197 lines
5.7 KiB
SQL
197 lines
5.7 KiB
SQL
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-- Practical SQL: A Beginner's Guide to Storytelling with Data
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-- by Anthony DeBarros
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-- Chapter 6 Code Examples
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--------------------------------------------------------------
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-- Listing 6-1: Creating the departments and employees tables
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CREATE TABLE departments (
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dept_id bigserial,
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dept varchar(100),
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city varchar(100),
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CONSTRAINT dept_key PRIMARY KEY (dept_id),
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CONSTRAINT dept_city_unique UNIQUE (dept, city)
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);
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CREATE TABLE employees (
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emp_id bigserial,
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first_name varchar(100),
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last_name varchar(100),
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salary integer,
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dept_id integer REFERENCES departments (dept_id),
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CONSTRAINT emp_key PRIMARY KEY (emp_id),
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CONSTRAINT emp_dept_unique UNIQUE (emp_id, dept_id)
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);
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INSERT INTO departments (dept, city)
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VALUES
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('Tax', 'Atlanta'),
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('IT', 'Boston');
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INSERT INTO employees (first_name, last_name, salary, dept_id)
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VALUES
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('Nancy', 'Jones', 62500, 1),
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('Lee', 'Smith', 59300, 1),
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('Soo', 'Nguyen', 83000, 2),
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('Janet', 'King', 95000, 2);
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-- Listing 6-2: Joining the employees and departments tables
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SELECT *
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FROM employees JOIN departments
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ON employees.dept_id = departments.dept_id;
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-- Listing 6-3: Creating two tables to explore JOIN types
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CREATE TABLE schools_left (
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id integer CONSTRAINT left_id_key PRIMARY KEY,
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left_school varchar(30)
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);
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CREATE TABLE schools_right (
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id integer CONSTRAINT right_id_key PRIMARY KEY,
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right_school varchar(30)
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);
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INSERT INTO schools_left (id, left_school) VALUES
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(1, 'Oak Street School'),
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(2, 'Roosevelt High School'),
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(5, 'Washington Middle School'),
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(6, 'Jefferson High School');
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INSERT INTO schools_right (id, right_school) VALUES
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(1, 'Oak Street School'),
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(2, 'Roosevelt High School'),
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(3, 'Morrison Elementary'),
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(4, 'Chase Magnet Academy'),
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(6, 'Jefferson High School');
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-- Listing 6-4: Using JOIN
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SELECT *
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FROM schools_left JOIN schools_right
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ON schools_left.id = schools_right.id;
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-- Bonus: Also can be specified as INNER JOIN
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SELECT *
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FROM schools_left INNER JOIN schools_right
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ON schools_left.id = schools_right.id;
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-- Listing 6-5: Using LEFT JOIN
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SELECT *
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FROM schools_left LEFT JOIN schools_right
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ON schools_left.id = schools_right.id;
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-- Listing 6-6: Using RIGHT JOIN
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SELECT *
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FROM schools_left RIGHT JOIN schools_right
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ON schools_left.id = schools_right.id;
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-- Listing 6-7: Using FULL OUTER JOIN
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SELECT *
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FROM schools_left FULL OUTER JOIN schools_right
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ON schools_left.id = schools_right.id;
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-- Listing 6-8: Using CROSS JOIN
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SELECT *
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FROM schools_left CROSS JOIN schools_right;
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-- Listing 6-9: Filtering to show missing values with IS NULL
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SELECT *
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FROM schools_left LEFT JOIN schools_right
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ON schools_left.id = schools_right.id
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WHERE schools_right.id IS NULL;
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-- Listing 6-10: Querying specific columns in a join
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SELECT schools_left.id,
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schools_left.left_school,
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schools_right.right_school
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FROM schools_left LEFT JOIN schools_right
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ON schools_left.id = schools_right.id;
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-- Listing 6-11: Simplifying code with table aliases
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SELECT lt.id,
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lt.left_school,
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rt.right_school
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FROM schools_left AS lt LEFT JOIN schools_right AS rt
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ON lt.id = rt.id;
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-- Listing 6-12: Joining multiple tables
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CREATE TABLE schools_enrollment (
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id integer,
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enrollment integer
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);
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CREATE TABLE schools_grades (
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id integer,
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grades varchar(10)
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);
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INSERT INTO schools_enrollment (id, enrollment)
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VALUES
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(1, 360),
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(2, 1001),
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(5, 450),
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(6, 927);
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INSERT INTO schools_grades (id, grades)
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VALUES
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(1, 'K-3'),
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(2, '9-12'),
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(5, '6-8'),
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(6, '9-12');
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SELECT lt.id, lt.left_school, en.enrollment, gr.grades
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FROM schools_left AS lt LEFT JOIN schools_enrollment AS en
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ON lt.id = en.id
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LEFT JOIN schools_grades AS gr
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ON lt.id = gr.id;
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-- Listing 6-13: Performing math on joined Census tables
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-- Decennial Census 2000. Full data dictionary at https://www.census.gov/prod/cen2000/doc/pl94-171.pdf
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-- Note: Some non-number columns have been given more descriptive names
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CREATE TABLE us_counties_2000 (
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geo_name varchar(90), -- County/state name,
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state_us_abbreviation varchar(2), -- State/U.S. abbreviation
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state_fips varchar(2), -- State FIPS code
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county_fips varchar(3), -- County code
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p0010001 integer, -- Total population
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p0010002 integer, -- Population of one race:
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p0010003 integer, -- White Alone
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p0010004 integer, -- Black or African American alone
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p0010005 integer, -- American Indian and Alaska Native alone
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p0010006 integer, -- Asian alone
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p0010007 integer, -- Native Hawaiian and Other Pacific Islander alone
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p0010008 integer, -- Some Other Race alone
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p0010009 integer, -- Population of two or more races
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p0010010 integer, -- Population of two races
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p0020002 integer, -- Hispanic or Latino
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p0020003 integer -- Not Hispanic or Latino:
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);
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COPY us_counties_2000
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FROM 'C:\YourDirectory\us_counties_2000.csv'
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WITH (FORMAT CSV, HEADER);
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SELECT c2010.geo_name,
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c2010.state_us_abbreviation AS state,
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c2010.p0010001 AS pop_2010,
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c2000.p0010001 AS pop_2000,
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c2010.p0010001 - c2000.p0010001 AS raw_change,
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round( (CAST(c2010.p0010001 AS numeric(8,1)) - c2000.p0010001)
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/ c2000.p0010001 * 100, 1 ) AS pct_change
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FROM us_counties_2010 c2010 INNER JOIN us_counties_2000 c2000
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ON c2010.state_fips = c2000.state_fips
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AND c2010.county_fips = c2000.county_fips
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AND c2010.p0010001 <> c2000.p0010001
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ORDER BY pct_change DESC;
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