tech.tablesaw.aggregate.AggregateFunctions Maven / Gradle / Ivy
package tech.tablesaw.aggregate;
import org.apache.commons.math3.stat.StatUtils;
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
import org.apache.commons.math3.stat.descriptive.moment.Kurtosis;
import org.apache.commons.math3.stat.descriptive.moment.Skewness;
import tech.tablesaw.api.BooleanColumn;
import tech.tablesaw.api.DateColumn;
import tech.tablesaw.api.DateTimeColumn;
import tech.tablesaw.api.NumericColumn;
import tech.tablesaw.columns.Column;
import tech.tablesaw.columns.numbers.DoubleColumnType;
import java.time.LocalDate;
import java.time.LocalDateTime;
public class AggregateFunctions {
public static DateTimeAggregateFunction earliestDateTime = new DateTimeAggregateFunction("Earliest Date-Time") {
@Override
public LocalDateTime summarize(DateTimeColumn column) {
return column.min();
}
};
public static DateAggregateFunction earliestDate = new DateAggregateFunction("Earliest Date") {
@Override
public LocalDate summarize(DateColumn column) {
return column.min();
}
};
public static DateAggregateFunction latestDate = new DateAggregateFunction("Latest Date") {
@Override
public LocalDate summarize(DateColumn column) {
return column.max();
}
};
public static DateTimeAggregateFunction latestDateTime = new DateTimeAggregateFunction("Latest Date-Time") {
@Override
public LocalDateTime summarize(DateTimeColumn column) {
return column.max();
}
};
public static BooleanCountFunction countTrue = new BooleanCountFunction("Number True") {
@Override
public Integer summarize(BooleanColumn column) {
return column.countTrue();
}
};
public static BooleanAggregateFunction allTrue = new BooleanAggregateFunction("All True") {
@Override
public Boolean summarize(BooleanColumn column) {
return column.all();
}
};
public static BooleanAggregateFunction anyTrue = new BooleanAggregateFunction("Any True") {
@Override
public Boolean summarize(BooleanColumn column) {
return column.any();
}
};
public static BooleanAggregateFunction noneTrue = new BooleanAggregateFunction("None True") {
@Override
public Boolean summarize(BooleanColumn column) {
return column.none();
}
};
public static BooleanCountFunction countFalse = new BooleanCountFunction("Number False") {
@Override
public Integer summarize(BooleanColumn column) {
return (column).countFalse();
}
};
public static BooleanNumericFunction proportionTrue = new BooleanNumericFunction("Proportion True") {
@Override
public Double summarize(BooleanColumn column) {
return (column).proportionTrue();
}
};
public static BooleanNumericFunction proportionFalse = new BooleanNumericFunction("Proportion False") {
@Override
public Double summarize(BooleanColumn column) {
return (column).proportionFalse();
}
};
/**
* A function that returns the first item
*/
public static NumericAggregateFunction first = new NumericAggregateFunction("First") {
@Override
public Double summarize(NumericColumn column) {
return column.isEmpty() ? DoubleColumnType.missingValueIndicator() : column.getDouble(0);
}
};
/**
* A function that returns the last item
*/
public static NumericAggregateFunction last = new NumericAggregateFunction("Last") {
@Override
public Double summarize(NumericColumn column) {
return column.isEmpty() ? DoubleColumnType.missingValueIndicator() : column.getDouble(column.size() - 1);
}
};
/**
* A function that returns the difference between the last and first items
*/
public static NumericAggregateFunction change = new NumericAggregateFunction("Change") {
@Override
public Double summarize(NumericColumn column) {
return column.size() < 2 ? DoubleColumnType.missingValueIndicator() : column.getDouble(column.size() - 1) - column.getDouble(0);
}
};
/**
* A function that returns the difference between the last and first items
*/
public static NumericAggregateFunction pctChange = new NumericAggregateFunction("Percent Change") {
@Override
public Double summarize(NumericColumn column) {
return column.size() < 2 ? DoubleColumnType.missingValueIndicator() : (column.getDouble(column.size() - 1) - column.getDouble(0)) / column.getDouble(0);
}
};
/**
* A function that calculates the count of values in the column excluding missing values
*/
public static CountFunction countNonMissing = new CountFunction("Count") {
@Override
public Integer summarize(Column column) {
return column.size() - column.countMissing();
}
};
/**
* A function that calculates the count of values in the column excluding missing values. A synonym for countNonMissing
*/
public static final CountFunction count = countNonMissing;
/**
* A function that calculates the count of values in the column excluding missing values
*/
public static CountFunction countMissing = new CountFunction("Missing Values") {
@Override
public Integer summarize(Column column) {
return column.countMissing();
}
};
/**
* A function that returns the number of non-missing unique values in the column param
*/
public static CountFunction countUnique = new CountFunction("Count Unique") {
@Override
public Integer summarize(Column doubles) {
return doubles.unique().removeMissing().size();
}
};
/**
* A function that calculates the mean of the values in the column param
*/
public static final NumericAggregateFunction mean = new NumericAggregateFunction("Mean") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.mean(removeMissing(column));
}
};
/**
* A function that calculates the sum of the values in the column param
