Docs: Fix links to transforms (#30194)

docs/sources/panels/transformations/types-options.md

@@ -8,7 +8,7 @@ weight = 300
 Grafana comes with the following transformations:
 Grafana comes with the following transformations:
 
 
 - [Reduce](#reduce)
 - [Reduce](#reduce)
-- [Filter by name](#filter-by-name)
+- [Filter data by name](#filter-data-by-name)
 - [Filter data by query](#filter-data-by-query)
 - [Filter data by query](#filter-data-by-query)
 - [Filter data by value](#filter-data-by-value)
 - [Filter data by value](#filter-data-by-value)
 - [Organize fields](#organize-fields)
 - [Organize fields](#organize-fields)
@@ -26,7 +26,7 @@ Keep reading for detailed descriptions of each type of transformation and the op
 ## Reduce
 ## Reduce
 
 
 The _Reduce_ transformation will apply a calculation to each field in the frame and return a single value.  Time fields are removed when applying
 The _Reduce_ transformation will apply a calculation to each field in the frame and return a single value.  Time fields are removed when applying
-this transformation.  
+this transformation.
 
 
 Consider the input:
 Consider the input:
 
 
@@ -48,11 +48,11 @@ The reduce transformer has two modes:
 - **Series to rows -** Creates a row for each field and a column for each calculation.
 - **Series to rows -** Creates a row for each field and a column for each calculation.
 - **Reduce fields -** Keeps the existing frame structure, but collapses each field into a single value.
 - **Reduce fields -** Keeps the existing frame structure, but collapses each field into a single value.
 
 
-For example, if you used the **First** and **Last** calculation with a **Series to rows** transformation, then 
+For example, if you used the **First** and **Last** calculation with a **Series to rows** transformation, then
 the result would be:
 the result would be:
 
 
-| Field   | First   | Last    | 
-| ------- | ------- | ------- | 
+| Field   | First   | Last    |
+| ------- | ------- | ------- |
 | Temp    | 12.3    | 15.4    |
 | Temp    | 12.3    | 15.4    |
 | Uptime  | 256122  | 1230233 |
 | Uptime  | 256122  | 1230233 |
 | AQI     | 6.5     | 3.2     |
 | AQI     | 6.5     | 3.2     |
@@ -104,7 +104,7 @@ Here is the result after applying the Merge transformation.
 | 2020-07-07 11:34:20 | node    | 15     | 25260122  |
 | 2020-07-07 11:34:20 | node    | 15     | 25260122  |
 | 2020-07-07 11:24:20 | postgre | 5      | 123001233 |
 | 2020-07-07 11:24:20 | postgre | 5      | 123001233 |
 
 
-## Filter by name
+## Filter data by name
 
 
 Use this transformation to remove portions of the query results.
 Use this transformation to remove portions of the query results.
 
 
@@ -214,22 +214,22 @@ If you selected Server as the **Value field name**, then you would get one field
 
 
 The labels to fields transformer is internally two separate transformations. The first acts on single series and extracts labels to fields. The second is the [merge](#merge) transformation that joins all the results into a single table. The merge transformation tries to join on all matching fields. This merge step is required and cannot be turned off.
 The labels to fields transformer is internally two separate transformations. The first acts on single series and extracts labels to fields. The second is the [merge](#merge) transformation that joins all the results into a single table. The merge transformation tries to join on all matching fields. This merge step is required and cannot be turned off.
 
 
-To illustrate this, here is an example where you have two queries that return time series with no overlapping labels. 
+To illustrate this, here is an example where you have two queries that return time series with no overlapping labels.
 
 
 * Series 1: labels Server=ServerA
 * Series 1: labels Server=ServerA
 * Series 2: labels Datacenter=EU
 * Series 2: labels Datacenter=EU
 
 
 This will first result in these two tables:
 This will first result in these two tables:
 
 
-| Time                | Server  | Value | 
-| ------------------- | ------- | ----- | 
+| Time                | Server  | Value |
+| ------------------- | ------- | ----- |
 | 2020-07-07 11:34:20 | ServerA | 10
 | 2020-07-07 11:34:20 | ServerA | 10
 
 
-| Time                | Datacenter | Value | 
+| Time                | Datacenter | Value |
 | ------------------- | ---------- | ----- |
 | ------------------- | ---------- | ----- |
 | 2020-07-07 11:34:20 | EU         | 20
 | 2020-07-07 11:34:20 | EU         | 20
 
 
-After merge: 
+After merge:
 
 
 | Time                | Server  | Value | Datacenter |
 | Time                | Server  | Value | Datacenter |
 | ------------------- | ------- | ----- | ---------- |
 | ------------------- | ------- | ----- | ---------- |
@@ -358,7 +358,7 @@ Here is the result after applying the Series to rows transformation.
 | 2020-07-07 09:30:57 | Humidity    | 33    |
 | 2020-07-07 09:30:57 | Humidity    | 33    |
 | 2020-07-07 09:30:05 | Temperature | 19    |
 | 2020-07-07 09:30:05 | Temperature | 19    |
 
 
-## Filter by value
+## Filter data by value
 
 
 > **Note:** This transformation is available in Grafana 7.4+.
 > **Note:** This transformation is available in Grafana 7.4+.