Data Analysis With Open Source Tools

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Data Analysis with Open Source Tools

Philipp K. Janert
Data Analysis with Open Source Tools Book PDF

Author : Philipp K. Janert
Publisher : "O'Reilly Media, Inc."
Page : 540 pages
File Size : 48,9 Mb
Release : 2010-11-11
Category : Computers
ISBN : 1449396658

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Data Analysis with Open Source Tools by Philipp K. Janert Pdf

Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you. Use graphics to describe data with one, two, or dozens of variables Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments Mine data with computationally intensive methods such as simulation and clustering Make your conclusions understandable through reports, dashboards, and other metrics programs Understand financial calculations, including the time-value of money Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora

Open Source Geospatial Tools

Daniel McInerney,Pieter Kempeneers
Open Source Geospatial Tools Book PDF

Author : Daniel McInerney,Pieter Kempeneers
Publisher : Springer
Page : 358 pages
File Size : 43,7 Mb
Release : 2014-11-22
Category : Science
ISBN : 9783319018249

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Open Source Geospatial Tools by Daniel McInerney,Pieter Kempeneers Pdf

This book focuses on the use of open source software for geospatial analysis. It demonstrates the effectiveness of the command line interface for handling both vector, raster and 3D geospatial data. Appropriate open-source tools for data processing are clearly explained and discusses how they can be used to solve everyday tasks. A series of fully worked case studies are presented including vector spatial analysis, remote sensing data analysis, landcover classification and LiDAR processing. A hands-on introduction to the application programming interface (API) of GDAL/OGR in Python/C++ is provided for readers who want to extend existing tools and/or develop their own software.

Data Analytics Using Open-Source Tools

Jeffrey Strickland
Data Analytics Using Open Source Tools Book PDF

Author : Jeffrey Strickland
Publisher : Lulu.com
Page : 708 pages
File Size : 43,6 Mb
Release : 2016-07
Category : Business & Economics
ISBN : 9781365213847

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Data Analytics Using Open-Source Tools by Jeffrey Strickland Pdf

This book is about using open-source tools in data analytics. The book covers several subjects, including descriptive and predictive modeling, gradient boosting, cluster modeling, logistic regression, and artificial neural networks, among other topics.

Practical Data Analysis

Hector Cuesta,Dr. Sampath Kumar
Practical Data Analysis Book PDF

Author : Hector Cuesta,Dr. Sampath Kumar
Publisher : Packt Publishing Ltd
Page : 338 pages
File Size : 40,5 Mb
Release : 2016-09-30
Category : Computers
ISBN : 9781785286667

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Practical Data Analysis by Hector Cuesta,Dr. Sampath Kumar Pdf

A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Open Source Software for Statistical Analysis of Big Data

Richard Segall,Gao Niu
Open Source Software for Statistical Analysis of Big Data Book PDF

Author : Richard Segall,Gao Niu
Publisher : Engineering Science Reference
Page : 128 pages
File Size : 54,7 Mb
Release : 2020
Category : Big data
ISBN : 1799827690

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Open Source Software for Statistical Analysis of Big Data by Richard Segall,Gao Niu Pdf

"This book explores topics in the field of open source software for big data"--

Python for Data Analysis

Wes McKinney
Python for Data Analysis Book PDF

Author : Wes McKinney
Publisher : "O'Reilly Media, Inc."
Page : 676 pages
File Size : 55,8 Mb
Release : 2017-09-25
Category : Computers
ISBN : 9781491957615

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Python for Data Analysis by Wes McKinney Pdf

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities

Segall, Richard S.,Niu, Gao
Open Source Software for Statistical Analysis of Big Data Emerging Research and Opportunities Book PDF

Author : Segall, Richard S.,Niu, Gao
Publisher : IGI Global
Page : 237 pages
File Size : 53,6 Mb
Release : 2020-02-21
Category : Computers
ISBN : 9781799827702

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Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities by Segall, Richard S.,Niu, Gao Pdf

With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

Bioinformatics Data Skills

Vince Buffalo
Bioinformatics Data Skills Book PDF

Author : Vince Buffalo
Publisher : "O'Reilly Media, Inc."
Page : 538 pages
File Size : 50,8 Mb
Release : 2015-07
Category : Computers
ISBN : 9781449367510

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Bioinformatics Data Skills by Vince Buffalo Pdf

Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youâ??re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles

Remote Sensing and GIS for Ecologists

Martin Wegmann,Benjamin Leutner,Stefan Dech
Remote Sensing and GIS for Ecologists Book PDF

Author : Martin Wegmann,Benjamin Leutner,Stefan Dech
Publisher : Pelagic Publishing Ltd
Page : 410 pages
File Size : 46,9 Mb
Release : 2016-02-08
Category : Science
ISBN : 9781784270247