*/
public static final NumericAggregateFunction sum = new NumericAggregateFunction("Sum") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.sum(removeMissing(column));
}
};
public static final NumericAggregateFunction median = new NumericAggregateFunction("Median") {
@Override
public Double summarize(NumericColumn column) {
return percentile(column, 50.0);
}
};
public static final CountFunction countWithMissing = new CountFunction("Count (incl. missing)") {
@Override
public Integer summarize(Column column) {
return column.size();
}
};
public static final NumericAggregateFunction quartile1 = new NumericAggregateFunction("First Quartile") {
@Override
public Double summarize(NumericColumn column) {
return percentile(column, 25.0);
}
};
public static final NumericAggregateFunction quartile3 = new NumericAggregateFunction("Third Quartile") {
@Override
public Double summarize(NumericColumn column) {
return percentile(column, 75.0);
}
};
public static final NumericAggregateFunction percentile90 = new NumericAggregateFunction("90th Percentile") {
@Override
public Double summarize(NumericColumn column) {
return percentile(column, 90.0);
}
};
public static final NumericAggregateFunction percentile95 = new NumericAggregateFunction("95th Percentile") {
@Override
public Double summarize(NumericColumn column) {
return percentile(column, 95.0);
}
};
public static final NumericAggregateFunction percentile99 = new NumericAggregateFunction("99th Percentile") {
@Override
public Double summarize(NumericColumn column) {
return percentile(column, 99.0);
}
};
public static final NumericAggregateFunction range = new NumericAggregateFunction("Range") {
@Override
public Double summarize(NumericColumn column) {
double[] data = removeMissing(column);
return StatUtils.max(data) - StatUtils.min(data);
}
};
public static final NumericAggregateFunction min = new NumericAggregateFunction("Min") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.min(removeMissing(column));
}
};
public static final NumericAggregateFunction max = new NumericAggregateFunction("Max") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.max(removeMissing(column));
}
};
public static final NumericAggregateFunction product = new NumericAggregateFunction("Product") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.product(removeMissing(column));
}
};
public static final NumericAggregateFunction geometricMean = new NumericAggregateFunction("Geometric Mean") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.geometricMean(removeMissing(column));
}
};
public static final NumericAggregateFunction populationVariance = new NumericAggregateFunction("Population Variance") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.populationVariance(removeMissing(column));
}
};
/**
* Returns the quadratic mean, aka, the root-mean-square
*/
public static final NumericAggregateFunction quadraticMean = new NumericAggregateFunction("Quadratic Mean") {
@Override
public Double summarize(NumericColumn column) {
return new DescriptiveStatistics(removeMissing(column)).getQuadraticMean();
}
};
public static final NumericAggregateFunction kurtosis = new NumericAggregateFunction("Kurtosis") {
@Override
public Double summarize(NumericColumn column) {
double[] data = removeMissing(column);
return new Kurtosis().evaluate(data, 0, data.length);
}
};
public static final NumericAggregateFunction skewness = new NumericAggregateFunction("Skewness") {
@Override
public Double summarize(NumericColumn column) {
double[] data = removeMissing(column);
return new Skewness().evaluate(data, 0, data.length);
}
};
public static final NumericAggregateFunction sumOfSquares = new NumericAggregateFunction("Sum of Squares") {
@Override
public String functionName() {
return "Sum of Squares";
}
@Override
public Double summarize(NumericColumn column) {
return StatUtils.sumSq(removeMissing(column));
}
};
public static final NumericAggregateFunction sumOfLogs = new NumericAggregateFunction("Sum of Logs") {
@Override
public Double summarize(NumericColumn column) {
return StatUtils.sumLog(removeMissing(column));
}
};
public static final NumericAggregateFunction variance = new NumericAggregateFunction("Variance") {
@Override
public Double summarize(NumericColumn column) {
double[] values = removeMissing(column);
return StatUtils.variance(values);
}
};
public static final NumericAggregateFunction stdDev = new NumericAggregateFunction("Std. Deviation") {
@Override
public Double summarize(NumericColumn column) {
return Math.sqrt(StatUtils.variance(removeMissing(column)));
}
};
public static final NumericAggregateFunction standardDeviation = stdDev;
public static Double percentile(NumericColumn data, Double percentile) {
return StatUtils.percentile(removeMissing(data), percentile);
}
private static double[] removeMissing(NumericColumn column) {
NumericColumn numericColumn = (NumericColumn) column.removeMissing();
return numericColumn.asDoubleArray();
}
// TODO(lwhite): These are two column reductions. We need a class for that
public static Double meanDifference(NumericColumn column1, NumericColumn column2) {
return StatUtils.meanDifference(column1.asDoubleArray(), column2.asDoubleArray());
}
public static Double sumDifference(NumericColumn column1, NumericColumn column2) {
return StatUtils.sumDifference(column1.asDoubleArray(), column2.asDoubleArray());
}
}
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