Selecting Elements Based on Rank

What is ranking?

When a Source is sorted according to some attribute (or attributes), then the position of the elements of the Source represents a kind of ranking -- the so-called unique ranking. Finding the position of an element is discussed in "Finding the position of elements".

There are many other types of rankings that are not unique and that are called variant rankings. These are discussed in "Ranking elements in different ways".

Finding the position of elements

The position method returns a Source that represents the position of any given element in the original Source. The new Source has the type of Integer and has the original Source as an input. The position method returns a Source that represents the position of any given element of the base Source. If the base Source is sorted according to some attribute (or attributes), then the position represents a kind of ranking - the so called unique ranking.

You can also use the shortcut methods described in the following table to find elements based on their position in a Source object or to find the position of elements with the specified value or values.

Method	Description
at(pos)	Identifies the values of elements in a Source that have the specified position. There are two versions of this method. One version allows you specify the position using a Source object; in the other, you specify position using an int value.
first()	Identifies the element or elements in a Source that have position 1.
last()	Identifies the element or elements in a Source that have the largest position value.
positionOfValue(value)	Identifies the positions of elements in a Source that have the specified value. There are two versions of this method. One version allows you specify the value using a Source; in the other, you specify value using a String.
positionOfValues(values)	Identifies the positions of elements in a Source that have the specified values. There are two versions of this method. One version allows you specify the value using a Source; in the other, you specify value using an array of String objects.

Example: Finding the positions of elements when there are no keys

Assume that there is a Source named products whose elements are the unique identifiers of products. To create a new Source whose elements are the positions of the elements of products, issue the following code.

Source productsPosition = products.position();

A tabular representation of productsPosition showing the position of the elements in products is shown below. Note that the position() method is one based.

Input	Element
products	Integer
395	1
400	2
405	3
415	4
420	5
425	6
...

Example: Finding the positions of elements when there are inputs

Assume that there is a Source named unitsSoldByCountry (shown below) that has an input of products, an output of countries, and elements whose values are the total number of units for each product sold for each country.

Input	Output	Element	Position
product	countries	Integer
395	Australia	500	1
395	United States	800	2
...	...		...
49780	Australia	10000	1
49780	United States	50	2
49780	...		...

To create a new Source named positionUnitsSoldByCountry whose elements are the positions of the elements of unitsSoldByCountry, issue the following code.

Source positionUnitsSoldByCountry = unitsSoldByCountry.position();

Ranking elements in different ways

The following table provides example code for ranking elements in different ways where the Source (named base) whose elements you want to rank has two inputs named input1 and input2.

Rank	Example Code
ascending	Source sortedTuples = base.sortAscending()
descending	Source sortedTuples = base.sortDescending()
same order as another Source	Source sortedTuples = base.sortAscending (Source sortValue)
reverse order as another Source	Source sortedTuples = base.sortDescending (Source sortValue)
minimum	Source sortedTuples = base.join(input1).sortDescending(input2); Source equivalentRankedTuples =  sortedTuples.join(input2, input2); NumberSource minRank = sortedTuples. positionOfValues(equivalentRankedTuples).minimum(); The minimum ranking differs from unique ranking in the way it deals with ties (elements in the Source that share the same value for the attribute). All ties are given the same rank, which is the minimum possible.
maximum	Source sortedTuples = base.join(input1).sortDescending(input2); Source equivalentRankedTuples =  sortedTuples.join(input2, input2); NumberSource maxRank = sortedTuples.positionOfValues (equivalentRankedTuples).maximum(); The maximum ranking differs from unique ranking in the way it deals with ties (elements in the Source that share the same value for the attribute). All ties are given the same rank, which is the maximum possible rank.
average	Source sortedTuples = base.join(input1).sortDescending(input2; Source equivalentRankedTuples =  sortedTuples.join(input2, input2); NumberSource averageRank = sortedTuples.positionOfValues (equivalentRankedTuples).average(); The average ranking differs from unique ranking in the way it deals with ties (elements in the Source that share the same value for the attribute). All ties are given the same rank, which is equal to the average unique rank for the tied values.
packed	Source tuples = base.join(o utput1); Source firstEquivalentTuple = tuples.join(input2, input2.first(); Source packedRank = firstEquivalentTuple.join(tuples). sortDescending(input2).positionOfValues(base.value(). join(time.value()); Packed ranking, also called dense ranking, is distinguished from minimum ranking by the fact that the ranks are packed into consecutive integers.
percentile	Source sortedTuples = base.join(input1).sortDescending(input2); Source equivalentRankedTuples =  sortedTuples.join(input2, input2); NumberSource minRank = sortedTuples.      positionOfValues(equivalentRankedTuples).minimum(); NumberSource percentile = minRank.minus(1).times(100).      div(sortedTuples.count()); This code uses the following formula to calculate the percentile of an attribute A for a Source S with N elements. Percentile(x) =  number of elements  (for which the A differs from A(x))  that come before x in the ordering * 100 / N The percentile, then, is equivalent to the minimum rank -1 * 100 / N.
ntile	NumberSource n = ...; Source sortedTuples = base.join(input1).sortDescending(input2); NumberSource uniqueRank = sortedTuple.       positionOfValues(base.value().join(input1.value()); NumberSource ntile = uniqueRank.times(n).      div(sortedTuples.count()).ceiling(); In this code, the ntile ranking for a given n is defined by dividing the ordered Source of size count into n buckets, where the bucket with rank k is of size. The ntile rank is equivalent to the following formula. ceiling*((uniqueRank*n)/count).