IPR
Updated 2023-10-23 20:04:22.383000
Syntax
SELECT [westclintech].[wct].[IPR] (
<@x, float,>
,<@kl, float,>
,<@ku, float,>
,<@mthd, nvarchar(4000),>)
Description
Use the aggregate function IPR to calculate the difference in value between two percentiles in a dataset.
Arguments
@mthd
the percentile calculation method. Use 'INC' for the inclusive method and 'EXC' for the exclusive method. If you enter NULL, @mthd defaults to NULL. For more information about the two methods, see the PERCENTILE and the PERCENTILE_EXC documentation.
@x
the input values for the function. @ x is an expression of type float or of a type that can be implicitly converted to float.
@ku
is the upper percentile value in the range 0 through 1, inclusive. @ku is an expression of type float or of a type that can be implicitly converted to float.
@kl
i s the lower percentile value in the range 0 through 1, inclusive. @kl is an expression of type float or of a type that can be implicitly converted to float.
Return Type
float
Remarks
If @ku <0 or @ku > 1 one, IPR returns an error.
If @kl <0 or @kl > 1 one, IPR returns an error.
If @mthd not NULL, ‘INC’, or ‘EXC’, IPR returns an error.
@kl must remain invariant for a group.
@ku must remain invariant for a group.
@mthd must remain invariant for a group.
IPR is an aggregate function and follows the same conventions as all other aggregate functions in SQL Server.
If there is only one value in the dataset, that value will be returned by the function.
Examples
In this example, we calculate the range from the 10th to the 90th percentile for selected salary inforrmation collected from 10 cities.
SELECT wct.IPR(salary, .10, .90, NULL) as [Inter-Percentile Range]
FROM
(
VALUES
('New York', '429-00-6486', 236503),
('New York', '90-70-2526', 224472),
('New York', '87-85-0404', 139802),
('New York', '716-89-3089', 185287),
('New York', '159-78-5370', 211900),
('New York', '195-97-6820', 186703),
('New York', '95-49-2813', 167451),
('New York', '37-20-7422', 149462),
('New York', '44-48-0076', 214708),
('New York', '514-79-0041', 226485),
('Los Angeles', '526-34-4521', 196402),
('Los Angeles', '800-50-0868', 205359),
('Los Angeles', '41-34-3618', 195679),
('Los Angeles', '854-29-9398', 131925),
('Los Angeles', '673-30-3623', 171091),
('Los Angeles', '537-58-8889', 110217),
('Los Angeles', '808-68-4234', 192836),
('Los Angeles', '359-81-6735', 209346),
('Los Angeles', '731-80-2303', 182186),
('Los Angeles', '214-58-0842', 125355),
('Chicago', '456-79-9682', 183698),
('Chicago', '807-97-4784', 194282),
('Chicago', '981-16-3724', 156083),
('Chicago', '252-34-3054', 226619),
('Chicago', '613-28-9452', 153366),
('Chicago', '785-25-8628', 205709),
('Chicago', '451-26-7350', 206085),
('Chicago', '443-94-2401', 120587),
('Chicago', '696-26-8113', 171185),
('Chicago', '277-31-9760', 211160),
('Dallas', '537-88-7532', 245231),
('Dallas', '393-25-3503', 238733),
('Dallas', '612-17-0712', 103152),
('Dallas', '384-93-7285', 228842),
('Dallas', '745-10-7587', 154749),
('Dallas', '950-20-4045', 102156),
('Dallas', '477-48-7550', 196533),
('Dallas', '427-52-8597', 238970),
('Dallas', '891-19-0810', 245204),
('Dallas', '564-79-7612', 196946),
('Boston', '216-84-7134', 128035),
('Boston', '515-84-4073', 249093),
('Boston', '92-43-5775', 205026),
('Boston', '144-08-1092', 198120),
('Boston', '469-14-5012', 174143),
('Boston', '379-92-8313', 166215),
('Boston', '71-22-5132', 105058),
('Boston', '257-39-0324', 107247),
('Boston', '611-57-4279', 118561),
('Boston', '956-53-2865', 232789),
('Denver', '711-81-0072', 240720),
('Denver', '673-39-5028', 159706),
('Denver', '554-33-3980', 232493),
('Denver', '770-03-5304', 203310),
('Denver', '732-47-5077', 123106),
('Denver', '573-18-3567', 149999),
