SQL ISNUMERIC Function
The SQL ISNUMERIC
function is used to determine whether an expression is a valid numeric type. It returns 1
if the expression can be converted to a number; otherwise, it returns 0
.
This function is commonly used to validate data entries, filter numeric values, and perform conditional logic in SQL queries.
Syntax of SQL ISNUMERIC Function
The basic syntax of the ISNUMERIC
function is as follows:
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SELECT ISNUMERIC(expression);
Parameters:
expression
: The value or column to check for numeric validity.
The function returns:
1
– If the value is numeric.0
– If the value is not numeric.
Step-by-Step Examples Using SQL ISNUMERIC
1. Checking if Values are Numeric
Let’s test various inputs using the ISNUMERIC
function:
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SELECT ISNUMERIC('123') AS Result1,
ISNUMERIC('Arjun') AS Result2,
ISNUMERIC('45.67') AS Result3,
ISNUMERIC('10A') AS Result4;
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Explanation:
'123'
is a valid number, soISNUMERIC
returns1
.'Arjun'
is not a number, soISNUMERIC
returns0
.'45.67'
is a valid decimal number, soISNUMERIC
returns1
.'10A'
contains a non-numeric character, soISNUMERIC
returns0
.
2. Using ISNUMERIC in a WHERE Clause
We can use ISNUMERIC
to filter only numeric values in a table. Let’s create a sample customers
table:
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CREATE TABLE customers (
id INT PRIMARY KEY IDENTITY(1, 1),
name VARCHAR(50),
contact_info VARCHAR(50)
);
Insert sample data:
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INSERT INTO customers (name, contact_info)
VALUES
('Arjun', '9876543210'),
('Priya', 'email@example.com'),
('Ram', '4567891234'),
('Sara', 'contact@domain');
Now, let’s retrieve only those customers whose contact information is numeric:
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SELECT name, contact_info
FROM customers
WHERE ISNUMERIC(contact_info) = 1;
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Explanation:
- The
ISNUMERIC(contact_info) = 1
condition filters out non-numeric contact information. - The result will include only
'Arjun'
and'Ram'
, as their contact info contains numeric values.
Conclusion
In this tutorial, how ISNUMERIC
function in SQL is used for:
- Checking if a value can be converted into a numeric data type.
- Filtering numeric data within a table.
- Ensuring data validation in queries.