PostgreSQL – HAVING Clause
The HAVING clause allows us to pick out particular rows where the function’s result meets some condition.
The WHERE clause places conditions on the selected columns, whereas the HAVING clause places conditions on groups created by the GROUP BY clause.
The following is the position of the HAVING clause in a SELECT query −
SELECT FROM WHERE GROUP BY HAVING ORDER BY
The HAVING clause must follow the GROUP BY clause in a query and must also precede the ORDER BY clause if used. The following is the syntax of the SELECT statement, including the HAVING clause −
SELECT column1, column2 FROM table1, table2 WHERE [ conditions ] GROUP BY column1, column2 HAVING [ conditions ] ORDER BY column1, column2
Consider the table COMPANY having records as follows −
# select * from COMPANY; id | name | age | address | salary ----+-------+-----+-----------+-------- 1 | Paul | 32 | California| 20000 2 | Allen | 25 | Texas | 15000 3 | Teddy | 23 | Norway | 20000 4 | Mark | 25 | Rich-Mond | 65000 5 | David | 27 | Texas | 85000 6 | Kim | 22 | South-Hall| 45000 7 | James | 24 | Houston | 10000 (7 rows)
The following is an example, which would display record for which the name count is less than 2 −
testdb-# SELECT NAME FROM COMPANY GROUP BY name HAVING count(name) < 2;
This would produce the following result −
name ------- Teddy Paul Mark David Allen Kim James (7 rows)
Now, let us create three more records in COMPANY table using the following INSERT statements −
INSERT INTO COMPANY VALUES (8, 'Paul', 24, 'Houston', 20000.00); INSERT INTO COMPANY VALUES (9, 'James', 44, 'Norway', 5000.00); INSERT INTO COMPANY VALUES (10, 'James', 45, 'Texas', 5000.00);
Now, our table has the following records with duplicate names −
id | name | age | address | salary ----+-------+-----+--------------+-------- 1 | Paul | 32 | California | 20000 2 | Allen | 25 | Texas | 15000 3 | Teddy | 23 | Norway | 20000 4 | Mark | 25 | Rich-Mond | 65000 5 | David | 27 | Texas | 85000 6 | Kim | 22 | South-Hall | 45000 7 | James | 24 | Houston | 10000 8 | Paul | 24 | Houston | 20000 9 | James | 44 | Norway | 5000 10 | James | 45 | Texas | 5000 (10 rows)
The following is the example, which would display record for which the name count is greater than 1 −
testdb-# SELECT NAME FROM COMPANY GROUP BY name HAVING count(name) > 1;
This would produce the following result −
name ------- Paul James (2 rows)
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
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