December 2022
Beginner to intermediate
740 pages
18h 11m
English
Content preview from Python for Finance Cookbook - Second Edition
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2
Data Preprocessing
You often hear in the data science industry that a data scientist typically spends close to 80% of their time on getting the data, processing it, cleaning it, and so on. And only then the remaining 20% of the time is actually spent on modeling, which is often considered to be the most interesting part. In the previous chapter, we have already learned how to download data from various sources. We still need to go through a few steps before we can draw actual insights from the data.
In this chapter, we will cover data preprocessing, that is, general wrangling/manipulation applied to the data before using it. The goal is not only to enhance the model’s performance but also to ensure the validity of any analysis based on that ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.