Calculate a weekly mean
This example uses NOAA water sample data.
This example calculates a temperature weekly mean and stores it in a separate bucket.
The following query:
- Uses filter() to filter the
average_temperature
measurement. - Uses range() to define a time range.
- Uses aggregateWindow() to group average temperature by week and compute the mean.
- Sends the weekly mean to a new bucket (
weekly_means
)
option task = {name: "weekly-means", every: 1w}
from(bucket: "noaa")
|> filter(fn: (r) => r._measurement == "average_temperature")
|> range(start: 2019-09-01T11:24:00Z)
|> aggregateWindow(every: 1w, fn: mean)
|> to(bucket: "weekly_means")
Example results
_start | _stop | _field | _measurement | location | _value | _time |
---|---|---|---|---|---|---|
2019-09-01T11:24:00Z | 2020-10-19T20:39:49Z | degrees | average_temperature | coyote_creek | 80.31005917159763 | 2019-09-05T00:00:00Z |
2019-09-01T11:24:00Z | 2020-10-19T20:39:49Z | degrees | average_temperature | coyote_creek | 79.8422619047619 | 2019-09-12T00:00:00Z |
2019-09-01T11:24:00Z | 2020-10-19T20:39:49Z | degrees | average_temperature | coyote_creek | 79.82710622710623 | 2019-09-19T00:00:00Z |
_start | _stop | _field | _measurement | location | _value | _time |
---|---|---|---|---|---|---|
2019-09-01T11:24:00Z | 2020-10-19T20:39:49Z | degrees | average_temperature | santa_monica | 80.19952494061758 | 2019-09-05T00:00:00Z |
2019-09-01T11:24:00Z | 2020-10-19T20:39:49Z | degrees | average_temperature | santa_monica | 80.01964285714286 | 2019-09-12T00:00:00Z |
2019-09-01T11:24:00Z | 2020-10-19T20:39:49Z | degrees | average_temperature | santa_monica | 80.20451 |