December 2016
Beginner
388 pages
8h 35m
English
Content preview from Principles of Data ScienceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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The road thus far…
So far in this chapter, we have looked at the differences between structured and unstructured data as well as between qualitative and quantitative characteristics. These two simple distinctions can have drastic effects on the analysis that is performed. Allow me to summarize before moving on the second half of the chapter.
Data as a whole can either be structured or unstructured, meaning that the data can either take on an organized row/column structure with distinct features that describe each row of the dataset, or exist in a free-form state that usually must be preprocessed into a form that is easily digestible.
If data is structured, we can look at each column (feature) of the dataset as being either quantitative or qualitative ...
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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.