Big Data Analysis with Python: Combine Spark and Python to unlock the powers of parallel computing and machine learning
bGet to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python./b h4Key Features/h4 ul liGet a hands-on, fast-paced introduction to the Python data science stack /li liExplore ways to create useful metrics and statistics from large data...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2019
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| Ausgabe: | 1 |
| Schlagworte: | |
| Zusammenfassung: | bGet to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python./b h4Key Features/h4 ul liGet a hands-on, fast-paced introduction to the Python data science stack /li liExplore ways to create useful metrics and statistics from large datasets /li liCreate detailed analysis reports with real-world data /li /ul h4Book Description/h4 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. h4What you will learn/h4 ul liUse Python to read and transform data into different formats /li liGenerate basic statistics and metrics using data on disk /li liWork with computing tasks distributed over a cluster /li liConvert data from various sources into storage or querying formats /li liPrepare data for statistical analysis, visualization, and machine learning /li liPresent data in the form of effective visuals/li /ul h4Who this book is for/h4 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 |
| Beschreibung: | 1 Online-Ressource (276 Seiten) |
| ISBN: | 9781789950731 |
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| 520 | |a bGet to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python./b h4Key Features/h4 ul liGet a hands-on, fast-paced introduction to the Python data science stack /li liExplore ways to create useful metrics and statistics from large datasets /li liCreate detailed analysis reports with real-world data /li /ul h4Book Description/h4 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. | ||
| 520 | |a 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. | ||
| 520 | |a h4What you will learn/h4 ul liUse Python to read and transform data into different formats /li liGenerate basic statistics and metrics using data on disk /li liWork with computing tasks distributed over a cluster /li liConvert data from various sources into storage or querying formats /li liPrepare data for statistical analysis, visualization, and machine learning /li liPresent data in the form of effective visuals/li /ul h4Who this book is for/h4 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 | ||
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| spelling | Marin, Ivan Verfasser aut Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning Marin, Ivan 1 Birmingham Packt Publishing Limited 2019 1 Online-Ressource (276 Seiten) txt rdacontent c rdamedia cr rdacarrier bGet to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python./b h4Key Features/h4 ul liGet a hands-on, fast-paced introduction to the Python data science stack /li liExplore ways to create useful metrics and statistics from large datasets /li liCreate detailed analysis reports with real-world data /li /ul h4Book Description/h4 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. h4What you will learn/h4 ul liUse Python to read and transform data into different formats /li liGenerate basic statistics and metrics using data on disk /li liWork with computing tasks distributed over a cluster /li liConvert data from various sources into storage or querying formats /li liPrepare data for statistical analysis, visualization, and machine learning /li liPresent data in the form of effective visuals/li /ul h4Who this book is for/h4 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 COMPUTERS / Data Processing COMPUTERS / Data Visualization Shukla, Ankit Sonstige oth VK, Sarang Sonstige oth |
| spellingShingle | Marin, Ivan Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning COMPUTERS / Data Processing COMPUTERS / Data Visualization |
| title | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning |
| title_auth | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning |
| title_exact_search | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning |
| title_exact_search_txtP | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning |
| title_full | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning Marin, Ivan |
| title_fullStr | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning Marin, Ivan |
| title_full_unstemmed | Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning Marin, Ivan |
| title_short | Big Data Analysis with Python |
| title_sort | big data analysis with python combine spark and python to unlock the powers of parallel computing and machine learning |
| title_sub | Combine Spark and Python to unlock the powers of parallel computing and machine learning |
| topic | COMPUTERS / Data Processing COMPUTERS / Data Visualization |
| topic_facet | COMPUTERS / Data Processing COMPUTERS / Data Visualization |
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