Learning Ipython For Interactive Computing And Data Visualization
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Learning Ipython For Interactive Computing And Data Visualization
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Author : Cyrille Rossant
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-21
Learning Ipython For Interactive Computing And Data Visualization written by Cyrille Rossant 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 2015-10-21 with Computers categories.
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.
Ipython Interactive Computing And Visualization Cookbook
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Author : Cyrille Rossant
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-09-25
Ipython Interactive Computing And Visualization Cookbook written by Cyrille Rossant 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 2014-09-25 with Computers categories.
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
Learning Ipython For Interactive Computing And Data Visualization Second Edition
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Author : Cyrille Rossant
language : en
Publisher:
Release Date : 2015
Learning Ipython For Interactive Computing And Data Visualization Second Edition written by Cyrille Rossant and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer graphics categories.
IPython provides a rich architecture for interactive computing, and as a Python developer you can take advantage of this practical hands-on guide to make yourself an expert. Covers numerical computing, data analysis, and more. Overview A practical step-by-step tutorial which will help you to replace the Python console with the powerful IPython command-line interface Use the IPython notebook to modernize the way you interact with Python Perform highly efficient computations with NumPy and Pandas Optimize your code using parallel computing and Cython In Detail You already use Python as a scripting language, but did you know it is also increasingly used for scientific computing and data analysis? Interactive programming is essential in such exploratory tasks and IPython is the perfect tool for that. Once you've learnt it, you won't be able to live without it. "Learning IPython for Interactive Computing and Data Visualization" is a practical, hands-on, example-driven tutorial to considerably improve your productivity during interactive Python sessions, and shows you how to effectively use IPython for interactive computing and data analysis. This book covers all aspects of IPython, from the highly powerful interactive Python console to the numerical and visualization features that are commonly associated with IPython. You will learn how IPython lets you perform efficient vectorized computations, through examples covering numerical simulations with NumPy, data analysis with Pandas, and visualization with Matplotlib. You will also discover how IPython can be conveniently used to optimize your code using parallel computing and dynamic compilation in C with Cython. "Learning IPython for Interactive Computing and Data Visualization" will allow you to optimize your productivity in interactive Python sessions. What you will learn from this book Debug your code from the IPython console Benchmark and profile your code from IPython Perform efficient vectorized computations with NumPy Analyze data tables with Pandas Create visualizations with Matplotlib Parallelize your code easily with IPython Customize IPython and create your own magic commands Accelerate your Python code using dynamic C compilation with Cython Approach A practical hands-on guide which focuses on interactive programming, numerical computing, and data analysis with IPython. Who this book is written for This book is for Python developers who use Python as a scripting language or for software development, and are interested in learning IPython for increasing their productivity during interactive sessions in the console. Knowledge of Python is required, whereas no knowledge of IPython is necessary.
Learning Ipython For Interactive Computing And Data Visualization
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Author : Cyrille Rossant
language : en
Publisher:
Release Date : 2015-02-24
Learning Ipython For Interactive Computing And Data Visualization written by Cyrille Rossant and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-24 with Computers categories.
IPython provides a rich architecture for interactive computing, and as a Python developer you can take advantage of this practical hands-on guide to make yourself an expert. Covers numerical computing, data analysis, and more. Overview A practical step-by-step tutorial which will help you to replace the Python console with the powerful IPython command-line interface Use the IPython notebook to modernize the way you interact with Python Perform highly efficient computations with NumPy and Pandas Optimize your code using parallel computing and Cython In Detail You already use Python as a scripting language, but did you know it is also increasingly used for scientific computing and data analysis? Interactive programming is essential in such exploratory tasks and IPython is the perfect tool for that. Once you've learnt it, you won't be able to live without it. "Learning IPython for Interactive Computing and Data Visualization" is a practical, hands-on, example-driven tutorial to considerably improve your productivity during interactive Python sessions, and shows you how to effectively use IPython for interactive computing and data analysis. This book covers all aspects of IPython, from the highly powerful interactive Python console to the numerical and visualization features that are commonly associated with IPython. You will learn how IPython lets you perform efficient vectorized computations, through examples covering numerical simulations with NumPy, data analysis with Pandas, and visualization with Matplotlib. You will also discover how IPython can be conveniently used to optimize your code using parallel computing and dynamic compilation in C with Cython. "Learning IPython for Interactive Computing and Data Visualization" will allow you to optimize your productivity in interactive Python sessions. What you will learn from this book Debug your code from the IPython console Benchmark and profile your code from IPython Perform efficient vectorized computations with NumPy Analyze data tables with Pandas Create visualizations with Matplotlib Parallelize your code easily with IPython Customize IPython and create your own magic commands Accelerate your Python code using dynamic C compilation with Cython Approach A practical hands-on guide which focuses on interactive programming, numerical computing, and data analysis with IPython. Who this book is written for This book is for Python developers who use Python as a scripting language or for software development, and are interested in learning IPython for increasing their productivity during interactive sessions in the console. Knowledge of Python is required, whereas no knowledge of IPython is necessary.
Ipython Interactive Computing And Visualization Cookbook Second Edition
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Author : Cyrille Rossant
language : en
Publisher:
Release Date : 2018-01-31
Ipython Interactive Computing And Visualization Cookbook Second Edition written by Cyrille Rossant and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with categories.
Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Book Description Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. What you will learn Master all features of the Jupyter Notebook Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory Who this book is for This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
Ipython Interactive Computing And Visualization Cookbook
DOWNLOAD
Author : Cyrille Rossant
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-31
Ipython Interactive Computing And Visualization Cookbook written by Cyrille Rossant 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 2018-01-31 with Computers categories.
Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Book Description Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. What you will learn Master all features of the Jupyter Notebook Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory Who this book is for This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
Learning Predictive Analytics With Python
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Author : Ashish Kumar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-02-15
Learning Predictive Analytics With Python written by Ashish Kumar 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 2016-02-15 with Computers categories.
Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Get to grips with the basics of Predictive Analytics with Python Learn how to use the popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Who This Book Is For If you wish to learn how to implement Predictive Analytics algorithms using Python libraries, then this is the book for you. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about Predictive Analytics algorithms, this book will also help you. The book will be beneficial to and can be read by any Data Science enthusiasts. Some familiarity with Python will be useful to get the most out of this book, but it is certainly not a prerequisite. What You Will Learn Understand the statistical and mathematical concepts behind Predictive Analytics algorithms and implement Predictive Analytics algorithms using Python libraries Analyze the result parameters arising from the implementation of Predictive Analytics algorithms Write Python modules/functions from scratch to execute segments or the whole of these algorithms Recognize and mitigate various contingencies and issues related to the implementation of Predictive Analytics algorithms Get to know various methods of importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and numpy Create dummy datasets and simple mathematical simulations using the Python numpy and pandas libraries Understand the best practices while handling datasets in Python and creating predictive models out of them In Detail Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You'll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. Style and approach All the concepts in this book been explained and illustrated using a dataset, and in a step-by-step manner. The Python code snippet to implement a method or concept is followed by the output, such as charts, dataset heads, pictures, and so on. The statistical concepts are explained in detail wherever required.
Interactive Applications Using Matplotlib
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Author : Benjamin V. Root
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-03-24
Interactive Applications Using Matplotlib written by Benjamin V. Root 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 2015-03-24 with Computers categories.
This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
Learning Cython Programming
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Author : Philip Herron
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-02-22
Learning Cython Programming written by Philip Herron 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 2016-02-22 with Computers categories.
Learn the fundamentals of Cython to extend the legacy of your applications About This Book Learn how to extend C applications with pure Python code Get more from Python – you'll not only learn Cython, you'll also unlock a greater understanding of how to harness Python Packed with tips and tricks that make Cython look easy, dive into this accessible programming guide and find out what happens when you bring C and Python together! Who This Book Is For This book is for developers who are familiar with the basics of C and Python programming and wish to learn Cython programming to extend their applications. What You Will Learn Reuse Python logging in C Make an IRC bot out of your C application Extend an application so you have a web server for rest calls Practice Cython against your C++ code Discover tricks to work with Python ConfigParser in C Create Python bindings for native libraries Find out about threading and concurrency related to GIL Expand Terminal Multiplexer Tmux with Cython In Detail Cython is a hybrid programming language used to write C extensions for Python language. Combining the practicality of Python and speed and ease of the C language it's an exciting language worth learning if you want to build fast applications with ease. This new edition of Learning Cython Programming shows you how to get started, taking you through the fundamentals so you can begin to experience its unique powers. You'll find out how to get set up, before exploring the relationship between Python and Cython. You'll also look at debugging Cython, before moving on to C++ constructs, Caveat on C++ usage, Python threading and GIL in Cython. Finally, you'll learn object initialization and compile time, and gain a deeper insight into Python 3, which will help you not only become a confident Cython developer, but a much more fluent Python developer too. Style and approach This practical and a fast-paced guide gives you all the information you need to start programming using Cython.
Mastering Ipython 4 0
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Author : Thomas Bitterman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-05-30
Mastering Ipython 4 0 written by Thomas Bitterman 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 2016-05-30 with Computers categories.
Get to grips with the advanced concepts of interactive computing to make the most out of IPython About This Book Most updated book on Interactive computing with IPython 4.0; Detailed, example-rich guide that lets you use the most advanced level interactive programming with IPython; Get flexible interactive programming with IPython using this comprehensive guide Who This Book Is For This book is for IPython developers who want to make the most of IPython and perform advanced scientific computing with IPython utilizing the ease of interactive computing. It is ideal for users who wish to learn about the interactive and parallel computing properties of IPython 4.0, along with its integration with third-party tools and concepts such as testing and documenting results. What You Will Learn Develop skills to use IPython for high performance computing (HPC) Understand the IPython interactive shell Use XeroMQ and MPI to pass messages Integrate third-party tools like R, Julia, and JavaScript with IPython Visualize the data Acquire knowledge to test and document the data Get to grips with the recent developments in the Jupyter notebook system In Detail IPython is an interactive computational environment in which you can combine code execution, rich text, mathematics, plots, and rich media. This book will get IPython developers up to date with the latest advancements in IPython and dive deep into interactive computing with IPython. This an advanced guide on interactive and parallel computing with IPython will explore advanced visualizations and high-performance computing with IPython in detail. You will quickly brush up your knowledge of IPython kernels and wrapper kernels, then we'll move to advanced concepts such as testing, Sphinx, JS events, interactive work, and the ZMQ cluster. The book will cover topics such as IPython Console Lexer, advanced configuration, and third-party tools. By the end of this book, you will be able to use IPython for interactive and parallel computing in a high-performance computing environment. Style and approach This is a comprehensive guide to IPython for interactive, exploratory and parallel computing. It will let the IPython get up to date with the latest advancements in IPython and dive deeper into interactive computing with IPython