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Statistics integration: Add state characteristic docu (#17660)

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Co-authored-by: Franck Nijhof <frenck@frenck.nl>
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@ -14,47 +14,83 @@ ha_platforms:
- sensor
---
The `statistics` sensor platform consumes the state from other sensors. It exports the `mean` value as state and the following values as attributes: `count`, `mean`, `median`, `quantiles`, `standard_deviation`, `variance`, `total`, `min_value`, `max_value`, `min_age`, `max_age`, `change`, `average_change` and `change_rate`. If the source is a binary sensor then only state changes are counted.
The `statistics` sensor platform observes the state of a source sensor and provides statistical characteristics about its recent past. This integration can be quite useful in automations, e.g., to trigger an action when the air humidity in the bathroom settles after a hot shower or when the number of brewed coffee over a day gets too high.
Assuming the [`recorder`](/integrations/recorder/) integration is running (either configured explicitly or as part of a meta-integration/dependency, e.g., [`default_config`](/integrations/default_config/), [`history`](/integrations/history/), etc.), historical sensor data is read from the database on startup and is available immediately after a restart of the platform. If the [`recorder`](/integrations/recorder/) integration is *not* running, it can take time for the sensor to start reporting data because some attribute calculations require more than one value.
The created sensor presents one characteristic as its state (the `mean` value by default) and many more as attributes. The time period and/or number of recent state changes to be considered is defined as part of the sensor configuration. The sensor and its characteristics update with every source sensor update.
Both `sensor` and `binary_sensor` are supported as source sensor. In the case of a binary sensor only the state changes are counted.
Assuming the [`recorder`](/integrations/recorder/) integration is running, historical sensor data is read from the database on startup and is available immediately after a restart of the platform. If the [`recorder`](/integrations/recorder/) integration is *not* running, it can take some time for the sensor to start reporting data because some characteristics calculations require more than one source sensor value.
## Characteristics
The following statistical characteristics are provided for the collected source sensor. Pay close attention to the right configuration of `sampling_size` and `max_age`, as most characteristics are directly related to the count of samples or the age of processed samples.
| Identifier | Description |
| ---------- | ----------- |
| `count` | The number of stored source sensor readings. This number is limited by `sampling_size` and can be low within the bounds of `max_age`.
| `total` | The sum of all source sensor measurements within the given time and sampling size limits.
| `mean` | The average value computed for all measurements. Be aware that this does not take into account uneven time intervals between measurements.
| `median` | The [median](https://en.wikipedia.org/wiki/Mode_(statistics)#Comparison_of_mean,_median_and_mode) value computed for all measurements.
| `standard_deviation` | The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of an assumed normal distribution from all measurements.
| `variance` | The [variance](https://en.wikipedia.org/wiki/Standard_deviation) of an assumed normal distribution from all measurements.
| `min_value` | The smallest value among the number of measurements.
| `max_value` | The biggest value among the number of measurements.
| `min_age` | The timestamp of the oldest measurement stored.
| `max_age` | The timestamp of the newest measurement stored.
| `change` | The difference between the oldest and newest measurement stored.
| `average_change` | The difference between the oldest and newest measurement stored, divided by the number of in-between measurements (n-1).
| `change_rate` | The difference between the oldest and newest measurement stored, divided by seconds between them.
| `quantiles` | Quantiles divide the range of a normal probability distribution of all considered source sensor measurements into continuous intervals with equal probabilities. Check the configuration parameters `quantile_intervals` and `quantile_method` for further details.
## Configuration
To enable the statistics sensor, add the following lines to your `configuration.yaml`:
Define a statistics sensor by adding the following lines to your `configuration.yaml`:
```yaml
# enable the recorder integration (optional)
recorder:
# Example configuration.yaml entry
sensor:
- platform: statistics
entity_id: sensor.cpu
name: "Bathroom humidity mean over last 24 hours"
entity_id: sensor.bathroom_humidity
max_age:
hours: 24
- platform: statistics
name: "Bathroom humidity change over 5 minutes"
entity_id: sensor.bathroom_humidity
max_age:
minutes: 5
state_characteristic: change
precision: 1
- platform: statistics
entity_id: binary_sensor.movement
```
{% configuration %}
entity_id:
description: The entity to monitor. Only [sensors](/integrations/sensor/) and [binary sensor](/integrations/binary_sensor/).
description: The source sensor to observe and compute statistical characteristics for. Only [sensors](/integrations/sensor/) and [binary sensor](/integrations/binary_sensor/) are supported.
required: true
type: string
name:
description: Name of the sensor to use in the frontend.
description: Name of the new statistics sensor.
required: false
default: Stats
type: string
state_characteristic:
description: The characteristic that should be used as the state of the statistics sensor (see above). All other characteristics are provided as attributes.
required: false
default: mean
type: string
sampling_size:
description: Size of the sampling. If the limit is reached then the values are rotated.
description: Maximum number of source sensor measurements stored. Be sure to choose a reasonably high number if the limit should be driven by `max_age` instead.
required: false
default: 20
type: integer
max_age:
description: Maximum age of measurements. Setting this to a time interval will cause older values to be discarded. Please note that you might have to increase the [`sampling_size`](/integrations/statistics#sampling_size) parameter. If you e.g., have a sensor value updated every second you will by default only get a `max_age` of 20s. Furthermore the sensor gets `unknown` if the entity is not updated within the time interval.
description: Maximum age of source sensor measurements stored. Setting this to a time period will cause older values to be discarded. If omitted, the number of considered source sensor measurements is limitted by `sampling_size` only. Set both parameters appropriately to create suited limits for your use case. The sensor value will become `unkown` if the source sensor is not updated within the time period.
required: false
type: time
precision:
description: Defines the precision of the calculated values, through the argument of [`round()`](/docs/configuration/templating/#numeric-functions-and-filters).
description: Defines the number of decimal places of the calculated sensor value.
required: false
default: 2
type: integer