PyCharm supports the following tools for scientific computing:
The Data View tool window supports NumPy arrays and pandas dataframes.
Matplotlib provides a set of Python plotting libraries.
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.
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.
Last modified: 11 August 2021