Python for Data Mining Quick Syntax Reference
Nonfiction, Computers, Database Management, Programming, Programming Languages, General Computing
| Author: | Valentina Porcu | ISBN: | 9781484241134 |
| Publisher: | Apress | Publication: | December 19, 2018 |
| Imprint: | Apress | Language: | English |
| Author: | Valentina Porcu |
| ISBN: | 9781484241134 |
| Publisher: | Apress |
| Publication: | December 19, 2018 |
| Imprint: | Apress |
| Language: | English |
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.
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.
