This article describes the possibility to hide some of the columns defined in the grid. This way, you can show different columns to the user, depending on what you want.
For example, if the user has said there was partner, you can show the column ‘income partner’, but if there is no partner, you can hide that column.
This article describes at a (very) technical level how the servers handles datasets. Datasets can hold a lot of data, making working with them sometimes a bit slow. By understanding what datasets are and how the server handles them, the author can make a model much less memory and CPU heavy.
This article describes some of the functions you can perform on datasets. All these functions can also be found in the Finder. For convenience, we split this section in the general and more advanced functions. If you do not know how formulas and/or functions work, please see introduction to formulas and introduction to functions from the guided tour or formulas for extra explanation.
In the sections Introduction to datasets up to and including Using the dataset III datasets are discussed and the basics applications are explained. This section deals with datasets that have a more complicated structure, and it is therefore advisable to have a good understanding of them. Reading the model structure page also helps.
In the sections Introduction to datasets up to and including Using the dataset II we created a model that will be used here. If you haven’t done these, it is highly recommended to do so.
When you have an empty grid in your model, upon which your end users
can add (or remove) rows, it can sometimes be useful to automatically
generate one or more rows. In this tutorial, you will learn how to
force just that.
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.
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.
To create the dataset briefly described in the introduction on datasets, first create a new model. In this model, add a node ‘add_dataset’ to our model. In this node, we will create our first dataset. To start, click [Actions > Dataset] to open the dataset window. The following screen will pop up:
In the Berkeley Studio you can make use of datasets. Generally speaking, a dataset is a collection of structured data. Most people are more or less familiar with datasets as they appear in spreadsheet software, like Microsoft Excel. For example, consider the following example in Excel:
This section uses the model created in the first, the second and third step of the dataset tutorial. If you did not do them you can do them first or use your own model with a dataset.
