February 2024
Beginner
352 pages
8h 16m
English
book
Learn Python the Hard Way: A Deceptively Simple Introduction to the Terrifyingly Beautiful World of Computers and Data Science, 5th Edition
by Zed A. Shaw
Content preview from Learn Python the Hard Way: A Deceptively Simple Introduction to the Terrifyingly Beautiful World of Computers and Data Science, 5th Edition
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Exercise 58
SQL Normalization
In the previous exercise, we explored SQL basics using the European Central Bank’s historic Euro data set. In this exercise I’m going to teach you about data modeling by reshaping this data into multiple tables to “normalize” it.
What Is Normalization?
Normalization is about reducing redundancy in your data set. You see some form of redundancy, move it into a separate table, and then link the two tables via an id column. It gets far more complex and theoretical, but this is the general idea. Doing this has a few advantages:
It reduces the size of your data, and reduced size generally improves performance (but not always).
It helps you understand the structure of the data possibly giving you better insights into ...
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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.