Scientific tools

PyCharm supports the following tools for scientific computing:

• Formats for data view

  The Data View tool window supports NumPy arrays and pandas dataframes.

• Data visualization formats

  Matplotlib provides a set of Python plotting libraries.

• Jupyter Notebook

  IPython provides a rich architecture for interactive computing with data visualization.

  With the Jupyter Notebook integration available in PyCharm , you can easily edit, execute, and debug notebook source code and examine execution outputs including stream data, images, and other media.

• R language

  This support is available through the R plugin, which enables statistical computing using R language.

Support for these packages is enabled through the Scientific Mode, which is available only in the Professional edition of PyCharm.

note

You can try DataSpell, a new IDE that is tailored to the data science workflow. It provides a brand-new experience for working with Jupyter notebooks. The IDE is available as part of the Early Access program to collect early feedback and gain insight into the needs and behavior of data scientists. See the DataSpell Getting Started Guide for more details.