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Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/README.md

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+# IBM: Databases and SQL for Data Science
+
+<img src="https://i.imgur.com/YCFnjvg.png" alt="Smiley face" height="300" width="600">
+
+![IBM](http://i.imgur.com/Qktqnu1.png) INSTRUCTORS
+#### Instructors: Rav Ahuja
+
+## Course Description
+
+You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. 
+
+## Topics include
+
+#### Week 1 - Databases and SQL
+- Explain SQL and Relational Databases
+- Create a database instance on the Cloud
+- Learn how to write SQL statements
+- Practice SQL statements hands-on on a live database
+
+#### Week 2 - Advanced SQL
+- Explain how to use string patterns and ranges in SQL queries
+- Demonstrate how to sort and order result sets
+- Practice use of grouping data in result sets
+- Employ Built-in functions in Queries
+- Demonstrate how to write sub-queries and nested selects
+- Build queries to access multiple tables
+
+#### Week 3 - Accessing Databases using Python
+- Describe concepts related to accessing Databases using Python
+- Learn and Practice how to connect to a database from a Jupyter notebook
+- Understand and demonstrate how to create tables and insert data from Python
+- Write SQL queries and retrieve result sets from Python
+- Practice how to perform simplified database access from Python using SQL magic
+- Enumerate different type of JOIN operations
+- Explain what is an INNER JOIN and practice hands-on
+- Distinguish between different types of OUTER JOINs and apply your understanding
+
+This course is part of the 'IBM Data Science Professional Certificate'
+![IBM](https://i.imgur.com/j6yW3WS.png)

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/CREATE and DROP tables.pdf

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+-- 0. Drop table INSTRUCTOR in case it already exists
+drop table INSTRUCTOR
+;
+--1. Create table INSTRUCTOR
+CREATE TABLE INSTRUCTOR
+  (ins_id INTEGER PRIMARY KEY NOT NULL, 
+   lastname VARCHAR(15) NOT NULL, 
+   firstname VARCHAR(15) NOT NULL, 
+   city VARCHAR(15), 
+   country CHAR(2)
+  )
+;
+--2A. Insert single row for Rav Ahuja
+INSERT INTO INSTRUCTOR
+  (ins_id, lastname, firstname, city, country)
+  VALUES 
+  (1, 'Ahuja', 'Rav', 'Toronto', 'CA')
+;
+--2B. Insert the two rows for Raul and Hima
+INSERT INTO INSTRUCTOR
+  VALUES
+  (2, 'Chong', 'Raul', 'Toronto', 'CA'),
+  (3, 'Vasudevan', 'Hima', 'Chicago', 'US')
+;
+--3. Select all rows in the table
+SELECT * FROM INSTRUCTOR
+;
+--3b. Select firstname, lastname and country where city is Toronto
+SELECT firstname, lastname, country from INSTRUCTOR where city='Toronto'
+;
+--4. Change the city for Rav to Markham
+UPDATE INSTRUCTOR SET city='Markham' where ins_id=1
+;
+--5. Delete the row for Raul Chong
+DELETE FROM INSTRUCTOR where ins_id=2
+;
+--5b. Retrieve all rows from the table
+SELECT * FROM INSTRUCTOR 
+;
+

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/Count, Distinct, Limit.pdf

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+-- Drop the PETSALE table in case it exists
+drop table PETSALE;
+-- Create the PETSALE table 
+create table PETSALE (
+	ID INTEGER PRIMARY KEY NOT NULL,
+	ANIMAL VARCHAR(20),
+	QUANTITY INTEGER,
+	SALEPRICE DECIMAL(6,2),
+	SALEDATE DATE
+	);
+-- Insert saple data into PETSALE table
+insert into PETSALE values 
+	(1,'Cat',9,450.09,'2018-05-29'),
+	(2,'Dog',3,666.66,'2018-06-01'),
+	(3,'Dog',1,100.00,'2018-06-04'),
+	(4,'Parrot',2,50.00,'2018-06-04'),
+	(5,'Dog',1,75.75,'2018-06-10'),
+	(6,'Hamster',6,60.60,'2018-06-11'),
+	(7,'Cat',1,44.44,'2018-06-11'),
+	(8,'Goldfish',24,48.48,'2018-06-14'),
+	(9,'Dog',2,222.22,'2018-06-15')
+	
+;

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/Lab2-solution-Script.sql.txt

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+select SUM(SALEPRICE) from PETSALE;
+select SUM(SALEPRICE) AS SUM_OF_SALEPRICE from PETSALE;
+select MAX(QUANTITY) from PETSALE;
+select AVG(SALEPRICE) from PETSALE;
+select AVG( SALEPRICE / QUANTITY ) from PETSALE where ANIMAL = 'Dog';
+select ROUND(SALEPRICE) from PETSALE;
+select LENGTH(ANIMAL) from PETSALE;
+select UCASE(ANIMAL) from PETSALE;
+select DISTINCT(UCASE(ANIMAL)) from PETSALE;
+select * from PETSALE where LCASE(ANIMAL) = 'cat';
+select DAY(SALEDATE) from PETSALE where ANIMAL = 'Cat';
+select COUNT(*) from PETSALE where MONTH(SALEDATE)='05';
+select (SALEDATE + 3 DAYS) from PETSALE;
+select (CURRENT DATE - SALEDATE) from PETSALE;
+

