See Demo. If you have an unknown number of columnnames that you want to transpose, then you can use dynamic SQL:. This could also be completed using multiple joins, but you will need some column to associate each of the rows which you do not have in your sample data.
But the basic syntax would be:. This is rather a method than just a single script but gives you much more possibilities. Learn more. Efficiently convert rows to columns in sql server Ask Question. Asked 7 years ago. Active 7 months ago. Viewed k times. A Friend 7 7 silver badges 17 17 bronze badges.
Active Oldest Votes. There are several ways that you can transform data from multiple rows into columns. Using multiple joins This could also be completed using multiple joins, but you will need some column to associate each of the rows which you do not have in your sample data.
But the basic syntax would be: select fn. But in the last example, you can use cross join rather than left join because each subquery returns one row. I need to build a dynamic query because I don't know the number of rows.
Lets talk about converting a table with I can't use a view for that transformation, what about using a TFV? I cant recommend it for any production environments but does the job for adhoc BI requests.
Bartosz X Bartosz X 1, 17 17 silver badges 28 28 bronze badges. All good until Could not find stored procedure 'dbo. Any advice? Thanks Bartosz, managed to use some of the ideas from your script and done what I had on my mind already, but nevertheless, thanks for updating it :. I should have thought to change that line, but honestly thought is a stored procedure you've forgot is not default in the system or something like that. I will give it a run when i get close to that project again, and update here!
The Overflow Blog. Featured on Meta. Community and Moderator guidelines for escalating issues via new response…. Feedback on Q2 Community Roadmap. Technical site integration observational experiment live on Stack Overflow.
Dark Mode Beta - help us root out low-contrast and un-converted bits. Linked 2. Related The Olympics is over for another year. But there's still plenty of time for SQL-style data wrangling of the results! To do this, I've compiled a table of medal winners from Rio for each sport:. This is great when looking for a specific result. But what everyone really wants to know how their country fared overall. To get this you need to convert the table above to the final medal table:.
To do this, you need to count the number of gold, silver and bronze rows for each country. Then create new columns to hold the results. This post will teach you. You'll also learn various row and column transformations with SQL including:. If you want to play along you can access the scripts in LiveSQL. Or you can nab the create table scripts at the bottom of this post. Oracle Database 11g introduced the pivot operator. This makes switching rows to columns easy.
To use this you need three things:. The value in the new columns must be an aggregate. For example, count, sum, min, etc. Place a pivot clause containing these items after the table name, like so:. Hmmm, that's not right! You wanted the total medals for each country. This is giving the results per athlete! This is because Oracle adds an implicit group by for all the columns not in the pivot clause.
To avoid this, use an inline view that selects just the columns you want in the results:. This is looking promising. But it's still not right. China didn't finish second.MS SQL. SQL Server has a PIVOT relational operator to turn the unique values of a specified column from multiple rows into multiple column values in the output cross-tabeffectively rotating a table.
Is UNPIVOT the best way for converting columns into rows?
It also allows performing aggregations, wherever required, for column values that are expected in the final output. As you can see in the image below, it has sales information for some countries for a couple of years.
Also, if you notice, for each country and for each year there is a separate row. Now by using the PIVOT operator, we will convert row values into column values with the script given below and the results as shown in the image below.
Though we have used the SUM aggregation function, in this case there is no summation, as there is only one row for each unique combination for country and year.
Please note the use of brackets for pivot column values; these are required.
If you notice in the above script, we have provided values, and for pivot columns as these values are available in the original datasets. But what if some additional values are expected to come in the future, for example andetc. In that case, you can still use the pivot column values, which are expected to come or which are still not available in the original dataset in the future though you will see NULL for its values. The script below shows this scenario and the image below shows NULLs for the years and as there is no data for these years.
In that case, you can write a dynamic query to first grab all the unique values for the pivot column at runtime and then a write dynamic query to execute it with the pivot query as shown below:. Let me demonstrate this with an example; lets create a table with pivoted data from the previous query with the script below.
The image below shows data of the newly created table with pivoted data. The image below shows rotated data:. The reason is, Pivot performs aggregation while rotating row values into column values and might merge possible multiple row values into single column value in the output.
For example, consider for a given country and year there are two values, say and Now when you pivot it, the output will have as the column value if you have SUM as the aggregation function. Later if you want to unpivot it back, you will get not the bi-furcated values and as original. Having said that, we can say if the pivoted values are aggregated values, it will not be possible to get the original data back. I also talked about writing a dynamic query to write a dynamic pivot query in which possible pivot column values are determined at runtime.Comment 2.
Data integrity, data consistency, and data anomalies play a primary role when storing data into a database. Data is provided in different formats to create different visualizations for analysis. For this purpose, you need to pivot rows to columns and unpivot columns to rows your data. We'll convert row data into column data using custom logic and temp tables, and populate aggregated data in the temp table. A sample dataset containing information about movies and its user ratings is used in this use case.
Data modeling for the sample dataset is as follows:. To convert a single row into multiple columns, perform the following. The single row transposed into multiple columns is shown in the below diagram: The transposed ratings of the movies are graphically represented using MS Excel as follows:.
To convert multiple rows into multiple columns, perform the following:.
How to Convert Rows to Columns and Back Again with SQL (Aka PIVOT and UNPIVOT)
Multiple columns converted into a single column are shown in the below diagram:. Multiple rows converted into multiple columns are shown in the below diagram:.
