IDE or Integrated Development Environment is a code programming tool used for writing, testing, debugging, and intuitively compile code. Any people who work with the programming language would need an IDE to make their job easier. Well, you could code in the notepad, but obviously, why you want to do that? — There are many IDE developed that support our works.

For you who already familiar with the Jupyter Notebook, it is also an IDE that is interactive, beginner-friendly, and could be used for presentation. It is a great tool for any level of Data Scientist. However, you would realize that Jupyter Notebook lacks any development and debugging purposes. This is because Jupyter Notebook is mainly developed for testing and document sharing rather than code development. Hence you might want to look into another IDE that still suits Data Scientist needs but could use for development.

In this article, I want to share my top 4 IDE for Data Scientist that I used in a different situation. Let’s get into it.

• Spyder
• Thonny
• Atom
• PyCharm

#python #data-science #pycharm #atom #thonny