Matplotlib 2x By Example

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Matplotlib 2.x By Example

Author : Allen Yu
Publisher : Packt Publishing Ltd
ISBN 13 : 1788292138
Total Pages : 328 pages
Book Rating : 4.7/5 (882 download)

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Book Synopsis Matplotlib 2.x By Example by : Allen Yu

Download or read book Matplotlib 2.x By Example written by Allen Yu and published by Packt Publishing Ltd. This book was released on 2017-08-28 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock deeper insights into visualization in form of 2D and 3D graphs using Matplotlib 2.x About This Book Create and customize live graphs, by adding style, color, font to make appealing graphs. A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits. Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more. Who This Book Is For This book is for anyone interested in data visualization, to get insights from big data with Python and Matplotlib 2.x. With this book you will be able to extend your knowledge and learn how to use python code in order to visualize your data with Matplotlib. Basic knowledge of Python is expected. What You Will Learn Familiarize with the latest features in Matplotlib 2.x Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more. Make clear and appealing figures for scientific publications. Create interactive charts and animation. Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn. Design intuitive infographics for effective storytelling. In Detail Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization. Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts. By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable. Style and approach Step by step comprehensive guide filled with real world examples.

Python Data Science Handbook

Author : Jake VanderPlas
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491912138
Total Pages : 743 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Python Data Science Handbook by : Jake VanderPlas

Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Numerical Methods in Chemical Engineering Using Python® and Simulink®

Author : Nayef Ghasem
Publisher : CRC Press
ISBN 13 : 1000907325
Total Pages : 371 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Numerical Methods in Chemical Engineering Using Python® and Simulink® by : Nayef Ghasem

Download or read book Numerical Methods in Chemical Engineering Using Python® and Simulink® written by Nayef Ghasem and published by CRC Press. This book was released on 2023-07-17 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical methods are vital to the practice of chemical engineering, allowing for the solution of real-world problems. Written in a concise and practical format, this textbook introduces readers to the numerical methods required in the discipline of chemical engineering and enables them to validate their solutions using both Python and Simulink. Introduces numerical methods, followed by the solution of linear and nonlinear algebraic equations. Deals with the numerical integration of a definite function and solves initial and boundary value ordinary differential equations with different orders. Weaves in examples of various numerical methods and validates solutions to each with Python and Simulink graphical programming. Features appendices on how to use Python and Simulink. Aimed at advanced undergraduate and graduate chemical engineering students, as well as practicing chemical engineers, this textbook offers a guide to the use of two of the most widely used programs in the discipline. The textbook features numerous video lectures of applications and a solutions manual for qualifying instructors.

Python Machine Learning Case Studies

Author : Danish Haroon
Publisher : Apress
ISBN 13 : 1484228235
Total Pages : 216 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Python Machine Learning Case Studies by : Danish Haroon

Download or read book Python Machine Learning Case Studies written by Danish Haroon and published by Apress. This book was released on 2017-10-27 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You’ll see machine learning techniques that you can use to support your products and services. Moreover you’ll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs. By taking a step-by-step approach to coding in Python you’ll be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems. What You Will Learn Gain insights into machine learning concepts Work on real-world applications of machine learning Learn concepts of model selection and optimization Get a hands-on overview of Python from a machine learning point of view Who This Book Is For Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.

Python for Scientists

Author : John M. Stewart
Publisher : Cambridge University Press
ISBN 13 : 1009014803
Total Pages : 301 pages
Book Rating : 4.0/5 (9 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 2023-08-31 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Python starting from the very basics all the way to numerical and symbolic math, quantitative analysis, and beyond.

Python and Matplotlib Essentials for Scientists and Engineers

Author : Matt A Wood
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1627056203
Total Pages : 150 pages
Book Rating : 4.6/5 (27 download)

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Book Synopsis Python and Matplotlib Essentials for Scientists and Engineers by : Matt A Wood

Download or read book Python and Matplotlib Essentials for Scientists and Engineers written by Matt A Wood and published by Morgan & Claypool Publishers. This book was released on 2015-06-01 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 for Scientists

Author : John M. Stewart
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.

Numerical Python

Author : Robert Johansson
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.

A Primer on Scientific Programming with Python

Author : Hans Petter Langtangen
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

matplotlib Plotting Cookbook

Author : Alexandre Devert
Publisher : Packt Publishing Ltd
ISBN 13 : 1849513279
Total Pages : 222 pages
Book Rating : 4.8/5 (495 download)

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Book Synopsis matplotlib Plotting Cookbook by : Alexandre Devert

Download or read book matplotlib Plotting Cookbook written by Alexandre Devert and published by Packt Publishing Ltd. This book was released on 2014-03-26 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book follows a cookbook style approach that puts orthogonal and non-redundant recipes in your hands. Rather than rehashing the user manual, the explanations expose the underlying logic behind Matplotlib. If you are an engineer or scientist who wants to create great visualizations with Python, rather than yet another specialized language, this is the book for you. While there are several very competent plotting packages, Matplotlib is just a Python module. Thus, if you know some Python already, you will feel at home from the first steps on. In case you are an application writer, you won't be left out since the integration of Matplolib is covered.

