Skip to Content
Practical Data Analysis Cookbook
book

Practical Data Analysis Cookbook

by Tomasz Drabas
April 2016
Beginner to intermediate content levelBeginner to intermediate
384 pages
8h 36m
English
Packt Publishing
Content preview from Practical Data Analysis Cookbook

Removing duplicates

We can safely assume that all the data that lands on our desks is dirty (until proven otherwise). It is a good habit to check whether everything with our data is in order. The first thing I always check for is the duplication of rows.

Getting ready

To follow this recipe, you need to have OpenRefine and virtually any Internet browser installed on your computer.

We assume that you followed the previous recipes and your data is already loaded to OpenRefine and the data types are now representative of what the columns hold. No other prerequisites are required.

How to do it…

First, we assume that within the seven days of property sales, a row is a duplicate if the same address appears twice (or more) in the dataset. It is quite unlikely ...

Become 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,
and much more.
Start your free trial

You might also like

Python Data Analysis Cookbook

Python Data Analysis Cookbook

Ivan Idris
Practical Simulations for Machine Learning

Practical Simulations for Machine Learning

Paris Buttfield-Addison, Mars Buttfield-Addison, Tim Nugent, Jon Manning

Publisher Resources

ISBN: 9781783551668Supplemental Content