June 2020
Intermediate to advanced
322 pages
7h 25m
English
Content preview from Practical Data Analysis Using Jupyter Notebook
Exploring, Cleaning, Refining, and Blending Datasets
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In the previous chapter, we learned about the power of data visualizations, and the importance of having good-quality, consistent data defined with dimensions and measures.
Now that we understand why that's important, we are going to focus on the how throughout this chapter by working hands-on with data. Most of the examples provided so far included data that was already prepped (prepared) ahead of time for easier consumption. We are now switching gears by learning the skills that are necessary to be comfortable working with data to increase your data literacy.
A key concept of this chapter is cleaning, filtering, and refining data. In many cases, the reason why you need to perform these ...
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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.