Python for Data Mining Quick Syntax Reference
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Beschreibung
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.
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
Programmers new to Python's data mining packages or with experience in other languages, who want a quick guide to Pythonic tools and techniques.
A concise guide to common Python features and popular data mining tools including pandas, SciPy, NumPy, and Matplotlib Quick reference format offers readers essential information and brief explanations with many examples Includes scikit-learn and core machine learning concepts
Autor*in
Valentina Porcu
Themen in »Python for Data Mining Quick Syntax Reference«
data object-oriented programming OOP pandas SciPy NumPy Matplotlib objects functions scikit-learn machine learning