Introduction to Python Programming for Business and Social Science Applications
- Frederick Kaefer - Loyola University Chicago, USA
- Paul Kaefer - Carrot Health
Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python.
First there was IBM® SPSS®, then there was R, and now there's Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.
Data files, Python code files, and SCU exercises and solutions are available on an accompanying website.
“The text explains how to set up and program in Python language from the very basic in an easy-to-read manner with lots of graphical illustrations and example-based approaches. Clear learning objectives in the beginning of each chapter with tips and know-hows, concluding with the chapter exercises and references are very well structured for the first-time programmers without scientific backgrounds.”
“The organization is good, and the range of topics is very adaptable to courses.”
“Explains the code line by line, great examples, code is simple and clear, coverage is relevant.”
“Practical examples, content organized around practical use, clear and non-technical language.”
Sample Materials & Chapters
Chapter 1 • Introduction to Python
Chapter 2 • Building Blocks of Programming