I started using Python for data science about a year ago. On day one, I spent the first four hours figuring out how to access Python. It turns out its

Low Code Python is available in Jupyter

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2021-06-15 17:30:15

I started using Python for data science about a year ago. On day one, I spent the first four hours figuring out how to access Python. It turns out its a lot easier to use your terminal to wipe your hard drive than it is to download Python.

Opening a Jupyter Notebook for the first time is a weird experience. It looks old — not vintage — old. The combination of grey, white, tan is humbling. You definitely feel on your own and the interface screams “you better learn to code.”

So I did. A combination of Kaggle, YouTube videos (shout out to the Data Professor) and harassing my data scientist friends (shout out to my friends) got me to a pretty comfortable place with Pandas. I understood the capabilities that I had in the Pandas tool belt and I was able to plot a course of action for many tasks.

But I quickly approached a wall. For the life of me, I couldn’t remember the syntax for a Pandas pivot… or a merge… or a filter…. or changing a data type…. or my sister’s birthday (I know it’s always on a Wednesday). Pandas is not the hardest syntax for a computer language by any stretch, but it can still give grief to intermediate and advanced users.