Simple implementation of Descriptive Statistics, calculating : sum, count, average, mode, median, variance, standard deviation.

Data.java

import java.util.*;

/** 
 * For Descriptive Statistics
 * @AUTHOR: Francis Nduba Numbi
 * @YEAR: 2017
 *
 * REMEMBER : AFTER ALL DATA HAVE BEEN ADDED, call update().
 * else some calculations will be wrong.
 */
public class Data {
	private ArrayList<Datum> list;

	public Data() {
		list = new ArrayList<Datum>();
	}

	public int count() {
		int i = 0;
		for (Datum d : list) {
			i += d.f;
		}
		return i;
	}

	public void add(int f, double x) {
		list.add(new Datum(f, x));
		sort();
	}

	public void remove(int f, double x) {
		Iterator<Datum> iter = list.iterator();
		while (iter.hasNext()) {
			Datum d = iter.next();
			if (d.f == f && d.x == x) {
				iter.remove();
			}
		}
		sort();
	}

	public double sum() {
		double sum = 0;
		for (Datum d : list) {
			sum += d.y;
		}
		return sum;
	}

	public double average() {
		return sum() / count();
	}

	public double mode() {
		sort();
		float ii = 0f;
		for (Datum d : list) {
			if (d.f > ii) {
				ii = d.f;
			}
		}

		double pl = 0;
		int ct = 0;
		for (Datum d : list) {
			if (d.f == ii) {
				pl += d.x;
				ct++;
			}
		}

		pl /= ct;

		return pl;
	}

	public double median() {
		sort();
		float ii = 0f;
		for (Datum d : list) {
			ii += d.f;
			if (ii > (float)(count() / 2)) {
				return d.x;
			}
		}
		return 0;
	}

	public ArrayList<Datum> list() {
		return list;
	}

	/**  */
	public ArrayList<Double> pondList() {
		ArrayList<Double> pl = new ArrayList<Double>();
		for (Datum d : list) {
			pl.add(d.y);
		}
		return pl;
	}

	public ArrayList<Double> deviationList() {
		ArrayList<Double> pl = new ArrayList<Double>();
		for (Datum d : list) {
			pl.add(d.X);
		}
		return pl;
	}

	public ArrayList<Double> deviationListSqr() {
		ArrayList<Double> pl = new ArrayList<Double>();
		for (Datum d : list) {
			pl.add(d.XX);
		}
		return pl;
	}

	/** variance */
	public double var() {
		double sum = 0;
		for (Datum d : list) {
			sum += d.XX;
		}
		return sum / count();
	}

	/** standard deviation */
	public double stDev() {
		return Math.sqrt(var());
	}

	private void sort() {
		Collections.sort(list);
	}

	@Override
	public String toString() {
		return list.toString();
	}

	/** after all data have been added, update */
	public void update() {
		for (Datum d : list) {
			d.X = d.x - average();
			d.XX = d.X * d.X;
		}

	}

	/** inner class Datum that hold and wrap data */
	class Datum implements Comparable {


		public int f; // frequency
		public double x; // value
		public double y; // ponderation (f*x);
		public double X; // deviation from the mean
		public double XX; // deviation squared


		public Datum(int f, double x) {
			this.f = f;
			this.x = x;
			y = x * f;
		}

		// compareTo() and equals() methods are necessary for sorting
		// the 2 methods use the same comparison process for integrity
		@Override
		public int compareTo(Object p1) {
			// TODO: Implement this method
			return Double.compare(x, ((Datum)p1).x);
		}

		@Override
		public boolean equals(Object o) {
			// TODO: Implement this method
			return Double.compare(x, ((Datum)o).x) == 1;
		}

		@Override
		public String toString() {
			// TODO: Implement this method
			return "| " + f + " | " + x + " | " + y + " | " + X + " | " + XX + " |\n";
		}


	} // end of inner class Datum
}