Chapter 7 data and code updates
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@ -2,7 +2,7 @@
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-- Practical SQL: A Beginner's Guide to Storytelling with Data, 2nd Edition
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-- by Anthony DeBarros
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-- Chapter 7 Code Examples
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-- Chapter 7 Code Examples
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----------------------------------------------------------------------------
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@ -46,152 +46,183 @@ ON employees.dept_id = departments.dept_id;
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-- Listing 7-3: 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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CREATE TABLE district_2020 (
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id integer CONSTRAINT id_key_2020 PRIMARY KEY,
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school_2020 text
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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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CREATE TABLE district_2035 (
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id integer CONSTRAINT id_key_2035 PRIMARY KEY,
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school_2035 text
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);
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INSERT INTO schools_left (id, left_school) VALUES
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INSERT INTO district_2020 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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(5, 'Dover Middle School'),
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(6, 'Webutuck High School');
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INSERT INTO schools_right (id, right_school) VALUES
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INSERT INTO district_2035 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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(6, 'Webutuck High School');
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-- Listing 7-4: 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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FROM district_2020 JOIN district_2035
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ON district_2020.id = district_2035.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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FROM district_2020 INNER JOIN district_2035
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ON district_2020.id = district_2035.id;
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-- Listing 7-5: 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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FROM district_2020 LEFT JOIN district_2035
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ON district_2020.id = district_2035.id;
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-- Listing 7-6: 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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FROM district_2020 RIGHT JOIN district_2035
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ON district_2020.id = district_2035.id;
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-- Listing 7-7: 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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FROM district_2020 FULL OUTER JOIN district_2035
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ON district_2020.id = district_2035.id;
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-- Listing 7-8: Using CROSS JOIN
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SELECT *
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FROM schools_left CROSS JOIN schools_right;
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FROM district_2020 CROSS JOIN district_2035;
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-- Listing 7-9: 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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FROM district_2020 LEFT JOIN district_2035
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ON district_2020.id = district_2035.id
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WHERE district_2035.id IS NULL;
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SELECT *
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FROM district_2020 RIGHT JOIN district_2035
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ON district_2020.id = district_2035.id
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WHERE district_2020.id IS NULL;
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-- Listing 7-10: 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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SELECT district_2020.id,
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district_2020.school_2020,
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district_2035.school_2035
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FROM district_2020 LEFT JOIN district_2035
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ON district_2020.id = district_2035.id;
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-- Listing 7-11: 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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SELECT d20.id,
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d20.school_2020,
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d35.school_2035
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FROM district_2020 AS d20 LEFT JOIN district_2035 AS d35
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ON d20.id = d35.id;
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-- Listing 7-12: Joining multiple tables
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CREATE TABLE schools_enrollment (
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CREATE TABLE district_2020_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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CREATE TABLE district_2020_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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INSERT INTO district_2020_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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INSERT INTO district_2020_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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SELECT d20.id,
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d20.school_2020,
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en.enrollment,
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gr.grades
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FROM district_2020 AS d20 LEFT JOIN district_2020_enrollment AS en
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ON d20.id = en.id
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LEFT JOIN district_2020_grades AS gr
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ON d20.id = gr.id;
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-- Listing 7-13: 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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-- Listing 7-13: Combining query results with UNION
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SELECT * FROM district_2020
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UNION
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SELECT * FROM district_2035
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ORDER BY id;
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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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-- Listing 7-14: Combining query results with UNION ALL
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SELECT * FROM district_2020
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UNION ALL
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SELECT * FROM district_2035
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ORDER BY id;
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-- Listing 7-15: Customizing a UNION query
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SELECT '2020' AS year,
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school_2020 AS school
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FROM district_2020
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UNION
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SELECT '2035' AS year,
