Adventures in Machine Learning

Mastering SQL Joins Without a Common Column

Combining Two Tables Without a Common ColumnSQL is a programming language widely used for managing and manipulating data in databases. One of the most common tasks in data analysis is joining tables.

Joining tables means combining two or more tables based on a matching column or key. But what if you need to join tables that do not have a common column or key?

In this article, we will explore different approaches to combine tables that do not have a common column. When Do You Need to Join Tables Without a Common Column?

In real-world scenarios, data analysts and professionals often face non-equi joins, which means joining tables without a common column. For example, you may have two tables regarding a restaurant: one with the menu items and their prices, and another with the customers’ orders.

You might want to combine these tables to analyze the sales of different menu items and their popularity. In such cases, you need to join tables that do not have a common column.

Getting to Know the Data:

Assuming we have two tables, the first table is suppliers, with their contact information, and the second table is products, containing the list of products and prices. We do not have a common column between the tables and want to combine them.

Before exploring different ways to combine them, let’s get to know the data. Table 1: Suppliers

| Supplier ID | Company Name | Contact Name | Contact Title | Address | City | Country |

|————-|————–|————–|—————|—————-|————|———|

| 1 | Supplier A | John | Manager | 123 Main Street | New York | USA |

| 2 | Supplier B | Tom | Sales Rep | 456 Oak Avenue | Los Angeles | USA |

| 3 | Supplier C | Lisa | Sales Rep | 789 Birch Lane | Chicago | USA |

| 4 | Supplier D | Mike | Manager | 101 Pine Street | Miami | USA |

Table 2: Products

| Product ID | Product Name | Supplier ID | Category | Price |

|————|————-|————|———-|——-|

| 1 | Product A | 1 | Clothing | 34.99 |

| 2 | Product B | 2 | Furniture | 499.99 |

| 3 | Product C | 3 | Electronics | 999.99 |

| 4 | Product D | 4 | Toys | 29.99 |

How to Combine Two Tables Without a Common Column:

There are different approaches to join tables without a common column.

Let’s explore them one by one. Using the

FROM Table1, Table2 Syntax:

This approach uses the obsolete syntax but still works in most SQL environments, and it is a good way to understand the logic behind combining tables without a common column. The idea is to list the two tables in the FROM clause, separated by a comma.

All possible combinations of rows between the two tables are produced. Then, we filter out the irrelevant rows using the WHERE clause.

Syntax:

SELECT *

FROM Table1, Table2

WHERE Table1.column1 = Table2.column2;

For our example, let’s assume we want to consolidate supplier information with their products trading information. For this, we need to combine both tables.

Every product in table 2 has a corresponding supplier in table 1. We can use the Supplier ID column to join both tables.

Query:

SELECT *

FROM Suppliers, Products

WHERE Suppliers.Supplier ID = Products.Supplier ID;

This query generates a cartesian product of the two tables and filters out the rows that do not match, using the WHERE clause. The resulting output is a table that contains information from both tables.

Using the CROSS JOIN Operator:

In SQL, the cross join operator (CROSS JOIN) generates a cartesian product of two tables without a common column. It is a more readable syntax compared to the obsolete syntax.

Syntax:

SELECT *

FROM Table1

CROSS JOIN Table2;

For our example, we can use the cross join operator to join both tables. Query:

SELECT *

FROM Suppliers

CROSS JOIN Products;

The output of this query looks the same as the output generated by the previous approach. Using UNION or UNION ALL:

Suppose we have two tables with identical structures and want to combine them without a common column.

We can use the union or union all operator to consolidate both tables. The union operator consolidates tables by selecting only the unique rows across both tables, and the union all operator consolidates tables by selecting all rows from both tables, including duplicates.

Syntax:

SELECT column1, column2,

FROM Table1

UNION [ALL]

SELECT column1, column2,

FROM Table2;

For our example, let’s assume we want to consolidate supplier information from two different tables. Table 1: Suppliers 1

| Supplier Name | Contact Name | Contact Title | Address | City | Country |

|—————|————–|————–|—————-|————|———|

| Supplier A | John | Manager | 123 Main Street | New York | USA |

| Supplier B | Tom | Sales Rep | 456 Oak Avenue | Los Angeles | USA |

| Supplier C | Lisa | Sales Rep | 789 Birch Lane | Chicago | USA |

| Supplier D | Mike | Manager | 101 Pine Street | Miami | USA |

Table 2: Suppliers 2

| Supplier Name | Contact Name | Contact Title | Address | City | Country |

|—————|————–|————–|———————|————|———|

| Supplier E | Kim | Manager | 1111 Broadway | New York | USA |

| Supplier F | Jake | Sales Rep | 8181 Hollywood Blvd | Los Angeles | USA |

| Supplier G | Molly | Sales Rep | 123 Magnolia Drive | Chicago | USA |

| Supplier H | Tom | Manager | 99 Ocean Drive | Miami | USA |

We can consolidate both tables using the UNION operator.

