Skip to main content

Create data frames

The data frame is a columnar data structure that allows for efficient querying of large amounts of data. Since data frames are a central concept when developing data source and other plugins for Grafana, in this guide we'll look at some ways you can use them.

The DataFrame interface contains a name and an array of fields where each field contains the name, type, and the values for the field.


If you want to migrate an existing plugin to use the data frame format, refer to Migrate to data frames.

Create a data frame

If you build a data source plugin, then you'll most likely want to convert a response from an external API to a data frame. Let's look at how to do this.

Let's start with creating a simple data frame that represents a time series. The easiest way to create a data frame is to use the toDataFrame function.

// Need to be of the same length.
const timeValues = [1599471973065, 1599471975729];
const numberValues = [12.3, 28.6];

// Create data frame from values.
const frame = toDataFrame({
name: 'http_requests_total',
fields: [
{ name: 'Time', type: FieldType.time, values: timeValues },
{ name: 'Value', type: FieldType.number, values: numberValues },

Data frames representing time series contain at least a time field and a number field. By convention, built-in plugins use Time and Value as field names for data frames containing time series data.

As you can see from the example, to create data frames like this, your data must already be stored as columnar data. If you already have the records in the form of an array of objects, then you can pass it to toDataFrame. In this case, toDataFrame tries to guess the schema based on the types and names of the objects in the array. To create complex data frames this way, be sure to verify that you get the schema you expect.

const series = [
{ Time: 1599471973065, Value: 12.3 },
{ Time: 1599471975729, Value: 28.6 },

const frame = toDataFrame(series); = 'http_requests_total';

See also