Download or read book 40 PYTHON LIBRARIES written by Diego Rodrigues and published by Diego Rodrigues. This book was released on 2024-10-30 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 🚀 TAKE ADVANTAGE OF THIS YEAR'S LAUNCH PROMOTIONAL PRICE 🚀 Become a Python expert with "40 PYTHON LIBRARIES: An Essential Guide for Students and Professionals - 2024 Edition", a must-have by Diego Rodrigues for students, developers, and professionals eager to master Python’s vast applications. Dive deep into Python's ecosystem and take your skills to the next level with essential libraries for scientific computing, data analysis, machine learning, web development, computer vision, and more. This guide simplifies complex concepts, showing you how to harness the power of NumPy, Pandas, Scikit-learn, Flask, Django, TensorFlow, PyTorch, and many others, to build robust applications and data solutions. Bring these libraries to life in practical projects—from large-scale data analysis and predictive modeling to web/mobile development, task automation, and integration with AWS, Google Cloud, and Microsoft Azure. With this book, you’ll develop the hands-on experience to tackle industry challenges and gain a competitive edge in the tech field. Boost your career with the knowledge to innovate and lead, mastering essential tools that will make your work more efficient and impactful. This practical, results-oriented book accelerates your learning and empowers your career. Order your copy today and start transforming your Python skills into a strategic advantage, turning complex challenges into effective solutions. TAGS: Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes

Download or read book Ultimate Python Libraries for Data Analysis and Visualization written by Abhinaba Banerjee and published by Orange Education Pvt Ltd. This book was released on 2024-04-04 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Test your Data Analysis skills to its fullest using Python and other no-code tools KEY FEATURES ● Comprehensive coverage of Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, Julius AI for data acquisition, preparation, analysis, and visualization ● Real-world projects and practical applications for hands-on learning ● In-depth exploration of low-code and no-code tools for enhanced productivity DESCRIPTION Ultimate Data Analysis and Visualization with Python is your comprehensive guide to mastering the intricacies of data analysis and visualization using Python. This book serves as your roadmap to unlocking the full potential of Python for extracting insights from data using Pandas, NumPy, Matplotlib, Seaborn, and Julius AI. Starting with the fundamentals of data acquisition, you'll learn essential techniques for gathering and preparing data for analysis. From there, you’ll dive into exploratory data analysis, uncovering patterns and relationships hidden within your datasets. Through step-by-step tutorials, you'll gain proficiency in statistical analysis, time series forecasting, and signal processing, equipping you with the tools to extract actionable insights from any dataset. What sets this book apart is its emphasis on real-world applications. With a series of hands-on projects, you’ll apply your newfound skills to analyze diverse datasets spanning industries such as finance, healthcare, e-commerce, and more. By the end of the book, you'll have the confidence and expertise to tackle any data analysis challenge with Python. To aid your journey, the book includes a handy Python cheat sheet in the appendix, serving as a quick reference guide for common functions and syntax. WHAT WILL YOU LEARN ● Acquire data from various sources using Python, including web scraping, APIs, and databases. ● Clean and prepare datasets for analysis, handling missing values, outliers, and inconsistencies. ● Conduct exploratory data analysis to uncover patterns, trends, and relationships within your data. ● Perform statistical analysis using Python libraries such as NumPy and Pandas, including hypothesis testing and regression analysis. ● Master time series analysis techniques for forecasting future trends and making data-driven decisions. ● Apply signal processing methods to analyze and interpret signals in data, such as audio, image, and sensor data. ● Engage in real-world projects across diverse industries, from finance to healthcare, to reinforce your skills and experience. ● Utilize Python for in-depth analysis of real-world datasets, gaining practical experience and insights. ● Refer to the Python cheat sheet in the appendix for quick access to common functions and syntax, aiding your learning and development. WHO IS THIS BOOK FOR? This book is ideal for beginners, professionals, or students aiming to enhance their careers through hands-on experience in data acquisition, preparation, analysis, time series, and signal processing. Prerequisite knowledge includes basic Python and introductory statistics. Whether starting fresh or seeking to refresh skills, this comprehensive guide helps readers upskill effectively. TABLE OF CONTENTS 1. Introduction to Data Analysis and Data Visualization using Python 2. Data Acquisition 3. Data Cleaning and Preparation 4. Exploratory Data Analysis 5. Statistical Analysis 6. Time Series Analysis and Forecasting 7. Signal Processing 8. Analyzing Real-World Data Sets using Python APPENDIX A Python Cheat Sheet Index

Download or read book Effective Python written by Brett Slatkin and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Profound Python Libraries written by Önder Teker and published by Godoro. This book was released on 2022-07-08 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book contains Python libraries used in many applications. Internet, Downloads, JSON, REST are covered. Utilities such as time, random, regular expressions are included. The operating systems & process are explained in detail. File system operations and Pathlib are covered. Some introductions to Big Data & Artificial Intelligence are added. CSV, Samples are explained as a preperation for data science. Visual libraries such as PIL & Matplotlib are included. Speech Recognition is covered. Finally Tk is is explained & a full sample application is supplied.

