Скачать или смотреть How to Effectively Merge Two Tables in SQL and Convert Values to Negative Before Merging

Discover a step-by-step method to efficiently `merge two tables` in SQL while converting one table's values to negative. Learn best practices in MS Access for seamless data manipulation!
---
This video is based on the question https://stackoverflow.com/q/70082465/ asked by the user 'TourEiffel' ( https://stackoverflow.com/u/11167163/ ) and on the answer https://stackoverflow.com/a/70082547/ provided by the user 'ScaisEdge' ( https://stackoverflow.com/u/3522312/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How do I merge 2 table in 1 and change value from the second table to negative value before merge

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Effectively Merge Two Tables in SQL and Convert Values to Negative Before Merging

SQL is an incredibly powerful tool for managing databases, and sometimes you need to combine data from two separate tables into one. In this guide, we'll explore how to merge two tables in SQL, particularly focusing on a scenario where you need to change the values from one of the tables to negative before performing the merge.

Understanding the Problem

Imagine you have two tables:

Table 1:

TheNameTheVal1Blue2Red8Orange6Green13Blue14Green25Table 2:

TheNameTheVal2Blue9Red30Pink8Green10Blue3Green2You want to merge these tables based on the TheName column while converting all values in Table 2 to negative before combining the totals. The expected output should resemble:

TheNameTheValBlue4Red-22Pink-8Green26Orange6Calculation Details

To obtain the desired values, some calculations must first be performed for merging the data:

Blue = (2 + 14) - (9 + 3) = 4

Red = (8) - (30) = -22

Pink = (0) - (8) = -8

Green = (13 + 25) - (10 + 2) = 26

Orange = (6) - (0) = 6

Solution Steps

Let's break down how to achieve this:

Step 1: Use a Subquery with UNION

We'll utilize a subquery combined with the UNION operator to merge both tables. This will allow us to collect the sums from both Table 1 and Table 2, while changing the values from Table 2 to negative.

Here’s how the SQL statement looks:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code:

Subquery: The first part of the union gathers names and sums from Table 1. The second part does the same but for Table 2, multiplying the sums by -1 to convert them to negatives.

Outer Query: The outer query aggregates everything into one final table by grouping the TheName column, allowing for a total sum per name, resulting in the desired outcome.

Advantages of This Approach

Simplicity: Using a subquery and UNION keeps the query organized and easy to understand.

Flexibility: Adding conditions for filtering data is also manageable using this structure.

Step 2: Execute in MS Access

Make sure you're running this query in your MS Access environment. This structure is compatible and will help in merging your datasets efficiently.

Conclusion

Merging two tables in SQL can seem daunting, especially when values need to be altered before the merge. However, by breaking the process into clear steps and utilizing SQL commands effectively, you can achieve the required output with ease.

Feel free to try incorporating these techniques into your SQL practice, and watch your database handling skills grow!

If you have more questions or need further clarification, don’t hesitate to ask!