Learning IPython for Interactive Computing and Data Visualization

Author : Cyrille Rossant
Publisher : Packt Publishing Ltd
ISBN 13 : 1783986999
Total Pages : 201 pages
Book Rating : 4.7/5 (839 download)

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Book Synopsis Learning IPython for Interactive Computing and Data Visualization by : Cyrille Rossant

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

Programming for Computations - Python

Author : Svein Linge
Publisher : Springer Nature
ISBN 13 : 3030168778
Total Pages : 350 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Programming for Computations - Python by : Svein Linge

Download or read book Programming for Computations - Python written by Svein Linge and published by Springer Nature. This book was released on 2019-10-30 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

Chemical and Biomedical Engineering Calculations Using Python

Author : Jeffrey J. Heys
Publisher : John Wiley & Sons
ISBN 13 : 1119267064
Total Pages : 278 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Chemical and Biomedical Engineering Calculations Using Python by : Jeffrey J. Heys

Download or read book Chemical and Biomedical Engineering Calculations Using Python written by Jeffrey J. Heys and published by John Wiley & Sons. This book was released on 2017-01-10 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents standard numerical approaches for solving common mathematical problems in engineering using Python. Covers the most common numerical calculations used by engineering students Covers Numerical Differentiation and Integration, Initial Value Problems, Boundary Value Problems, and Partial Differential Equations Focuses on open ended, real world problems that require students to write a short report/memo as part of the solution process Includes an electronic download of the Python codes presented in the book

NumPy Simply In Depth

Author : Ajit Singh
Publisher : Ajit Singh
ISBN 13 :
Total Pages : 115 pages
Book Rating : 4./5 ( download)

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Book Synopsis NumPy Simply In Depth by : Ajit Singh

Download or read book NumPy Simply In Depth written by Ajit Singh and published by Ajit Singh. This book was released on with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers Python mathematical library NumPy in detail. NumPy (short for Numerical Python) provides an efficient interface to store and operate on dense data buffers. In some ways, NumPy arrays are like Python's built-in list type, but NumPy arrays provide much more efficient storage and data operations as the arrays grow larger in size. NumPy arrays form the core of nearly the entire ecosystem of data science tools in Python, so time spent learning to use NumPy effectively will be valuable no matter what aspect of data science interests you. You will learn all the essential things needed to become a confident NumPy user. NumPy started originally as part of SciPy and then was singled out as a fundamental library, which other open source Python APIs build on. As such, it is a crucial part of the common Python stack used for numerical and data analysis. Anyone with basic (and upward) knowledge of Python is the targeted audience for this book. Although the tools in NumPy are relatively advanced, using them is simple and should keep even a novice Python programmer happy. Features; ● 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 After reading this book, you 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.

Author :
Publisher : Cengage Learning
ISBN 13 : 0357684583
Total Pages : 978 pages
Book Rating : 4.3/5 (576 download)

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Book Synopsis by :

Download or read book written by and published by Cengage Learning. This book was released on with total page 978 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Optimization of Chemical Processes

Author : José María Ponce-Ortega
Publisher : Springer Nature
ISBN 13 : 303157270X
Total Pages : 496 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Optimization of Chemical Processes by : José María Ponce-Ortega

Download or read book Optimization of Chemical Processes written by José María Ponce-Ortega and published by Springer Nature. This book was released on with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt:

MACHINE LEARNING WITH PYTHON

Author : Abhishek Vijayvargia
Publisher : BPB Publications
ISBN 13 : 9387284883
Total Pages : 266 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis MACHINE LEARNING WITH PYTHON by : Abhishek Vijayvargia

Download or read book MACHINE LEARNING WITH PYTHON written by Abhishek Vijayvargia and published by BPB Publications. This book was released on 2018-06-02 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: DescriptionThis book provides the concept of machine learning with mathematical explanation and programming examples. Every chapter starts with fundamentals of the technique and working example on the real-world dataset. Along with the advice on applying algorithms, each technique is provided with advantages and disadvantages on the data.In this book we provide code examples in python. Python is the most suitable and worldwide accepted language for this. First, it is free and open source. It contains very good support from open community. It contains a lot of library, so you don't need to code everything. Also, it is scalable for large amount of data and suitable for big data technologies.This book:Covers all major areas in Machine Learning.Topics are discussed with graphical explanations.Comparison of different Machine Learning methods to solve any problem.Methods to handle real-world noisy data before applying any Machine Learning algorithm.Python code example for each concept discussed.Jupyter notebook scripts are provided with dataset used to test and try the algorithms ContentsIntroduction to Machine Learning Understanding Python Feature Engineering Data VisualisationBasic and Advanced Regression techniquesClassification Un Supervised LearningText AnalysisNeural Network and Deep Learning Recommendation System Time Series Analysis