Create query.sql

Author: elmoallistair

Joining Data in SQL/01 Introduction to joins/01 Inner join/query.sql

@@ -0,0 +1,5 @@
+-- 1. Select name fields (with alias) and region 
+SELECT cities.name as city, countries.name as country, countries.region
+FROM cities
+ INNER JOIN countries
+ ONe cities.country_code = countries.code;

Joining Data in SQL/01 Introduction to joins/02 Inner join (2)/query.sql

@@ -0,0 +1,7 @@
+-- 3. Select fields with aliases
+SELECT c.code AS country_code, c.name, e.year, e.inflation_rate
+FROM countries AS c
+ -- 1. Join to economies (alias e)
+ INNER JOIN economies AS e
+ -- 2. Match on code
+ ON c.code = e.code;

Joining Data in SQL/01 Introduction to joins/03 Inner join (3)/query.sql

@@ -0,0 +1,12 @@
+-- 6. Select fields
+SELECT c.code, name, region, e.year, fertility_rate, unemployment_rate
+ -- 1. From countries (alias as c)
+ FROM countries AS c
+ -- 2. Join to populations (as p)
+ INNER JOIN populations AS p
+ -- 3. Match on country code
+ ON c.code = p.country_code
+ -- 4. Join to economies (as e)
+ INNER JOIN economies AS e
+ -- 5. Match on country code and year
+ ON c.code = e.code AND e.year = p.year;

…duction to joins/01 Inner join/script.py …/04 Review inner join using on/readme.mdJoining Data in SQL/01 Introduction to joins/01 Inner join/script.py renamed to Joining Data in SQL/01 Introduction to joins/04 Review inner join using on/readme.md Joining Data in SQL/01 Introduction to joins/01 Inner join/script.py renamed to Joining Data in SQL/01 Introduction to joins/04 Review inner join using on/readme.md

@@ -0,0 +1,8 @@
+-- 4. Select fields
+SELECT c.name AS country, c.continent, l.name AS language, l.official
+ -- 1. From countries (alias as c)
+ FROM countries AS c
+ -- 2. Join to languages (as l)
+ JOIN languages as l
+ -- 3. Match using code
+ USING(code)

Joining Data in SQL/01 Introduction to joins/05 Inner join with using/query.sql

@@ -0,0 +1,13 @@
+SELECT p1.country_code,
+ p1.size AS size2010, 
+ p2.size AS size2015,
+ -- 1. calculate growth_perc
+ ((p2.size - p1.size)/p1.size * 100.0) AS growth_perc
+-- 2. From populations (alias as p1)
+FROM populations AS p1
+ -- 3. Join to itself (alias as p2)
+ INNER JOIN populations AS p2
+ -- 4. Match on country code
+ ON p1.country_code = p2.country_code
+ -- 5. and year (with calculation)
+ AND p1.year = p2.year - 5;

Joining Data in SQL/01 Introduction to joins/06 Self-join/query.sql

@@ -0,0 +1,11 @@
+SELECT name, continent, code, surface_area,
+ -- 1. First case
+ CASE WHEN surface_area > 2000000 THEN 'large'
+ -- 2. Second case
+ WHEN surface_area > 350000 THEN 'medium'
+ -- 3. Else clause + end
+ ELSE 'small' END
+ -- 4. Alias name
+ AS geosize_group
+-- 5. From table
+FROM countries;

Joining Data in SQL/01 Introduction to joins/06 Self-join/script.py

@@ -0,0 +1,21 @@
+SELECT country_code, size,
+ CASE WHEN size > 50000000
+ THEN 'large'
+ WHEN size > 1000000
+ THEN 'medium'
+ ELSE 'small' END
+ AS popsize_group
+INTO pop_plus 
+FROM populations
+WHERE year = 2015;
+
+-- 5. Select fields
+SELECT *
+-- 1. From countries_plus (alias as c)
+FROM countries_plus AS c
+ -- 2. Join to pop_plus (alias as p)
+ JOIN pop_plus AS p
+ -- 3. Match on country code
+ ON c.code = p.country_code
+-- 4. Order the table 
+ORDER BY geosize_group ASC;