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Introduction to Data Science for Social and Policy Research: Collecting and Organizing Data with R and Python - Rilegato
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This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
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Informazioni sull'autore
Jose Manuel Magallanes Reyes has degrees in Computer Science, Public Management and Psychology. He has a second Ph.D. (Computational Social Science) from George Mason University, where he is an Affiliated Researcher at the Center for Social Complexity (GMU-CSC). He is currently Associate Professor at the Department of Social Sciences at Pontificia Universidad Católica del Perú; while also a Senior Data Science Fellow (eScience Institute), and a Visiting Professor (Evans School) at the University of Washington. He is a Catalyst Fellow at the University of California, Berkeley Initiative for the Transparency in the Social Sciences. His interdisciplinary work has been funded by the National Science Foundation via the CDI Program grant no. IIS-1125171 (granted by GMU-CSC), and via the EITM program (granted by Duke University in 2017). Since 2015, his work is funded by the Washington Research Fund, the Alfred P. Sloan Foundation, and the Gordon and Betty Moore Foundation (granted by the eScience Institute).
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Introduction to Data Science for Social and Policy Research: Collecting and Organizing Data with R and Python
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Cambridge University Press, 2017
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ISBN 13: 9781107117419
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Introduction to Data Science for Social and Policy Research: Collecting and Organizing Data with R and Python
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Introduction to Data Science for Social and Policy Research: Collecting and Organizing Data with R and Python
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Introduction to Data Science for Social and Policy Research: Collecting and Organizing Data with R and Python
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Introduction to Data Science for Social and Policy Research
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Real-world data sets are messy and complicated. This book shows students in social science and public management how to prepare these data sets for analysis, with detailed, step-by-step instructions. R and Python code is introduced gradually, providing read. Codice articolo 447216081
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Hardcover. Condizione: new. Hardcover. Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience. Real-world data sets are messy and complicated. This book shows students in social science and public management how to prepare these data sets for analysis, with detailed, step-by-step instructions. R and Python code is introduced gradually, providing readers with the tools they need to work with real data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781107117419
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