Python for Data Scientists - IPython


Introduction


Having learned some basic packages of Python, you probably started to wonder that working through the python console is not very productive. In R we have RStudio, of which we've already talked in first articles. Good folks of Python community have developed an IPython - an interactive Python console and web environment.

Installation


As usual we are using python pip package manager to install the package: 
pip install ipython

Usage


Once the package is installed, you can launch the console version by simply typing it's name in the console: 
ipython
Once the application is started, one can simply type python commands and observe the results. Though it doesn't look that far different from the ordinary python console, it provides auto-quoting, code completion, search of previously executed commands, output caching and many more.
As I said previously, there are two modes of running the IPython - console and web. To launch the web interface, one must add the "notebook" parameter: 
ipython notebook
This will open http://localhost:8888/tree URL using a default browser. You can then create new IPython files, with ipynb extension, or upload one from the local file system.

The graphical interface is no doubt much more comfortable to use and adds numerous editing and flow control features on top of those supported by the console mode.



If you have chosen to work with Python language for your data project, IPython is a must to have tool. Make sure to have it in your toolkit.

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