GROUPING SQL function
1. Usage of GROUPING to show order total based on shipped country
SQL Server Query 1
-- Analyze order counts by customer and customer demographics
SELECT
c.CustomerID,
c.CompanyName,
c.ContactName,
c.Country,
COUNT_BIG(o.OrderID) AS TotalOrders, -- Use COUNT_BIG here
AVG(CAST(od.Quantity * od.UnitPrice * (1 - od.Discount) AS DECIMAL(18, 2))) AS AverageOrderValue,
MAX(CAST(od.Quantity * od.UnitPrice * (1 - od.Discount) AS DECIMAL(18, 2))) AS MaxOrderValue,
MIN(CAST(od.Quantity * od.UnitPrice * (1 - od.Discount) AS DECIMAL(18, 2))) AS MinOrderValue
FROM Customers AS c
JOIN Orders AS o ON c.CustomerID = o.CustomerID
JOIN [Order Details] AS od ON o.OrderID = od.OrderID
GROUP BY c.CustomerID, c.CompanyName, c.ContactName, c.Country
ORDER BY TotalOrders DESC;
Create SQL query with SqlQueryBuilder 1
var (sql1, parameters1) = new SqlQueryBuilder()
.Select()
.Columns("c.CustomerID","c.CompanyName","c.ContactName","c.Country")
.Column(new COUNT_BIG(new Column("o.OrderID")), "TotalOrders")
.Column(new AVG(new CAST(new ColumnArithmatic("od.Quantity").MULTIPLY("od.UnitPrice").MULTIPLY()
.StartBracket(1).SUBTRACT("od.Discount").EndBracket(), SqlDataType.DECIMAL, new Tuple<int,int>(18,2)))
, "AverageOrderValue")
.Column(new MAX(new CAST(new ColumnArithmatic("od.Quantity").MULTIPLY("od.UnitPrice").MULTIPLY()
.StartBracket(1).SUBTRACT("od.Discount").EndBracket(), SqlDataType.DECIMAL, new Tuple<int, int>(18, 2)))
, "MaxOrderValue")
.Column(new MIN(new CAST(new ColumnArithmatic("od.Quantity").MULTIPLY("od.UnitPrice").MULTIPLY()
.StartBracket(1).SUBTRACT("od.Discount").EndBracket(), SqlDataType.DECIMAL, new Tuple<int, int>(18, 2)))
, "MinOrderValue")
.From("Customers", "c")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Orders", "o")
.On(new Column("c.CustomerID").Equale(new Column("o.CustomerID"))),
new INNERJOIN().TableName("[Order Details]", "od")
.On(new Column("o.OrderID").Equale(new Column("od.OrderID")))
})
.GroupBy(new GroupBy("c.CustomerID","c.CompanyName","c.ContactName","c.Country"))
.OrderBy(new OrderBy()
.SetColumnDescending("TotalOrders"))
.Build();
Query build by SqlQueryBuilder 1
WITH OrderDetailsWithGrouping
AS (SELECT ShipCountry AS ShipCountry,
SUM(UnitPrice * Quantity * (@pMAIN_2512060920281697800 - Discount)) AS OrderTotal,
GROUPING(ShipCountry) AS GroupingLevel
FROM [Order Details]
INNER JOIN
Orders
ON [Order Details].OrderID = Orders.OrderID
GROUP BY ROLLUP(ShipCountry))
SELECT ShipCountry,
OrderTotal,
CASE WHEN GroupingLevel = @pMAIN_2512060920281697801 THEN @pMAIN_2512060920281697802 WHEN GroupingLevel = @pMAIN_2512060920281697803 THEN @pMAIN_2512060920281697804 ELSE @pMAIN_2512060920281697805 END AS GroupingSource
FROM OrderDetailsWithGrouping
WHERE GroupingLevel IN (@pMAIN_2512060920281697806, @pMAIN_2512060920281697807)
ORDER BY GroupingLevel ASC;
Parameters (If used)
| Name |
Value |
| @pMAIN_2512060920281697800 |
1 |
| @pMAIN_2512060920281697801 |
0 |
| @pMAIN_2512060920281697802 |
Grouped by Country |
| @pMAIN_2512060920281697803 |
1 |
| @pMAIN_2512060920281697804 |
Grand Total |
| @pMAIN_2512060920281697805 |
Invalid Grouping Level |
| @pMAIN_2512060920281697806 |
0 |
| @pMAIN_2512060920281697807 |
1 |
Query Results 1:
| |
ShipCountry |
OrderTotal |
GroupingSource |
| 1 |
Argentina
|
8119.09997558594
|
Grouped by Country
|
| 2 |
Austria
|
128003.838745117
|
Grouped by Country
|
| 3 |
Belgium
|
33824.8549804688
|
Grouped by Country
|
| 4 |
Brazil
|
106925.776360512
|
Grouped by Country
|
| 5 |
Canada
|
50196.2903213501
|
Grouped by Country
