PostgreSQL Example – How to Compare Values To Subquery

Compare Values To Subquery

Create Table Of Elves

- Create table called elves
CREATE TABLE elves (
    - string variable
    name varchar(255),
    - integer variable
    age int,
    - string variable
    race varchar(255),
    - string variable
    weapon varchar(255)
)

Create Table Of Dwarves

- Create table called dwarves
CREATE TABLE dwarves (
    - string variable
    name varchar(255),
    - integer variable
    age int,
    - string variable
    race varchar(255),
    - string variable
    weapon varchar(255)
)

Insert Rows Into Elf Table


INSERT INTO elves (name, age, race, weapon)
VALUES ('Dallar Woodfoot', 25, 'Elf', 'Bow'),
       ('Cordin Garner', 29, 'Elf', 'Bow'),
       ('Keat Knigh', 24, 'Elf', 'Sword'),
       ('Colbat Nalor', 124, 'Elf', 'Magic')

Insert Rows Into Dwarf Table


INSERT INTO dwarves (name, age, race, weapon)
VALUES ('Kalog', 23, 'Dwarf', 'Axe'),
       ('Dranar', 145, 'Dwarf', 'Bow'),
       ('Bratar', 12, 'Dwarf', 'Axe'),
       ('Dragga', 23, 'Dwarf', 'Axe')

Check If Each Elf Is Older Than Any Of The Dwarves

- Retrieve All The Elves
SELECT * FROM elves
- Where their age is greater than at least one
WHERE age > ANY (
    - Of all the Dwarves
    SELECT age FROM dwarves
    )
name age race weapon
Dallar Woodfoot 25 Elf Bow
Cordin Garner 29 Elf Bow
Keat Knigh 24 Elf Sword
Colbat Nalor 124 Elf Magic

Check If Each Elf Is Older Than All Of The Dwarves


- Retrieve All The Elves
SELECT * FROM elves
- Where their age is greater than all
WHERE age > ALL (
    - Of all the Dwarves
    SELECT age FROM dwarves
    )

 

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

Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!

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