Grafana's "wide tent" philosophy means we want Grafana to work with our users' data, and not make our users work to use Grafana. The data frame structure is a concept borrowed from data analysis like R and Pandas to allow us to do this.
Data frames allow users' data to be more accurately represented and with less effort.
- The data binding throughout Grafana's is now shared. Data moved between Grafana's backend plugins, Grafana server, and frontend is now less destructive. The means there is less data munging and more supported data types such as time, nullable types, various number types and other primitives.
- Time series data can be returned in different shapes that match those more commonly found.
- Time series and table data now exist in the same structure.
- Tables exist in the same structure as time series.
Data frames allow for transformations.
- Since Data frame fields contain type information, we use that information to allow users to be able to transform their data.
Data frames allow for data driven visualization through metadata.
- Data frames can contain metadata bound to the data that (such as Units, scaling, etc) that can provide information for visualizations.