You can remove the field filter to get all your fields.
Here you go:
myField = from(bucket: "Air sensor sample dataset")
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "airSensors")
|> filter(fn: (r) => r["_field"] == "co")
|> filter(fn: (r) => r["sensor_id"] == "TLM0100")
|> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
|> findRecord(fn: (key) => true, idx: 0)
data = from(bucket: "Air sensor sample dataset")
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "airSensors")
|> filter(fn: (r) => r["_field"] != "co")
|> filter(fn: (r) => r["sensor_id"] == "TLM0100")
|> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
data
|> map(fn: (r) => ({ r with muyfield: string(v: myField._value)}))
|> set(key: "_measurement", value: "my_new_measurement")
|> to(
bucket: "my-bucket",
org: "my-org",
timeColumn: "_time",
tagColumns: ["myfield", "sensor_id"]
)
You don’t have to include the tagColumns as all columns with string values will default to tags, but you can define them explicitly.