the modern we. Beijing: O'Reilly.
Mosteller, Frederic. and Tukey, John Wilde. 1977. Data analysis and regression: A second course in statistic. Addison-Wesley Series in Behavioral Scienc. Reading, MA: Addison-Wesley.
Munzert, Simo. 2014. Automated data collection with R: A practical guide to Web scraping and text minin. Chichester, UK: John Wiley & Sons.
R Core Team. 2015 (Aug.). Read data stored by Minitab, S, SAS, SPSS, Stata, Systat, Weka, dBase, …
Raghunathan, Trivellor. 2015. Missing data analysis in practic. Boca Raton, FL: CRC Press.
Ram, Karthi. 2015 (July). rdrop2: Programmatic interface to the ‘Dropbox’ API.
Richardson, Leonar. 2015 (Nov.). Beautiful Soup.
Rubba, Christia. 2016 (May). htmltab: Assemble data frames from HTML tables.
Ryan, Jeffrey A. and Ulrich, Joshua M. 2014 (Jan.). xts: eXtensible time series.
Sherouse, Olive. 2014 (May). wbdata.
Simon, Herbert A. 1996. The sciences of the artificia. Cambridge, MA: MIT Press.
Solon, Gar. Haider, Steve. and Wooldridge,, Jeffre. 2013 (Feb.). What are we weighting for. Tech. Rep. #18859. Bureau of Economic Research, Cambridge, MA.
Stevens, S. S.194. On the theory of scales of measurement. Science, 103(2684), 677– 680.
Temple Lang, Dunca. and CRAN team. 2015a (June). RCurl: General network (HTTP/FTP/…) client interface for R.
Temple Lang, Dunca. and CRAN Team. 2015b (June). XML: Tools for parsing and generating XML within R and S-Plus.
Velleman, Paul F. and Wilkinson, Lelan. 1993. Nominal, Ordinal, Interval, and Ratio Typologies Are Misleading. American statistician, 47(1), 65.Google Scholar

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  • References
  • Jose Manuel Magallanes Reyes
  • Book: Introduction to Data Science for Social and Policy Research
  • Online publication: 15 September 2017
  • Chapter DOI: https://doi.org/10.1017/9781316338599.008
Available formats
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Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Jose Manuel Magallanes Reyes
  • Book: Introduction to Data Science for Social and Policy Research
  • Online publication: 15 September 2017
  • Chapter DOI: https://doi.org/10.1017/9781316338599.008
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Jose Manuel Magallanes Reyes
  • Book: Introduction to Data Science for Social and Policy Research
  • Online publication: 15 September 2017
  • Chapter DOI: https://doi.org/10.1017/9781316338599.008
Available formats
×