Introduction to Python for Humanists

Introduction to Python for Humanists

Author: William Mattingly

Publisher: CRC Press

Published: 2023-07-26

Total Pages: 337

ISBN-13: 1000884597

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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 Synopsis Introduction to Python for Humanists by : William Mattingly

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

Introduction to Python for Humanists

Introduction to Python for Humanists

Author: William Mattingly

Publisher: CRC Press

Published: 2023-07-26

Total Pages: 362

ISBN-13: 1000884538

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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 Synopsis Introduction to Python for Humanists by : William Mattingly

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

Introduction to Python

Introduction to Python

Author: David Báez-López

Publisher: CRC Press

Published: 2024-07-02

Total Pages: 453

ISBN-13: 1040040667

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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 Synopsis Introduction to Python by : David Báez-López

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

A Simple Introduction to Python

A Simple Introduction to Python

Author: Stephen Lynch

Publisher: CRC Press

Published: 2024-06-11

Total Pages: 113

ISBN-13: 1040034756

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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 Synopsis A Simple Introduction to Python by : Stephen Lynch

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

Tidy Finance with Python

Tidy Finance with Python

Author: Christoph Scheuch

Publisher: CRC Press

Published: 2024-07-12

Total Pages: 262

ISBN-13: 1040048617

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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 Synopsis Tidy Finance with Python by : Christoph Scheuch

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.

Learning Professional Python

Learning Professional Python

Author: Usharani Bhimavarapu

Publisher: CRC Press

Published: 2023-10-16

Total Pages: 248

ISBN-13: 1000927768

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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 Synopsis Learning Professional Python by : Usharani Bhimavarapu

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

Data Mining with Python

Data Mining with Python

Author: Di Wu

Publisher: CRC Press

Published: 2024-04-10

Total Pages: 415

ISBN-13: 1040010385

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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 Synopsis Data Mining with Python by : Di Wu

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.

Foundations of Data Science with Python

Foundations of Data Science with Python

Author: John M. Shea

Publisher: CRC Press

Published: 2024-02-22

Total Pages: 503

ISBN-13: 1003838545

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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 Synopsis Foundations of Data Science with Python by : John M. Shea

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

Exploratory Programming for the Arts and Humanities

Exploratory Programming for the Arts and Humanities

Author: Nick Montfort

Publisher: MIT Press

Published: 2016-04-08

Total Pages: 329

ISBN-13: 0262331985

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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 Synopsis Exploratory Programming for the Arts and Humanities by : Nick Montfort

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.

Learning Advanced Python by Studying Open Source Projects

Learning Advanced Python by Studying Open Source Projects

Author: Rongpeng Li

Publisher: CRC Press

Published: 2023-11-10

Total Pages: 139

ISBN-13: 1000992977

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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 Synopsis Learning Advanced Python by Studying Open Source Projects by : Rongpeng Li

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.