# Timeseries: Simple Use Case

**URL:** <https://scilab.discourse.group/t/timeseries-simple-use-case/253>\
**Category:** Data handling\
**Created:** [November 22, 2023, 2:03pm UTC](https://scilab.discourse.group/t/timeseries-simple-use-case/253 "2023-11-22T14:03:44Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![david](https://avatars.discourse-cdn.com/v4/letter/d/aeb1de/32.png) [@david](https://scilab.discourse.group/u/david)\
**Post date:** [January 3, 2024, 5:32pm UTC](https://scilab.discourse.group/t/timeseries-simple-use-case/253/2 "2024-01-03T17:32:59Z")

</div>

Hello,  
I’ve been evaluating a few functions and properties around timeseries new features: the test case is to get data from a .csv typical test file downloaded from french DSO enedis for residential power meter “Linky”, as illustrated below.  
The data range is about 2 years, of hourly power consumption records (some irregular sample times here and there).

> Identifiant PRM;Type de donnees;Date de debut;Date de fin;Grandeur physique;Grandeur metier;Etape metier;Unite;Pas en minutes  
> 12345678909876;Courbe de charge;11/01/2022;01/01/2024;Energie active;Consommation;Comptage Brut;W;  
> Horodate;Valeur  
> 2022-01-11T01:00:00+01:00;278  
> 2022-01-11T02:00:00+01:00;1462  
> 2022-01-11T03:00:00+01:00;1501  
> 2022-01-11T04:00:00+01:00;601  
> 2022-01-11T05:00:00+01:00;344  
> 2022-01-11T06:00:00+01:00;365  
> 2022-01-11T07:00:00+01:00;594  
> 2022-01-11T08:00:00+01:00;518  
> 2022-01-11T09:00:00+01:00;412  
> 2022-01-11T10:00:00+01:00;378  
> 2022-01-11T11:00:00+01:00;520  
> 2022-01-11T12:00:00+01:00;431  
> 2022-01-11T13:00:00+01:00;474  
> 2022-01-11T14:00:00+01:00;418  
> 2022-01-11T15:00:00+01:00;395  
> 2022-01-11T16:00:00+01:00;289  
> 2022-01-11T17:00:00+01:00;264  
> 2022-01-11T18:00:00+01:00;372  
> 2022-01-11T19:00:00+01:00;309  
> 2022-01-11T20:00:00+01:00;404

I first tried to detect the import option automatically (as `readtimeseries()` with no options ) but it failed because of the header structure, with some irregular introductive lines in the beginning of files until the real regular data:

```auto
dummyfile= "TMPDIR\Enedis_Conso_Heure_20220111-20240101_12345678909876.csv"
opts= detectImportOptions(dummyfile)

```

it fails :

> Attention : Une incohérence a été trouvée dans les colonnes. À la ligne 2, 2 colonnes ont été trouvées, alors que la précédente en avait 9.  
> à la ligne 64 de la fonction detectImportOptions ( C:\Program Files\scilab-2024.0.0\modules\spreadsheet\macros\detectImportOptions.sci ligne 75 )  
> csvTextScan: can not read file, error in the column structure

then I created manually import structure : several attempts required to properly set the details of the fields ‘header’ and ‘inputFormat’ (help page could be refined with more exotic test cases here I guess. or improvement of autodetect header file) :

```auto
opts= struct("variableNames", ["Horodate","Valeur"],"variableTypes", ["datetime","double"],"delimiter", ";","datalines", [4,33448],"header", ["Identifiant PRM;Type de donnees;Date de debut;Date de fin;Grandeur physique;Grandeur metier;Etape metier;Unite;Pas en minutes"
"12345678909876;Courbe de charge;11/01/2022;01/01/2024;Energie active;Consommation;Comptage Brut;W;"
"Horodate;Valeur"],"inputFormat","yyyy-MM-ddTHH:mm:ss+","emptyCol",[])
ts= readtimeseries(dummyfile,opts)

```

which ran successully, except the current limitation (warning is properly issued) to manage UTC and daylight saving time information in datetime : then everything behind the ‘+’ in inputformat, the ‘+01:00 or +02:00’ information is not used to obtain true local time : this may be also indicated in the help page.

> ATTENTION : UTC/GMT format is not managed. The result does not take it into account.  
> ts =  
> …  
> 33445x1 timeseries  
> Horodate Valeur  
> … \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ \_\_\_\_\_\_  
> …  
> 2022-01-11 01:00:00 278  
> 2022-01-11 02:00:00 1462  
> 2022-01-11 03:00:00 1501  
> … …  
> 2023-12-31 23:00:00 144  
> 2023-12-31 23:30:00 126  
> 2024-01-01 00:00:00 152

Then i tried the timeseries plot feature

```auto
stackedplot(ts)

```

it’s fine to get basic outlook of the whole data but the lack of callback function to set automatically the x\_ticks with properly formatted datetime information according to the level of zoom prevent any real practical interpretation of this plot:

 ![image](https://global.discourse-cdn.com/free1/uploads/utc/original/1X/3eab96033d53cd791e198a8ca3da07fcb41e91af.png)  
Then I suggest that the [Simple date and time plotting on x-axis](https://scilab.discourse.group/t/simple-date-and-time-plotting-on-x-axis/169) is still an issue to work on in the next Scilab releases.

Thank you for the discussion and the developments already performed!

David

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