![]() Or more like something so technical and difficult that I would never be able to learn it. But I didn’t know how to “interchain” and automate these.īack then, scripting seemed like some kind of magic to me. ![]() I wrote commands and code snippets in the command line or in Jupyter… Sure. You want to write scripts! When I first learned how a script works…īefore we get into this, let me share one of my personal experiences regarding learning data science…īack in the day, when I was an intern and I had never ever written any data scripts yet, I couldn’t imagine at all how they work. You want to automate the execution of your Python codes. That’s coding.īut, in data projects, you don’t want to run everything manually. ![]() We’ve run Python functions, methods, commands and other operations one by one, manually. See, in most of my Python for data science tutorials we were writing code in Jupyter Notebooks. But when you start to automate these tasks (either it’s data cleaning, data loading, analytics, machine learning algorithms or anything else) you’ll rely heavily on scripting. When working on data science projects, you’ll write Python code all the time… You know that already. In this tutorial, you’ll learn how to run a Python script.
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