Higher Ed. and Vocational >> Engineering and Computer Science >> Computer Science >> Computer Science


Pandas for Everyone: Pandas for Everyone

Pandas for Everyone:   Pandas for Everyone

Author(s):
  • Daniel Y Chen
  • Author: Daniel Y Chen
    • ISBN:9789352869169
    • 10 Digit ISBN:9352869168
    • Price:Rs. 579.00
    • Pages:416
    • Imprint:Pearson Education
    • Binding:Paperback
    • Status:Available


    Be the first to rate the book !!

    This tutorial teaches students everything they need to get started with Python programming for the fast-growing field of data analysis. Daniel Chen tightly links each new concept with easy-to-apply, relevant examples from modern data analysis.


    Unlike other beginner's books, this guide helps today's newcomers learn both Python and its popular Pandas data science toolset in the context of tasks they'll really want to perform. Following the proven Software Carpentry approach to teaching programming, Chen introduces each concept with a simple motivating example, slowly offering deeper insights and expanding your ability to handle concrete tasks.

     

    Table of Content

    Part I: Introduction
    Part II: Data Manipulation
    Part III: Data Munging
    Part IV: Data Modeling
    Part V: Conclusion
    Part VI: Appendixes
    Appendix A: Installation
    Appendix B: Command Line
    Appendix C: Project Templates
    Appendix D: Using Python
    Appendix E: Working Directories
    Appendix F: Environments
    Appendix G: Install Packages
    Appendix H: Importing Libraries
    Appendix I: Lists
    Appendix J: Tuples
    Appendix K: Dictionaries
    Appendix L: Slicing Values
    Appendix M: Loops
    Appendix N: Comprehensions
    Appendix O: Functions
    Appendix P: Ranges and Generators
    Appendix Q: Multiple Assignment
    Appendix R: numpy ndarray
    Appendix S: Classes
    Appendix T: Odo: The Shapeshifter

    Salient Features

    Establishes a solid foundation for all the Pandas basics needed to be effective
    Covers dataframes, statistical calculations, data munging, modeling, machine learning, reproducible documents, and much more
    Teaches step-by-step through easy, incremental examples, with plenty of opportunities to ""code along"""