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Learning Ipython for Interactive Computing and Data Visualization - Second Edition
Get started with Python for data analysis and numerical computing in the Jupyter notebook
Learning Ipython for Interactive Computing and Data Visualization - Second Edition
物品 #: 86750251

Learning Ipython for Interactive Computing and Data Visualization - Second Edition

物品 #: 86750251

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What Stands Out

Interactive Learning
Offers an engaging, hands-on approach to mastering IPython and Jupyter Notebook, making it ideal for data analysts eager to enhance their skills in real-time computing.
Comprehensive Coverage
Provides in-depth tutorials on data visualization and numerical computing, ensuring learners gain a thorough understanding crucial for effective data analysis.
Updated Techniques
Features the latest practices and tools in interactive computing, empowering users to leverage current technology trends for optimized data manipulation and visualization.

產品詳情

Shop Learning Ipython for Interactive Computing and Data Visualization - Second Edition online at a best price in 香港. 1783986980
  • Get started with Python for data analysis and numerical computing in the Jupyter notebookAbout This BookLearn the basics of Python in the Jupyter NotebookAnalyze and visualize data with pandas, NumPy, matplotlib, and seabornPerform highly-efficient numerical computations with Numba, Cython, and ipyparallelWho This Book Is ForThis 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.Table of ContentsWhat You Will LearnInstall Anaconda and code in Python in the Jupyter NotebookLoad and explore datasets interactivelyPerform complex data manipulations effectively with pandasCreate engaging data visualizations with matplotlib and seabornSimulate mathematical models with NumPyVisualize and process images interactively in the Jupyter Notebook with scikit-imageAccelerate your code with Numba, Cython, and IPython.parallelExtend the Notebook interface with HTML, JavaScript, and D3In DetailPython 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.
Publisher Packt Publishing
Publication date October 1, 2015
Edition 2nd
Language English
Print length 175 pages
ISBN-10 1783986980
ISBN-13 978-1783986989
Item Weight 12.8 ounces (362.88 grams)
Dimensions 7.5 x 0.46 x 9.25 inches (19.1 x 1.2 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Analysts

    Ideal for data analysts seeking practical skills in data visualization and interactive computing with Python.

  • Beginners

    Great for programming novices wanting to learn Python and data analysis using Jupyter Notebook effectively.

  • Educators

    Useful for teachers wishing to incorporate interactive computing and data visualization in their curriculum using IPython.

Not Suitable For
  • Advanced Users

    May not suit experienced programmers who already possess advanced skills in Python and data visualization.

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