('Denver', '93-92-0334', 162657),
('Denver', '424-76-1468', 116322),
('Denver', '403-47-0063', 246058),
('Denver', '460-58-1833', 198043),
('Miami', '221-04-4153', 130962),
('Miami', '179-09-9839', 227246),
('Miami', '564-76-9437', 144027),
('Miami', '407-48-4081', 138549),
('Miami', '526-79-1840', 208006),
('Miami', '72-68-4977', 170109),
('Miami', '235-72-3903', 191669),
('Miami', '436-62-0474', 161164),
('Miami', '430-52-3914', 162507),
('Miami', '459-27-5541', 238972),
('Phoenix', '576-38-4531', 238281),
('Phoenix', '65-64-1278', 197678),
('Phoenix', '880-29-1997', 159183),
('Phoenix', '304-72-1881', 194733),
('Phoenix', '61-20-1046', 221045),
('Phoenix', '64-95-5514', 105577),
('Phoenix', '262-63-4021', 186399),
('Phoenix', '661-84-1023', 234974),
('Phoenix', '892-31-4821', 115076),
('Phoenix', '319-91-9463', 239548),
('San Franciso', '136-67-6873', 148829),
('San Franciso', '5-41-7374', 114161),
('San Franciso', '381-26-8852', 232509),
('San Franciso', '620-64-6243', 112686),
('San Franciso', '128-33-5550', 208679),
('San Franciso', '422-00-0156', 107685),
('San Franciso', '370-98-5607', 133224),
('San Franciso', '91-58-9543', 218955),
('San Franciso', '911-35-0448', 187826),
('San Franciso', '734-65-1268', 223683),
('Atlanta', '334-97-0585', 240384),
('Atlanta', '405-12-4222', 124350),
('Atlanta', '43-05-7567', 233836),
('Atlanta', '882-97-7996', 134091),
('Atlanta', '368-91-4292', 173787),
('Atlanta', '408-04-5921', 140769),
('Atlanta', '232-13-5280', 206307),
('Atlanta', '88-41-2584', 118159),
('Atlanta', '539-03-7548', 116718),
('Atlanta', '587-63-6935', 174801)
) p (city, id, salary);
This produces the following result.
{"columns":[{"field":"Inter-Percentile Range","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"Inter-Percentile Range":"123487.2"}]}
In this example we will calculate the same inter-percentile range in each city.
SELECT city
,wct.IPR(salary, .10, .90, 'EXC') as [Inter-Percentile Range]
FROM (VALUES
('New York','429-00-6486',236503),
('New York','90-70-2526',224472),
('New York','87-85-0404',139802),
('New York','716-89-3089',185287),
('New York','159-78-5370',211900),
('New York','195-97-6820',186703),
('New York','95-49-2813',167451),
('New York','37-20-7422',149462),
('New York','44-48-0076',214708),
('New York','514-79-0041',226485),
('Los Angeles','526-34-4521',196402),
('Los Angeles','800-50-0868',205359),
('Los Angeles','41-34-3618',195679),
('Los Angeles','854-29-9398',131925),
('Los Angeles','673-30-3623',171091),
('Los Angeles','537-58-8889',110217),
('Los Angeles','808-68-4234',192836),
('Los Angeles','359-81-6735',209346),
('Los Angeles','731-80-2303',182186),
('Los Angeles','214-58-0842',125355),
('Chicago','456-79-9682',183698),
('Chicago','807-97-4784',194282),
('Chicago','981-16-3724',156083),
('Chicago','252-34-3054',226619),
('Chicago','613-28-9452',153366),
('Chicago','785-25-8628',205709),
('Chicago','451-26-7350',206085),
('Chicago','443-94-2401',120587),
('Chicago','696-26-8113',171185),
('Chicago','277-31-9760',211160),
('Dallas','537-88-7532',245231),
('Dallas','393-25-3503',238733),
('Dallas','612-17-0712',103152),
('Dallas','384-93-7285',228842),
('Dallas','745-10-7587',154749),
('Dallas','950-20-4045',102156),
('Dallas','477-48-7550',196533),
('Dallas','427-52-8597',238970),
('Dallas','891-19-0810',245204),
('Dallas','564-79-7612',196946),
('Boston','216-84-7134',128035),
('Boston','515-84-4073',249093),
('Boston','92-43-5775',205026),
('Boston','144-08-1092',198120),
('Boston','469-14-5012',174143),
('Boston','379-92-8313',166215),
('Boston','71-22-5132',105058),
('Boston','257-39-0324',107247),
('Boston','611-57-4279',118561),
('Boston','956-53-2865',232789),
('Denver','711-81-0072',240720),
('Denver','673-39-5028',159706),
