Adventures in Machine Learning

Mastering SQL Server: Extracting and Creating Tables

Extracting Characters Using LEFT, RIGHT, and SUBSTRING in SQL Server

SQL Server is a powerful relational database management system that allows users to manage large amounts of data effectively. It is widely used in many industries, including finance, healthcare, and e-commerce, to store, organize, and extract data.

One of the most common tasks in SQL Server is to extract a specific number of characters from a string. This article will discuss how to extract characters from fields using LEFT, RIGHT, and SUBSTRING functions.

Scenario 1: Extracting characters from the LEFT

The LEFT function can be used to extract a specific number of characters from the left side of a string. The syntax of the LEFT function is as follows:

LEFT (field_name, number of characters)

The first argument is the field or column name from which we want to extract characters, and the second argument is the number of characters that we want to extract.

For example, suppose we have a table called “Customers” that contains a column named “Full Name.” To extract the first four characters of the Full Name column, we can use the following SQL query:

SELECT LEFT(Full Name, 4) FROM Customers;

Scenario 2: Extracting characters from the RIGHT

Extracting characters from the right side of a string is similar to extracting characters from the left side. However, we use the RIGHT function instead of the LEFT function.

The syntax of the RIGHT function is as follows:

RIGHT (field_name, number of characters)

The first argument is the field or column name from which we want to extract characters, and the second argument is the number of characters that we want to extract. For example, suppose we have a table called “Customers” that contains a column named “Last Name.” To extract the last four characters of the Last Name column, we can use the following SQL query:

SELECT RIGHT(Last Name, 4) FROM Customers;

Scenario 3: Extracting characters from the middle

Sometimes we need to extract characters from the middle of a string. We can achieve this using the SUBSTRING function. The syntax of the SUBSTRING function is as follows:

SUBSTRING (field_name, starting position, digits)

The first argument is the field or column name from which we want to extract characters, the second argument is the starting position from which we want to extract, and the third argument is the number of characters that we want to extract.

For example, suppose we have a table called “Products” that contains a column named “Product Name.” To extract the characters between the 4th and 7th position of the Product Name column, we can use the following SQL query:

SELECT SUBSTRING(Product Name, 4, 4) FROM Products;

Scenario 4: Extracting characters before a symbol

It is common to need to extract characters before a symbol in a string. To achieve this, we can use the LEFT and CHARINDEX functions in combination.

The CHARINDEX function returns the position of a specified character or substring within a string. The syntax of the CHARINDEX function is as follows:

CHARINDEX (symbol, field_name)

The first argument is the symbol that we want to find, and the second argument is the field or column name in which we want to search.

For example, suppose we have a table called “Emails” that contains a column named “Email Address.” To extract characters before the “@” symbol in the Email Address column, we can use the following SQL query:

SELECT LEFT(Email Address, CHARINDEX('@', Email Address)-1) FROM Emails;

Scenario 5: Extracting characters before a space

We can also extract characters before a space in a string using a similar method as scenario 4. To achieve this, we can use the LEFT and CHARINDEX functions in combination.

For example, suppose we have a table called “Addresses” that contains a column named “Street Address.” To extract characters before the first space in the Street Address column, we can use the following SQL query:

SELECT LEFT(Street Address, CHARINDEX(' ', Street Address)-1) FROM Addresses;

Scenario 6: Extracting characters after a symbol

In some cases, we may need to extract characters after a symbol in a string. We can use the REVERSE and RIGHT functions in combination to achieve this.

The REVERSE function reverses a string, allowing us to find the position of the symbol from the back of the string. The syntax of the REVERSE function is as follows:

REVERSE (field_name)

The argument is the field or column name that we want to reverse. For example, suppose we have a table called “Orders” that contains a column named “Order ID.” To extract characters after the “_” symbol in the Order ID column, we can use the following SQL query:

SELECT RIGHT(Order ID, CHARINDEX('_', REVERSE(Order ID))-1) FROM Orders;

Scenario 7: Extracting characters between identical symbols

We may need to extract characters between two identical symbols in a string. We can use the hyphen symbol and the SUBSTRING function to achieve this. For example, suppose we have a table called “Invoices” that contains a column named “Invoice Number.” To extract characters between the first and second hyphen in the Invoice Number column, we can use the following SQL query:

SELECT SUBSTRING(Invoice Number, CHARINDEX('-', Invoice Number)+1, CHARINDEX('-', Invoice Number, CHARINDEX('-', Invoice Number)+1)-CHARINDEX('-', Invoice Number)-1) FROM Invoices;

Scenario 8: Extracting characters between different symbols

We may also need to extract characters between two different symbols in a string. We can use the hyphen symbol, the LEN function, and the LEFT and RIGHT functions in combination to achieve this. For example, suppose we have a table called “Orders” that contains a column named “Order Number.” To extract characters between the first hyphen and the “@” symbol in the Order Number column, we can use the following SQL query:

SELECT SUBSTRING(Order Number, CHARINDEX('-', Order Number)+1, LEN(Order Number)-CHARINDEX('-', Order Number)-CHARINDEX('@', Order Number)+1) FROM Orders;

Creating and Using Tables in SQL Server

Scenario 1: Creating a table

To create a table in SQL Server, we use the CREATE TABLE statement. The syntax of the CREATE TABLE statement is as follows:

CREATE TABLE table_name (

column1 datatype1 constraints,
  column2 datatype2 constraints,
  ...    );

The table_name is the name of the table that we want to create.

Each column is assigned a data type and can have any constraints that we want to apply, such as NOT NULL or UNIQUE. For example, suppose we want to create a table called “Employees” that has three columns: “Employee ID,” “First Name,” and “Last Name.” The “Employee ID” column is an integer type, and both “First Name” and “Last Name” columns are character types. We can use the following SQL query:

CREATE TABLE Employees (

Employee ID int NOT NULL,
  First Name varchar(50) NOT NULL,
  Last Name varchar(50) NOT NULL
  );

Scenario 2: Extracting data from tables using queries

Once we have created a table in SQL Server, we can extract data from it using queries. The most basic query is the SELECT statement.

The syntax of the SELECT statement is as follows:

SELECT column1, column2, ...

FROM table
WHERE condition;

The columns that we want to select are separated by commas. We use the FROM keyword to specify the table from which we want to select data. We can also use the WHERE clause to filter data based on any conditions that we want to apply. For example, suppose we want to select all the data from the “Employees” table. We can use the following SQL query:

SELECT *
FROM Employees;

Conclusion

In conclusion, SQL Server is a powerful relational database management system that offers a range of functions and statements to work with data effectively. This article discussed two essential concepts in SQL Server: extracting characters from fields using LEFT, RIGHT, and SUBSTRING functions and creating and using tables in SQL Server.

By applying these concepts, we can manipulate data in various ways and extract valuable insights from it. In today’s data-driven world, companies need to manage large volumes of data effectively to extract meaningful insights.

Popular Posts