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Python for data mining quick syntax ...

Porcu, Valentina.

Python for data mining quick syntax reference

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Python for data mining quick syntax reference/ by Valentina Porcu.
Author:	Porcu, Valentina.
Published:	Berkeley, CA :Apress : : 2018.,
Description:	xv, 260 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Python (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-4113-4
ISBN:	9781484241134

Python for data mining quick syntax reference
Porcu, Valentina.

Python for data mining quick syntax reference[electronic resource] /by Valentina Porcu. - Berkeley, CA :Apress :2018. - xv, 260 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9781484241134

Standard No.: 10.1007/978-1-4842-4113-4doiSubjects--Topical Terms:

566246
Python (Computer program language)

LC Class. No.: QA76.9.D343 / P673 2018

Dewey Class. No.: 006.312

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245 1 0 $a Python for data mining quick syntax reference $h [electronic resource] / $c by Valentina Porcu.
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300 $a xv, 260 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
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950 $a Professional and Applied Computing (Springer-12059)

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