| Publisher | Packt Publishing |
| ISBN 10 | 1783988347 |
| Author | Luiz Felipe Martins |
| Publication Date | 23 November 2014 |
| ISBN 13 | 9781783988341 |
| Book Description | Compute scientific data and execute code interactively with NumPy and SciPy About This Book Perform Computational ysis interactively Create quality displays using matplotlib and Python Data ysis Step-by-step guide with a rich set of examples and a thorough presentation of The IPython Notebook Who This Book Is For 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 ysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment. What You Will Learn Quickly install and get started with IPython Notebook Create interactive widgets in the Notebook Master the Notebook's interface and navigation features Create publication-quality graphs and displays of data with matplotlib Add media to the Notebook with IPython's Rich Display System Accelerate code using NumbaPro and concurrent computing Perform advanced scientific computations with SciPy Work with data in the Notebook with pandas In Detail In data science, it is difficult to present interesting visual or technical content, as it involves scientific notations that are not easy to type in a normal doent format. IPython provides a web-based UI called Notebook, which creates a working environment for interactive computing that combines code execution with computational doents. IPython Notebook makes the task simpler as it was developed for scientific programming to solve larger problems through a series of smaller programs. IPython Notebook is used to learn Python in a fun and interactive way and to do some serious parallel / technical computing. The book begins with an introduction to the efficient use of IPython Notebook for interactive computation. The book then focuses on the integration of technologies such as matplotlib, pandas, and SciPy. |
| Language | English |
| Number of Pages | 190 pages |
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