Interleave two influx tables to create one plot

[James-O2]

I have two queries that are each creating a table. Since I am querying the max & min of the same field I know table A will not contain any entries with the same timestamp as any entry in table B & vice versa.

The two tables are plotted as two traces, but I’d like them plotted as one trace as shown by this yellow line:

is there a way I can interleave the two results so they can be plotted as one table

[James-O2]

from(bucket: “gomboc”)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r[“_measurement”] == “20220527-164812/002/”)
|> filter(fn: (r) => r[“_field”] == " … Area")
|> window(every: 1s)
|> max()
|> window(every: inf)
|> yield(name: “max”)

from(bucket: “gomboc”)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r[“_measurement”] == “20220527-164812/002/”)
|> filter(fn: (r) => r[“_field”] == " … Area")
|> window(every: 1s)
|> min()
|> window(every: inf)
|> yield(name: “min”)

[Jay_Clifford]

Hi @James-O2 welcome to the community! Have you considered using the band visualization to achieve this? Here is an example with my data:

raw = from(bucket: "generators")
  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
  |> filter(fn: (r) => r["_measurement"] == "genData")
  |> filter(fn: (r) => r["generatorID"] == "generator1")
  |> filter(fn: (r) => r["_field"] == "fuel")
  |> yield(name: "raw") 

  

mean = raw  
  |> aggregateWindow(every: 1m, fn: mean, createEmpty: false)
  |> yield(name: "mean")

max = raw  
  |> aggregateWindow(every: 1m, fn: max, createEmpty: false)
  |> yield(name: "max")  

min = raw  
  |> aggregateWindow(every: 1m, fn: min, createEmpty: false)
|> yield(name: "min")