practical-sql-2/Chapter_07/Chapter_07.sql

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-- Practical SQL: A Beginner's Guide to Storytelling with Data, 2nd Edition
-- by Anthony DeBarros

-- Chapter 7     Code Examples
----------------------------------------------------------------------------


-- Listing 7-1: Creating the departments and employees tables

CREATE TABLE departments (
    dept_id integer,
    dept text,
    city text,
    CONSTRAINT dept_key PRIMARY KEY (dept_id),
    CONSTRAINT dept_city_unique UNIQUE (dept, city)
);

CREATE TABLE employees (
    emp_id integer,
    first_name text,
    last_name text,
    salary numeric(10,2),
    dept_id integer REFERENCES departments (dept_id),
    CONSTRAINT emp_key PRIMARY KEY (emp_id),
    CONSTRAINT emp_dept_unique UNIQUE (emp_id, dept_id)
);

INSERT INTO departments
VALUES
    (1, 'Tax', 'Atlanta'),
    (2, 'IT', 'Boston');

INSERT INTO employees
VALUES
    (1, 'Julia', 'Reyes', 115300, 1),
    (2, 'Janet', 'King', 98000, 1),
    (3, 'Arthur', 'Pappas', 72700, 2),
    (4, 'Michael', 'Taylor', 89500, 2);

-- Listing 7-2: Joining the employees and departments tables

SELECT *
FROM employees JOIN departments
ON employees.dept_id = departments.dept_id;

-- Listing 7-3: Creating two tables to explore JOIN types

CREATE TABLE schools_left (
    id integer CONSTRAINT left_id_key PRIMARY KEY,
    left_school varchar(30)
);

CREATE TABLE schools_right (
    id integer CONSTRAINT right_id_key PRIMARY KEY,
    right_school varchar(30)
);

INSERT INTO schools_left (id, left_school) VALUES
    (1, 'Oak Street School'),
    (2, 'Roosevelt High School'),
    (5, 'Washington Middle School'),
    (6, 'Jefferson High School');

INSERT INTO schools_right (id, right_school) VALUES
    (1, 'Oak Street School'),
    (2, 'Roosevelt High School'),
    (3, 'Morrison Elementary'),
    (4, 'Chase Magnet Academy'),
    (6, 'Jefferson High School');

-- Listing 7-4: Using JOIN

SELECT *
FROM schools_left JOIN schools_right
ON schools_left.id = schools_right.id;

-- Bonus: Also can be specified as INNER JOIN

SELECT *
FROM schools_left INNER JOIN schools_right
ON schools_left.id = schools_right.id;

-- Listing 7-5: Using LEFT JOIN

SELECT *
FROM schools_left LEFT JOIN schools_right
ON schools_left.id = schools_right.id;

-- Listing 7-6: Using RIGHT JOIN

SELECT *
FROM schools_left RIGHT JOIN schools_right
ON schools_left.id = schools_right.id;

-- Listing 7-7: Using FULL OUTER JOIN

SELECT *
FROM schools_left FULL OUTER JOIN schools_right
ON schools_left.id = schools_right.id;

-- Listing 7-8: Using CROSS JOIN

SELECT *
FROM schools_left CROSS JOIN schools_right;

-- Listing 7-9: Filtering to show missing values with IS NULL

SELECT *
FROM schools_left LEFT JOIN schools_right
ON schools_left.id = schools_right.id
WHERE schools_right.id IS NULL;

-- Listing 7-10: Querying specific columns in a join
SELECT schools_left.id,
       schools_left.left_school,
       schools_right.right_school
FROM schools_left LEFT JOIN schools_right
ON schools_left.id = schools_right.id;

-- Listing 7-11: Simplifying code with table aliases
SELECT lt.id,
       lt.left_school,
       rt.right_school
FROM schools_left AS lt LEFT JOIN schools_right AS rt
ON lt.id = rt.id;

-- Listing 7-12: Joining multiple tables
CREATE TABLE schools_enrollment (
    id integer,
    enrollment integer
);

CREATE TABLE schools_grades (
    id integer,
    grades varchar(10)
);

INSERT INTO schools_enrollment (id, enrollment)
VALUES
    (1, 360),
    (2, 1001),
    (5, 450),
    (6, 927);

INSERT INTO schools_grades (id, grades)
VALUES
    (1, 'K-3'),
    (2, '9-12'),
    (5, '6-8'),
    (6, '9-12');

SELECT lt.id, lt.left_school, en.enrollment, gr.grades
FROM schools_left AS lt LEFT JOIN schools_enrollment AS en
    ON lt.id = en.id
LEFT JOIN schools_grades AS gr
    ON lt.id = gr.id;

-- Listing 7-13: Performing math on joined Census tables
-- Decennial Census 2000. Full data dictionary at https://www.census.gov/prod/cen2000/doc/pl94-171.pdf
-- Note: Some non-number columns have been given more descriptive names

CREATE TABLE us_counties_2000 (
    geo_name varchar(90),              -- County/state name,
    state_us_abbreviation varchar(2),  -- State/U.S. abbreviation
    state_fips varchar(2),             -- State FIPS code
    county_fips varchar(3),            -- County code
    p0010001 integer,                  -- Total population
    p0010002 integer,                  -- Population of one race:
    p0010003 integer,                      -- White Alone
    p0010004 integer,                      -- Black or African American alone
    p0010005 integer,                      -- American Indian and Alaska Native alone
    p0010006 integer,                      -- Asian alone
    p0010007 integer,                      -- Native Hawaiian and Other Pacific Islander alone
    p0010008 integer,                      -- Some Other Race alone
    p0010009 integer,                  -- Population of two or more races
    p0010010 integer,                  -- Population of two races
    p0020002 integer,                  -- Hispanic or Latino
    p0020003 integer                   -- Not Hispanic or Latino:
);

COPY us_counties_2000
FROM 'C:\YourDirectory\us_counties_2000.csv'
WITH (FORMAT CSV, HEADER);

SELECT c2010.geo_name,
       c2010.state_us_abbreviation AS state,
       c2010.p0010001 AS pop_2010,
       c2000.p0010001 AS pop_2000,
       c2010.p0010001 - c2000.p0010001 AS raw_change,
       round( (CAST(c2010.p0010001 AS numeric(8,1)) - c2000.p0010001)
           / c2000.p0010001 * 100, 1 ) AS pct_change
FROM us_counties_2010 c2010 INNER JOIN us_counties_2000 c2000
ON c2010.state_fips = c2000.state_fips
   AND c2010.county_fips = c2000.county_fips
   AND c2010.p0010001 <> c2000.p0010001
ORDER BY pct_change DESC;