Hi everyone ππ.I wanted to introduce Pandas to you in case itβs new to you. We will be working a lot with it in the future so a nice introduction will go a long way π.I have asked a few of my friends βΌοΈ to help me introduce Pandas to you by showing up on the post ππ.Jokes aside, Pandas is a really powerful data analytics library in Python that I use almost everyday. Itβs robust, fast, and great for prototyping data science problems π§ ..It quickly feels like youβre working with a database, so if you know SQL this wonβt feel too different..Let me know who your favorite founder is from the 4 on the picture. Iβll keep mine a secret for now. π
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Hi everyone ππ.My friends are here again for part 2 of our intro to Pandasπππ.In Pandas, you can easily extract more useful data points from existing data in the table, and because Pandas has been optimized to work on large amounts of data, column operations are super fast π¨..Here I divide the foundersβ net worth by their age, to get a sense of their average wealth accumulation rate.Then I am interested to see whoβs accumulated wealth the fastest, so I sort the column in the descending order ππ».Super fast, in a few lines, I have answered a couple of my questions about my favorite founders π.
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