If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.;Cov
IPython Notebook Essentials: Compute scientific data and execute code interactively with NumPy and SciPy
β Scribed by Martins L.F.
- Tongue
- English
- Leaves
- 190
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Packt Publishing; 2014. β 190 p. β ISBN: 9781783988341
Scientists, engineers, and programmers were quick to address this issue. Hardware costs decreased as performance went up, and there was a great push to develop scripting languages that allowed integration of disparate libraries through multiple platforms. It was in this environment that Python was being developed in the late 1980s, under the leadership of Guido Van Rossum. From the beginning, Python was designed to be a cutting-edge, high-level computer language with a simple enough structure that its basics could be quickly learned even by programmers who are not experts.One of Python's attractive features for rapid development was its interactive shell, through which programmers could experiment with concepts interactively before including them in scripts. However, the original Python shell had a limited set of features and better interactivity was necessary. Starting from 2001, Fernando Perez started developing IPython, an improved interactive Python shell designed specifically for scientific computing.
β¦ Subjects
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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, demon
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, demon
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, demon
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