Introduction to Python programming for business and social science applications

By: Kaefer, Frederick
Contributor(s): Kaefer, Paul [Co-author]
Material type: TextTextPublisher: Thousand Oaks Sage Publications 2021Description: xxiv, 365 p.: ill. Includes references and indexISBN: 9781544377445Subject(s): Business enterprises - Computer program | Python - Computer program language | Technical innovationDDC classification: 005.133 Summary: 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. https://in.sagepub.com/en-in/sas/introduction-to-python-programming-for-business-and-social-science-applications/book268933
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Slot 67 (0 Floor, West Wing) Non-fiction 005.133 K2I6 (Browse shelf) Checked out 06/02/2022 204039

Table of contents

Chapter 1 • Introduction to Python
Learning Objectives
Chapter 2 • Building Blocks of Programming
Learning Objectives
Chapter 3 • Further Foundations of Python Programming
Learning Objectives
Chapter 4 • Control Logic and Loops
Learning Objectives
Chapter 5 • Reading and Writing to Files Using Python
Learning Objectives
Chapter 6 • Preparing and Working With Data Using Pandas
Learning Objectives
Chapter 7 • Obtaining Data From the Web Using Python
Learning Objectives
Chapter 8 • Statistical Calculations Using Python
Learning Objectives
Chapter 9 • Data Visualization Using Python
Learning Objectives
Chapter 10 • Machine Learning and Text Mining
Learning Objectives
Chapter 11 • Developing Graphical User Interfaces With tkinter
Learning Objectives
References
Appendix A • Links to Other Resources
Appendix B • Debugging Using IDLE Debug Mode
Appendix C • Timing Code Execution

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.

https://in.sagepub.com/en-in/sas/introduction-to-python-programming-for-business-and-social-science-applications/book268933

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