Defining new conditions

Use conditions to filter and enhance your data. Conditions are parts of data that you interactively select. Alternatively you can define a condition through a formula. Finally, you can visualize and export your conditions for further use, as well as use them during your analysis.

Intro new condition process

Preparation (to follow this lesson using demo data)

For the tutorial, load the solar power demo dataset from the welcome dialog, as shown below.   

Naming a selection

In case you want to "keep" a relevant selection you can save it as a category. This allows you to load it as your focus again at a later time (and more).

1. Select the time series "Temperature_Outdoor_BrightCounty_Weather" in the "Statistics" view by clicking on its name.

2. Then select the "vertical 1D interval brushing mode" as "selection mode" in the "Time Series" panel menu

Preparation before naming a selection

1. Perform an interval selection in the "Time Series" panel by drawing a box.

2. Refine the selection if you want by clicking on the selection next to the focus (alternatively click on the gear button next to the selection).

3. Create a named condition and enter the name "Below 2°C" in the following dialog.

Name a selection

Note: you can create a condition from any selection (also in the other panels). This selection can also be options within a category, or for example using the lasso selection in the scatter plot as shown below.

Naming outliers with a free selection

Use the lasso selection to select and name outliers quickly.

1. Clear your focus. Notice that your category will still be available and can be used to get the cleared focus back.

2. Select "Solar_Radiation_Happyville_Weather" and use the tickbox to also select "Power_Generation_Happyville_PV" (it is helpful to use the filter "happy power or happy solar").

3. Open the scatter plot, select the "lasso brushing mode" and perform a lasso selection as shown below.

4. Name condition as "Unexpected operation" (we don't expect PV production without corresponding solar irradiation!)

5. Optionally zoom in to "Time Series" with right mouse button in highlighted areas to see what is going on in detail.

Use lasso selection to highlight unexpected operation

Defining conditions with min/max duration

If you want to remove short periods or individual data points in your condition that are not of interest to you, you can restrict your condition with a min/max duration. In the following example we only want to see periods where the temperature was below 2°C for longer than one hour.

1. Make sure you have only "Below 2°C" in your focus. If you do not, clear your focus, click on the category "Below 2°C" and select "Put in Focus".

2. Create a new named condition called "Long below 2°C".

3. Select the advanced function of defining a minimum duration of 1 hour. You will see how the individual data points from the previous selection disappeared and one longer period remains.

Naming a condition with minimum duration.

Defining conditions from a formula

Use a formula to select/label subsets of your data records. Think of it as scripting a (database) query, like "select all data where time series X is below time series Y", for example. Then, these conditions can be used in the analysis - for example, to see how often the condition occurs, and how it is distributed across categories or time.

Select the time series "Pressure_BrightCounty_Weather" and add the second time series "Pressure_Happyville_Weather" by using the checkbox. Then, click "New condition" in the toolbar:

Create scripted condition

The shown dialog can be used in the same way as the dialog for creating new data attributes. The only difference is that the output here is a boolean (= logical, or binary) array, and not a numerical or categorical one.

In the "Script" field, type: result = i_1 > i_2

Confirm with "Compute"/ "OK". In the following dialog give it a shorter name, like "BrightCounty > Happyville", and confirm with "OK".

Formula to create scripted condition.

Visplore then shows the condition in the upper area as an orange shape:

Scripted condition in GUI

Finally, we want to see how often this condition occurs:

Click the orange shape of the condition we just created, then choose "Put in focus".

Put scripted condition into focus

Now, the times where the condition is fulfilled are in focus. We see in the footer bar of Visplore, that this only happens at 5 timestamps, corresponding to 50 minutes of the data. The "Time series" view highlights these points.

Line plot with scripted condtion highlighed

Zoom in to these points in the "Time Series" view by dragging a rectangle around them with the right mouse button, to inspect this rare case in detail (see image above).

It appears, this is a rare condition appearing due to a data artifact rather than in a plausible way.

Zoom into highlighed line plot

You can also dynamically edit the script of a condition. Click the orange shape of the condition Icon edit condition, and choose "Edit / rename". This allows for dynamically querying your data, and seeing in real-time how often it occurs, how it distributes, etc.

You can change the script of a computed data attribute later on. For example, if you discover you made a mistake in the formula, or you want to tweak some parameters based on what you saw in the visualization. For editing refer to the chapter Computing new data attributes.

Conditions as 1/0 variable

You can add a condition also as a variable. This allows you to plot and export conditions like any other variable. Note that these conditions are a little different as they contain values of either 1 (for true) and 0 (for false).

Click on your condition "BrightCounty > Happyville" and choose "Add as variable".

Add condition as variable.

Characters such as “<” and “>” are not allowed to be part of a variable name. As such they will be removed. Please adjust your naming in this case using the edit button Icon edit. Here we renamed the condition to "BrightCounty larger than Happyville".

Add "BrightCounty larger than Happyville" using the check box to see the variable indicating either 0 or 1 in the "Time Series" plot.

Add condition as variable plot.

When you save your session, all the created data attributes and conditions are kept, so that you can apply the same analysis again when you get new data. By adding a condition as a variable, you can also export them as csv.

Now you know how to use conditions to filter and refine your data through the use of selections or formula. Also you can export your conditions

License Statement for the Photovoltaic and Weather dataset used for Screenshots:
"Contains public sector information licensed under the Open Government Licence v3.0."
Source of Dataset (in its original form):
License: UK Open Government Licence OGL 3:
Dataset was modified (e.g. columns renamed) for easier communication of Visplore USPs.