Mastering Matplotlib Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Mastering Matplotlib book. This book definitely worth reading, it is an incredibly well-written.
matplotlib is a Python plotting library that provides a large feature set for a multitude of platforms. Given the depth of the library's legacy and the variety of related open source projects, gaining expert knowledge can be a time-consuming and often confusing process. You'll begin your exciting journey learning about the skills that are necessary in leading technical teams for a visualization project or to become a matplotlib contributor. Supported by highly-detailed IPython Notebooks, this book takes you through the conceptual components underlying the library and then provides a detailed overview of its APIs. From there, you will learn about event handling and how to code for interactive plots. Next you will move on to customization techniques, local configuration of matplotib, and then deployments in Cloud environments. The adventure culminates in an exploration of big data visualization and matplotlib clustering.
Mastering Matplotlib 2.x by Benjamin Walter Keller Pdf
Understand and build beautiful and advanced plots with Matplotlib and Python Key FeaturesPractical guide with hands-on examples to design interactive plotsAdvanced techniques to constructing complex plotsExplore 3D plotting and visualization using Jupyter NotebookBook Description In this book, you’ll get hands-on with customizing your data plots with the help of Matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more about tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this book. You’ll delve into niche plots and visualize ordinal and tabular data. In this book, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you’ll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook What you will learnDeal with non-trivial and unusual plotsUnderstanding Basemap methodsCustomize and represent data in 3D Construct Non-Cartesian and vector plotsDesign interactive plots using Jupyter NotebookMake movies for enhanced data representationWho this book is for This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of Matplotlib and Python is required.
Mastering Python Networking by Eric Chou,Michael Kennedy,Mandy Whaley Pdf
New edition of the bestselling guide to mastering Python Networking, updated to Python 3 and including the latest on network data analysis, Cloud Networking, Ansible 2.8, and new libraries Key FeaturesExplore the power of Python libraries to tackle difficult network problems efficiently and effectively, including pyATS, Nornir, and Ansible 2.8Use Python and Ansible for DevOps, network device automation, DevOps, and software-defined networkingBecome an expert in implementing advanced network-related tasks with Python 3Book Description Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In Mastering Python Networking, Third edition, you'll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This new edition is completely revised and updated to work with Python 3. In addition to new chapters on network data analysis with ELK stack (Elasticsearch, Logstash, Kibana, and Beats) and Azure Cloud Networking, it includes updates on using newer libraries such as pyATS and Nornir, as well as Ansible 2.8. Each chapter is updated with the latest libraries with working examples to ensure compatibility and understanding of the concepts. Starting with a basic overview of Python, the book teaches you how it can interact with both legacy and API-enabled network devices. You will learn to leverage high-level Python packages and frameworks to perform network automation tasks, monitoring, management, and enhanced network security followed by Azure and AWS Cloud networking. Finally, you will use Jenkins for continuous integration as well as testing tools to verify your network. What you will learnUse Python libraries to interact with your networkIntegrate Ansible 2.8 using Python to control Cisco, Juniper, and Arista network devicesLeverage existing Flask web frameworks to construct high-level APIsLearn how to build virtual networks in the AWS & Azure CloudLearn how to use Elastic Stack for network data analysisUnderstand how Jenkins can be used to automatically deploy changes in your networkUse PyTest and Unittest for Test-Driven Network Development in networking engineering with PythonWho this book is for Mastering Python Networking, Third edition is for network engineers, developers, and SREs who want to use Python for network automation, programmability, and data analysis. Basic familiarity with Python programming and networking-related concepts such as Transmission Control Protocol/Internet Protocol (TCP/IP) will be useful.
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Use advanced features of Python to write high-quality, readable code and packages Key Features Extensively updated for Python 3.10 with new chapters on design patterns, scientific programming, machine learning, and interactive Python Shape your scripts using key concepts like concurrency, performance optimization, asyncio, and multiprocessing Learn how advanced Python features fit together to produce maintainable code Book Description Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python's capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code's performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges What you will learn Write beautiful Pythonic code and avoid common Python coding mistakes Apply the power of decorators, generators, coroutines, and metaclasses Use different testing systems like pytest, unittest, and doctest Track and optimize application performance for both memory and CPU usage Debug your applications with PDB, Werkzeug, and faulthandler Improve your performance through asyncio, multiprocessing, and distributed computing Explore popular libraries like Dask, NumPy, SciPy, pandas, TensorFlow, and scikit-learn Extend Python's capabilities with C/C++ libraries and system calls Who this book is for This book will benefit more experienced Python programmers who wish to upskill, serving as a reference for best practices and some of the more intricate Python techniques. Even if you have been using Python for years, chances are that you haven't yet encountered every topic discussed in this book. A good understanding of Python programming is necessary
Mastering Python Scientific Computing by Hemant Kumar Mehta Pdf
A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered. Most of the Python APIs and tools used in scientific computing are discussed in detail The concepts are discussed with suitable example programs Who This Book Is For If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming. What You Will Learn Fundamentals and components of scientific computing Scientific computing data management Performing numerical computing using NumPy and SciPy Concepts and programming for symbolic computing using SymPy Using the plotting library matplotlib for data visualization Data analysis and visualization using Pandas, matplotlib, and IPython Performing parallel and high performance computing Real-life case studies and best practices of scientific computing In Detail In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing. At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python. The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs. Style and approach This book follows a hands-on approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.
