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Book Introduction to Python for Humanists

Download or read book Introduction to Python for Humanists written by William Mattingly and published by CRC Press. This book was released on 2023-07-26 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose. Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysis App development

Book Introduction to Python for Humanists

Download or read book Introduction to Python for Humanists written by William Mattingly and published by CRC Press. This book was released on 2023-07-26 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose. Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysis App development

Book Introduction to Python

    Book Details:
  • Author : David Báez-López
  • Publisher : CRC Press
  • Release : 2024-07-02
  • ISBN : 1040040667
  • Pages : 453 pages

Download or read book Introduction to Python written by David Báez-López and published by CRC Press. This book was released on 2024-07-02 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Python: with Applications in Optimization, Image and Video Processing, and Machine Learning is intended primarily for advanced undergraduate and graduate students in quantitative sciences such as mathematics, computer science, and engineering. In addition to this, the book is written in such a way that it can also serve as a self-contained handbook for professionals working in quantitative fields including finance, IT, and many other industries where programming is a useful or essential tool. The book is written to be accessible and useful to those with no prior experience of Python, but those who are somewhat more adept will also benefit from the more advanced material that comes later in the book. Features Covers introductory and advanced material. Advanced material includes lists, dictionaries, tuples, arrays, plotting using Matplotlib, object-oriented programming Suitable as a textbook for advanced undergraduates or postgraduates, or as a reference for researchers and professionals Solutions manual, code, and additional examples are available for download

Book A Simple Introduction to Python

Download or read book A Simple Introduction to Python written by Stephen Lynch and published by CRC Press. This book was released on 2024-06-11 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Simple Introduction to Python is aimed at pre-university students and complete novices to programming. The whole book has been created using Jupyter notebooks. After introducing Python as a powerful calculator, simple programming constructs are covered, and the NumPy, MatPlotLib and SymPy modules (libraries) are introduced. Python is then used for Mathematics, Cryptography, Artificial Intelligence, Data Science and Object Oriented Programming. The reader is shown how to program using the integrated development environments: Python IDLE, Spyder, Jupyter notebooks, and through cloud computing with Google Colab. Features: No prior experience in programming is required. Demonstrates how to format Jupyter notebooks for publication on the Web. Full solutions to exercises are available as a Jupyter notebook on the Web. All Jupyter notebook solution files can be downloaded through GitHub. GitHub Repository of Data Files and a Jupyter Solution notebook: https://github.com/proflynch/A-Simple-Introduction-to-Python Jupyter Solution notebook web page: https://drstephenlynch.github.io/webpages/A-Simple-Introduction-to-Python-Solutions.html

Book Tidy Finance with Python

Download or read book Tidy Finance with Python written by Christoph Scheuch and published by CRC Press. This book was released on 2024-07-12 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques. Key Features: Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader’s research or as a reference for courses on empirical finance. Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide. A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods. We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics. Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.

Book Learning Professional Python

Download or read book Learning Professional Python written by Usharani Bhimavarapu and published by CRC Press. This book was released on 2023-10-16 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 1 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills. Learning Professional Python: Volume 1 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications

Book Data Mining with Python

Download or read book Data Mining with Python written by Di Wu and published by CRC Press. This book was released on 2024-04-10 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is everywhere and it’s growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge. The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study. This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work.

Book Foundations of Data Science with Python

Download or read book Foundations of Data Science with Python written by John M. Shea and published by CRC Press. This book was released on 2024-02-22 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality. This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a more contemporary approach in courses like Engineering Statistics. However, it is also intended to be accessible to practicing engineers and scientists who need to gain foundational knowledge of data science. Key Features: Applies a modern, computational approach to working with data Uses real data sets to conduct statistical tests that address a diverse set of contemporary issues Teaches the fundamentals of some of the most important tools in the Python data-science stack Provides a basic, but rigorous, introduction to Probability and its application to Statistics Offers an accompanying website that provides a unique set of online, interactive tools to help the reader learn the material

Book Exploratory Programming for the Arts and Humanities

Download or read book Exploratory Programming for the Arts and Humanities written by Nick Montfort and published by MIT Press. This book was released on 2016-04-08 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: A book for anyone who wants to learn programming to explore and create, with exercises and projects to help the reader learn by doing. This book introduces programming to readers with a background in the arts and humanities; there are no prerequisites, and no knowledge of computation is assumed. In it, Nick Montfort reveals programming to be not merely a technical exercise within given constraints but a tool for sketching, brainstorming, and inquiring about important topics. He emphasizes programming's exploratory potential—its facility to create new kinds of artworks and to probe data for new ideas. The book is designed to be read alongside the computer, allowing readers to program while making their way through the chapters. It offers practical exercises in writing and modifying code, beginning on a small scale and increasing in substance. In some cases, a specification is given for a program, but the core activities are a series of “free projects,” intentionally underspecified exercises that leave room for readers to determine their own direction and write different sorts of programs. Throughout the book, Montfort also considers how computation and programming are culturally situated—how programming relates to the methods and questions of the arts and humanities. The book uses Python and Processing, both of which are free software, as the primary programming languages.

Book Learning Advanced Python by Studying Open Source Projects

Download or read book Learning Advanced Python by Studying Open Source Projects written by Rongpeng Li and published by CRC Press. This book was released on 2023-11-10 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and, most importantly, passion. Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python. Throughout this book, readers will learn how to write Python code that is efficient, readable and maintainable, covering key topics such as data structures, algorithms, object-oriented programming and more. The author’s passion for Python shines through in this book, making it an enjoyable and inspiring read for both beginners and experienced programmers.

