This section uses the model created in the first and the second step of the dataset tutorial. If you did not do them you can do them first or use your own model with a dataset.
The first step we need to take before we can take a look at our dataset is adding a node. We add a node after our node ‘add_dataset’ called ‘done’. In it, add some text and we’re done. Now, save and run your model! When you arrived at the ‘done’ node, click
[File > Data Inspector] or press
[F11]. This will show the data inspector:
To the left the data inspector will show four nodes: the three you can see in the Berkeley Studio (start, add_dataset and done) and one to create the dataset. In the top-right you can see the contents of each node (see debugging for more information). The most important node right now is ‘add_dataset’ and is selected in the picture above. It contains our dataset ‘ds_employee’! If you doubleclick the dataset and select the ‘tree’ tab, the following screen will appear:
As you can see, this is the data we entered in row 1 of our dataset! From here we can see the full structure of our dataset. We have a graph of the type ‘employee_data’ with a node ‘data’. The node ‘data’ then has all six variables we gave it (first name, last name and so on). Each row in our dataset is presented by a different ‘iteration’ of our graph. This can be seen by the #0, #1, #2 and so on after each employee_data. Lastly, we can see that there is also a field ‘visible’ when this is set to false we can toggle these tuples with the checkbox in the top right. When this checkbox is checked the invisible fields will not be shown in your tree.
Viewed in our Excel spreadsheet, you can access the data this way:
You might wonder why the rows in our Excel spreadsheet differ from our dataset iterations - for example, Hank is in row 2 in Excel and is iteration 0 in the Berkeley Studio. This is because datasets in the Berkeley Studio always start at 0. Furthermore, you may notice that the Berkeley Studio added a node ‘data’ in our dataset. Because each variable needs a node and we did not specify one when creating the dataset, the Berkeley Studio added one itself.
In the next section we will finally use our dataset!