CARTO Builder is becoming the easiest tool to predict and discover insights behind your location data. Making decisions using data-driven maps means more than just visualizing points or polygons. After plotting data in your maps, the real analysis begins as you employ widgets to visualize information in different ways and calculate aggregated values for particular areas.
Widgets are an integral part of CARTO Builder’s experience and workflow. Not only do widgets filter data but they also update the styling of that data and initiate analysis. At their core, widgets allow users to question their data further and discover answers more readily with modules that can visualize, aggregate, and filter data. These intuitive modules can be used in many different ways by either clicking on the widgets tab, or by clicking on the different columns that appear under the data tab on each one of your layers. The widget results will reflect the data you see in the current bounding box view.
Users can customize their apps with CARTO Builder to filter data through:
- Formula Widgets calculate aggregated values from numeric columns in AVG, MAX, MIN, SUM, and COUNT - support for text columns is on it’s way!
- Histogram Widgets can examine numerical values within a given range distributed across your data map.
- Category Widgets allow users to ask different context-based questions of a dataset.
- The Time Series Widget allows you to set a temporal parameter upon your data to display across time.
Another very powerful feature of the Widgets is the auto-style button - which you can identify by the drop icon in the top right of the Widget. Select auto-style to apply a new temporary color ramp to the widget data. This is useful for better visualizing the widget results. As you continue to filter your data by using widgets, the color scheme applied during the auto-styling will be maintained as the map recalculates and renders based on the parameters you set with the widgets.
Adding widgets to your maps opens up the possibility for exploring your data in a new way, in addition to providing insights that facilitate predictive analysis. The user experience is characterized by a unique, new level of engagement and interactivity with the data while continuing to function quickly and efficiently.
Now, finding the highest value in an area, for example, when looking at filtered data, is only a few clicks away!
Let us know what you come up with. We would love to see it!