Time Series Data Table for Multiple Attributes

Time Series Data Table for Multiple Attributes

A Time Series Data Table is a table capable to display the time series values of an attribute within the Pi Vision time bar time range.

PI Vision doesn't have a native Time Series Data Table symbol. A custom symbol for this purpose.

OSIsoft used to have an official GitHub with several supported custom symbols, but this GitHub is not online anymore. The OSIsoft GitHub used to have a time series table that could be used as a code base for developers to develop their own custom symbols.

The most noticeable improvement of the Time Series Data Table for Multiple Attributes Custom Symbol shown in this article is the ability to handle multiple attributes. It is possible to display multiple attributes, with multiple timestamps and the symbol will place empty strings "" on the eventual values for timestamps that are not present on all Attributes.

No alt text provided for this image

The image displays the "Pressure" attribute and "Pressure2" attribute. It is possible to notice that "Pressure2" has fewer values than "Pressure". When combining the two attributes the Custom Symbol adds blanks to "Pressure2" correspondent timestamps.

The Time Series Data Table for Multiple Attributes Custom Symbol presented in this article can be downloaded at: https://github.com/pscampos/timeseriesdatatable

The Time Series Data Table on this article is based on jefftwhite code?https://github.com/PIVisionSymbols/Datatable

Paola Casabona

Ingeniera Electrónica | CIP | SMPC? | Ciencia de Datos

7 个月

?Excelente aporte! Muchas gracias

回复
Claude Martineau-Boucher

Lead Data Historian Engineer

1 年

This is exactly what I am looking for. However, I see that when too many events are to be displayed, then the table is not able to show them all. Timestamps are displayed, but not the values. As an example, if Sinusoid and Sinusoidu are added to the table and the table displays 8 hours of data, then everything is shown. If the display is changed to 24 h, then the table mostly displays empty values.

Gregor Vilkner, Ph.D.

Digital Transformation | TimeSeries + Graph DB | Data Visualization | BIM | DCIM | Industry 4.0

2 年

This is good stuff and a very fundamental time series analytics capability. It is also the underlying requirement for doing xy correlations and scatter charts. Do you accommodate different interpolation rules to fill in blanks?

Edivaldo Junior

Automation Engineer | Aveva PI System consultant | SEEQ | Digitalization Enthusiastic

2 年

Great post!

Steve Taylor

Digital Solutions Specialist | PI AF Project Coach

2 年

Such a simple but powerful idea. Thanks for sharing!

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