PostgreSQL 10 High Performance - Third Edition: Expert techniques for query optimization, high availability, and efficient database maintenance

Pirozzi, Enrico, Ibrar Ahmed und Gregory Smith:

ISBN 10: 1788474481 / ISBN 13: 9781788474481

Edité par Packt Publishing, 2018

A propos de cet article

Seiten; 9781788474481.3 Gewicht in Gramm: 1.

N° de réf. du vendeur 696969

Détails bibliographiques

• Titre: PostgreSQL 10 High Performance - Third Edition: Expert techniques for query optimization, high availability, and efficient database maintenance
• Éditeur: Packt Publishing
• Date de parution: 2018
• Langue: anglais
• ISBN à 10 chiffres: 1788474481
• ISBN à 13 chiffres: 9781788474481
• Reliure: paperback
• Édition: 3ème Édition
• État de l'article: Gut
• Catalogues du vendeur:
  • Varia

A propos de ce titre

Synopsis

Acquire and analyze data from all corners of the social web with Python

Key Features

• Make sense of highly unstructured social media data with the help of the insightful use cases provided in this guide
• Use this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social data
• This is your one-stop solution to fetching, storing, analyzing, and visualizing social media data

Book Description

Your social media is filled with a wealth of hidden data - unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights.

This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data.

Style and approach

This practical, hands-on guide will help you learn everything you need to perform data mining for social media. Throughout the book, we take an example-oriented approach to use Python for data analysis and provide useful tips and tricks that you can use in day-to-day tasks.

What You Will Learn

• Interact with a social media platform via their public API with Python
• Store social data in a convenient format for data analysis
• Slice and dice social data using Python tools for data science
• Apply text analytics techniques to understand what people are talking about on social media
• Apply advanced statistical and analytical techniques to produce useful insights from data
• Build beautiful visualizations with web technologies to explore data and present data products

Who This Book Is For

This book is for intermediate Python developers who want to engage with the use of public APIs to collect data from social media platforms and perform statistical analysis in order to produce useful insights from data. The book assumes a basic understanding of the Python Standard Library and provides practical examples to guide you toward the creation of your data analysis project based on social data.

À propos des auteurs

Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a PhD in information retrieval from Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems. He maintains a personal blog at http

//marcobonzanini.com, where he discusses different technical topics, mainly around Python, text analytics, and data science. When not working on Python projects, he likes to engage with the community at PyData conferences and meet-ups, and he also enjoys brewing homemade beer.