将JFreeChart TimeSeries系列与Day数据转换为Week或Month数据？ [英] Converting a JFreeChart TimeSeries series with Day data to Week or Month data?

问题描述

我意识到这可能是一个愚蠢的问题，我知道可以通过确定每个数据点的周或月等来完成，但是，我正在寻找一种避免编码的方法。如果它是在一个库中完成的（大概是所有的陷阱都得到了）我宁愿使用它。

I realize this may be a silly question, and I know it could be done by determining what week or month each data point is in, etc. but, I'm looking for a way to avoid coding that. If it's been done in a library (presumably all the gotchas gotten) I would rather use that.

原始数据存储在Excel电子表格中，但我不能操纵电子表格直。如果它是唯一的解决方案，我可以制作副本并操纵它，但这将是最后的手段。我目前正在将这些数据用于JFreeChart图表，如果这有任何区别的话。我也愿意使用任何图书馆。

The raw data is stored in Excel spreadsheets, but I cannot manipulate the spreadsheets directly. I could make a copy and manipulate that if it's the only solution, but this would be the last resort. I am currently using this data for JFreeChart charts, if that makes any difference. I am also open to using any library.

非常感谢您提出的任何建议。

Thank you very much for any advice you can offer.

推荐答案

没有什么说你必须使用 TimeSeries 或 RegularTimePeriod 。工厂方法 ChartFactory.createTimeSeriesChart（）将接受任何 XYDataset ，其中域表示来自Java 纪元。以下示例扩展了 AbstractXYDataset 以合成一系列日期。您的实现必须规范化Excel日期，这些日期使用不同的纪元。

Nothing says you have to use a TimeSeries or RegularTimePeriod. The factory method ChartFactory.createTimeSeriesChart() will accept any XYDataset in which the domain represents milliseconds from the Java epoch. The example below extends AbstractXYDataset to synthesize a series of days. Your implementation would have to normalize the Excel dates, which use a different epoch.

附录： Apache POI 包括静态 DateUtil.getJavaDate（）执行转换的方法。生成的时间可以直接用于您选择的数据集。可以在此处找到完整示例。

Addendum: Apache POI includes static DateUtil.getJavaDate() methods to perform the conversion. The resulting times can be used directly in your chosen data set. A complete example may be found here.

import java.awt.Dimension;
import java.text.DateFormat;
import java.util.Date;
import javax.swing.JFrame;
import org.jfree.chart.*;
import org.jfree.chart.axis.DateAxis;
import org.jfree.chart.plot.XYPlot;
import org.jfree.data.xy.AbstractXYDataset;
import org.jfree.data.xy.XYDataset;

/** @see https://stackoverflow.com/a/12481509/230513 */
public class AbstractXYTest {

    private static XYDataset createDataset() {
        return new AbstractXYDataset() {

            private static final int N = 16;
            private final long t = new Date().getTime();

            @Override
            public int getSeriesCount() {
                return 1;
            }

            @Override
            public Comparable getSeriesKey(int series) {
                return "Data";
            }

            @Override
            public int getItemCount(int series) {
                return N;
            }

            @Override
            public Number getX(int series, int item) {
                return Double.valueOf(t + item * 1000 * 3600 * 24);
            }

            @Override
            public Number getY(int series, int item) {
                return Math.pow(item, 1.61);
            }
        };
    }

    private static JFreeChart createChart(final XYDataset dataset) {
        JFreeChart chart = ChartFactory.createTimeSeriesChart(
            "Test", "Day", "Value", dataset, false, false, false);
        XYPlot plot = (XYPlot) chart.getPlot();
        DateAxis domain = (DateAxis) plot.getDomainAxis();
        domain.setDateFormatOverride(DateFormat.getDateInstance());
        return chart;
    }

    public static void main(String[] args) {

        JFrame f = new JFrame();
        f.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        XYDataset dataset = createDataset();
        JFreeChart chart = createChart(dataset);
        ChartPanel chartPanel = new ChartPanel(chart) {

            @Override
            public Dimension getPreferredSize() {
                return new Dimension(800, 300);
            }
        };
        f.add(chartPanel);
        f.pack();
        f.setLocationRelativeTo(null);
        f.setVisible(true);
    }
}

这篇关于将JFreeChart TimeSeries系列与Day数据转换为Week或Month数据？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！