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Remote Sensing and GIS for Ecologists by Martin Wegmann,Benjamin Leutner,Stefan Dech Pdf

This is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. All practical examples in this book rely on OpenSource software and freely available data sets. Quantum GIS (QGIS) is introduced for basic GIS data handling, and in-depth spatial analytics and statistics are conducted with the software packages R and GRASS. Readers will learn how to apply remote sensing within ecological research projects, how to approach spatial data sampling and how to interpret remote sensing derived products. The authors discuss a wide range of statistical analyses with regard to satellite data as well as specialised topics such as time-series analysis. Extended scripts on how to create professional looking maps and graphics are also provided. This book is a valuable resource for students and scientists in the fields of conservation and ecology interested in learning how to get started in applying remote sensing in ecological research and conservation planning.

Open Source Software in Life Science Research

Lee Harland,Mark Forster
Open Source Software in Life Science Research Book PDF

Author : Lee Harland,Mark Forster
Publisher : Elsevier
Page : 583 pages
File Size : 49,9 Mb
Release : 2012-10-31
Category : Computers
ISBN : 9781908818249

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Open Source Software in Life Science Research by Lee Harland,Mark Forster Pdf

The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems. The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an ‘omics’ platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. Discusses a broad range of applications from a variety of sectors Provides a unique perspective on work normally performed behind closed doors Highlights the criteria used to compare and assess different approaches to solving problems

Managerial Perspectives on Intelligent Big Data Analytics

Sun, Zhaohao
Managerial Perspectives on Intelligent Big Data Analytics Book PDF

Author : Sun, Zhaohao
Publisher : IGI Global
Page : 335 pages
File Size : 43,5 Mb
Release : 2019-02-22
Category : Computers
ISBN : 9781522572787

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Managerial Perspectives on Intelligent Big Data Analytics by Sun, Zhaohao Pdf

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

Hands-On Exploratory Data Analysis with Python

Suresh Kumar Mukhiya,Usman Ahmed
Hands On Exploratory Data Analysis with Python Book PDF

Author : Suresh Kumar Mukhiya,Usman Ahmed
Publisher : Packt Publishing Ltd
Page : 342 pages
File Size : 41,6 Mb
Release : 2020-03-27
Category : Computers
ISBN : 9781789535624

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Hands-On Exploratory Data Analysis with Python by Suresh Kumar Mukhiya,Usman Ahmed Pdf

Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandas Key FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook Description Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes. What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is for This EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.

Practical Data Analysis

Dhiraj Bhuyan
Practical Data Analysis Book PDF

Author : Dhiraj Bhuyan
Publisher : Dhiraj Bhuyan
Page : 323 pages
File Size : 47,8 Mb
Release : 2019-11-30
Category : Computers
ISBN : 8210379456XXX

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Practical Data Analysis by Dhiraj Bhuyan Pdf

“Practical Data Analysis – Using Python & Open Source Technology” uses a case-study based approach to explore some of the real-world applications of open source data analysis tools and techniques. Specifically, the following topics are covered in this book: 1. Open Source Data Analysis Tools and Techniques. 2. A Beginner’s Guide to “Python” for Data Analysis. 3. Implementing Custom Search Engines On The Fly. 4. Visualising Missing Data. 5. Sentiment Analysis and Named Entity Recognition. 6. Automatic Document Classification, Clustering and Summarisation. 7. Fraud Detection Using Machine Learning Techniques. 8. Forecasting - Using Data to Map the Future. 9. Continuous Monitoring and Real-Time Analytics. 10. Creating a Robot for Interacting with Web Applications. Free samples of the book is available at - http://timesofdatascience.com

Research Anthology on Big Data Analytics, Architectures, and Applications

Management Association, Information Resources
Research Anthology on Big Data Analytics Architectures and Applications Book PDF

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 1988 pages
File Size : 48,9 Mb
Release : 2021-09-24
Category : Computers
ISBN : 9781668436639

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Research Anthology on Big Data Analytics, Architectures, and Applications by Management Association, Information Resources Pdf

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Data Analytics in Marketing, Entrepreneurship, and Innovation

Mounir Kehal,Shahira El Alfy
Data Analytics in Marketing Entrepreneurship and Innovation Book PDF

Author : Mounir Kehal,Shahira El Alfy
Publisher : CRC Press
Page : 193 pages
File Size : 42,6 Mb
Release : 2021-01-12
Category : Business & Economics
ISBN : 9780429591686

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Data Analytics in Marketing, Entrepreneurship, and Innovation by Mounir Kehal,Shahira El Alfy Pdf

Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at: Business analytics Applying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analytics Developing new products Technopreneurship Disruptive versus incremental innovation The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.