Trend Lines in ASP.NET MVC Chart Component
18 Nov 20186 minutes to read
Trendlines are used to show the direction and speed of price.
Trendlines can be generated for Cartesian type series (Line, Column, Scatter, Area, Candle, Hilo etc.) except bar type series. You can add more than one trendline to a series.
Chart supports 6 types of trendlines.
Linear
A linear trendline is a best fit straight line that is used with simpler data sets. To render a linear trendline, use trendline Type as Linear.
Exponential
An exponential trendline is a curved line that is most useful when data values rise or fall at increasingly higher rates. You cannot create an exponential trendline, if your data contains zero or negative values.
To render a exponential trendline, use trendline Type as Exponential.
Logarithmic
A logarithmic trendline is a best-fit curved line that is most useful when the rate of change in the data increases or decreases quickly and then levels out.
A logarithmic trendline can use negative and/or positive values.
To render a logarithmic trendline, use trendline Type as Logarithmic.
Polynomial
A polynomial trendline is a curved line that is used when data fluctuates.
To render a polynomial trendline, use trendline Type as Polynomial.
PolynomialOrder used to define the polynomial value.
Power
A power trendline is a curved line that is best used with data sets that compare measurements that increase at a specific rate.
To render a power trendline, use trendline Type as Power.
Moving Average
A moving average trendline smoothen out fluctuations in data to show a pattern or trend more clearly.
To render a moving average trendline, use trendline Type as MovingAverage.
Period property defines the period to find the moving average.
Customization of Trendlines
The Fill and Width properties are used to customize the appearance of the trendline.
Forecasting
Trendlines forecasting is the prediction of future/past situations.
Forecasting can be classified into two types as follows
- Forward Forecasting
- Backward Forecasting
Forward Forecasting
The value set for forwardForecast is used to determine the distance moving towards the future trend.
Backward Forecasting
The value set for the backwardForecast is used to determine the past trends.
Show or hide a trendline
You can show or hide the trendline by setting trendline visible property.
@Html.EJS().Chart("container").Series(series =>
{
series.Trendlines(ViewBag.trendLines)
.Type(Syncfusion.EJ2.Charts.ChartSeriesType.Line)
.XName("x").YName("y")
.Marker(ViewBag.marker)
.DataSource("series1")
.Name("Rupees")
.Width(2).Add(); })
.PrimaryXAxis(px => px.EdgeLabelPlacement(Syncfusion.EJ2.Charts.EdgeLabelPlacement.Shift)
.MajorGridLines(ViewBag.majorGridLines))
.PrimaryYAxis(py => py.Title("Rupees against Dollars")
.Interval(10)
.MajorTickLines(ViewBag.majorTickLines)
.LineStyle(ViewBag.lineStyle))
.ChartArea(area => area.Border(ViewBag.ChartBorder))
.Title("Historical Indian Rupee Rate (INR USD)")
.LegendSettings(lg => lg.Visible(false))
.Trendlines(tl => tl.Visible(false))
.Tooltip(tt => tt.Enable(true)).Render()
<script type="text/javascript">
var series1 = [];
var yValue = [7.66, 8.03, 8.41, 8.97, 8.77, 8.20, 8.16, 7.89, 8.68, 9.48, 10.11, 11.36, 12.34, 12.60, 12.95,
13.91, 16.21, 17.50, 22.72, 28.14, 31.26, 31.39, 32.43, 35.52, 36.36,
41.33, 43.12, 45.00, 47.23, 48.62, 46.60, 45.28, 44.01, 45.17, 41.20, 43.41, 48.32, 45.65, 46.61, 53.34, 58.53];
var point1;
var i;
var j = 0;
for (i = 1973; i <= 2013; i++) {
point1 = { x: i, y: yValue[j] };
series1.push(point1);
j++;
}
var powerData = [
{ x: 1, y: 10 }, { x: 2, y: 50 }, { x: 3, y: 80 }, { x: 4, y: 110 },
{ x: 5, y: 180 }, { x: 6, y: 220 }, { x: 7, y: 300 }, { x: 8, y: 370 }, { x: 9, y: 490 }, { x: 10, y: 500 }
];
</script>public IActionResult Index()
{
return View();
}