Hogan, Bernie creator author. text bibliography cau 2023 monographic eng

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xxxiv, 361 pages : illustrations (chiefly color) ; 26 cm From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python. From beginning to end, this book will enable you to understand merging, accessing, cleaning and interpreting data whilst gaining a deeper understanding into computational techniques and seeing the bigger picture. With key features such as tables, figures, step-by-step instruction and explanations giving a wider context, Hogan presents a clear and concise analysis on key data collection and skills in Python. -- Part I. Thinking programmatically -- Introduction: thinking of life at scale -- The series: taming the distribution -- The data frame: python's tabular format -- Part II. Accessing and converting data -- File types: getting data in -- Merging and grouping data -- Accessing data on the world wide web using code -- Accessing APIs, including twitter and reddit -- Part III. Interpreting data: expectations versus observations -- Research questions -- Visualizing expectations: comparing statistical tests and plots -- Part IV. Social data science in practice: four approaches -- Cleaning data for socially interesting features -- Introducing natural language processing: cleaning, summarizing, and classifying text -- Introducing time-series data: showing periods and trends -- Introducing network analysis: structuring relationships -- Introducing geographic information systems: data across space and place -- Conclusion: there (to do science) and back again (to social science). Bernie Hogan. Includes bibliographical references and index. Social sciences Research Data processing Data mining Python (Computer program language) Python (Computer program language) Social sciences Research Data processing H62 .H64 2023 300.72 H678f 9781529707489 2022938266 YDX 220509 20250717093812.0 22540304 eng