2017 - Python Data Science Handbook - VanderPlas J

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There are several choices for development environments for Python, and I’m usually asked that one I take advantage of in my very own work. My answer generally surprises people: my preferred surroundings is IPython and a text editor (in my case, Emacs or Atom depending on my mood).

IPython (short for Interactive Python) was started in 2001 by Fernando Perez as Associate Python interpreter, and has since enlarge so big into a project planning to give, in Perez’s words, “Tools for the whole lifecycle of analysis computing”. If Python is the engine of our knowledge science task, you would possibly think about IPython as the interactive board. As well as being a helpful interactive interface to Python, IPython conjointly provides a number of helpful grammar additions to the language; we’ll cowl the foremost helpful of these additions here.

Additionally, IPython is closely tied with the Jupyter project, which provides a browser-based handbook that is helpful for development, collaboration, sharing and even publication of knowledge science results. This IPython handbook is actually a special case of the broader Jupyter notebook structure, that encompasses notebooks for Julia, R, and different programming languages.

As Associate in example of the quality of the notebook format, look no more than the page you're reading: the entire manuscript for this book was composed as a group of IPython notebooks.

IPython consist on is regarding Python effectively for interactive scientific and data-intensive computing. This chapter can begin by stepping through a number of the IPython options that are helpful to the apply of knowledge science, focusing particularly on the syntax it offers on the far side the quality options of Python. Next, we'll move into a small amount additional depth on a number of the additional helpful “magic commands” which will speed up common tasks to create and use knowledge science code. Finally, we'll bit on a number of the options the handbook create it helpful in understanding knowledge and sharing results.


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