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Python for Data Mining ­Quick Syntax Reference

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Format
Paperback, 260 pages
Published
United States, 1 December 2018


¿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


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Product Description


¿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


Show more
Product Details
EAN
9781484241127
ISBN
1484241126
Publisher
Other Information
Illustrated
Dimensions
23.4 x 15.6 x 1.5 centimeters (0.33 kg)

Table of 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.

About the Author

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.

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