('Denver','554-33-3980',232493),
('Denver','770-03-5304',203310),
('Denver','732-47-5077',123106),
('Denver','573-18-3567',149999),
('Denver','93-92-0334',162657),
('Denver','424-76-1468',116322),
('Denver','403-47-0063',246058),
('Denver','460-58-1833',198043),
('Miami','221-04-4153',130962),
('Miami','179-09-9839',227246),
('Miami','564-76-9437',144027),
('Miami','407-48-4081',138549),
('Miami','526-79-1840',208006),
('Miami','72-68-4977',170109),
('Miami','235-72-3903',191669),
('Miami','436-62-0474',161164),
('Miami','430-52-3914',162507),
('Miami','459-27-5541',238972),
('Phoenix','576-38-4531',238281),
('Phoenix','65-64-1278',197678),
('Phoenix','880-29-1997',159183),
('Phoenix','304-72-1881',194733),
('Phoenix','61-20-1046',221045),
('Phoenix','64-95-5514',105577),
('Phoenix','262-63-4021',186399),
('Phoenix','661-84-1023',234974),
('Phoenix','892-31-4821',115076),
('Phoenix','319-91-9463',239548),
('San Franciso','136-67-6873',148829),
('San Franciso','5-41-7374',114161),
('San Franciso','381-26-8852',232509),
('San Franciso','620-64-6243',112686),
('San Franciso','128-33-5550',208679),
('San Franciso','422-00-0156',107685),
('San Franciso','370-98-5607',133224),
('San Franciso','91-58-9543',218955),
('San Franciso','911-35-0448',187826),
('San Franciso','734-65-1268',223683),
('Atlanta','334-97-0585',240384),
('Atlanta','405-12-4222',124350),
('Atlanta','43-05-7567',233836),
('Atlanta','882-97-7996',134091),
('Atlanta','368-91-4292',173787),
('Atlanta','408-04-5921',140769),
('Atlanta','232-13-5280',206307),
('Atlanta','88-41-2584',118159),
('Atlanta','539-03-7548',116718),
('Atlanta','587-63-6935',174801)
)p(city, id, salary)
GROUP BY city;
This produces the following result.
{"columns":[{"field":"city"},{"field":"Inter-Percentile Range","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"city":"Atlanta","Inter-Percentile Range":"122867.1"},{"city":"Boston","Inter-Percentile Range":"142185.7"},{"city":"Chicago","Inter-Percentile Range":"101208.2"},{"city":"Dallas","Inter-Percentile Range":"142972.7"},{"city":"Denver","Inter-Percentile Range":"128523.8"},{"city":"Los Angeles","Inter-Percentile Range":"97216.5"},{"city":"Miami","Inter-Percentile Range":"106078.7"},{"city":"New York","Inter-Percentile Range":"94733.2"},{"city":"Phoenix","Inter-Percentile Range":"132894.4"},{"city":"San Franciso","Inter-Percentile Range":"123441.3"}]}
In this example, we only select those cities where the interpercentile range, using the inclusive method, is less than 100,000.
SELECT city,
wct.IPR(salary, .10, .90, 'INC') as [Inter-Percentile Range]
FROM
(
VALUES
('New York', '429-00-6486', 236503),
('New York', '90-70-2526', 224472),
('New York', '87-85-0404', 139802),
('New York', '716-89-3089', 185287),
('New York', '159-78-5370', 211900),
('New York', '195-97-6820', 186703),
('New York', '95-49-2813', 167451),
('New York', '37-20-7422', 149462),
('New York', '44-48-0076', 214708),
('New York', '514-79-0041', 226485),
('Los Angeles', '526-34-4521', 196402),
('Los Angeles', '800-50-0868', 205359),
('Los Angeles', '41-34-3618', 195679),
('Los Angeles', '854-29-9398', 131925),
('Los Angeles', '673-30-3623', 171091),
('Los Angeles', '537-58-8889', 110217),
('Los Angeles', '808-68-4234', 192836),
('Los Angeles', '359-81-6735', 209346),
('Los Angeles', '731-80-2303', 182186),
('Los Angeles', '214-58-0842', 125355),
('Chicago', '456-79-9682', 183698),
('Chicago', '807-97-4784', 194282),
('Chicago', '981-16-3724', 156083),
('Chicago', '252-34-3054', 226619),
('Chicago', '613-28-9452', 153366),
('Chicago', '785-25-8628', 205709),
('Chicago', '451-26-7350', 206085),
('Chicago', '443-94-2401', 120587),
('Chicago', '696-26-8113', 171185),
('Chicago', '277-31-9760', 211160),
('Dallas', '537-88-7532', 245231),
