Elegant SciPy

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491922958
Total Pages : 277 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Elegant SciPy by : Juan Nunez-Iglesias

Download or read book Elegant SciPy written by Juan Nunez-Iglesias and published by "O'Reilly Media, Inc.". This book was released on 2017-08-11 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to Scientific Python and its community. If you’re a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. You’ll learn how to write elegant code that’s clear, concise, and efficient at executing the task at hand. Throughout the book, you’ll work with examples from the wider scientific Python ecosystem, using code that illustrates principles outlined in the book. Using actual scientific data, you’ll work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries. Explore the NumPy array, the data structure that underlies numerical scientific computation Use quantile normalization to ensure that measurements fit a specific distribution Represent separate regions in an image with a Region Adjacency Graph Convert temporal or spatial data into frequency domain data with the Fast Fourier Transform Solve sparse matrix problems, including image segmentations, with SciPy’s sparse module Perform linear algebra by using SciPy packages Explore image alignment (registration) with SciPy’s optimize module Process large datasets with Python data streaming primitives and the Toolz library

Elegant SciPy

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149192294X
Total Pages : 280 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Elegant SciPy by : Juan Nunez-Iglesias

Download or read book Elegant SciPy written by Juan Nunez-Iglesias and published by "O'Reilly Media, Inc.". This book was released on 2017-08-11 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to Scientific Python and its community. If you’re a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. You’ll learn how to write elegant code that’s clear, concise, and efficient at executing the task at hand. Throughout the book, you’ll work with examples from the wider scientific Python ecosystem, using code that illustrates principles outlined in the book. Using actual scientific data, you’ll work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries. Explore the NumPy array, the data structure that underlies numerical scientific computation Use quantile normalization to ensure that measurements fit a specific distribution Represent separate regions in an image with a Region Adjacency Graph Convert temporal or spatial data into frequency domain data with the Fast Fourier Transform Solve sparse matrix problems, including image segmentations, with SciPy’s sparse module Perform linear algebra by using SciPy packages Explore image alignment (registration) with SciPy’s optimize module Process large datasets with Python data streaming primitives and the Toolz library

SciPy and NumPy

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449305466
Total Pages : 68 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis SciPy and NumPy by : Eli Bressert

Download or read book SciPy and NumPy written by Eli Bressert and published by "O'Reilly Media, Inc.". This book was released on 2012 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Optimizing and boosting your Python programming"--Cover.

Clean Python

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Publisher : Apress
ISBN 13 : 1484248783
Total Pages : 274 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Clean Python by : Sunil Kapil

Download or read book Clean Python written by Sunil Kapil and published by Apress. This book was released on 2019-05-21 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the right way to code in Python. This book provides the tips and techniques you need to produce cleaner, error-free, and eloquent Python projects. Your journey to better code starts with understanding the importance of formatting and documenting your code for maximum readability, utilizing built-in data structures and Python dictionary for improved maintainability, and working with modules and meta-classes to effectively organize your code. You will then dive deep into the new features of the Python language and learn how to effectively utilize them. Next, you will decode key concepts such as asynchronous programming, Python data types, type hinting, and path handling. Learn tips to debug and conduct unit and integration tests in your Python code to ensure your code is ready for production. The final leg of your learning journey equips you with essential tools for version management, managing live code, and intelligent code completion. After reading and using this book, you will be proficient in writing clean Python code and successfully apply these principles to your own Python projects. What You’ll Learn Use the right expressions and statements in your Python code Create and assess Python Dictionary Work with advanced data structures in Python Write better modules, classes, functions, and metaclassesStart writing asynchronous Python immediatelyDiscover new features in Python Who This Book Is For Readers with a basic Python programming knowledge who want to improve their Python programming skills by learning right way to code in Python.

A Primer on Scientific Programming with Python

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Author :
Publisher : Springer
ISBN 13 : 3662498871
Total Pages : 942 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis A Primer on Scientific Programming with Python by : Hans Petter Langtangen

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

Python for Scientists

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Publisher : Cambridge University Press
ISBN 13 : 1316641236
Total Pages : 272 pages
Book Rating : 4.3/5 (166 download)

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Book Synopsis Python for Scientists by : John M. Stewart

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.

Python for Finance Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789617324
Total Pages : 426 pages
Book Rating : 4.7/5 (896 download)

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Book Synopsis Python for Finance Cookbook by : Eryk Lewinson

Download or read book Python for Finance Cookbook written by Eryk Lewinson and published by Packt Publishing Ltd. This book was released on 2020-01-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook Description Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach. What you will learnDownload and preprocess financial data from different sourcesBacktest the performance of automatic trading strategies in a real-world settingEstimate financial econometrics models in Python and interpret their resultsUse Monte Carlo simulations for a variety of tasks such as derivatives valuation and risk assessmentImprove the performance of financial models with the latest Python librariesApply machine learning and deep learning techniques to solve different financial problemsUnderstand the different approaches used to model financial time series dataWho this book is for This book is for financial analysts, data analysts, and Python developers who want to learn how to implement a broad range of tasks in the finance domain. Data scientists looking to devise intelligent financial strategies to perform efficient financial analysis will also find this book useful. Working knowledge of the Python programming language is mandatory to grasp the concepts covered in the book effectively.

The Quick Python Book

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Author :
Publisher : Manning Publications Company
ISBN 13 : 9781935182207
Total Pages : 336 pages
Book Rating : 4.1/5 (822 download)

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Book Synopsis The Quick Python Book by : Vernon L. Ceder

Download or read book The Quick Python Book written by Vernon L. Ceder and published by Manning Publications Company. This book was released on 2010 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the programming language's syntax, control flow, and basic data structures and covers its interaction with applications and mangement of large collections of code.

