Mastering Python Data Visualization
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Mastering Python Data Visualization
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Author : Kirthi Raman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-27
Mastering Python Data Visualization written by Kirthi Raman and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-27 with Computers categories.
Generate effective results in a variety of visually appealing charts using the plotting packages in Python About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms in diverse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems. Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields
Mastering Python Data Analysis
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Author : Magnus Vilhelm Persson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-06-27
Mastering Python Data Analysis written by Magnus Vilhelm Persson and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-27 with Computers categories.
Become an expert at using Python for advanced statistical analysis of data using real-world examples About This Book Clean, format, and explore data using graphical and numerical summaries Leverage the IPython environment to efficiently analyze data with Python Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For If you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed. What You Will Learn Read, sort, and map various data into Python and Pandas Recognise patterns so you can understand and explore data Use statistical models to discover patterns in data Review classical statistical inference using Python, Pandas, and SciPy Detect similarities and differences in data with clustering Clean your data to make it useful Work in Jupyter Notebook to produce publication ready figures to be included in reports In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You'll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You'll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you'll move on to review statistical inference using Python, Pandas, and SciPy. After that, we'll focus on performing regression using computational tools and you'll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you'll discover how to use Python's tools for supervised machine learning. Style and approach This book takes a step-by-step approach to reading, processing, and analyzing data in Python using various methods and tools. Rich in examples, each topic connects to real-world examples and retrieves data directly online where possible. With this book, you are given the knowledge and tools to explore any data on your own, encouraging a curiosity befitting all data scientists.
Python Data Analytics And Visualization
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Author : Phuong Vo.T.H
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-31
Python Data Analytics And Visualization written by Phuong Vo.T.H and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Computers categories.
Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan Learning Predictive Analytics with Python, Ashish Kumar Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization
Mastering Python Forensics
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Author : Dr. Michael Spreitzenbarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-30
Mastering Python Forensics written by Dr. Michael Spreitzenbarth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-30 with Computers categories.
Master the art of digital forensics and analysis with Python About This Book Learn to perform forensic analysis and investigations with the help of Python, and gain an advanced understanding of the various Python libraries and frameworks Analyze Python scripts to extract metadata and investigate forensic artifacts The writers, Dr. Michael Spreitzenbarth and Dr. Johann Uhrmann, have used their experience to craft this hands-on guide to using Python for forensic analysis and investigations Who This Book Is For If you are a network security professional or forensics analyst who wants to gain a deeper understanding of performing forensic analysis with Python, then this book is for you. Some Python experience would be helpful. What You Will Learn Explore the forensic analysis of different platforms such as Windows, Android, and vSphere Semi-automatically reconstruct major parts of the system activity and time-line Leverage Python ctypes for protocol decoding Examine artifacts from mobile, Skype, and browsers Discover how to utilize Python to improve the focus of your analysis Investigate in volatile memory with the help of volatility on the Android and Linux platforms In Detail Digital forensic analysis is the process of examining and extracting data digitally and examining it. Python has the combination of power, expressiveness, and ease of use that makes it an essential complementary tool to the traditional, off-the-shelf digital forensic tools. This book will teach you how to perform forensic analysis and investigations by exploring the capabilities of various Python libraries. The book starts by explaining the building blocks of the Python programming language, especially ctypes in-depth, along with how to automate typical tasks in file system analysis, common correlation tasks to discover anomalies, as well as templates for investigations. Next, we'll show you cryptographic algorithms that can be used during forensic investigations to check for known files or to compare suspicious files with online services such as VirusTotal or Mobile-Sandbox. Moving on, you'll learn how to sniff on the network, generate and analyze network flows, and perform log correlation with the help of Python scripts and tools. You'll get to know about the concepts of virtualization and how virtualization influences IT forensics, and you'll discover how to perform forensic analysis of a jailbroken/rooted mobile device that is based on iOS or Android. Finally, the book teaches you how to analyze volatile memory and search for known malware samples based on YARA rules. Style and approach This easy-to-follow guide will demonstrate forensic analysis techniques by showing you how to solve real-word-scenarios step by step.
Mastering Python Data Analysis
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Author : Magnus Vilhelm Persson
language : en
Publisher: Packt Publishing
Release Date : 2016-06-27
Mastering Python Data Analysis written by Magnus Vilhelm Persson and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-27 with Computers categories.
Become an expert at using Python for advanced statistical analysis of data using real-world examplesAbout This Book- Clean, format, and explore data using graphical and numerical summaries- Leverage the IPython environment to efficiently analyze data with Python- Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex dataWho This Book Is ForIf you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed.What You Will Learn- Read, sort, and map various data into Python and Pandas- Recognise patterns so you can understand and explore data- Use statistical models to discover patterns in data- Review classical statistical inference using Python, Pandas, and SciPy- Detect similarities and differences in data with clustering- Clean your data to make it useful- Work in Jupyter Notebook to produce publication ready figures to be included in reportsIn DetailPython, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want!Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You'll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making.You'll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you'll move on to review statistical inference using Python, Pandas, and SciPy. After that, we'll focus on performing regression using computational tools and you'll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you'll discover how to use Python's tools for supervised machine learning.Style and approachThis book takes a step-by-step approach to reading, processing, and analyzing data in Python using various methods and tools. Rich in examples, each topic connects to real-world examples and retrieves data directly online where possible. With this book, you are given the knowledge and tools to explore any data on your own, encouraging a curiosity befitting all data scientists.
