Drilldowns are an important UX element of any reports and dashboards. SQL Frames
provides several charting features like multi-series, multi-axis, multi-lod (levels of detail), static and dynamic grid charts. However, the ability to drilldown has been missing. But today, I am pleased to announce that has changed with the introduction of the drillpath API to SQL Frames, a low-code data, visualization and intelligence platform for the browser.
Pivot tables and Sparkline charts have something in common. Both can show a column transformed view of data. Sparklines have the additional advantage of using less space. However, they also have the disadvantage that they only show the outline of the data due to smaller space. When done incorrectly, sparklines lead to incorrect decision making and bad user experience. This article provides the details of how SQL Frames implemented Sparkline charts to take care of both correctness and performance.
One of the design goals of SQL Frames is to make integrated UI components that are able to leverage the underlying DataFrame data model. Charts is considered as a key UI component for visualizing the data stored in the DataFrames. While evaluating to pick the right charting library one clearly stood out. It is Apache ECharts.