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/SELECT statement.pdf

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+2,Architect Group,30001,L0001
+5,Software Group,30002,L0002
+7,Design Team,30003,L0003
+5,Software Group,30004,L0004

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/sql-cheat-sheet-for-data-scientists-by-tomi-mester.pdf

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+E1001,John,Thomas,123456,01/09/1976,M,"5631 Rice, OakPark,IL",100,100000,30001,2
+E1002,Alice,James,123457,07/31/1972,F,"980 Berry ln, Elgin,IL",200,80000,30002,5
+E1003,Steve,Wells,123458,08/10/1980,M,"291 Springs, Gary,IL",300,50000,30002,5
+E1004,Santosh,Kumar,123459,07/20/1985,M,"511 Aurora Av, Aurora,IL",400,60000,30004,5
+E1005,Ahmed,Hussain,123410,01/04/1981,M,"216 Oak Tree, Geneva,IL",500,70000,30001,2
+E1006,Nancy,Allen,123411,02/06/1978,F,"111 Green Pl, Elgin,IL",600,90000,30001,2
+E1007,Mary,Thomas,123412,05/05/1975,F,"100 Rose Pl, Gary,IL",650,65000,30003,7
+E1008,Bharath,Gupta,123413,05/06/1985,M,"145 Berry Ln, Naperville,IL",660,65000,30003,7
+E1009,Andrea,Jones,123414,07/09/1990,F,"120 Fall Creek, Gary,IL",234,70000,30003,7
+E1010,Ann,Jacob,123415,03/30/1982,F,"111 Britany Springs,Elgin,IL",220,70000,30004,5

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/terms.jpg

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+100,Sr. Architect,60000,100000
+200,Sr. Software Developer,60000,80000
+300,Jr.Software Developer,40000,60000
+400,Jr.Software Developer,40000,60000
+500,Jr. Architect,50000,70000
+600,Lead Architect,70000,100000
+650,Jr. Designer,60000,70000
+660,Jr. Designer,60000,70000
+234,Sr. Designer,70000,90000
+220,Sr. Designer,70000,90000

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/tuple_record.jpg

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+E1001,08/01/2000,100,2
+E1002,08/01/2001,200,5
+E1003,08/16/2001,300,5
+E1004,08/16/2000,400,5
+E1005,05/30/2000,500,2
+E1006,08/16/2001,600,2
+E1007,05/30/2002,650,7
+E1008,05/06/2010,660,7
+E1009,08/16/2016,234,7
+E1010,08/16/2016,220,5

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week1- Databases and SQL/variables-and-tables-14-728.jpg

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+L0001,2
+L0002,5
+L0003,7

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week2- Advanced SQL/Additional Information on Keys and Constraints.pdf

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+-- Query 1------
+;
+select F_NAME , L_NAME
+from EMPLOYEES
+where ADDRESS LIKE '%Elgin,IL%' ;
+--Query 2--
+;
+select F_NAME , L_NAME
+from EMPLOYEES
+where B_DATE LIKE '197%' ;
+---Query3--
+;
+select *
+from EMPLOYEES
+where (SALARY BETWEEN 60000 and 70000)  and DEP_ID = 5 ;
+--Query4A--
+;
+select F_NAME, L_NAME, DEP_ID 
+from EMPLOYEES
+order by DEP_ID;
+--Query4B--
+;
+select F_NAME, L_NAME, DEP_ID 
+from EMPLOYEES
+order by DEP_ID desc, L_NAME desc;
+--Query5A--
+;
+select DEP_ID, COUNT(*)
+from EMPLOYEES
+group by DEP_ID;
+--Query5B--
+;
+select DEP_ID, COUNT(*), AVG(SALARY)
+from EMPLOYEES
+group by DEP_ID;
+--Query5C--
+;
+select DEP_ID, COUNT(*) AS "NUM_EMPLOYEES", AVG(SALARY) AS "AVG_SALARY"
+from EMPLOYEES
+group by DEP_ID;
+--Query5D--
+;
+select DEP_ID, COUNT(*) AS "NUM_EMPLOYEES", AVG(SALARY) AS "AVG_SALARY"
+from EMPLOYEES
+group by DEP_ID
+order by AVG_SALARY;
+--Query5E--
+;
+select DEP_ID, COUNT(*) AS "NUM_EMPLOYEES", AVG(SALARY) AS "AVG_SALARY"
+from EMPLOYEES
+group by DEP_ID
+having count(*) < 4
+order by AVG_SALARY;
+--5E alternative: if you want to use the label
+select DEP_ID, NUM_EMPLOYEES, AVG_SALARY from
+  ( select DEP_ID, COUNT(*) AS NUM_EMPLOYEES, AVG(SALARY) AS AVG_SALARY from EMPLOYEES group by DEP_ID)
+  where NUM_EMPLOYEES < 4
+order by AVG_SALARY;
+--BONUS Query6--
+;
+select D.DEP_NAME , E.F_NAME, E.L_NAME
+from EMPLOYEES as E, DEPARTMENTS as D
+where E.DEP_ID = D.DEPT_ID_DEP
+order by D.DEP_NAME, E.L_NAME desc ;

