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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

HAVING clause


The HAVING clause has similar effect to the WHERE clause. The syntax is virtually the same:

SELECT <some column(s)> FROM <table> HAVING <met a certain condition>;

Indeed, in some statements, one can be tempted to replace WHERE with HAVING because the syntax is so similar, and sometimes one would not notice much, if any, difference in the returned data. However, each has its purpose and is applied differently, as discussed later in this chapter.

WHERE versus HAVING: Syntax

The HAVING clause can only be applied to columns that have been previously indicated in the statement. For example, using the sakila database, let's say we wanted every record from film that was updated since 2005. Trying to hack from our knowledge of WHERE, we might try the following:

SELECT title FROM film HAVING YEAR(last_update) > '2005';

But we would be wrong and would be greeted with an error:

ERROR 1054 (42S22): Unknown column 'last_update' in 'having clause'

One way of resolving the...

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