Data Wrangling

Author: ptyadana

Advanced SQL for Data Scientists/02.Data_Wrangling.sql

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+/**************** Data Wrangling / Data Munging *************/
+
+SELECT DISTINCT(department)
+FROM staff
+ORDER BY department;
+
+
+/********* Reformatting Characters Data *********/
+
+SELECT DISTINCT(UPPER(department))
+FROM staff
+ORDER BY 1;
+
+
+SELECT DISTINCT(LOWER(department))
+FROM staff
+ORDER BY 1;
+
+
+/*** Concatetation ***/
+SELECT 
+	last_name,
+	job_title || ' - ' || department AS title_with_department 
+FROM staff;
+
+/*** Trim ***/
+SELECT
+	TRIM('    data sciece rocks !    ');
+
+-- with trim is 19 characters
+SELECT
+	LENGTH(TRIM('    data sciece rocks !    '));
+	
+-- without trim is 27 characters
+SELECT
+	LENGTH('    data sciece rocks !    ');
+
+
+/* How many employees with Assistant roles */
+SELECT
+	COUNT(*) AS employees_with_Assistant_role
+FROM staff
+WHERE job_title LIKE '%Assistant%';
+
+
+/* What are those Assistant roles? */
+SELECT DISTINCT(job_title)
+FROM staff
+WHERE job_title LIKE '%Assistant%'
+ORDER BY 1;
+
+
+/* let's check which roles are assistant role or not */
+SELECT 
+	DISTINCT(job_title),
+	job_title LIKE '%Assistant%' is_assistant_role
+FROM staff
+ORDER BY 1;
+
+--------------------------------------------------------------------------------------------
+
+
+/********* Extracting Strings from Characters *********/
+-- SUBSTRING('string' FROM position FOR how_many)
+
+---------------------- SubString words ----------------------------------------------------
+SELECT 'abcdefghijkl' as test_string;
+
+
+SELECT 
+	SUBSTRING('abcdefghikl' FROM 5 FOR 3) as sub_string;
+
+
+SELECT 
+	SUBSTRING('abcdefghikl' FROM 5) as sub_string;
+
+
+SELECT job_title
+FROM staff
+WHERE job_title LIKE 'Assistant%';
+
+
+/* We want to extract job category from the assistant position which starts with word Assisant */
+SELECT 
+	SUBSTRING(job_title FROM LENGTH('Assistant')+1) AS job_category,
+	job_title
+FROM staff
+WHERE job_title LIKE 'Assistant%';
+
+
+/* As there are several duplicated ones, we want to know only unique ones */
+SELECT 
+	DISTINCT(SUBSTRING(job_title FROM LENGTH('Assistant')+1)) AS job_category,
+	job_title
+FROM staff
+WHERE job_title LIKE 'Assistant%';
+
+
+---------------------- Replacing words ----------------------------------------------------
+
+/* we want to replace word Assistant with Asst.  */
+SELECT
+	OVERLAY(job_title PLACING 'Asst.' FROM 1 FOR LENGTH('Assistant')) AS shorten_job_title
+FROM staff
+WHERE job_title LIKE 'Assistant%';
+
+
+--------------------------------------------------------------------------------------------
+
+/********* Filtering with Regualar Expressions *********/
+-- SIMILAR TO
+
+/* We want to know job title with Assistant with Level 3 and 4 */
+-- we will put the desired words into group
+-- Pipe character | is for OR condition 
+SELECT
+	job_title
+FROM staff
+WHERE job_title SIMILAR TO '%Assistant%(III|IV)';
+
+
+/* now we want to know job title with Assistant, started with roman numerial I, follwed by 1 character
+it can be II,IV, etc.. as long as it starts with character I 
+
+underscore _ : for one character */
+
+SELECT
+	DISTINCT(job_title)
+FROM staff
+WHERE job_title SIMILAR TO '%Assistant I_';
+
+
+/* job title starts with either E, P or S character , followed by any characters*/
+SELECT job_title
+FROM staff
+WHERE job_title SIMILAR TO '[EPS]%';
+
+--------------------------------------------------------------------------------------------
+
+/********* Reformatting Numerics Data *********/
+-- TRUNC() Truncate values Note: trunc just truncate value, not rounding value.
+-- CEIL
+-- FLOOR
+-- ROUND
+
+SELECT 
+	department, 
+	AVG(salary) AS avg_salary, 
+	TRUNC(AVG(salary)) AS truncated_salary,
+	TRUNC(AVG(salary), 2) AS truncated_salary_2_decimal,
+	ROUND(AVG(salary), 2) AS rounded_salary,
+	CEIL(AVG(salary)) AS ceiling_salary,
+	FLOOR(AVG(salary)) AS floor_salary
+FROM staff
+GROUP BY department;
+
+
+
+
+