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week2- Advanced SQL/Built-in Functions, Dates, Timestamps.pdf

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+-- Query 1------
+;
+select F_NAME , L_NAME
+from EMPLOYEES
+where ADDRESS LIKE '%Elgin,IL%' ;
+--Query 2--
+;
+select F_NAME , L_NAME
+from EMPLOYEES
+where B_DATE LIKE '197%' ;
+---Query3--
+;
+select *
+from EMPLOYEES
+where (SALARY BETWEEN 60000 and 70000)  and DEP_ID = 5 ;
+--Query4A--
+;
+select F_NAME, L_NAME, DEP_ID 
+from EMPLOYEES
+order by DEP_ID;
+--Query4B--
+;
+select F_NAME, L_NAME, DEP_ID 
+from EMPLOYEES
+order by DEP_ID desc, L_NAME desc;
+--Query5A--
+;
+select DEP_ID, COUNT(*)
+from EMPLOYEES
+group by DEP_ID;
+--Query5B--
+;
+select DEP_ID, COUNT(*), AVG(SALARY)
+from EMPLOYEES
+group by DEP_ID;
+--Query5C--
+;
+select DEP_ID, COUNT(*) AS "NUM_EMPLOYEES", AVG(SALARY) AS "AVG_SALARY"
+from EMPLOYEES
+group by DEP_ID;
+--Query5D--
+;
+select DEP_ID, COUNT(*) AS "NUM_EMPLOYEES", AVG(SALARY) AS "AVG_SALARY"
+from EMPLOYEES
+group by DEP_ID
+order by AVG_SALARY;
+--Query5E--
+;
+select DEP_ID, COUNT(*) AS "NUM_EMPLOYEES", AVG(SALARY) AS "AVG_SALARY"
+from EMPLOYEES
+group by DEP_ID
+having count(*) < 4
+order by AVG_SALARY;
+--5E alternative: if you want to use the label
+select DEP_ID, NUM_EMPLOYEES, AVG_SALARY from
+  ( select DEP_ID, COUNT(*) AS NUM_EMPLOYEES, AVG(SALARY) AS AVG_SALARY from EMPLOYEES group by DEP_ID)
+  where NUM_EMPLOYEES < 4
+order by AVG_SALARY;
+--BONUS Query6--
+;
+select D.DEP_NAME , E.F_NAME, E.L_NAME
+from EMPLOYEES as E, DEPARTMENTS as D
+where E.DEP_ID = D.DEPT_ID_DEP
+order by D.DEP_NAME, E.L_NAME desc ;

Applied-Data-Science-Specialization-IBM/IBM - Databases and SQL for Data Science/week2- Advanced SQL/Difference between Primary and Foreign Key in Database.png

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+------------------------------------------
+--DDL statement for table 'HR' database--
+--------------------------------------------
+
+CREATE TABLE EMPLOYEES (
+                            EMP_ID CHAR(9) NOT NULL, 
+                            F_NAME VARCHAR(15) NOT NULL,
+                            L_NAME VARCHAR(15) NOT NULL,
+                            SSN CHAR(9),
+                            B_DATE DATE,
+                            SEX CHAR,
+                            ADDRESS VARCHAR(30),
+                            JOB_ID CHAR(9),
+                            SALARY DECIMAL(10,2),
+                            MANAGER_ID CHAR(9),
+                            DEP_ID CHAR(9) NOT NULL,
+                            PRIMARY KEY (EMP_ID));
+                            
+  CREATE TABLE JOB_HISTORY (
+                            EMPL_ID CHAR(9) NOT NULL, 
+                            START_DATE DATE,
+                            JOBS_ID CHAR(9) NOT NULL,
+                            DEPT_ID CHAR(9),
+                            PRIMARY KEY (EMPL_ID,JOBS_ID));
+ 
+ CREATE TABLE JOBS (
+                            JOB_IDENT CHAR(9) NOT NULL, 
+                            JOB_TITLE VARCHAR(15) ,
+                            MIN_SALARY DECIMAL(10,2),
+                            MAX_SALARY DECIMAL(10,2),
+                            PRIMARY KEY (JOB_IDENT));
+
+CREATE TABLE DEPARTMENTS (
+                            DEPT_ID_DEP CHAR(9) NOT NULL, 
+                            DEP_NAME VARCHAR(15) ,
+                            MANAGER_ID CHAR(9),
+                            LOC_ID CHAR(9),
+                            PRIMARY KEY (DEPT_ID_DEP));
+
+CREATE TABLE LOCATIONS (
+                            LOCT_ID CHAR(9) NOT NULL,
+                            DEP_ID_LOC CHAR(9) NOT NULL,
+                            PRIMARY KEY (LOCT_ID,DEP_ID_LOC));
+