Python for Data Mining Quick Syntax Reference

1. Front Matter

   Pages i-xv

   PDF

2. Getting Started

   • Valentina Porcu

   Pages 1-11

3. Introductory Notes

   • Valentina Porcu

   Pages 13-26

4. Basic Objects and Structures

   • Valentina Porcu

   Pages 27-57

5. Functions

   • Valentina Porcu

   Pages 59-68

6. Conditional Instructions and Writing Functions

   • Valentina Porcu

   Pages 69-88

7. Other Basic Concepts

   • Valentina Porcu

   Pages 89-111

8. Importing Files

   • Valentina Porcu

   Pages 113-120

9. pandas

   • Valentina Porcu

   Pages 121-176

10. SciPy and NumPy

    • Valentina Porcu

    Pages 177-200

11. Matplotlib

    • Valentina Porcu

    Pages 201-234

12. Scikit-learn

    • Valentina Porcu

    Pages 235-253

13. Back Matter

    Pages 255-260

    PDF

​Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.

Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them. 



The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning.  


What You'll Learn

• Install Python and choose a development environment
  
• Understand the basic concepts of object-oriented programming
  
• Import, open, and edit files
  
• Review the differences between Python 2.x and 3.x

Who This Book Is For



Programmers new to Python's data mining packages or with experience in other languages, who want a quick guide to Pythonic tools and techniques.

• data
• object-oriented programming
• OOP
• pandas
• SciPy
• NumPy
• Matplotlib
• objects
• functions
• scikit-learn
• machine learning

• Nuoro, Italy

  Valentina Porcu

Valentina Porcu is a computer geek with a passion for data mining and research, and a Ph.D in communication and complex systems. She has years of experience in teaching in universities in Italy, France and Morocco, and online, of course! She works as consultant in the field of data mining and machine learning and enjoys writing about new technologies and data mining. She spent the last 9 years working as freelancer and researcher in the field of social media analysis, benchmark analysis and web scraping for database building, in particular in the field of buzz analysis and sentiment analysis for universities, startups and web agencies across UK, France, US and Italy. Valentina is the founder of Datawiring, a popular Italian data science resource.

Policies and ethics