---
title: anomalydetection.mad() function
description: anomalydetection.mad() uses the median absolute deviation (MAD) algorithm to detect anomalies in a data set.
url: https://docs.influxdata.com/flux/v0/stdlib/contrib/anaisdg/anomalydetection/mad/
estimated_tokens: 1821
product: Flux
version: v0
publisher: InfluxData
canonical: https://docs.influxdata.com/flux/v0/stdlib/contrib/anaisdg/anomalydetection/mad/
date: '2024-04-08T16:01:02-06:00'
lastmod: '2024-04-08T16:01:02-06:00'
---

* Flux 0.90.0+

InfluxDB support

> [!Important]
> `anomalydetection.mad()` is a user-contributed function maintained by
> the [package author](#package-author-and-maintainer).

`anomalydetection.mad()` uses the median absolute deviation (MAD) algorithm to detect anomalies in a data set.

Input data requires `_time` and `_value` columns.
Output data is grouped by `_time` and includes the following columns of interest:

* **\_value**: difference between of the original `_value` from the computed MAD
  divided by the median difference.
* **MAD**: median absolute deviation of the group.
* **level**: anomaly indicator set to either `anomaly` or `normal`.

##### Function type signature

```js
(<-table: stream[B], ?threshold: A) => stream[{C with level: string, _value_diff_med: D, _value_diff: D, _value: D}] where A: Comparable + Equatable, B: Record, D: Comparable + Divisible + Equatable
```

For more information, see [Function type signatures](/flux/v0/function-type-signatures/).

## Parameters

### threshold

Deviation threshold for anomalies.

### table

Input data. Default is piped-forward data (`<-`).

## Examples

### Use the MAD algorithm to detect anomalies

```js
import "contrib/anaisdg/anomalydetection"
import "sampledata"

sampledata.float()
    |> anomalydetection.mad(threshold: 1.0)
```

[](#view-example-input-and-output)

View example input and output

#### Input data

|       \_time       |\*tag|\_value|
|--------------------|-----|-------|
|2021-01-01T00:00:00Z| t1  |\-2.18 |
|2021-01-01T00:00:10Z| t1  | 10.92 |
|2021-01-01T00:00:20Z| t1  | 7.35  |
|2021-01-01T00:00:30Z| t1  | 17.53 |
|2021-01-01T00:00:40Z| t1  | 15.23 |
|2021-01-01T00:00:50Z| t1  | 4.43  |

|       \_time       |\*tag|\_value|
|--------------------|-----|-------|
|2021-01-01T00:00:00Z| t2  | 19.85 |
|2021-01-01T00:00:10Z| t2  | 4.97  |
|2021-01-01T00:00:20Z| t2  |\-3.75 |
|2021-01-01T00:00:30Z| t2  | 19.77 |
|2021-01-01T00:00:40Z| t2  | 13.86 |
|2021-01-01T00:00:50Z| t2  | 1.86  |

#### Output data

|   MAD   |      \*\_time      |\_value|\_value\_diff|\_value\_diff\_med| level |tag|
|---------|--------------------|-------|-------------|------------------|-------|---|
|16.330839|2021-01-01T00:00:00Z|   1   |   11.015    |      11.015      |anomaly|t1 |
|16.330839|2021-01-01T00:00:00Z|   1   |   11.015    |      11.015      |anomaly|t2 |

|  MAD   |      \*\_time      |     \_value      |  \_value\_diff   |\_value\_diff\_med| level |tag|
|--------|--------------------|------------------|------------------|------------------|-------|---|
|4.410735|2021-01-01T00:00:10Z|0.9999999999999999|2.9749999999999996|      2.975       |normal |t1 |
|4.410735|2021-01-01T00:00:10Z|1.0000000000000002|2.9750000000000005|      2.975       |anomaly|t2 |

|  MAD  |      \*\_time      |\_value|\_value\_diff|\_value\_diff\_med| level |tag|
|-------|--------------------|-------|-------------|------------------|-------|---|
|8.22843|2021-01-01T00:00:20Z|   1   |    5.55     |       5.55       |anomaly|t1 |
|8.22843|2021-01-01T00:00:20Z|   1   |    5.55     |       5.55       |anomaly|t2 |

|       MAD        |      \*\_time      |     \_value      |  \_value\_diff   |\_value\_diff\_med| level |tag|
|------------------|--------------------|------------------|------------------|------------------|-------|---|
|1.6605119999999987|2021-01-01T00:00:30Z|0.9999999999999984|1.1199999999999974|1.1199999999999992|normal |t1 |
|1.6605119999999987|2021-01-01T00:00:30Z|1.0000000000000016|1.120000000000001 |1.1199999999999992|anomaly|t2 |

