====Calculating an Average====

There are actually a couple of different ways to capture average, min or max values, depending on if you want to capture //all// of the values in your table, or just a couple.

===Capturing All Values===

To capture the average value of all of the columns in a table, you can use the [[flatten|Flatten]] layer. 

This captures a key aggregate (such as first, last, min, max or avg) value from a table and writes it to your capture attributes.

Note that unless you set the value of 'retain' to //true//, this also removes any table or timeframe data the layer contains.

See the following example...

Assuming we have a table (probably loaded with [[get_query|Get Query]]) containing the following...

^Temperature^Speed^Current^Product^
|10|211|5.1|1|
|10|210|5.2|1|
|20|209|5.1|2|
|20|210|5.2|2|

...along with the configuration below...

<code javascript>
{
   "type": "flatten"
   "method": "avg"
}
</code>

Your final capture would contain something like the results below...

**Temperature: 15 \\
Speed: 210 \\
Current: 5.15 \\
Product: 1.5**.

===Capturing Specific Values===

If you're looking for something //specific// or you'd like to control what each point is //called//, you can use the [[valuesummary|ValueSummary]] layer.

In this case, we list the names of the columns we want to average. We can also provide conditions.

You can use the following...

<code javascript>
{
   "columns": ["Temperature"],
   "named": ["Average Water Temp"],
   "methods": ["avg"]
}
</code>

Your final capture would contain...

**Average Water Temp: 15**.

===Splitting By Other Values===

The ValueSummary method can also include //conditions// and be //split//. For example, if we wanted to know the average temperature **per product**, we could use...

<code javascript>
{
   "columns": ["Temperature"],
   "prefix": "Average ",
   "named": " Water Temperature"
   "methods": ["avg"],
   "splitby": "Product"
}
</code>

Your final capture would contain...

**Average 1 Water Temp: 10** \\
**Average 2 Water Temp: 20**