Big Data Analysis with Python: Combine Spark and Python to unlock the powers of parallel computing and machine learning


Big Data Analysis with Python: Combine Spark and Python to unlock the powers of parallel computing and machine learning
Authors: Ivan Marin - Ankit Shukla - Sarang VK
ISBN-10 书号: 1789955289
ISBN-13 书号: 9781789955286
Publisher Finelybook 出版日期: 2019-04-10
pages 页数: 276 pages
Publisher Finelybook 出版社: Packt


Book Description
More Information
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
About
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.
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
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

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