How to use data-forge - 10 common examples
To help you get started, we’ve selected a few data-forge examples, based on popular ways it is used in public projects.
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SockTrader / SockTrader / src / __tests__ / data / candleNormalizer.spec.ts View on Github 
function createDataFrame() {
// @formatter:off
return new DataFrame([
{high: 5663.99, low: 5639.25, open: 5658.11, close: 5647.88, volume: 0.67, timestamp: moment("2019-05-06T10:00:00.000Z")},
{high: 5660, low: 5608.04, open: 5627.37, close: 5658.11, volume: 10.623, timestamp: moment("2019-05-06T02:00:00.000Z")},
{high: 5638, low: 5613.12, open: 5621.01, close: 5627.3766, volume: 20, timestamp: moment("2019-05-06T01:00:00.000Z")},
]);
// @formatter:on
}}
const seriesPlotDefaults: IPlotConfig = {
legend: {
show: false,
},
};
function plotSeries(this: ISeries, plotConfig?: IPlotConfig, axisMap?: IAxisMap): IPlotAPI {
const serializedData = this
.inflate((value: any) => ({ __value__: value }))
.serialize();
return new PlotAPI(serializedData, plotConfig || {}, axisMap || {}, seriesPlotDefaults);
}
Series.prototype.startPlot = startPlot;
Series.prototype.endPlot = endPlot;
Series.prototype.plot = plotSeries;
//
// Augment IDataFrame and DataFrame with plot function.
//
declare module "data-forge/build/lib/dataframe" {
interface IDataFrame {
startPlot(): void;
endPlot(): void;
plot(plotDef?: IPlotConfig, axisMap?: IAxisMap): IPlotAPI;
}
interface DataFrame {
startPlot(): void;const seriesPlotDefaults: IPlotConfig = {
legend: {
show: false,
},
};
function plotSeries(this: ISeries, plotConfig?: IPlotConfig, axisMap?: IAxisMap): IPlotAPI {
const serializedData = this
.inflate((value: any) => ({ __value__: value }))
.serialize();
return new PlotAPI(serializedData, plotConfig || {}, axisMap || {}, seriesPlotDefaults);
}
Series.prototype.startPlot = startPlot;
Series.prototype.endPlot = endPlot;
Series.prototype.plot = plotSeries;
//
// Augment IDataFrame and DataFrame with plot function.
//
declare module "data-forge/build/lib/dataframe" {
interface IDataFrame {
startPlot(): void;
endPlot(): void;
plot(plotDef?: IPlotConfig, axisMap?: IAxisMap): IPlotAPI;
}
interface DataFrame {
startPlot(): void;
endPlot(): void;const seriesPlotDefaults: IPlotConfig = {
legend: {
show: false,
},
};
function plotSeries(this: ISeries, plotConfig?: IPlotConfig, axisMap?: IAxisMap): IPlotAPI {
const serializedData = this
.inflate((value: any) => ({ __value__: value }))
.serialize();
return new PlotAPI(serializedData, plotConfig || {}, axisMap || {}, seriesPlotDefaults);
}
Series.prototype.startPlot = startPlot;
Series.prototype.endPlot = endPlot;
Series.prototype.plot = plotSeries;
//
// Augment IDataFrame and DataFrame with plot function.
//
declare module "data-forge/build/lib/dataframe" {
interface IDataFrame {
startPlot(): void;
endPlot(): void;
plot(plotDef?: IPlotConfig, axisMap?: IAxisMap): IPlotAPI;
}
interface DataFrame {
startPlot(): void;
endPlot(): void;let peakCapital = startingCapital;
let workingDrawdown = 0;
for (const trade of trades) {
workingCapital *= trade.growth;
if (workingCapital < peakCapital) {
workingDrawdown = workingCapital - peakCapital;
}
else {
peakCapital = workingCapital;
workingDrawdown = 0; // Reset at the peak.
}
drawdown.push(workingDrawdown);
}
return new Series(drawdown);
}function ema(this: ISeries, period: number): ISeries {
assert.isNumber(period, "Expected 'period' parameter to 'Series.ema' to be a number that specifies the time period of the moving average.");
// https://www.investopedia.com/ask/answers/122314/what-exponential-moving-average-ema-formula-and-how-ema-calculated.asp
const mult = (2 / (period + 1));
let avgValue = this.take(period).average(); //TODO: this destroy the index.
return new Series({
index: [ this.getIndex().skip(period-1).first() ], // TODO: The construction of this 1 elements series is quite awkward.
values: [ avgValue ],
})
.concat(
this.skip(period)
.select(value => {
avgValue = ((value - avgValue) * mult) + avgValue;
return avgValue;
})
.bake()
);
}async function main(): Promise {
const df = new DataFrame({
columns: {
versicolor_x: versicolor_x,
versicolor_y: versicolor_y,
setosa_x: setosa_x,
setosa_y: setosa_y,
},
});
//console.log(df.head(10).toString());
const plot = df.plot()
.chartType(ChartType.Scatter)
.y()
.addSeries("versicolor_y")
.label("Versicolor")
//todo: .color("blue")async function main(): Promise {
const df = new DataFrame({
columns: {
versicolor_x: versicolor_x,
versicolor_y: versicolor_y,
},
});
//console.log(df.toString());
const plot = df.plot({ chartType: ChartType.Scatter }, { x: "versicolor_x", y: "versicolor_y" });
await plot.renderImage(path.join(outputPath, "image.png"), { openImage: false });
await plot.exportWeb(path.join(outputPath, "web"), { overwrite: true, openBrowser: false });
}async function main(): Promise {
const df = new DataFrame({
columns: {
date: x,
data1: data1,
data2: data2
},
})
.parseDates("date", "YYYY-MM-DD");
//console.log(df.toString());
const plot = df.plot({}, { x: "date", y: [ "data1", "data2" ]});
await plot.renderImage(path.join(outputPath, "image.png"), { openImage: false });
await plot.exportWeb(path.join(outputPath, "web"), { overwrite: true, openBrowser: false });
}async function main(): Promise {
const df = new DataFrame({
columns: {
data1: data1,
data2: data2,
data3: data3,
},
});
//console.log(df.toString());
const plot = df.plot()
.chartType(ChartType.Bar);
await plot.renderImage(path.join(outputPath, "image.png"), { openImage: false });
await plot.exportWeb(path.join(outputPath, "web"), { overwrite: true, openBrowser: false });
}data-forge
JavaScript data transformation and analysis toolkit inspired by Pandas and LINQ.