Mastering Python Scripting for System Administrators by Ganesh Sanjiv Naik Pdf
Leverage the features and libraries of Python to administrate your environment efficiently. Key FeaturesLearn how to solve problems of system administrators and automate routine activitiesLearn to handle regular expressions, network administration Building GUI, web-scraping and database administration including data analyticsBook Description Python has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project. This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting). By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasks What you will learnUnderstand how to install Python and debug Python scriptsUnderstand and write scripts for automating testing and routine administrative activitiesUnderstand how to write scripts for text processing, encryption, decryption, and archivingHandle files, such as pdf, excel, csv, and txt files, and generate reportsWrite scripts for remote network administration, including handling emailsBuild interactive tools using a graphical user interfaceHandle Apache log files, SOAP and REST APIs communicationAutomate database administration and perform statistical analysisWho this book is for This book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior knowledge of Python would be necessary.
Mastering Python Data Visualization by Kirthi Raman Pdf
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 for Finance by James Ma Weiming Pdf
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key FeaturesExplore advanced financial models used by the industry and ways of solving them using PythonBuild state-of-the-art infrastructure for modeling, visualization, trading, and moreEmpower your financial applications by applying machine learning and deep learningBook Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learnSolve linear and nonlinear models representing various financial problemsPerform principal component analysis on the DOW index and its componentsAnalyze, predict, and forecast stationary and non-stationary time series processesCreate an event-driven backtesting tool and measure your strategiesBuild a high-frequency algorithmic trading platform with PythonReplicate the CBOT VIX index with SPX options for studying VIX-based strategiesPerform regression-based and classification-based machine learning tasks for predictionUse TensorFlow and Keras in deep learning neural network architectureWho this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.
Mastering OpenCV 4 with Python by Alberto Fernández Villán Pdf
Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key FeaturesDevelop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and PythonApply machine learning and deep learning techniques with TensorFlow and KerasDiscover the modern design patterns you should avoid when developing efficient computer vision applicationsBook Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learnHandle files and images, and explore various image processing techniquesExplore image transformations, including translation, resizing, and croppingGain insights into building histogramsBrush up on contour detection, filtering, and drawingWork with Augmented Reality to build marker-based and markerless applicationsWork with the main machine learning algorithms in OpenCVExplore the deep learning Python libraries and OpenCV deep learning capabilitiesCreate computer vision and deep learning web applicationsWho this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.
