From social science to data science / Bernie Hogan.

Includes bibliographical references and index.

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).

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. -- Provided by publisher.