Once GeoFlow is finished plotting you can start aggregating the data. For example, you can drag Actual Price into the Height field to see bars representing the sum of tickets sold in each zip code as shown below. How to prepare your data for visualizing in GeoFlow For best results with GeoFlow, the data should be organized in an Excel table or in a PowerPivot Data Model. For example if your sales data is in an aggregated PivotTable format, you will want to go back to the actual data or table used to create the PivotTable. Here’s why: While a PivotTable aggregates the total sales or instances of sales for regions, GeoFlow can leverage each instance of a sale as a point in time, animate it over time, and also plot it in the exact spot. Similarly, aggregations done geographically in a PivotTable (for example, cities across a state, states across a country, or countries across a region/continent) can now be detailed on a GeoFlow map that retains the same granular level of detail. NOTE: GeoFlow exclusively uses the Vertipaq/xVelocity engine in Excel as its data source. Any data that is added into Vertipaq will be accessible to GeoFlow. GeoFlow can only work with Excel’s Data Model – it cannot connect to external servers. In addition, GeoFlow does not support hierarchies in the Data Model To get external data into the Data Model in Excel, click Data > the connection you want in the External Data group, and then follow the steps in the Data Connection Wizard, making sure you check the option to use the Data Model in Excel on the last step. All data has to be in English. Working with non-aggregated data doesn’t always show you data quality issues, such as typos and inaccurate data. In some cases, it is good to question the quality of the data GeoFlow has plotted. This may result in some iterative data-cleansing work to be done before you refresh your data and run your exploration in GeoFlow again. Note that you can refresh the data model from the GeoFlow ribbon. You can add tables or ranges to the model from the GeoFlow split button under Insert tab in the Excel ribbon.
Now, change the Chart Type from Column to Heat Map using the Chart Type drop down list. Heat maps animate through time, the same as the other chart types supported by GeoFlow. When switching the chart type from Columns to Heat Map, the Height field changes to Value. Visualizing negative, null, and zero values GeoFlow supports visualizing negative, null, and zero values. The following visualization can be created for this simple table: City Value Date Seattle 3 1/2/2009 Portland -7 1/5/2009 Tacoma -2 1/5/2010 Seattle 3 1/2/2010 Portland 4 1/5/2011 Tacoma 5 1/5/2011 Edmonds 0 1/5/2011 You can see the zero value for Edmonds, WA as a hollow square next to the taller column which is Seattle. You can see the negative value -7 for Portland, OR on 1/5/2009 as a visual which is shown below the surface in this screen shot. NOTE: Zero values and Null values are visualized in the same way. You can turn on null, zero and negative values in the Layer Manager settings task pane. You can access Layers and their settings by selecting the layer manager and then clicking on the settings icons which correspond to different layers.