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High-performance Java Dataframe with integrated columnar storage (fork of tablesaw)

There is a newer version: 0.9.1

package org.datavec.dataframe.columns;

import org.datavec.dataframe.api.IntColumn;
import org.datavec.dataframe.filtering.IntBiPredicate;
import org.datavec.dataframe.filtering.IntPredicate;
import it.unimi.dsi.fastutil.ints.IntIterable;

/**
 *
 */
public interface IntColumnUtils extends Column, IntIterable {

    IntPredicate isZero = i -> i == 0;

    IntPredicate isNegative = i -> i < 0;

    IntPredicate isPositive = i -> i > 0;

    IntPredicate isNonNegative = i -> i >= 0;

    IntPredicate isEven = i -> (i & 1) == 0;

    IntPredicate isOdd = i -> (i & 1) != 0;

    IntBiPredicate isGreaterThan = (valueToTest, valueToCompareAgainst) -> valueToTest > valueToCompareAgainst;
    IntBiPredicate isGreaterThanOrEqualTo =
                    (valueToTest, valueToCompareAgainst) -> valueToTest >= valueToCompareAgainst;

    IntBiPredicate isLessThan = (valueToTest, valueToCompareAgainst) -> valueToTest < valueToCompareAgainst;
    IntBiPredicate isLessThanOrEqualTo = (valueToTest, valueToCompareAgainst) -> valueToTest <= valueToCompareAgainst;

    IntBiPredicate isNotEqualTo = (valueToTest, valueToCompareAgainst) -> valueToTest != valueToCompareAgainst;


    IntBiPredicate isEqualTo = (valueToTest, valueToCompareAgainst) -> valueToTest == valueToCompareAgainst;

    IntPredicate isMissing = i -> i == IntColumn.MISSING_VALUE;

    IntPredicate isNotMissing = i -> i != IntColumn.MISSING_VALUE;
}