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MySQL for Python

You're reading from   MySQL for Python Integrating MySQL and Python can bring a whole new level of productivity to your applications. This practical tutorial shows you how with examples and explanations that clarify even the most difficult concepts.

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Product type Paperback
Published in Sep 2010
Publisher Packt
ISBN-13 9781849510189
Length 440 pages
Edition 1st Edition
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Author (1):
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Albert Lukaszewski Albert Lukaszewski
Author Profile Icon Albert Lukaszewski
Albert Lukaszewski
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Table of Contents (20) Chapters Close

MySQL for Python
Credits
About the Author
About the Reviewers
Preface
1. Getting Up and Running with MySQL for Python FREE CHAPTER 2. Simple Querying 3. Simple Insertion 4. Exception Handling 5. Results Record-by-Record 6. Inserting Multiple Entries 7. Creating and Dropping 8. Creating Users and Granting Access 9. Date and Time Values 10. Aggregate Functions and Clauses 11. SELECT Alternatives 12. String Functions 13. Showing MySQL Metadata 14. Disaster Recovery Index

Trimming results


MySQL allows for two different ways of trimming results when using aggregate functions. One is a keyword that removes redundant data. The other is a function that pools the data into a single string value.

DISTINCT

The purpose of DISTINCT is to ensure that all results are unique. The examples above do not discriminate between duplicate values. Each value is treated as a separate record without quantitative comparison to the others, thus allowing for redundancy in the results.

This redundancy works well when comprehensiveness is required but can otherwise skew the results of a query. For example, if we want to know how many unique ratings are used in the film table of sakila, we would not want to use this query:

SELECT COUNT(rating) FROM film;

The results show every record that has a value for the rating column.

+---------------+
| COUNT(rating) |
+---------------+
|          1000 |
+---------------+

Instead of retrieving the actual values and process 1000 records in our program...

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