Python for Data Mining Quick Syntax Reference - Valentina Porcu

Python for Data Mining Quick Syntax Reference

(Autor)

Buch | Softcover
260 Seiten
2018 | 1st ed.
Apress (Verlag)
978-1-4842-4112-7 (ISBN)
29,95 inkl. MwSt
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.
​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.

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.

1. Getting Started.- 2. Introductory Notions.- 3. Basic Objects and Structures.- 4. Functions.- 5. Conditional Instructions and Writing Functions.- 6. Other Basic Concepts.- 7. Importing Files.- 8. pandas.- 9. SciPy and NumPy.- 10. Matplotlib.- 11. scikit-learn.

Erscheinungsdatum
Zusatzinfo 80 Illustrations, black and white; XV, 260 p. 80 illus.
Verlagsort Berkley
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Programmiersprachen / -werkzeuge Python
Mathematik / Informatik Informatik Web / Internet
Schlagworte Data • Functions • machine learning • matplotlib • NumPy • object-oriented programming • objects • OOP • Pandas • scikit-learn • SciPy
ISBN-10 1-4842-4112-6 / 1484241126
ISBN-13 978-1-4842-4112-7 / 9781484241127
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
Datenanalyse für Künstliche Intelligenz

von Jürgen Cleve; Uwe Lämmel

Buch | Softcover (2024)
De Gruyter Oldenbourg (Verlag)
74,95
Auswertung von Daten mit pandas, NumPy und IPython

von Wes McKinney

Buch | Softcover (2023)
O'Reilly (Verlag)
44,90