('Dallas', '393-25-3503', 238733),
('Dallas', '612-17-0712', 103152),
('Dallas', '384-93-7285', 228842),
('Dallas', '745-10-7587', 154749),
('Dallas', '950-20-4045', 102156),
('Dallas', '477-48-7550', 196533),
('Dallas', '427-52-8597', 238970),
('Dallas', '891-19-0810', 245204),
('Dallas', '564-79-7612', 196946),
('Boston', '216-84-7134', 128035),
('Boston', '515-84-4073', 249093),
('Boston', '92-43-5775', 205026),
('Boston', '144-08-1092', 198120),
('Boston', '469-14-5012', 174143),
('Boston', '379-92-8313', 166215),
('Boston', '71-22-5132', 105058),
('Boston', '257-39-0324', 107247),
('Boston', '611-57-4279', 118561),
('Boston', '956-53-2865', 232789),
('Denver', '711-81-0072', 240720),
('Denver', '673-39-5028', 159706),
('Denver', '554-33-3980', 232493),
('Denver', '770-03-5304', 203310),
('Denver', '732-47-5077', 123106),
('Denver', '573-18-3567', 149999),
('Denver', '93-92-0334', 162657),
('Denver', '424-76-1468', 116322),
('Denver', '403-47-0063', 246058),
('Denver', '460-58-1833', 198043),
('Miami', '221-04-4153', 130962),
('Miami', '179-09-9839', 227246),
('Miami', '564-76-9437', 144027),
('Miami', '407-48-4081', 138549),
('Miami', '526-79-1840', 208006),
('Miami', '72-68-4977', 170109),
('Miami', '235-72-3903', 191669),
('Miami', '436-62-0474', 161164),
('Miami', '430-52-3914', 162507),
('Miami', '459-27-5541', 238972),
('Phoenix', '576-38-4531', 238281),
('Phoenix', '65-64-1278', 197678),
('Phoenix', '880-29-1997', 159183),
('Phoenix', '304-72-1881', 194733),
('Phoenix', '61-20-1046', 221045),
('Phoenix', '64-95-5514', 105577),
('Phoenix', '262-63-4021', 186399),
('Phoenix', '661-84-1023', 234974),
('Phoenix', '892-31-4821', 115076),
('Phoenix', '319-91-9463', 239548),
('San Franciso', '136-67-6873', 148829),
('San Franciso', '5-41-7374', 114161),
('San Franciso', '381-26-8852', 232509),
('San Franciso', '620-64-6243', 112686),
('San Franciso', '128-33-5550', 208679),
('San Franciso', '422-00-0156', 107685),
('San Franciso', '370-98-5607', 133224),
('San Franciso', '91-58-9543', 218955),
('San Franciso', '911-35-0448', 187826),
('San Franciso', '734-65-1268', 223683),
('Atlanta', '334-97-0585', 240384),
('Atlanta', '405-12-4222', 124350),
('Atlanta', '43-05-7567', 233836),
('Atlanta', '882-97-7996', 134091),
('Atlanta', '368-91-4292', 173787),
('Atlanta', '408-04-5921', 140769),
('Atlanta', '232-13-5280', 206307),
('Atlanta', '88-41-2584', 118159),
('Atlanta', '539-03-7548', 116718),
('Atlanta', '587-63-6935', 174801)
) p (city, id, salary)
GROUP BY city
HAVING wct.IPR(salary, .10, .90, 'INC') < 100000;
This produces the following result.
{"columns":[{"field":"city"},{"field":"Inter-Percentile Range","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"city":"Chicago","Inter-Percentile Range":"62617.8"},{"city":"Los Angeles","Inter-Percentile Range":"81916.5"},{"city":"Miami","Inter-Percentile Range":"90628.3"},{"city":"New York","Inter-Percentile Range":"78990.8"}]}
In this example we calculate the 40th percentile for a variety of data groupings, including one NULL value and a GROUP that only contains one member.
SELECT dsc,
wct.IPR(x, .40, .60, 'INC') as [Inter-Percentile Range]
FROM
(
VALUES
('ABC', 15),
('ABC', 20),
('ABC', 35),
('ABC', 40),
('ABC', 50),
('DEF', 7),
('DEF', 10),
('DEF', 17),
('DEF', 20),
('DEF', 25),
('DEF', 70),
('GHI', 21),
('GHI', 28),
('GHI', NULL),
('GHI', 38),
('GHI', 31),
('GHI', 52),
('JKL', 37)
) p (dsc, x)
GROUP BY dsc;
This produces the following result.
{"columns":[{"field":"dsc"},{"field":"nter-Percentile Range","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"dsc":"ABC","nter-Percentile Range":"8"},{"dsc":"DEF","nter-Percentile Range":"3"},{"dsc":"GHI","nter-Percentile Range":"4"},{"dsc":"JKL","nter-Percentile Range":"0"}]}