Download or read book Python 101 written by Michael Driscoll and published by Lulu.com. This book was released on 2014-06-03 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to program with Python from beginning to end. This book is for beginners who want to get up to speed quickly and become intermediate programmers fast!

Download or read book Python for Scientists written by John M. Stewart and published by Cambridge University Press. This book was released on 2017-07-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.

Download or read book A Primer on Scientific Programming with Python written by Hans Petter Langtangen and published by Springer. This book was released on 2016-07-28 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015

Download or read book IPython Interactive Computing and Visualization Cookbook written by Cyrille Rossant and published by Packt Publishing Ltd. This book was released on 2014-09-25 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

Download or read book Real World Python written by Lee Vaughan and published by No Starch Press. This book was released on 2020-11-10 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: A project-based approach to learning Python programming for beginners. Intriguing projects teach you how to tackle challenging problems with code. You've mastered the basics. Now you're ready to explore some of Python's more powerful tools. Real-World Python will show you how. Through a series of hands-on projects, you'll investigate and solve real-world problems using sophisticated computer vision, machine learning, data analysis, and language processing tools. You'll be introduced to important modules like OpenCV, NumPy, Pandas, NLTK, Bokeh, Beautiful Soup, Requests, HoloViews, Tkinter, turtle, matplotlib, and more. You'll create complete, working programs and think through intriguing projects that show you how to: Save shipwrecked sailors with an algorithm designed to prove the existence of God Detect asteroids and comets moving against a starfield Program a sentry gun to shoot your enemies and spare your friends Select landing sites for a Mars probe using real NASA maps Send unbreakable messages based on a book code Survive a zombie outbreak using data science Discover exoplanets and alien megastructures orbiting distant stars Test the hypothesis that we're all living in a computer simulation And more! If you're tired of learning the bare essentials of Python Programming with isolated snippets of code, you'll relish the relevant and geeky fun of Real-World Python!

Download or read book Numerical Python written by Robert Johansson and published by Springer Nature. This book was released on with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Python written by Toby Donaldson and published by Pearson Education. This book was released on 2014 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is a remarkably powerful dynamic programming language used in a wide variety of situations such as Web, database access, desktop GUIs, game and software development, and network programming. Fans of Python use the phrase "batteries included" to describe the standard library, which covers everything from asynchronous processing to zip files. The language itself is a flexible powerhouse that can handle practically any application domain. This task-based tutorial on Python is for those new to the language and walks you through the fundamentals. You'll learn about arithmetic, strings, and variables; writing programs; flow of control, functions; strings; data structures; input and output; and exception handling. At the end of the book, a special section walks you through a longer, realistic application, tying the concepts of the book together.

Download or read book Learning IPython for Interactive Computing and Data Visualization written by Cyrille Rossant and published by Packt Publishing Ltd. This book was released on 2015-10-21 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with Python for data analysis and numerical computing in the Jupyter notebook About This Book Learn the basics of Python in the Jupyter Notebook Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn Perform highly-efficient numerical computations with Numba, Cython, and ipyparallel Who This Book Is For This book targets students, teachers, researchers, engineers, analysts, journalists, hobbyists, and all data enthusiasts who are interested in analyzing and visualizing real-world datasets. If you are new to programming and data analysis, this book is exactly for you. If you're already familiar with another language or analysis software, you will also appreciate this introduction to the Python data analysis platform. Finally, there are more technical topics for advanced readers. No prior experience is required; this book contains everything you need to know. What You Will Learn Install Anaconda and code in Python in the Jupyter Notebook Load and explore datasets interactively Perform complex data manipulations effectively with pandas Create engaging data visualizations with matplotlib and seaborn Simulate mathematical models with NumPy Visualize and process images interactively in the Jupyter Notebook with scikit-image Accelerate your code with Numba, Cython, and IPython.parallel Extend the Notebook interface with HTML, JavaScript, and D3 In Detail Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors. This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data. Style and approach This is a hands-on beginner-friendly guide to analyze and visualize data on real-world examples with Python and the Jupyter Notebook.

