Python for Data Mining Quick Syntax Reference / by Valentina Porcu.

By:

Porcu, Valentina

Material type: Text

TextPublisher: Berkeley, CA : Apress : Imprint: Apress, 2018Edition: 1st ed. South Asian EditionDescription: xv, 260p ; 23.3 cmContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781484241134

Subject(s):

Additional physical formats: Print version:: Python for data mining quick syntax reference; Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

005.762 1 PORV

Contents:

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.

Summary: 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.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Status	Barcode
Book	St Aloysius Institute of Management & Information Technology	MCA	005.762 PORV (Browse shelf(Opens below))	Available	MCA17079

Total holds: 0

Browsing St Aloysius Institute of Management & Information Technology shelves, Collection: MCA Close shelf browser (Hides shelf browser)

Previous								Next
Previous	005.762 PALS Pattern recognition algorithms for data mining : scalability knowledge discovery and soft granular computing /	005.762 PALS Pattern recognition algorithms for data mining : scalability knowledge discovery and soft granular computing /	005.762 PALS Pattern recognition algorithms for data mining : scalability knowledge discovery and soft granular computing /	005.762 PORV Python for Data Mining Quick Syntax Reference /	005.762 PRAS Data mining and warehousing.	005.762 PUDV Data mining /	005.762 PUDV Data mining /	Next

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.

Description based on publisher-supplied MARC data.

There are no comments on this title.

to post a comment.