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school_2035
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FROM district_2035
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ORDER BY school, year;
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-- Listing 7-16: Combining query results with INTERSECT and EXCEPT
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SELECT * FROM district_2020
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INTERSECT
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SELECT * FROM district_2035
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ORDER BY id;
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SELECT * FROM district_2020
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EXCEPT
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SELECT * FROM district_2035
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ORDER BY id;
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-- Listing 7-17: Performing math on joined Census population estimates tables
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CREATE TABLE us_counties_pop_est_2010 (
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state_fips text, -- State FIPS code
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county_fips text, -- County FIPS code
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region smallint, -- Region
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state_name text, -- State name
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county_name text, -- County name
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estimates_base_2010 integer, -- 4/1/2010 resident total population estimates base
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CONSTRAINT counties_2010_key PRIMARY KEY (state_fips, county_fips)
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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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COPY us_counties_pop_est_2010
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FROM 'C:\YourDirectory\us_counties_pop_est_2010.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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SELECT c2019.county_name,
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c2019.state_name,
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c2019.pop_est_2019 AS pop_2019,
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c2010.estimates_base_2010 AS pop_2010,
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c2019.pop_est_2019 - c2010.estimates_base_2010 AS raw_change,
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round( (c2019.pop_est_2019::numeric - c2010.estimates_base_2010)
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/ c2010.estimates_base_2010 * 100, 1 ) AS pct_change
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FROM us_counties_pop_est_2019 AS c2019
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JOIN us_counties_pop_est_2010 AS c2010
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ON c2019.state_fips = c2010.state_fips
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AND c2019.county_fips = c2010.county_fips
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ORDER BY pct_change DESC;
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File diff suppressed because one or more lines are too long
3143
Chapter_07/us_counties_pop_est_2010.csv
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Chapter_07/us_counties_pop_est_2010.csv
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File diff suppressed because it is too large
Load Diff
@ -306,7 +306,69 @@ FROM us_counties_pop_est_2019
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GROUP BY state_name;
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----------------------------------------------------------------------------
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-- Chapter 7: Joining Tables in a Relational Database
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----------------------------------------------------------------------------
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-- 1. According to the Census population estimates, which county had the
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-- greatest percentage loss of population between 2010 and 2019? Try
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-- an Internet search to find out what happened. (Hint: The loss is related
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-- to a particular type of facility.)
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-- Answer:
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-- Concho County, Texas, lost 33 percent of its population from 2010 to
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-- 2019, the result of the closure of Eden Detention Center.
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-- https://www.texasstandard.org/stories/after-edens-prison-closes-what-comes-next-for-this-small-texas-town/
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-- Simply use ASC in the ORDER BY clause to re-order the results, like this:
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SELECT c2019.county_name,
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c2019.state_name,
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c2019.pop_est_2019 AS pop_2019,
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c2010.estimates_base_2010 AS pop_2010,
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c2019.pop_est_2019 - c2010.estimates_base_2010 AS raw_change,
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round( (c2019.pop_est_2019::numeric - c2010.estimates_base_2010)
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/ c2010.estimates_base_2010 * 100, 1 ) AS pct_change
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FROM us_counties_pop_est_2019 AS c2019
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JOIN us_counties_pop_est_2010 AS c2010
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ON c2019.state_fips = c2010.state_fips
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AND c2019.county_fips = c2010.county_fips
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ORDER BY pct_change ASC;
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-- 2.
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SELECT '2010' AS year,
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state_fips,
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county_fips,
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county_name,
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state_name,
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estimates_base_2010 AS estimate
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FROM us_counties_pop_est_2010
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UNION
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SELECT '2019' AS year,
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state_fips,
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county_fips,
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county_name,
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state_name,
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pop_est_2019 AS estimate
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FROM us_counties_pop_est_2019
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ORDER BY state_fips, county_fips, year;
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-- 3. Using the percentile_cont() function from Chapter 6,
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-- determine the median of the percent change in estimated county
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-- population between 2010 and 2019.
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-- Answer: -0.5%
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SELECT percentile_cont(.5)
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WITHIN GROUP (ORDER BY round( (c2019.pop_est_2019::numeric - c2010.estimates_base_2010)
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/ c2010.estimates_base_2010 * 100, 1 )) AS percentile_50th
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FROM us_counties_pop_est_2019 AS c2019
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JOIN us_counties_pop_est_2010 AS c2010
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ON c2019.state_fips = c2010.state_fips
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AND c2019.county_fips = c2010.county_fips;
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