Visualisation for interval datatypes (continous data) without modifications like average

[gregers1972]

Hey,

I am currently working on a data set of interval data with a corresponding date as shown below:

The are more parameter and values than shown and I need a visuel representation of the actual values (not average, max, sum etc.).

Are anyone aware of such an add-on to BI?, thanks

VarName	TimeString	VarValue
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00	9913
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00	2628
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00	3184
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00	9799
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00	2623
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00	3216
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00	9340
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00	2623
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00	3120
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00	9307
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00	2623
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00	3088
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00	9536

[gregers1972]

The datatable was not so easy to read properly, now a better version

VarName	TimeString		VarValue
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9913
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00		2628
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00		3184
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9799
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00		2623
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00		3216
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9340
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00		2623
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00		3120
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9307
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00		2623
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00		3088
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9536
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00		2618
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00		2880
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9176
Melt temperature in front of melt filter - [Actual Value DB.melt_temp_in_front_of_mf]	03/05/2022 14:00		2614
Meltpressure in front of melt filter - [Actual Value DB.pressure_in_front_of_mf]	03/05/2022 14:00		2864
Load extruder [%] - [Actual Value DB.load_extruder]	03/05/2022 14:00		9225

[Anonymous · Accepted solution]

Hi @gregers1972 ,

According to your statement, I think you want to show all data instead of summarizing the data like sum ,max or average in visual.

Here I suggest you to try Don't summarize function in value field in your visual.

Best Regards,
Rico Zhou

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[gregers1972]

Thanks, I already did this however it only works in table format and not in line charts and cannot use the XY plot as I have date and time on the x-axis.

Anyhow, thanks for you valued input 🙂