Learn to Code SQL Example – SQL | MINUS Operator

(SQL Example for Citizen Data Scientist & Business Analyst)


SQL | MINUS Operator

The Minus Operator in SQL is used with two SELECT statements. The MINUS operator is used to subtract the result set obtained by first SELECT query from the result set obtained by second SELECT query. In simple words, we can say that MINUS operator will return only those rows which are unique in only first SELECT query and not those rows which are common to both first and second SELECT queries.

Pictorial Representation:
As you can see is in the above diagram, the MINUS operator will return only those rows which are present in the result set from Table1 and not present in the result set of Table2.

Basic Syntax:

SELECT column1 , column2 , ... columnN
FROM table_name
WHERE condition
SELECT column1 , column2 , ... columnN
FROM table_name
WHERE condition;

columnN: column1, column2.. are the name of columns of the table.
 Important Points:
  • The WHERE clause is optional in the above query.
  • The number of columns in both SELECT statements must be same.
  • The data type of corresponding columns of both SELECT statement must be same.

Sample Tables:table1


FROM Table1
FROM Table2

The above query will return only those rows which are unique in ‘Table1’. We can clearly see that values in the fields NAME, AGE and GRADE for the last row in both tables are same. Therefore, the output will be the first three rows from Table1. The obtained output is shown below:


Note: The MINUS operator is not supported with all databases. It is supported by Oracle database but not SQL server or PostgreSQL.


Beginners Guide to SQL – SQL IN & BETWEEN Operators


Learn to Code SQL Example – SQL | MINUS Operator

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

95% Discount on “Projects & Recipes, tutorials, ebooks”

Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!