The transposed movies ratings and its users are graphically represented using MS Excel as follows:. Published at DZone with permission of Rathnadevi Manivannan. See the original article here. Over a million developers have joined DZone. Let's be friends:. DZone 's Guide to. Free Resource. Like 5. Join the DZone community and get the full member experience. Join For Free. Create a database MovieLens and table objects based on data modeling and loaded sample data.
The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. There are several ways that you can transform this data. Then you apply the aggregate function sum with the case statement to get the new columns for each color.
If you know all of the values that you want to transform, you can hard-code them into a static version to get the result:. It takes the list of columns and turns it into rows, the PIVOT then performs the final transformation into columns. The dynamic version queries both yourtable and then the sys. This is then added to a query string to be executed.
Although the general consensus in the professional community is to stay away from SQL Server Cursors, there are still instances whereby the use of cursors is recommended. Anyway, Cursors present us with another option to transpose rows into columns.
Similar to the PIVOT, the cursor has the dynamic capability to append more rows as your dataset expands to include more policy numbers.
Unlike the PIVOT, the cursor excels in this area as it is able to expand to include newly added document, without altering the script. The major limitation of transposing rows into columns using CURSOR is a disadvantage that is linked to using cursors in general — they come at significant performance cost. Based on this solution from bluefeet here is a stored procedure that uses dynamic sql to generate the transposed table.
It requires that all the fields are numeric except for the transposed column the column that will be the header in the resulting table :. Adding to Paco Zarate's terrific answer above, if you want to transpose a table which has multiple types of columns, then add this to the end of line 39, so it only transposes int columns:.
I'm mixing this solution with the information about howto order rows without order by SQLAuthority. I was able to use Paco Zarate's solution and it works beautifully. There is a problem with my usage and I hope someone can help me with it:.One of the primary functions of a Business Intelligence team is to enable business users with an understanding of data created and stored by business systems.
Understanding the data should give business users an insight into how the business is performing. A typical understanding of data within an insurance industry could relate to measuring the number of claims received vs successfully processed claims. Such data could be stored in source system as per the layout in Table 1 :.
Although each data entry in Table 1 has a unique RecKey identifier, it all still relates to a single policy claim policy Pol Thus, a correct representation of this data ought to be in a single row that contains a single instance of policy Pol as shown in Table 2 :. The objective of this article is to demonstrate different SQL Server T-SQL options that could be utilised in order to transpose repeating rows of data into a single row with repeating columns as depicted in Table 2.
Some of the T-SQL options that will be demonstrated will use very few lines of code to successfully transpose Table 1 into Table 2 but may not necessary be optimal in terms query execution. Script 1 shows how a Pivot function can be utilised. The results of executing Script 1 are shown in Figure 1as it can be seen, the output is exactly similar to that of Table 2. Furthermore, as we add more policy numbers in our dataset i.
Polwe are able to automatically retrieve them without making any changes to Script 1. This is because the Pivot function works with only a predefined list of possible fields.
However, imagine if business later decides to add more documents that are required to process a claim? It would mean that you need to update your Pivot script and manually add those fields. Thus, although transposing rows using Pivot operator may seem simple, it may later be difficult to maintain. The actual estimated plan depicted in Figure 4indicates that only a single scan was made against the base table with a majority of the cost at Although the general consensus in the professional community is to stay away from SQL Server Cursors, there are still instances whereby the use of cursors is recommended.
I suppose if they were totally useless, Microsoft would have deprecated their usage long ago, right? Anyway, Cursors present us with another option to transpose rows into columns.
Script 2 displays a T-SQL code that can be used to transpose rows into columns using the Cursor function. Execution of Script 2 lead to the result set displayed in Figure 6 yet, the Cursor option uses far more lines of code than its T-SQL Pivot counterpart.Convertion of columns into rows is widely used in real tasks. We have a task to convert columns into rows. To receive execution plans automatically each time the query is executed we need to switch to the profiling mode:.
For this, the Generate Execution Plan command must be ran. SQL Server did not offer an efficient way to convert columns into rows. The crucial weakness of this practice is the multiple data reading, which considerably decreases the efficiency of the query execution. Using the dynamic SQL allows creating general-purpose query for any table on the condition that columns not included in the primary key have a compatible data-type between them:. Afterwards the name of the attribute and its value are parsed.
In our case that is the price we pay for it being universal. This is valid for the cases when simple transformation of columns into rows is taking place. In the execution plan its show that the bottleneck is the multiple data reading and sorting, which is necessary for organizing the data rows:. If after the convertion the received data rows should be used for aggregation or sorting, then we should rather use VALUES structure which, in most cases, results into more efficient execution plans.
For the tables, where different structure types might occur and the number of columns is unrestricted, it is recommended to use XML which unlike the dynamic SQL can be used inside the table functions. NAME, sys. Thanks for the comment. This is a built-in feature in dbForge Studio profiler.
Hi Kai, you mean spills into tempdb? If yes, in this case we have identical functionality as in SSMS. How To. SQL Server Tools. Players The crucial weakness of this practice is the multiple data reading, which considerably decreases the efficiency of the query execution. It is obvious, when we look at the execution plan of the following query: 2.
Players t Now the execution plan looks like this: Hurrah! Sergey Syrovatchenko. Products ADO. October 30th,
- effect of temperature on starch iodine complex
- how to overclock monitor response time
- energia: bollette, da 1° aprile elettricità -8,5%, gas -9,9%
- ps2 controller protocol
- sbc initial timing
- how to find tv channel url
- cwcheat ppsspp android
- step 7 safety download
- black tau
- v8 landcruiser problems
- 3d gps maps
- agency incubator teachable