Sql fundamentals group by part2
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This document discusses SQL aggregate functions, group by, and having clauses. It defines aggregate functions as functions that return a single output value after aggregating multiple input values. Common aggregate functions listed are AVG(), COUNT(), MAX(), MIN(), and SUM(). Group by allows aggregation of columns by category and is used with select and aggregate functions. Having allows filtering of group by results after aggregation. Examples show using group by to aggregate average values by category and having to filter groups where the aggregate sum is over 1000.
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It can be divided into fluid statics, the study of various fluids at rest, and fluid dynamics.
Fluid statics, also known as hydrostatics, is the study of fluids at rest, specifically when there's no relative motion between fluid particles. It focuses on the conditions under which fluids are in stable equilibrium and doesn't involve fluid motion.
Fluid kinematics is the branch of fluid mechanics that focuses on describing and analyzing the motion of fluids, such as liquids and gases, without considering the forces that cause the motion. It deals with the geometrical and temporal aspects of fluid flow, including velocity and acceleration. Fluid dynamics, on the other hand, considers the forces acting on the fluid.
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Sql fundamentals group by part2
- 2. Topics 1. Aggregate Functions 2. Group By 3. Having
- 3. Aggregate Functions ● Sql provides variety of aggregate functions. ● It returns single output.
- 4. Most Common Aggregate Functions 1. AVG() Return avg value 2. COUNT() Return number of values 3. MAX() Return maximum value 4. MIN() Return minimum value 5. SUM() Return sum of all values
- 5. Aggregate Function ● Aggregate function only used with Select Clause or having clause.
- 6. Group By ● Group By allows us to aggregate columns per some category.
- 7. Group By
- 8. Group By CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); Select category_column, AVG(data_col) FROM table GROUP BY category_column
- 9. Group By CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); Select category_column, AVG(data_col) FROM table WHERE category_col != ‘A’ GROUP BY category_column
- 10. Group By CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); Select category_column, AVG(data_col) FROM table WHERE category_col != ‘A’ GROUP BY category_column ORDER BY AVG(data_col)
- 11. Group By CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); CREATE TABLE food ( food_id SERIAL PRIMARY KEY, name VARCHAR(50) NOT NULL, type VARCHAR NOT NULL, created_on TIMESTAMP NOT NULL ); Select category_column, AVG(data_col) FROM table WHERE category_col != ‘A’ GROUP BY category_column ORDER BY AVG(data_col) LIMIT 5
- 12. Having ● Having Clause allows us to filter after an aggregation has already taken place. ● To perform filtering on Group By.
- 14. Having Select company, SUM(sales) FROM finance_table GROUP BY company Having sum(sales) > 1000
- 15. Having Select company, SUM(sales) FROM finance_table WHERE company != ‘Google’ GROUP BY company Having sum(sales) > 1000
- 16. Thank You