Trendline

Trendline is an additional line that indicates the slope (or trend) in a particular data series.

Trendline is an additional line that indicates the slope (or trend) in a particular data series and is also known as a line of best fit. Trendlines can be helpful when you are analyzing data because they can forecast future values based upon your current data. Users can create 6 different types of trendlines for their charts: including linear, exponential, logarithmic, polynomial, power, and moving average. Linear: a best fit straight line for simple linear data sets. Exponential: a best-fit curved line that illustrates how data values increase or decrease and then level out. Logarithmic: a best-fit curved line that illustrates the data increases or decreases quickly and then levels out. Polynomial: a curved line illustrating fluctuations in the data values based on the order property. Power: a curved line to compare measurements that increase at a specific rate. MovingAverage: averages a specific number of data points, and uses the value as a point in the line. Trendline supports the following chart types: Column Bar Line Scatter Area You can create a linear trendline using the following code: Customize order: Specify the number of terms in the Polynomial equation. The order is a integer with range 2 to 6. intercept: Specify the intercept for linear, exponential, polynomial trendline. displayEquation & displayRSquared: Specify whether to use equation or R squared for the trendline. forward & backward: use forward or backward to project the data. The displayEquation, displayRSquared, forward, backward supports linear, exponential, logarithmic, polynomial, power trendline. style: Specify the line style of the trendline, including color, width, and dash line. name: Specify the name of the trendline. The built-in name will be used if no name is provided. Period: Specify the period of the MovingAverage Trendline. The order is a integer with range 2 to data set count minus 1.
var advData = [ ['Advertising', 'Items sold'], [28, 17], [34, 19], [41, 18], [47, 20], [52, 24], [59, 26], [65, 29], [72, 31], [80, 34], [87, 39], [94, 40], [102, 42], ]; var salesData = [ ['', 'Sales'], ['Jan', 54], ['Feb', 60], ['Mar', 86], ['Apr', 92], ['May', 112], ['Jun', 157], ['Jul', 202], ['Aug', 195], ['Sep', 187], ['Oct', 194], ['Nov', 238], ['Dec', 289], ]; window.onload = function () { var spread = new GC.Spread.Sheets.Workbook(document.getElementById("ss"), { sheetCount: 2 }); initSheet1(spread); initSheet2(spread); }; function initSheet1(spread) { var sheet1 = spread.getSheet(0); sheet1.name('Basic'); sheet1.setArray(0, 0, advData); sheet1.setArray(18, 0, salesData); for (var i = 0; i < 12; i ++) { sheet1.getCell(i + 1, 0).formatter('$#,##0'); } // Choose a suitable trendline type from GC.Spread.Sheets.Charts.TrendlineType to fit your chart var chart1 = sheet1.charts.add("chart1", GC.Spread.Sheets.Charts.ChartType.xyScatter, 130, 5, 500, 350, "A1:B13", GC.Spread.Sheets.Charts.RowCol.columns); var axes = chart1.axes(); axes.primaryValue.title.text = 'Items sold'; axes.primaryCategory.title.text = 'Advertising'; axes.primaryCategory.majorGridLine.visible = true; axes.primaryCategory.majorUnit = 10; chart1.axes(axes); var targetSeriesIndex = 0; var targetSeries = chart1.series().get(targetSeriesIndex); var linearTrendline = { type: GC.Spread.Sheets.Charts.TrendlineType.linear, style: { color: 'red', width: 2 } }; targetSeries.trendlines = [ linearTrendline ]; chart1.series().set(targetSeriesIndex, targetSeries); var chart2 = sheet1.charts.add("chart2", GC.Spread.Sheets.Charts.ChartType.columnClustered, 130, 360, 500, 350, "A19:B31", GC.Spread.Sheets.Charts.RowCol.columns); var targetSeriesIndex = 0; var targetSeries = chart2.series().get(targetSeriesIndex); var exponentialTrendline = { type: GC.Spread.Sheets.Charts.TrendlineType.exponential, style: { color: 'orange', width: 2, dashStyle: GC.Spread.Sheets.Charts.LineDashStyle.dash } }; targetSeries.trendlines = [ exponentialTrendline ]; chart2.series().set(targetSeriesIndex, targetSeries); } function initSheet2(spread) { // More settings var sheet2 = spread.getSheet(1); sheet2.name('Advance'); sheet2.setArray(0, 0, advData); sheet2.setArray(18, 0, salesData); for (var i = 0; i < 12; i ++) { sheet2.getCell(i + 1, 0).formatter('$#,##0'); } // Change the order(the highest power for the independent variable) of polynomial trendline to adjust R-squared value // Also you could show the equation and R-squared value in chart area if you want var chart3 = sheet2.charts.add("chart3", GC.Spread.Sheets.Charts.ChartType.xyScatter, 130, 5, 500, 350, "A1:B13", GC.Spread.Sheets.Charts.RowCol.columns); var axes = chart3.axes(); axes.primaryValue.title.text = 'Items sold'; axes.primaryCategory.title.text = 'Advertising'; axes.primaryCategory.majorGridLine.visible = true; axes.primaryCategory.majorUnit = 10; chart3.axes(axes); var targetSeriesIndex = 0; var targetSeries = chart3.series().get(targetSeriesIndex); var polynomialTrendline = { type: GC.Spread.Sheets.Charts.TrendlineType.polynomial, order: 4, displayEquation: true, displayRSquared: true, style: { color: 'red', width: 2 } }; targetSeries.trendlines = [ polynomialTrendline ]; chart3.series().set(targetSeriesIndex, targetSeries); // Set a value in the Forward and Backward fields to project your data into the future. var chart4 = sheet2.charts.add("chart4", GC.Spread.Sheets.Charts.ChartType.columnClustered, 130, 360, 500, 350, "A19:B31", GC.Spread.Sheets.Charts.RowCol.columns); var targetSeriesIndex = 0; var targetSeries = chart4.series().get(targetSeriesIndex); var exponentialTrendline = { type: GC.Spread.Sheets.Charts.TrendlineType.exponential, forward: 3, style: { color: 'orange', width: 2, dashStyle: GC.Spread.Sheets.Charts.LineDashStyle.dash } }; targetSeries.trendlines = [ exponentialTrendline ]; chart4.series().set(targetSeriesIndex, targetSeries); }
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