Numerical Python

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Publisher : Apress
ISBN 13 : 1484242467
Total Pages : 709 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Numerical Python by : Robert Johansson

Download or read book Numerical Python written by Robert Johansson and published by Apress. This book was released on 2018-12-24 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning. What You'll Learn Work with vectors and matrices using NumPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its related ecosystem for numerical computing.

Text Analytics with Python

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Publisher : Apress
ISBN 13 : 1484223888
Total Pages : 397 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Text Analytics with Python by : Dipanjan Sarkar

Download or read book Text Analytics with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2016-11-30 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Guide to NumPy

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Author :
Publisher : CreateSpace
ISBN 13 : 9781517300074
Total Pages : 364 pages
Book Rating : 4.3/5 ( download)

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Book Synopsis Guide to NumPy by : Travis Oliphant

Download or read book Guide to NumPy written by Travis Oliphant and published by CreateSpace. This book was released on 2015-09-15 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second edition of Travis Oliphant's A Guide to NumPy originally published electronically in 2006. It is designed to be a reference that can be used by practitioners who are familiar with Python but want to learn more about NumPy and related tools. In this updated edition, new perspectives are shared as well as descriptions of new distributed processing tools in the ecosystem, and how Numba can be used to compile code using NumPy arrays. Travis Oliphant is the co-founder and CEO of Continuum Analytics. Continuum Analytics develops Anaconda, the leading modern open source analytics platform powered by Python. Travis, who is a passionate advocate of open source technology, has a Ph.D. from Mayo Clinic and B.S. and M.S. degrees in Mathematics and Electrical Engineering from Brigham Young University. Since 1997, he has worked extensively with Python for computational and data science. He was the primary creator of the NumPy package and founding contributor to the SciPy package. He was also a co-founder and past board member of NumFOCUS, a non-profit for reproducible and accessible science that supports the PyData stack. He also served on the board of the Python Software Foundation.

Python for Finance

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492024295
Total Pages : 720 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Python for Finance by : Yves Hilpisch

Download or read book Python for Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.

Violent Python

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Publisher : Newnes
ISBN 13 : 1597499641
Total Pages : 288 pages
Book Rating : 4.5/5 (974 download)

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Book Synopsis Violent Python by : TJ O'Connor

Download or read book Violent Python written by TJ O'Connor and published by Newnes. This book was released on 2012-12-28 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Violent Python shows you how to move from a theoretical understanding of offensive computing concepts to a practical implementation. Instead of relying on another attacker’s tools, this book will teach you to forge your own weapons using the Python programming language. This book demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts. It also shows how to write code to intercept and analyze network traffic using Python, craft and spoof wireless frames to attack wireless and Bluetooth devices, and how to data-mine popular social media websites and evade modern anti-virus. Demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts Write code to intercept and analyze network traffic using Python. Craft and spoof wireless frames to attack wireless and Bluetooth devices Data-mine popular social media websites and evade modern anti-virus

SciPy Programming Succinctly

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Author :
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781542809542
Total Pages : 120 pages
Book Rating : 4.8/5 (95 download)

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Book Synopsis SciPy Programming Succinctly by : James McCaffrey

Download or read book SciPy Programming Succinctly written by James McCaffrey and published by Createspace Independent Publishing Platform. This book was released on 2017-02-01 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: James McCaffrey's SciPy Programming Succinctly offers readers a quick, thorough grounding in knowledge of the Python open source extension SciPy. The SciPy library, accompanied by its interdependent NumPy, offers Python programmers advanced functions that work with arrays and matrices. Each section presents a complete demo program for programmers to experiment with, carefully chosen examples to best illustrate each function, and resources for further learning. Use this e-book to install and edit SciPy, and use arrays, matrices, and combinatorics in Python programming.

Python for Data Analysis

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491957611
Total Pages : 676 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Python for Data Analysis by : Wes McKinney

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 676 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

Learning Scientific Programming with Python

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Author :
Publisher : Cambridge University Press
ISBN 13 : 1108787460
Total Pages : 572 pages
Book Rating : 4.1/5 (87 download)

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Book Synopsis Learning Scientific Programming with Python by : Christian Hill

Download or read book Learning Scientific Programming with Python written by Christian Hill and published by Cambridge University Press. This book was released on 2020-11-12 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming.

Scientific Computing with Python - Second Edition

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Publisher :
ISBN 13 : 9781838822323
Total Pages : 392 pages
Book Rating : 4.8/5 (223 download)

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Book Synopsis Scientific Computing with Python - Second Edition by : CLAUS. FUHRER

Download or read book Scientific Computing with Python - Second Edition written by CLAUS. FUHRER and published by . This book was released on 2021-07-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage this example-packed, comprehensive guide for all your Python computational needs Key Features: Learn the first steps within Python to highly specialized concepts Explore examples and code snippets taken from typical programming situations within scientific computing. Delve into essential computer science concepts like iterating, object-oriented programming, testing, and MPI presented in strong connection to applications within scientific computing. Book Description: Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing. What You Will Learn: Understand the building blocks of computational mathematics, linear algebra, and related Python objects Use Matplotlib to create high-quality figures and graphics to draw and visualize results Apply object-oriented programming (OOP) to scientific computing in Python Discover how to use pandas to enter the world of data processing Handle exceptions for writing reliable and usable code Cover manual and automatic aspects of testing for scientific programming Get to grips with parallel computing to increase computation speed Who this book is for: This book is for students with a mathematical background, university teachers designing modern courses in programming, data scientists, researchers, developers, and anyone who wants to perform scientific computation in Python.