Skip to main content

WHERE and ORDER BY clause

* WHERE clause is used as a filter on the table  to get a desired output. It is used to full fill a given condition. 

Syntax:

SELECT column_name 

FROM table_name 

WHERE search_condition

ORDER BY expression;

  • WHERE clause appears after the FROM clause but before the ORDER BY clause. 
  • WHERE clause not only is used in SELECT statement but also in the UPDATE and DELETE clause.
  • We use ORDER BY clause at the very end of the query.
• Lets say we have the emp table:


and we want the names of the employees who's salary is greater than 2000.

• So we will write a query:


  • As we can see, the data is now filtered out. Earlier there were 14 rows but now after using WHERE clause we have 6 rows. 
  • We always use WHERE clause with comparison operators like: 

Now lets see ORDER BY clause:

• Say we have the same query viz "SELECT * FROM EMP WHERE SAL>2000;" but now we want the data to be sorted in ascending order of sal column then we write--

SELECT * FROM EMP WHERE SAL>2000 ORDER BY SAL;


• We can see the SAL column is now sorted in the ascending order. If we want to sort the data by descending order then just write desc viz a shorthand for descending.

SELECT * FROM EMP WHERE SAL>2000 ORDER BY SAL DESC;


  • We can also filter the data with the help of one or more columns
  • We can even display one or more columns.



Comments

Popular posts from this blog

Stock Market using Python

 "The stock market is a device for transferring money from the impatient to the patient." - Warren Buffett Today we'll look into few ways for accessing the stock market. And we'll do this using Python ! Now, as we know that there are 2 stock exchange in India; BSE and NSE So we'll get the data from both! To begin with let's access the data from BSE first. (P.S: I certainly like the 2nd and the 3rd method to access stock market!) * So, to import the BSE data we need to " pip install bsedata ". => And then import the module, => Create an object to store the Driver Class => Then we need to do " getQuote('script_code')" where we need to provide a script code of a company which we need to access. Just like here we have given; => And from here we can see that the script code was for the company named "V-MART". But we can't remember all the script code hence we need to download this script file from the BSE websi

Predicting whether the bank will give loan to its customers based on their credit score (Logistic Regression)

"The best thing about data is that it tells a story." - Naveen Jain Today let's have a look at another machine learning model know as Logistic Regression. Logistic Regression is a statistical model where the outcome is predicted as binary such as YES or NO, based on the previous/train_dataset. ( Please open the images in a new tab or try to zoom-in ) import required models read your dataframe visualize your dataset create Logistic Regression model split your data into train and test dataset fit your train dataset into the regression model predict future values visualize your predicted values Github link for pdf:  click here

Glowing Border effect using html/css

  {html code} <html>     <head>         <link href='E:\html\.vscode\.vscode\style.css' type='text/css' rel='stylesheet'>         <title>Glowing Border</title>     </head>     <body>         <div class='box'>             <div class='text'>             <h2><u>Glowing Border</u></h2>             <p>HTML and CSS are technically not the programming languages, they are the scripting languages.              Usually used for the front-end development.</p>             </div>         </div>             </body> </html> {css code} body{     background: black;     display: flex; } .text{     padding: 30px;     margin: 10px;     letter-spacing: 1px;     box-sizing: border-box;     color: white; } .box{     top: 20%;     left: 40%;     display: flex;     position: relative;     width: 300px;     height: 420px;     justify-items: center;     align-it