Vue ChartsLine Series

The Line series is a good choice when you need to spot a trend, render large amounts of data or create a real-time chart. Line series is also the preferred choice for rendering continuous data with irregular intervals or incomplete data that has some values missing.

Single Series

Since the 'line' series type is so common, it doesn't have to be specified explicitly. The chart factory method, AgChart.create, uses it as the default type.

The simplest line series config therefore only requires two properties, xKey and yKey:

series: [{
    // type: 'line' <-- assumed
    xKey: 'year',
    yKey: 'spending'
}]

The chart expects the data (chart.data property) to be an array of objects, where each object is a table row or a database record and each key is a column.

To plot anything on a plane, we need at least two coordinates: x and y. The xKey and yKey series configs tell the series which keys should be used to fetch the values of these coordinates from each object in the data array.

Showing labels on top of data points is also an option with the label config. Labels can be enabled independently of series markers. For example, to show bold labels on top of each data point (and in this case a marker) we would use the following config:

series: [{
    ...
    label: {
        enabled: true,
        fontWeight: 'bold'
    }
}]

The above config is used in the example below. Feel free to open it in Pluker and experiment with other label options.

Multiple Series

If we have more than two fields inside each object in the data array, we can create a multi-series line chart. For example, if a datum looks like this:

{
    quarter: 'Q1',
    petrol: 200,
    diesel: 100
}

We can use the same quarter key as xKey for both series and petrol and diesel keys for yKey of the first and second line series, respectively.

To create multiple line series we need to provide two config objects in the series array:

series: [
    {
        xKey: 'quarter',
        yKey: 'petrol'
    },
    {
        xKey: 'quarter',
        yKey: 'diesel'
    }
]

And we get a result like this:

Legend and Tooltip Information

By default the legend shows the keys used to fetch the series data, but those may not be very presentable. In our case, the petrol and diesel keys inside the data objects are not capitalised. We can provide a better display name using the yName config, and the legend will show that instead.

series: [
    {
        xKey: 'quarter',
        yKey: 'petrol',
        yName: 'Petrol'
    },
    {
        xKey: 'quarter',
        yKey: 'diesel',
        yName: 'Diesel'
    }
]

The provided yName will also show up in tooltip titles:

Line and Marker Colours

The chart above is not complicated, but it could still benefit from more visual separation. Let's make the diesel series look more like diesel. Just add the following two configs to the second series:

stroke: 'black',
marker: {
    fill: 'gray',
    stroke: 'black'
}

We'll get a result like this:

There are many other customisations you can make to the markers; see the markers section for more information.

Missing Data

In a perfect world all data would be 100% complete. Unfortunately, in the real one, data for certain items or time periods might be missing or corrupted. But that shouldn't result in corrupted charts, and AG Charts supports the correct rendering of incomplete data:

If the yKey value of a data point is positive or negative Infinity, null, undefined or NaN, that data point will be rendered as a gap.

If the bottom axis is also continuous (for example, if it's a 'number' axis too), rather than being rendered as a gap, invalid xKey values from the data will be skipped all together.

Continuous Data

By default, the bottom axis is a 'category' axis, but this can be changed if you have continuous data that you would like to plot. See the axes section for more information on configuring axes.

Time-Series Data

The following example shows how line series can be used to render time-series data, using a 'time' axis. In this case, we have two ambient temperature sensors that give us two independent data sets, with different numbers of readings taken at different times:

Because we have two separate data sets, we are using the series.data property of each series, rather than the data property of the chart itself:

series: [
    {
        data: [
            {
                time: new Date('01 Jan 2020 13:25:30 GMT'),
                sensor: 25
            },
            {
                time: new Date('01 Jan 2020 13:26:30 GMT'),
                sensor: 24
            }
        ],
        ...
    },
    {
        data: [
            {
                time: Date.parse('01 Jan 2020 13:25:00 GMT'),
                sensor: 21
            },
            {
                time: Date.parse('01 Jan 2020 13:26:00 GMT'),
                sensor: 22
            }
        ],
        ...
    }
]

Notice that even though one data set has dates as Date objects and another uses timestamps, it doesn't present a problem and both series render just fine.

The time axis automatically selects an appropriate label format depending on the time span of the data, making a best-effort attempt to prevent the labels from overlapping.

Real-Time Data

The chart will update whenever new data is supplied via the chart's or series' data property.

This example uses the 'time' axis which is configured to show a tick every 5 seconds and to use the %H:%M:%S label format to show colon separated hours, minutes and seconds.

API Reference