Query:

SELECT [Supplier Name], [Contact Name], [Contact Title], [Address], [City], [Country]

FROM Suppliers_1

UNION

SELECT [Supplier Name], [Contact Name], [Contact Title], [Address], [City], [Country]

FROM Suppliers_2;

This query produces a table that contains unique rows across both tables. Conclusion:

Joining tables without a common column is a common task in data analysis.

SQL provides different approaches to combine tables that do not have a common column, such as obsolete syntax, the cross join operator, and union or union all operator. Each approach has its pros and cons, and selecting the best approach depends on the specific scenario.

By using the right approach, you can consolidate data from multiple tables into a single table for analysis. Time to Practice CROSS JOINs and UNIONs!Structured Query Language (SQL) is used by many organizations for managing and manipulating data in databases.

SQL JOINS are commonly asked questions in job interviews for data analyst roles. Cross joins and unions are two types of joins that are used when there is no common column between the two tables.

In this article, we will focus on practicing cross joins and unions using different resources. Resources for Learning More About JOINs:

If you are new to SQL JOINS, it is a good idea to start with the SQL JOIN basics.

There are several resources available online for learning about SQL JOINS. Here are a few of them:

1.

W3Schools: W3Schools has an excellent tutorial on SQL JOINs that covers inner, left, right, and full outer joins. They also have a section on cross joins and self-joins, which are essential for practicing cross joins.

2. DataCamp: DataCamp is a comprehensive course that covers all aspects of SQL, including JOINs. Their course includes interactive exercises that help you practice JOINs in a simulated SQL environment.

3. SQL Zoo: If you prefer a more hands-on approach to learning JOINs, SQL Zoo offers a set of interactive exercises that allow you to practice JOINs directly in your web browser.

Practice Exercises for JOINs:

To practice cross joins and unions, we will use the SQL Zoo website as an example. In this example, we have two tables: one containing information about customers, and the other containing information about products.

Table 1: Customers

| Customer ID | Customer Name | Contact Name | City | Country |

|————-|—————|—————|————|———–|

| 1 | Customer A | John | London | UK |

| 2 | Customer B | David | Paris | France |

| 3 | Customer C | Mary | New York | USA |

| 4 | Customer D | Lucy | Sydney | Australia |

Table 2: Products

| Product ID | Product Name | Price |

|————|————–|——-|

| 1 | Product A | 10.99 |

| 2 | Product B | 15.99 |

| 3 | Product C | 5.99 |

| 4 | Product D | 25.99 |

To practice cross joins, we want to generate a list of all possible combinations of customers and products. We can use the CROSS JOIN operator to achieve this.

Query:

SELECT *

FROM Customers

CROSS JOIN Products;

The output of this query will produce a table containing all possible combinations of customers and products. To practice unions, we want to consolidate the information from two tables.

We will use the customers and products tables to demonstrate. Query:

SELECT ‘Customers’ AS Table_Name, Customer_ID AS ID, Customer_Name AS Name, Contact_Name AS Contact, City, Country, NULL AS Product_Name, NULL AS Price

FROM Customers

UNION

SELECT ‘Products’ AS Table_Name, Product_ID AS ID, NULL AS Name, NULL AS Contact, NULL AS City, NULL AS Country, Product_Name, Price

FROM Products;

The output of this query will produce a table containing consolidated information from both tables. Conclusion:

Cross joins and unions are two types of joins that are commonly used in SQL when joining tables that do not have a common column.

It is essential to practice these joins regularly to improve your SQL skills. There are several resources available to learn about SQL JOINs, including SQL Zoo, W3Schools, and DataCamp.

With regular practice, you can become proficient in SQL JOINs and improve your chances of securing a job in the data analytics field. In conclusion, SQL JOINS are an essential part of data analysis and management.

Cross joins and unions are commonly used when joining tables that do not have common columns. Various resources are available to learn about SQL JOINS, including interactive exercises and comprehensive courses.

Constant practice can enhance your SQL skills and improve the chances of landing a data analyst job. It is crucial to learn SQL JOINS to manage and manipulate databases effectively.

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