Book Python for Scientific Computing and Artificial Intelligence

Download or read book Python for Scientific Computing and Artificial Intelligence written by Stephen Lynch and published by CRC Press. This book was released on 2023-06-15 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web. Support Material GitHub Repository of Python Files and Notebooks: https://github.com/proflynch/CRC-Press/ Solutions to All Exercises: Section 1: An Introduction to Python: https://drstephenlynch.github.io/webpages/Solutions_Section_1.html Section 2: Python for Scientific Computing: https://drstephenlynch.github.io/webpages/Solutions_Section_2.html Section 3: Artificial Intelligence: https://drstephenlynch.github.io/webpages/Solutions_Section_3.html

Book Python Packages

    Book Details:
  • Author : Tomas Beuzen
  • Publisher : CRC Press
  • Release : 2022-04-20
  • ISBN : 1000555062
  • Pages : 243 pages

Download or read book Python Packages written by Tomas Beuzen and published by CRC Press. This book was released on 2022-04-20 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Packages introduces Python packaging at an introductory and practical level that’s suitable for those with no previous packaging experience. Despite this, the text builds up to advanced topics such as automated testing, creating documentation, versioning and updating a package, and implementing continuous integration and deployment. Covering the entire Python packaging life cycle, this essential guide takes readers from package creation all the way to effective maintenance and updating. Python Packages focuses on the use of current and best-practice packaging tools and services like poetry, cookiecutter, pytest, sphinx, GitHub, and GitHub Actions. Features: The book’s source code is available online as a GitHub repository where it is collaborated on, automatically tested, and built in real time as changes are made; demonstrating the use of good reproducible and clear project workflows. Covers not just the process of creating a package, but also how to document it, test it, publish it to the Python Package Index (PyPI), and how to properly version and update it. All concepts in the book are demonstrated using examples. Readers can follow along, creating their own Python packages using the reproducible code provided in the text. Focuses on a modern approach to Python packaging with emphasis on automating and streamlining the packaging process using new and emerging tools such as poetry and GitHub Actions.

Book XQuery for Humanists

    Book Details:
  • Author : Clifford B. Anderson
  • Publisher : Texas A&M University Press
  • Release : 2020-04-13
  • ISBN : 1623498309
  • Pages : 377 pages

Download or read book XQuery for Humanists written by Clifford B. Anderson and published by Texas A&M University Press. This book was released on 2020-04-13 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: XQuery is the best language for querying, manipulating, and transforming XML and JSON documents. Because XML is in many ways the lingua franca of the digital humanities, learning XQuery empowers humanists to discover and analyze their data in new ways. Until now, though, XQuery has been difficult to learn because there was no textbook designed for non- or beginner programmers. XQuery for Humanists fills this void with an approachable guidebook aimed directly at digital humanists. Clifford B. Anderson and Joseph C. Wicentowski introduce XQuery in terms accessible to humanities scholars and do not presuppose any prior background in programming. It provides an informed, opinionated overview and recommends the best implementations, libraries, and paradigms to empower those who need it most. Emphasizing practical applicability, the authors go beyond the XQuery language to include the basics of underlying standards like XPath, related standards like XQuery Full Text and XQuery Update, and explain the difference between XQuery and languages like Python and R. This book will afford readers the skills they need to build and analyze large-scale documentary corpora in XML. XQuery for Humanists is immeasurably valuable to instructors of digital humanities and library science courses alike and likewise is a ready reference for faculty, graduate students, and librarians who seek to master XQuery for their projects.

Book Humanities Data Analysis

    Book Details:
  • Author : Folgert Karsdorp
  • Publisher : Princeton University Press
  • Release : 2021-01-12
  • ISBN : 0691172366
  • Pages : 352 pages

Download or read book Humanities Data Analysis written by Folgert Karsdorp and published by Princeton University Press. This book was released on 2021-01-12 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations

Book Introduction to Python for Science and Engineering

Download or read book Introduction to Python for Science and Engineering written by David J. Pine and published by CRC Press. This book was released on 2019-03-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Series in Computational Physics Steven A. Gottlieb and Rubin H. Landau, Series Editors Introduction to Python for Science and Engineering This guide offers a quick and incisive introduction to Python programming for anyone. The author has carefully developed a concise approach to using Python in any discipline of science and engineering, with plenty of examples, practical hints, and insider tips. Readers will see why Python is such a widely appealing program, and learn the basics of syntax, data structures, input and output, plotting, conditionals and loops, user-defined functions, curve fitting, numerical routines, animation, and visualization. The author teaches by example and assumes no programming background for the reader. David J. Pine is the Silver Professor and Professor of Physics at New York University, and Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. He is an elected fellow of the American Physical Society and American Association for the Advancement of Science (AAAS), and is a Guggenheim Fellow.

Book An Introduction to Python Programming for Scientists and Engineers

Download or read book An Introduction to Python Programming for Scientists and Engineers written by Johnny Wei-Bing Lin and published by Cambridge University Press. This book was released on 2022-07-07 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: Textbook that uses examples and Jupyter notebooks from across the sciences and engineering to teach Python programming.

Book Digital Humanities Pedagogy

Download or read book Digital Humanities Pedagogy written by Brett D. Hirsch and published by Open Book Publishers. This book was released on 2012 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The essays in this collection offer a timely intervention in digital humanities scholarship, bringing together established and emerging scholars from a variety of humanities disciplines across the world. The first section offers views on the practical realities of teaching digital humanities at undergraduate and graduate levels, presenting case studies and snapshots of the authors' experiences alongside models for future courses and reflections on pedagogical successes and failures. The next section proposes strategies for teaching foundational digital humanities methods across a variety of scholarly disciplines, and the book concludes with wider debates about the place of digital humanities in the academy, from the field's cultural assumptions and social obligations to its political visions." (4e de couverture).