Popular IDEs for Python are Spyder, P圜harm, VSCode, and Jupyter Notebooks. Pretty much all educational content and examples you will find on-line about the subject are created in and for IDEs. In this mini-workshop I’ll focus on IDEs, as they are more commonly used alternative for data analysis and scientific computing with Python. Via an Integrated Development Environment (IDE).Via the terminal by running Python scripts written in a text editor.Via the terminal in Python interactive mode.There are several ways in which we can interact with Python:
IDEs: Integrated Development Environments The Jupyter Notebook version can be found in my GitHub here.This tutorial contains video-lessons at the end of each section.
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