# Derivative

The `derivative`

platform creates a sensor that estimates the derivative of the values provided by a source sensor.
Derivative sensors are updated upon changes of the **source**.

## Configuration

To enable Derivative Sensor in your installation, add the following to your `configuration.yaml`

file:

```
# Example configuration.yaml entry
sensor:
- platform: derivative
source: sensor.current_speed
```

### Configuration Variables

Round the calculated derivative value to at most N decimal places.

Metric unit to prefix the derivative result (Wikipedia). Available symbols are “n” (1e-9), “µ” (1e-6), “m” (1e-3), “k” (1e3), “M” (1e6), “G” (1e9), “T” (1e12).

SI unit of time of the derivative. Available units are s, min, h, d. If this parameter is set, the attribute **unit_of_measurement** will be set like x/y where x is the unit of the sensor given via the **source** parameter and y is the value given here.

Unit of Measurement to be used for the derivative. This will overwrite the automatically set **unit_of_measurement** as explained above.

## Temperature example

For example, you have a temperature sensor `sensor.temperature`

that outputs a value every few seconds, but rounds to the nearest half number.
That means that two consecutive output values might be the same (so the derivative is `Δy/Δx=0`

because `Δy=0`

!)
However, the temperature might actually be changing over time.
In order to capture this, you should use a `time_window`

, such that immediate jumps don’t result in high derivatives and that after the next sensor update, the derivatives doesn’t vanish to zero.
An example configuration that uses `time_window`

is

```
sensor:
- platform: derivative
source: sensor.temperature
name: Temperature change per hour
round: 1
unit_time: h # the resulting "unit_of_measurement" will be °C/h if the sensor.temperate has set °C as it's unit
time_window: "00:30:00" # we look at the change over the last half hour
```

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