Build a Quick Bar Chart in IBM SPSS Modeler

To improve your experience using IBM SPSS Modeler, the Version 1 SPSS experts have created various Tech Tips. This Tech Tip shows how to build a quick bar chart in IBM SPSS Modeler. 

IBM SPSS Modeler is an extensive predictive analytics platform designed to bring predictive intelligence to decisions made by individuals, groups, systems, and the enterprise. Modeler has an easy-to-use drag-and-drop user interface with a complete set of tools for accessing data, data examination, preparation, modelling, evaluation, and deployment.  

IBM SPSS Modeler users have a complete toolset to build predictive models from start to finish. Modeler uses node-based, visual programming. Users pick nodes from palettes and place them on the stream canvas. Once nodes have been placed on the stream canvas and edited, they can be linked to form a stream. A stream represents a flow of data through several operations (nodes) to a destination that can be in the form of output (either text or chart), a model, or the export of data to another format (e.g., a database).  

When building models, data examination is critical. Users can use the View Data option to examine data and quickly create visualisations. To start, right-click on a node in Modeler and select View Data. View Data opens a dashboard where users can create graphs, examine data in a spreadsheet, audit data, and use dashboard options.  

For example, we want to explore the relationship between income level and credit rating. Select the Bar Chart, select income level as the Category Variable, and order based on category value or name. Select Category Order as Descending and ask for Count. We can also split the bar chart by Credit Risk. Hovering your cursor over each bar gives information on credit risk in each income category. Users can download the image by selecting the Save as Image button to the right of the picture. The View Data option allows users to examine data and relationships between variables at any point in the model-building process.