[PDF] Python And Matplotlib Essentials For Scientists And Engineers - eBooks Review

Python And Matplotlib Essentials For Scientists And Engineers


Python And Matplotlib Essentials For Scientists And Engineers
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Python And Matplotlib Essentials For Scientists And Engineers


Python And Matplotlib Essentials For Scientists And Engineers
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Author : Matt A. Wood
language : en
Publisher:
Release Date : 2015

Python And Matplotlib Essentials For Scientists And Engineers written by Matt A. Wood and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Python (Computer program language) categories.




Python And Matplotlib Essentials For Scientists And Engineers


Python And Matplotlib Essentials For Scientists And Engineers
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Author : Matt A Wood
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2015-06-01

Python And Matplotlib Essentials For Scientists And Engineers written by Matt A Wood and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-01 with Computers categories.


This book provides an introduction to the core features of the Python programming language and Matplotlib plotting routings for scientists and engineers (or students of either discipline) who want to use PythonTM to analyse data, simulate physical processes, and render publication-quality plots. No previous programming experience is needed before reading the first page. Readers will learn the core features of the Python programming language in under a day. They will be able to immediately use Python to implement codes that solve their own problems and make beautiful plots and animations. Python code is extremely fast to prototype, allowing users to achieve results quickly and accurately. The examples within the book are available for download at http://pythonessentials.com. Python and Matplotlib Essentials for Scientists and Engineers is accessible for motivated high-school students, but will likely be most useful for undergraduate and graduate students as well as working professionals who have some background with the basic mathematical concepts. This book is intended for technical people who want to get things done.



Python Data Science Essentials


Python Data Science Essentials
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Author : Alberto Boschetti
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-10-28

Python Data Science Essentials written by Alberto Boschetti and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-28 with Computers categories.


Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.



Python For Scientists


Python For Scientists
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Author : John M. Stewart
language : en
Publisher: Cambridge University Press
Release Date : 2017-07-20

Python For Scientists written by John M. Stewart and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-20 with Computers categories.


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.



Python Data Science Handbook


Python Data Science Handbook
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Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21

Python Data Science Handbook written by Jake VanderPlas and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Computers categories.


For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms



An Introduction To Python Programming For Scientists And Engineers


An Introduction To Python Programming For Scientists And Engineers
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Author : Johnny Wei-Bing Lin
language : en
Publisher: Cambridge University Press
Release Date : 2022-07-07

An Introduction To Python Programming For Scientists And Engineers written by Johnny Wei-Bing Lin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-07 with Computers categories.


Textbook that uses examples and Jupyter notebooks from across the sciences and engineering to teach Python programming.



Introduction To Scientific Programming With Python


Introduction To Scientific Programming With Python
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Author : Joakim Sundnes
language : en
Publisher: Springer Nature
Release Date : 2020-07-01

Introduction To Scientific Programming With Python written by Joakim Sundnes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Mathematics categories.


This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.



Perspectives On The Transition Toward Green And Climate Neutral Economies In Asia


Perspectives On The Transition Toward Green And Climate Neutral Economies In Asia
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Author : Ordóñez de Pablos, Patricia
language : en
Publisher: IGI Global
Release Date : 2023-07-24

Perspectives On The Transition Toward Green And Climate Neutral Economies In Asia written by Ordóñez de Pablos, Patricia and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-24 with Business & Economics categories.


Knowledge management and advanced information technologies such as AI, IoT, machine learning, and more can create digital tools and solutions to build more resilient, climate neutral, and green economies and societies. These digital tools and solutions and knowledge management can have a heavy impact on the achievement of sustainable development goals (SDGs) in Asia. Perspectives on the Transition Toward Green and Climate Neutral Economies in Asia offers innovative conceptual frameworks and theories, case studies, and empirical studies to understand how knowledge management and digital innovation can foster the transition towards more circular and climate neutral economies as well as greener economies in Asia. This book discusses how key and enabling digital tools and solutions and knowledge management can support the achievement of SDGs by 2030. Covering topics such as climate neutral economies, image recognition, and usability evaluation, this premier reference source is an excellent resource for deans, heads of departments, directors, politicians, policymakers, corporate heads, senior general managers, managing directors, librarians, students and educators of higher education, academicians, and researchers.



Python Data Visualization Essentials Guide


Python Data Visualization Essentials Guide
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Author : Kallur Rahman
language : en
Publisher: BPB Publications
Release Date : 2021-07-30

Python Data Visualization Essentials Guide written by Kallur Rahman and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-30 with Computers categories.


Build your data science skills. Start data visualization Using Python. Right away. Become a good data analyst by creating quality data visualizations using Python. KEY FEATURES ● Exciting coverage on loads of Python libraries, including Matplotlib, Seaborn, Pandas, and Plotly. ● Tons of examples, illustrations, and use-cases to demonstrate visual storytelling of varied datasets. ● Covers a strong fundamental understanding of exploratory data analysis (EDA), statistical modeling, and data mining. DESCRIPTION Data visualization plays a major role in solving data science challenges with various capabilities it offers. This book aims to equip you with a sound knowledge of Python in conjunction with the concepts you need to master to succeed as a data visualization expert. The book starts with a brief introduction to the world of data visualization and talks about why it is important, the history of visualization, and the capabilities it offers. You will learn how to do simple Python-based visualization with examples with progressive complexity of key features. The book starts with Matplotlib and explores the power of data visualization with over 50 examples. It then explores the power of data visualization using one of the popular exploratory data analysis-oriented libraries, Pandas. The book talks about statistically inclined data visualization libraries such as Seaborn. The book also teaches how we can leverage bokeh and Plotly for interactive data visualization. Each chapter is enriched and loaded with 30+ examples that will guide you in learning everything about data visualization and storytelling of mixed datasets. WHAT YOU WILL LEARN ● Learn to work with popular Python libraries and frameworks, including Seaborn, Bokeh, and Plotly. ● Practice your data visualization understanding across numerous datasets and real examples. ● Learn to visualize geospatial and time-series datasets. ● Perform correlation and EDA analysis using Pandas and Matplotlib. ● Get to know storytelling of complex and unstructured data using Bokeh and Pandas. ● Learn best practices in writing clean and short python scripts for a quicker visual summary of datasets. WHO THIS BOOK IS FOR This book is for all data analytics professionals, data scientists, and data mining hobbyists who want to be strong data visualizers by learning all the popular Python data visualization libraries. Prior working knowledge of Python is assumed. TABLE OF CONTENTS 1. Introduction to Data Visualization 2. Why Data Visualization 3. Various Data Visualization Elements and Tools 4. Using Matplotlib with Python 5. Using NumPy and Pandas for Plotting 6. Using Seaborn for Visualization 7. Using Bokeh with Python 8. Using Plotly, Folium, and Other Tools for Data Visualization 9. Hands-on Examples and Exercises, Case Studies, and Further Resources



A Student S Guide To Python For Physical Modeling


A Student S Guide To Python For Physical Modeling
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Author : Jesse M. Kinder
language : en
Publisher: Princeton University Press
Release Date : 2018-01-30

A Student S Guide To Python For Physical Modeling written by Jesse M. Kinder and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-30 with Science categories.


A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.