Mastering Python For Data Science
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Author : Samir Madhavan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-08-31
Mastering Python For Data Science written by Samir Madhavan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-31 with Computers categories.
Explore the world of data science through Python and learn how to make sense of data About This Book Master data science methods using Python and its libraries Create data visualizations and mine for patterns Advanced techniques for the four fundamentals of Data Science with Python - data mining, data analysis, data visualization, and machine learning Who This Book Is For If you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed. What You Will Learn Manage data and perform linear algebra in Python Derive inferences from the analysis by performing inferential statistics Solve data science problems in Python Create high-end visualizations using Python Evaluate and apply the linear regression technique to estimate the relationships among variables. Build recommendation engines with the various collaborative filtering algorithms Apply the ensemble methods to improve your predictions Work with big data technologies to handle data at scale In Detail Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving. This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science. Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods. Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics. Style and approach This book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios.
Mastering Python From Basics To Advanced Programming
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Author : Mr. Pankaj Pandey
language : en
Publisher: Chyren Publication
Release Date : 2025-10-20
Mastering Python From Basics To Advanced Programming written by Mr. Pankaj Pandey and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-20 with Antiques & Collectibles categories.
Mastering Python For Data Science
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Author : Samir Medhaven
language : en
Publisher: Packt Publishing
Release Date : 2015-08-31
Mastering Python For Data Science written by Samir Medhaven and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-31 with Computers categories.
Explore the world of data science through Python and learn how to make sense of dataAbout This Book• Master data science methods using Python and its libraries• Create data visualizations and mine for patterns• Advanced techniques for the four fundamentals of Data Science with Python - data mining, data analysis, data visualization, and machine learningWho This Book Is ForIf you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed.What You Will Learn• Manage data and perform linear algebra in Python• Derive inferences from the analysis by performing inferential statistics• Solve data science problems in Python• Create high-end visualizations using Python• Evaluate and apply the linear regression technique to estimate the relationships among variables.• Build recommendation engines with the various collaborative filtering algorithms• Apply the ensemble methods to improve your predictions• Work with big data technologies to handle data at scaleIn DetailData science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving.This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods.Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.Style and approachThis book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios.
Mastering Pycharm
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Author : Quazi Nafiul Islam
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-23
Mastering Pycharm written by Quazi Nafiul Islam and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-23 with Computers categories.
Use PyCharm with fluid efficiency to write idiomatic python code About This Book Understand how PyCharm works and how you can leverage its strength to develop applications quickly Master PyCharm's editor to get a fast workflow Full of examples and illustrations that focus on the practical aspects of using PyCharm Who This Book Is For If you know PyCharm but want to understand it better and leverage its more powerful but less obvious tool set, this is the book for you. Serving as a launch pad for those who want to master PyCharm and completely harness its best features, it would be helpful if you were familiar with some of Python's most prominent tools such as virtualenv and Python's popular docstring formats such as reStructuredText and EpyType. What You Will Learn Understand the internal workings of the IntelliJ Platform Leverage PyCharm's powerful search tools, and learn which ones are the best for you and your workflow Customize PyCharm's enhanced Python interpreter and its inbuilt terminal Develop web applications quickly and easily with different frameworks such as Flask and Django Understand how code completion works in PyCharm for Python and JavaScript In Detail PyCharm is addictive, with powerful and configurable code completion, superb editing tools, top-notch support, diverse plugins, and a vibrant ecosystem to boot. Learning how PyCharm works and maximising the synergy of its powerful tools will help you to rapidly develop applications. From leveraging the power of the editor to understanding PyCharm's internals, this book will give you a comprehensive view of PyCharm and allow you to make your own choices about which workflow and tools are best for you. You will start by getting comfortable with PyCharm and making it look exactly like you want. You can customize the tools and taskbars to suit individual developers' coding styles. You also learn how to assign keyboard shortcuts. You will master debugging by inserting breakpoints, collecting runtime data, and debugging from the console. You will understand how PyCharm works underneath and how plugins such as Codemap, Vim, Bitbucket, Assets compressor, markdown, bash file, shortcut translator, and .gitignore leverage the power of the IntelliJ platform. You will become comfortable using the VCS interface in PyCharm and see the benefits of using it for some simple tasks as well as some more complex tasks such as partial commits using changelists. You will take an in-depth look at the various tools in PyCharm, improving your workflow drastically. Finally, you will deploy powerful PyCharm tools for Django, Flask, GAE, and Pyramid Development, becoming well acquainted with PyCharm's toolset for web development with popular platforms. Packed with insider tricks, this book will help you boost productivity with PyCharm. Style and approach An easy-to-follow guide with plenty of examples and screenshots. Each topic starts off with the goal of enhancing or changing a part of PyCharm to make it suit your needs.
Mastering Tools And Techniques Of Data Science
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Author : Mustafa Ali
language : en
Publisher: Mustafa Ali
Release Date : 2024-01-18
Mastering Tools And Techniques Of Data Science written by Mustafa Ali and has been published by Mustafa Ali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-18 with Computers categories.
Data science, in a nutshell, is about finding hidden gems in massive piles of data. It's like being a detective for information, using various tools and techniques to uncover patterns, trends, and insights that can be used to solve problems and make better decisions.