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Python: Data Analytics and Visualization
book

Python: Data Analytics and Visualization

by Phuong Vo.T.H, Martin Czygan, Ashish Kumar, Kirthi Raman
March 2017
Beginner to intermediate
866 pages
18h 4m
English
Packt Publishing
Content preview from Python: Data Analytics and Visualization

Concatenating and appending data

All the required information to build a model doesn't always come from a single table or data source. In many cases, two datasets need to be joined/merged to get more information (read new column/variable). Sometimes, small datasets need to be appended together to make a big dataset which contains the complete picture. Thus, merging and appending are important components of an analyst's armor.

Let's learn each of these methods one by one. For illustrating these methods, we will be using a lot of new interesting datasets. The one we are going to use first is a dataset about the mineral contents of wine; we will have separate datasets for red and white wine. Each sample represents a different sample of red or white ...

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Publisher Resources

ISBN: 9781788290098Supplemental ContentPurchase Link