August 2015
Beginner to intermediate
294 pages
5h 20m
English
Content preview from Mastering Python for 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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Chapter 1. Getting Started with Raw Data
In the world of data science, raw data comes in many forms and sizes. There is a lot of information that can be extracted from this raw data. To give an example, Amazon collects click stream data that records each and every click of the user on the website. This data can be utilized to understand if a user is a price-sensitive customer or prefer more popularly rated products. You must have noticed recommended products in Amazon; they are derived using such data.
The first step towards such an analysis would be to parse raw data. The parsing of the data involves the following steps:
- Extracting data from the source: Data can come in many forms, such as Excel, CSV, JSON, databases, and so on. Python makes it ...
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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.