Download or read book Python for Data Analysis written by Hari K.C. and published by Blue Rose Publishers. This book was released on 2022-05-26 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer programing is the vital field for the electronics, information and computer students. Programming with Python is trending topics nowadays. Its application has been increasing day by day. This book includes easy and readable theories with more examples. It also focusses on python projects. Computer Programming is the core subject for undergraduate students. With python, computer programming is not a big deal. This book is for beginners and intermediate students who wants to learn basics of Python Programming as well as Data Analysis and Visualization. In each Chapter, students will find necessary theories with relevant and practical examples. The concepts and examples used in this book are the inspiration from the different sources and authors. The whole text has been divided into seven chapters: 1. Introduction to Python 2. Data Structure and Conditional Statements 3. Loops and Functions 4. Object Oriented Programming in Python 5. Plotting graphs and charts in Python 6. Data analysis using NumPy and pandas 7. Mini Projects in Python

Download or read book Python Programming for Biology written by Tim J. Stevens and published by Cambridge University Press. This book was released on 2015-02-12 with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.

Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Python Passive Network Mapping written by Chet Hosmer and published by Syngress. This book was released on 2015-06-10 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Passive Network Mapping: P2NMAP is the first book to reveal a revolutionary and open source method for exposing nefarious network activity. The "Heartbleed" vulnerability has revealed significant weaknesses within enterprise environments related to the lack of a definitive mapping of network assets. In Python Passive Network Mapping, Chet Hosmer shows you how to effectively and definitively passively map networks. Active or probing methods to network mapping have traditionally been used, but they have many drawbacks - they can disrupt operations, crash systems, and - most importantly - miss critical nefarious activity. You require an accurate picture of the environments you protect and operate in order to rapidly investigate, mitigate, and then recover from these new attack vectors. This book gives you a deep understanding of new innovations to passive network mapping, while delivering open source Python-based tools that can be put into practice immediately. Python Passive Network Mapping is for practitioners, forensic investigators, IT teams, and individuals who work together when performing incident response and investigating potential damage, or are examining the impacts of new malware threats. Those defending critical infrastructures will have a special interest in this book, as active or probing methods of network mapping are rarely used within these environments as any resulting impacts can be disastrous. Python Passive Network Mapping is ideally suited for use as a text in a variety of academic programs to expose and engage students in the art of passively mapping enterprise networks, with the added benefit of providing exposure to open source Python solutions. - First book to show you how to use open source Python to conduct passive network mapping - Provides a new method for conducting incident response and investigating the extent of potential damage to your systems - Python code forensics toolkit for network mapping included on the companion website

Download or read book The Python 3 Standard Library by Example written by Doug Hellmann and published by Addison-Wesley Professional. This book was released on 2017-06-14 with total page 3262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Master the Powerful Python 3 Standard Library through Real Code Examples “The genius of Doug’s approach is that with 15 minutes per week, any motivated programmer can learn the Python Standard Library. Doug’s guided tour will help you flip the switch to fully power-up Python’s batteries.” –Raymond Hettinger, Distinguished Python Core Developer The Python 3 Standard Library contains hundreds of modules for interacting with the operating system, interpreter, and Internet–all extensively tested and ready to jump-start application development. Now, Python expert Doug Hellmann introduces every major area of the Python 3.x library through concise source code and output examples. Hellmann’s examples fully demonstrate each feature and are designed for easy learning and reuse. You’ll find practical code for working with text, data structures, algorithms, dates/times, math, the file system, persistence, data exchange, compression, archiving, crypto, processes/threads, networking, Internet capabilities, email, developer and language tools, the runtime, packages, and more. Each section fully covers one module, with links to additional resources, making this book an ideal tutorial and reference. The Python 3 Standard Library by Example introduces Python 3.x’s new libraries, significant functionality changes, and new layout and naming conventions. Hellmann also provides expert porting guidance for moving code from 2.x Python standard library modules to their Python 3.x equivalents. Manipulate text with string, textwrap, re (regular expressions), and difflib Use data structures: enum, collections, array, heapq, queue, struct, copy, and more Implement algorithms elegantly and concisely with functools, itertools, and contextlib Handle dates/times and advanced mathematical tasks Archive and data compression Understand data exchange and persistence, including json, dbm, and sqlite Sign and verify messages cryptographically Manage concurrent operations with processes and threads Test, debug, compile, profile, language, import, and package tools Control interaction at runtime with interpreters or the environment