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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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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 - Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 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

Chapter 8.  Working 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. Relationships may also be 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) as well as connections between columns in other tables.

Not Only SQL (NoSQL) databases are frequently used in big data and web applications. NoSQL systems may permit SQL-like query languages to be employed. NoSQL databases allow data to be stored in a more flexible manner than the relational model permits. This may mean not having a database schema or a flexible database schema. Of course, the flexibility and speed may come at a price, such as limited support for consistent transactions...

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