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Add sensor type=time to the history_stats.markdown (#37011)

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Rick Auch 2025-01-20 08:36:14 -06:00 committed by GitHub
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@ -124,7 +124,7 @@ Depending on the sensor type you choose, the `history_stats` integration can sho
- **count**: How many times the tracked entity matched the configured state during the time period. This will count states (for example, how many times a light was in the `on` state during the time period), as opposed to counting state transitions (for example, how many times a light was *turned* `on`). The difference is if the entity was already in the desired state at the start of the time period, that scenario will be counted with this sensor type.
{% note %}
For a count sensor that uses a time period that does not slide (such as one that resets upon each hour, as opposed to one which considers the trailing 60 minutes), consider using [customization](/docs/configuration/customizing-devices/#customizing-an-entity-in-yaml) to change the `state_class` to `total_increasing` to generate statistics that track the `sum`. This is useful when emulating the behavior of a `utility_meter` helper that has a defined reset cycle. Without intervention, the `state_class` of any `history_stats` sensor will be `measurement` and will therefore generate `average`, `min`, and `max` statistics.
For a **time** or **count** sensor that uses a time period that does not slide (such as one that resets upon each hour, as opposed to one which considers the trailing 60 minutes), consider using [customization](/docs/configuration/customizing-devices/#customizing-an-entity-in-yaml) to change the `state_class` to `total_increasing` to generate statistics that track the `sum`. This is useful when emulating the behavior of a `utility_meter` helper that has a defined reset cycle. Without intervention, the `state_class` of any `history_stats` sensor will be `measurement` and will therefore generate `average`, `min`, and `max` statistics.
{% endnote %}
## Time periods