Mastering Python 3 Programming by Subburaj Ramasamy Pdf
Learn the nitty-gritty of Python 3 programming language by coding and executing programs seamlessly in a lucid manner KEY FEATURES ● Python 3 fundamentals, from data manipulation to control flow. ● Key concepts like data structures, algorithms, and Python applications, catering to a diverse audience. ● Beginner-friendly guide with step-by-step explanations and practical examples. DESCRIPTION Python 3's clear and concise syntax and extensive collection of built-in libraries and frameworks make it a powerful and versatile programming language. This comprehensive guide, "Mastering Python 3 Programming", is designed to take you from the ground up to proficiency, equipping you to create effective Python programs. This book provides an extensive overview of Python programming, covering a diverse range of topics essential for understanding Python 3. Each chapter explores key concepts like Unicode strings, functions and recursions, lists, tuples, sets, and dictionaries, along with advanced topics such as object-oriented programming, file handling, exception handling, and more. With detailed explanations and real-life examples, you will be able to build a strong understanding of Python 3. Throughout the book, you will find useful concepts and Python libraries explained clearly, along with case studies, executable programs, exercises, and easy-to-follow style. This book focuses on real-world Python applications, developing critical thinking and problem-solving skills. It prepares students for Python challenges, equipping them to contribute meaningfully in their fields. With a deep understanding of Python, students gain confidence to explore new opportunities and drive innovation. WHAT YOU WILL LEARN ● Set up IDLE for Python programming and execute programs. ● Adapt algorithm based problem-solving techniques. ● Utilize Python libraries for data visualization. ● Grasp data structures and common algorithms. ● Master decorators, file handling, exception handling, inheritance, polymorphism, and recursion in Python. WHO THIS BOOK IS FOR The target audience for this book includes undergraduate students from diverse academic backgrounds, including life sciences, mathematics, commerce, management, arts, and individuals who are new to computer science. TABLE OF CONTENTS 1. Introduction to Python 3 2. Algorithmic Problem Solving 3. Numeric Computations and Console Input 4. Unicode, Strings and Console Output 5. Selection and Loops 6. Functions and Recursion 7. Lists 8. Tuples, Sets, and Dictionaries 9. Introduction to Object-Oriented Programming 10. Inheritance and Polymorphism 11. File Handling 12. Exception Handling 13. Gems of Python 14. Data Structures and Algorithms using Python 15. Data Visualization 16. Python Applications and Libraries Appendix 1: Python Projects Appendix 2: List of Built-in Functions in Python Appendix 3: Answers to Review Questions
Mastering Python: A Comprehensive Guide to Programming by Christine Lambertson Pdf
Python is a high-level, interpreted programming language that was created by Guido van Rossum in the late 1980s. It has gained immense popularity due to its simplicity, readability, and versatility. Python is an open-source language, which means its source code is freely available, and it has a vibrant community of developers who contribute to its continuous improvement. Python’s Design Philosophy and Guiding Principles: Python follows a design philosophy that emphasizes code readability and simplicity. This is often summarized in the Zen of Python, a collection of guiding principles for writing Python code.
Mastering Python. A comprehensive Journey from Beginner to Professional by Yusuf Buba Pdf
Beginners can develop a solid foundation in Python programming, while professionals can enhance their existing skills and expand their knowledge into advanced areas. Python's versatility, along with its vast collection of libraries and frameworks, empowers learners to tackle various real-world challenges and opens up exciting career opportunities in fields such as software development, data science, machine learning, web development, and more.
Mastering Python Network Automation by Tim Peters Pdf
Numerous sample programs & examples demonstrating the application of python tools to streamline network automation With "Mastering Python Network Automation," you can streamline container orchestration, configuration management, and resilient networking with Python and its libraries, allowing you to emerge as a skilled network engineer or a strong DevOps professional. From the ground up, this guide walks readers through setting up a network automation lab using the NS3 network simulator and Python programming. This includes the installation of NS3, as well as python libraries like nornir, paramiko, netmiko, and PyEZ, as well as the configuration of ports, hosts, and servers. This book will teach you the skills to become a proficient automation developer who can test and fix any bugs in automation scripts. This book examines the emergence of the service mesh as a solution to the problems associated with service-to-service communication over time. This book walks you through automating various container-related tasks in Python and its libraries, including container orchestration, service discovery, load balancing, container storage management, container performance monitoring, and rolling updates. Calico and Istio are two well-known service mesh tools, and you'll find out how to set them up and configure them to manage traffic routing, security, and monitoring. Additional topics covered in this book include the automation of network policies, the routing of workloads, and the collection and tracking of metrics, logs, and traces. You'll also pick up some tips and tricks for collecting and visualizing Istio metrics with the help of tools like Grafana. Key Learnings Use of Istio for cluster traffic management, traffic routing, and service mesh implementation. Utilizing Cilium and Calico to solve pod networking and automate network policy and workload routing. Monitoring and managing Kubernetes clusters with etcd and HAProxy load balancers and container storage. Establishing network automation lab with tools like NS3 emulator, Python, Virtual Environment, and VS Code. Establishing connectivity between hosts, port connectivity, SSH connectivity, python libraries, NS3, and network encryption. Table of Content Python Essentials for Networks File Handling and Modules in Python Preparing Network Automation Lab Configuring Libraries and Lab Components Code, Test & Validate Network Automation Automation of Configuration Management Managing Docker and Container Networks Orchestrating Container & Workloads Pod Networking Implementing Service Mesh Audience "Mastering Python Network Automation" is an essential guide for network engineers, DevOps professionals, and developers who want to streamline container orchestration and resilient networking with the help of Terraform, Calico, and Istio. Knowing Python and the basics of networking is sufficient to pursue this book.
Mastering Python Data Analysis by Magnus Vilhelm Persson,Luiz Felipe Martins Pdf
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.