|       MAD        |      \*\_time      |\_value|  \_value\_diff   |\_value\_diff\_med| level |tag|
|------------------|--------------------|-------|------------------|------------------|-------|---|
|1.0155810000000007|2021-01-01T00:00:40Z|   1   |0.6850000000000005|0.6850000000000005|anomaly|t1 |
|1.0155810000000007|2021-01-01T00:00:40Z|   1   |0.6850000000000005|0.6850000000000005|anomaly|t2 |

|       MAD        |      \*\_time      |     \_value      |  \_value\_diff   |\_value\_diff\_med| level |tag|
|------------------|--------------------|------------------|------------------|------------------|-------|---|
|1.9051409999999995|2021-01-01T00:00:50Z|        1         |1.2849999999999997|1.2849999999999997|anomaly|t1 |
|1.9051409999999995|2021-01-01T00:00:50Z|1.0000000000000002|      1.285       |1.2849999999999997|anomaly|t2 |
| _time | *tag | _value |
| --- | --- | --- |
| _time | *tag | _value |
| 2021-01-01T00:00:00Z | t1 | -2.18 |
| 2021-01-01T00:00:10Z | t1 | 10.92 |
| 2021-01-01T00:00:20Z | t1 | 7.35 |
| 2021-01-01T00:00:30Z | t1 | 17.53 |
| 2021-01-01T00:00:40Z | t1 | 15.23 |
| 2021-01-01T00:00:50Z | t1 | 4.43 |

| _time | *tag | _value |
| --- | --- | --- |
| _time | *tag | _value |
| 2021-01-01T00:00:00Z | t2 | 19.85 |
| 2021-01-01T00:00:10Z | t2 | 4.97 |
| 2021-01-01T00:00:20Z | t2 | -3.75 |
| 2021-01-01T00:00:30Z | t2 | 19.77 |
| 2021-01-01T00:00:40Z | t2 | 13.86 |
| 2021-01-01T00:00:50Z | t2 | 1.86 |

| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| --- | --- | --- | --- | --- | --- | --- |
| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| 16.330839 | 2021-01-01T00:00:00Z | 1 | 11.015 | 11.015 | anomaly | t1 |
| 16.330839 | 2021-01-01T00:00:00Z | 1 | 11.015 | 11.015 | anomaly | t2 |

| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| --- | --- | --- | --- | --- | --- | --- |
| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| 4.410735 | 2021-01-01T00:00:10Z | 0.9999999999999999 | 2.9749999999999996 | 2.975 | normal | t1 |
| 4.410735 | 2021-01-01T00:00:10Z | 1.0000000000000002 | 2.9750000000000005 | 2.975 | anomaly | t2 |

| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| --- | --- | --- | --- | --- | --- | --- |
| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| 8.22843 | 2021-01-01T00:00:20Z | 1 | 5.55 | 5.55 | anomaly | t1 |
| 8.22843 | 2021-01-01T00:00:20Z | 1 | 5.55 | 5.55 | anomaly | t2 |

| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| --- | --- | --- | --- | --- | --- | --- |
| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| 1.6605119999999987 | 2021-01-01T00:00:30Z | 0.9999999999999984 | 1.1199999999999974 | 1.1199999999999992 | normal | t1 |
| 1.6605119999999987 | 2021-01-01T00:00:30Z | 1.0000000000000016 | 1.120000000000001 | 1.1199999999999992 | anomaly | t2 |

| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| --- | --- | --- | --- | --- | --- | --- |
| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| 1.0155810000000007 | 2021-01-01T00:00:40Z | 1 | 0.6850000000000005 | 0.6850000000000005 | anomaly | t1 |
| 1.0155810000000007 | 2021-01-01T00:00:40Z | 1 | 0.6850000000000005 | 0.6850000000000005 | anomaly | t2 |

| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| --- | --- | --- | --- | --- | --- | --- |
| MAD | *_time | _value | _value_diff | _value_diff_med | level | tag |
| 1.9051409999999995 | 2021-01-01T00:00:50Z | 1 | 1.2849999999999997 | 1.2849999999999997 | anomaly | t1 |
| 1.9051409999999995 | 2021-01-01T00:00:50Z | 1.0000000000000002 | 1.285 | 1.2849999999999997 | anomaly | t2 |