> **Note:** This documentation refers to a Grafana 7.0 feature. This documentation will be frequently updated to reflect updates to the feature, and it will probably be broken into smaller sections when the feature moves out of beta.
Transformations process the result set before it’s passed to the visualization. You access transformations in the Transform tab of the Grafana panel editor.
Transformations allow you to rename fields, join separate time series together, do math across queries, and more. For users, with large dashboards or with heavy queries, being able to reuse the query result from one panel in another panel can be a huge performance gain.
> **Note:** Transformations sometimes result in data that cannot be graphed. When that happens, Grafana displays a suggestion on the visualization that you can click to switch to table visualization. This often helps you better understand what the transformation is doing to your data.
## Transformation execution order
Grafana applies transformations in the sequence that they are listed on the screen. Every transformation creates a new result set that is passed to the next transformation in the pipeline.
The order can make a huge difference in how your results look. For example, if you use a Reduce transformation to condense all the results of one column to a single value, then you can only apply transformations to that single value.
## Prerequisites
Before you apply transformations, all of the following must be true:
- You have entered a query and returned data from a data source. For more information about queries, refer to [Queries]({{< relref "queries.md" >}}).
- You have applied a visualization that supports queries, such as:
A transformation row appears that allows you to configure the transformation options.
Click **Add transformation** to apply another transformation. Keep in mind that the next transformation acts on the result set returned by the previous transformation.
If you have trouble, click the bug icon to [debug your transformations](#debug-transformations).
Click the trash can icon to remove a transformation.
Apply a _Reduce_ transformation when you want to simplify your results down to one value. Reduce basically removes time component. If visualized as a table, it reduces a column down to one row (value).
In the **Calculations** field, enter one or more calculation types. Click to see a list of calculation choices. For information about available calculations, refer to the [Calculation list]({{< relref "calculations-list.md" >}}).
Once you select at least one calculation, Grafana reduces the results down to one value using the calculation you select. If you select more than one calculation, then more than one value is displayed.
Here's an example of a table with time series data. Before I apply the transformation, you can see all the data organized by time.
After I apply the transformation, there is no time value and each column has been reduced to one row showing the results of the calculations that I chose.
Use this transformation to combine the result from multiple queries into one single result. This is helpful when using the table panel visualization. Values that can be merged are combined into the same row. Values are mergeable if the shared fields contains the same data.
Grafana displays the query identification letters in dark gray text. Click a query identifier to toggle filtering. If the query letter is white, then the results are displayed. If the query letter is dark, then the results are hidden.
In the example below, the panel has three queries (A, B, C). I removed the B query from the visualization.
Use this transformation to rename, reorder, or hide fields returned by the query.
> **Note:** This transformation only works in panels with a single query. If your panel has multiple queries, then you must either apply an Outer join transformation or remove the extra queries.
Grafana displays a list of fields returned by the query. You can:
- Change field order by hovering your cursor over a field. The cursor turns into a hand and then you can drag the field to its new place.
Use this transformation to join multiple time series from a result set by field.
This transformation is especially useful if you want to combine queries so that you can calculate results from the fields.
In the example below, I have a template query displaying time series data from multiple servers in a table visualization. I can only view the results of one query at a time.
I applied a transformation to join the query results using the time field. Now I can run calculations, combine, and organize the results in this new table.
Use this transformation to add a new field calculated from two other fields. Each transformation allows you to add one new field.
- **Mode -** Select a mode:
- **Reduce row -** Apply selected calculation on each row of selected fields independently.
- **Binary option -** Apply basic math operation(sum, multiply, etc) on values in a single row from two selected fields.
- **Field name -** Select the names of fields you want to use in the calculation for the new field.
- **Calculation -** Select a calculation to use when Grafana creates the new field. Click in the field to see a list of calculation choices. For information about available calculations, refer to the [Calculation list]({{< relref "calculations-list.md" >}}).
- **Alias -** (Optional) Enter the name of your new field. If you leave this blank, then the field will be named to match the calculation.
- **Replace all fields -** (Optional) Select this option if you want to hide all other fields and display only your calculated field in the visualization.
In the example below, I added two fields together and named them Sum.
This transformation groups the data by a specified field (column) value and processes calculations on each group. The available calculations are the same as the Reduce transformation.
This transformation goes in two steps. First you specify one or multiple fields to group the data by. This will group all the same values of those fields together, as if you sorted them. For instance if we `Group By` the `Server ID` field, it would group the data this way:
All rows with the same value of `Server ID` are grouped together.
After choosing which field you want to group your data by, you can add various calculations on the other fields, and the calculation will be applied on each group of rows. For instance, we could want to calculate the average `CPU temperature` for each of those servers. So we can add the _mean_ calculation applied on the `CPU Temperature` field to get the following:
Use this transformation to combine the result from multiple time series data queries into one single result. This is helpful when using the table panel visualization.
The result from this transformation will contain three columns: `Time`, `Metric`, and `Value`. The `Metric` column is added so you easily can see from which query the metric originates from. Customize this value by defining `Label` on the source query.
In the example below, we have two queries returning time series data. It is visualized as two separate tables before applying the transformation.
