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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (22) Chapters Close

Python Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency Key Concepts
Useful Functions Online Resources
Index

Chapter 8. Working with Databases

If you work with data, sooner or later, you will come into contact with databases. This chapter introduces various databases (relational and NoSQL) and related APIs. A relational database is a database that has a collection of tables containing data organized by the relations between data items. A relationship can be set up between each row in the table and a row in another table. A relational database does not just pertain to relationships between tables; firstly, it has to do with the relationship between columns inside a table (obviously, columns within a table have to be related, for instance, a name column and an address column in a customer table); secondly, it relates to connections between tables.

NoSQL (Not Only SQL) databases are undergoing substantial growth in Big Data and web applications. NoSQL systems may in fact permit SQL-like query languages to be employed. The main theme of NoSQL databases is allowing data to be stored in a more flexible...

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