Yes, a CSV file.
Would you like to share any more information about the system infrastructure which provided the sensor data? Are any special data processing systems involved there?
Would you like to perform any advanced time series analysis? https://en.wikipedia.org/wiki/Time_series
I want to look at the data to see if anything stands out and keep it for future analysis of my house's performance.
Thanks for such background information. Are you looking for trend displays?
Whether any of that counts as 'advanced' I do not know.
Would you like to get informed about extraordinary value distributions?
How do you think about to combine these fields in a data preparation step so that extra formulas could be avoided?
I think I shouldn't need to worry about stuff like this.
If you care for efficient (and considerably fast) data processing, corresponding development considerations are an usual consequence, aren't they?
In fact the data in the CSV file was a DATETIME,
Does this data format get automatically recognised by the used software?
but I couldn't figure out whether it was possible to import that to LO in a sensible way,
Did you get additional experiences on this detail?
so I added space to the separators and split it into two fields so the DATE format could cope.
Would you like to see an other adjustment approach at this place?
The data amount is also interesting.
In what way?
You observed surprisingly long data processing durations for diagram generation here, didn't you? The data size growth will trigger to reconsider analysis approaches, won't it?
Would you like to filter such records any more for your needs?
I don't know.
* Do you need to drill down into a time range? * Which conditions will become relevant for occasional data exclusion?
Will it help to store computation results into corresponding aggregate tables? https://en.wikipedia.org/wiki/Aggregate_(data_warehouse)
Err, I shouldn't need to think about any of this.
Other users came along similar software situations already. Dedicated data structures will provide special benefits so that available application knowledge is reused in easier ways.
The software tool should handle it competently.
Specific tools might support a more convenient way.
I'm not sure what you're suggesting. You mean the LO CSV import should be able to discard some columns?
Which tool would be more appropriate for data cleaning operations? How do you think about to split adjustments in the work flow?
https://help.libreoffice.org/6.1/en-GB/text/schart/01/wiz_chart_type.html
A line chart is the wrong type. LO requires me to select XY. The tool should either give me better help or automatically select the chart type better based on the data.
Would this situation motivate you to improve the program documentation?
Would you need outlines here? https://help.libreoffice.org/6.1/en-GB/text/scalc/01/12080000.html
I don't think so, I just want to be able to temprarily hide some of the lines representing individual data sets.
Would you like to explain corresponding constraints?
How helpful do you find the alternatives? https://en.wikipedia.org/wiki/List_of_charting_software https://en.wikipedia.org/wiki/List_of_statistical_packages
The lists aren't terribly helpful. Lists of time-series software are closer, but still no banana. Pretty much all assume that the graph is a final output of some carefully crafted process, whereas I see it as an initial attempt to view some data that I should be able to change on the fly (zoom time, hide datasets, integrate/differentiate etc).
Are you looking for more data mining and monitoring capabilities?
I had decided instead to import the CSV data into my emoncms system, which has a graph module that is much more functional and performant. But I've now learned of InfluxDB and Graphana, which may be interesting.
Is there any healthy competition evolving because of these tools? Regards, Markus -- To unsubscribe, e-mail: opensuse+unsubscribe@opensuse.org To contact the owner, e-mail: opensuse+owner@opensuse.org