Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Big Data Analysis with Python: Combine Spark and Python to unlock the powers of parallel computing and machine learning

Buy

Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python.

Key Features

  • Get a hands-on, fast-paced introduction to the Python data science stack
  • Explore ways to create useful metrics and statistics from large datasets
  • Create detailed analysis reports with real-world data

Book Description

Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems.

The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools.

By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs.

What you will learn

  • Use Python to read and transform data into different formats
  • Generate basic statistics and metrics using data on disk
  • Work with computing tasks distributed over a cluster
  • Convert data from various sources into storage or querying formats
  • Prepare data for statistical analysis, visualization, and machine learning
  • Present data in the form of effective visuals

Who this book is for

Big Data Analysis with Python is designed for Python developers, data analysts, and data scientists who want to get hands-on with methods to control data and transform it into impactful insights. Basic knowledge of statistical measurements and relational databases will help you to understand various concepts explained in this book.

Table of Contents

  1. The Python Data Science Stack
  2. Statistical Visualizations
  3. Working with Big Data Frameworks
  4. Diving Deeper with Spark
  5. Handling Missing Values and Correlation Analysis
  6. Exploratory Data Analysis
  7. Reproducibility in Big Data Analysis
  8. Creating a Full Analysis Report
(HTML tags aren't allowed.)

Practical Data Structures in C++
A Problem Book in Real Analysis (Problem Books in Mathematics)
A Problem Book in Real Analysis (Problem Books in Mathematics)

Today, nearly every undergraduate mathematics program requires at least one semester of real analysis. Often, students consider this course to be the most challenging or even intimidating of all their mathematics major requirements. The primary goal of A Problem Book in Real Analysis is to alleviate those concerns by systematically solving...

ITIL Version 3 at a Glance: Information Quick Reference
ITIL Version 3 at a Glance: Information Quick Reference
ITIL® Version 3 At a Glance takes a graphical approach to consolidating the information of ITIL® version 3. ITIL® is an internationally-recognized set of best practices for providing IT service management. IT organizations worldwide are implementing ITIL® as a vehicle for improving IT service quality and improve...

101 Boardroom Problems and How to Solve Them
101 Boardroom Problems and How to Solve Them
Before becoming a consultant on meetings and effective decision making, I was employed as an engineer. My motto then was: Silence is golden. Keeping quiet in meetings was safe and risk-free, and rarely did anyone solicit my ideas anyway. Had I shared my input, however, it might have improved the quality of my team’s decisions and reduced its...
Macroscopic Models for Vehicular Flows and Crowd Dynamics: Theory and Applications: Classical and Non–Classical Advanced Mathematics for Real Life Applications (Understanding Complex Systems)
Macroscopic Models for Vehicular Flows and Crowd Dynamics: Theory and Applications: Classical and Non–Classical Advanced Mathematics for Real Life Applications (Understanding Complex Systems)

This monograph presents a systematic treatment of the theory for hyperbolic conservation laws and their applications to vehicular traffics and crowd dynamics. In the first part of the book, the author presents very basic considerations and gradually introduces the mathematical tools necessary to describe and understand the mathematical models...

Modern Crop Protection Compounds
Modern Crop Protection Compounds
The leading reference on this topic has just gotten better. Building on the success of the previous two editions, all the chapters have been updated to reflect the latest developments in the field, and new chapters have been added on picolinic acids, oxathiapiprolin, flupyradifurone, and other topics.

This third edition
...
©2020 LearnIT (support@pdfchm.net) - Privacy Policy