|
| 6 |
Denmark
|
32661.0223455429
|
Grouped by Country
|
| 7 |
Finland
|
18810.052570343
|
Grouped by Country
|
| 8 |
France
|
81358.322476387
|
Grouped by Country
|
| 9 |
Germany
|
230284.633333206
|
Grouped by Country
|
| 10 |
Ireland
|
49979.9050006866
|
Grouped by Country
|
| 11 |
Italy
|
15770.1549053192
|
Grouped by Country
|
| 12 |
Mexico
|
23582.0776252747
|
Grouped by Country
|
| 13 |
Norway
|
5735.14999961853
|
Grouped by Country
|
| 14 |
Poland
|
3531.94997596741
|
Grouped by Country
|
| 15 |
Portugal
|
11472.3626556396
|
Grouped by Country
|
| 16 |
Spain
|
17983.2001066208
|
Grouped by Country
|
| 17 |
Sweden
|
54495.140045166
|
Grouped by Country
|
| 18 |
Switzerland
|
31692.658903122
|
Grouped by Country
|
| 19 |
UK
|
58971.3100633621
|
Grouped by Country
|
| 20 |
USA
|
245584.610227585
|
Grouped by Country
|
| 21 |
Venezuela
|
56810.6290016174
|
Grouped by Country
|
| 22 |
|
1265793.03961849
|
Grand Total
|
2. Usage of GROUPING to Total sales with ROLLUP
SQL Server Query 2
SELECT
o.ShipCountry,
c.CustomerID,
SUM(od.Quantity * od.UnitPrice * (1 - od.Discount)) AS TotalSales,
GROUPING(o.ShipCountry) AS CountryGrouping,
GROUPING(c.CustomerID) AS CustomerGrouping
FROM Orders AS o
JOIN Customers AS c ON o.CustomerID = c.CustomerID
JOIN [Order Details] AS od ON o.OrderID = od.OrderID
GROUP BY ROLLUP (o.ShipCountry, c.CustomerID) -- Using ROLLUP
ORDER BY o.ShipCountry, c.CustomerID;
Create SQL query with SqlQueryBuilder 2
var (sql2, parameters2) = new SqlQueryBuilder()
.Select()
.Columns("o.ShipCountry","c.CustomerID")
.Column(new SUM(new ColumnArithmatic("od.Quantity").MULTIPLY("od.UnitPrice").MULTIPLY()
.StartBracket(1).SUBTRACT("od.Discount").EndBracket()), "TotalSales")
.Column(new GROUPING(new Column("o.ShipCountry")), "CountryGrouping")
.Column(new GROUPING(new Column("c.CustomerID")), "CustomerGrouping")
.From("Orders","o")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Customers", "c")
.On(new Column("o.CustomerID").Equale(new Column("c.CustomerID"))),
new INNERJOIN().TableName("[Order Details]", "od")
.On(new Column("o.OrderID").Equale(new Column("od.OrderID")))
})
.GroupBy(new GroupBy("o.ShipCountry","c.CustomerID").WithRollUp())
.OrderBy(new OrderBy()
.SetColumnAscending("o.ShipCountry")
.SetColumnAscending("c.CustomerID"))
.Build();
Query build by SqlQueryBuilder 2
SELECT o.ShipCountry,
c.CustomerID,
SUM(od.Quantity * od.UnitPrice * (@pMAIN_2512060920281857750 - od.Discount)) AS TotalSales,
GROUPING(o.ShipCountry) AS CountryGrouping,
GROUPING(c.CustomerID) AS CustomerGrouping
FROM Orders AS o
INNER JOIN
Customers AS c
ON o.CustomerID = c.CustomerID
INNER JOIN
[Order Details] AS od
ON o.OrderID = od.OrderID
GROUP BY ROLLUP(o.ShipCountry, c.CustomerID)
ORDER BY o.ShipCountry ASC, c.CustomerID ASC;
Parameters (If used)
| Name |
Value |
| @pMAIN_2512060920281857750 |
1 |
Query Results 2:
| |
SHipCountry |
CustomerID |
TotalSales |
CountryGrouping |
CustomerGrouping |
| 1 |
|
|
1265793.03961849
|
1
|
1
|
| 2 |
Argentina
|
|
8119.09997558594
|
0
|
1
|
| 3 |
Argentina
|
CACTU
|
1814.79998779297
|
0
|
0
|
| 4 |
Argentina
|
OCEAN
|
3460.19999694824
|
0
|
0
|
| 5 |
Argentina
|
RANCH
|
2844.09999084473
|
0
|
0
|
| 6 |
Austria
|
|
128003.838745117
|
0
|
1
|
| 7 |
Austria
|
ERNSH
|
104874.978713989
|
0
|
0
|
| 8 |
Austria
|
PICCO
|
23128.8600311279
|
0
|
0
|
| 9 |
Belgium
|
|
33824.8549804688
|
0
|
1
|
| 10 |
Belgium
|
MAISD
|
9736.07500457764
|
0
|
0
|
| 11 |
Belgium
|
SUPRD
|
24088.7799758911
|
0
|
0
|
| 12 |
Brazil
|
|
106925.776360512
|
0
|
1
|
| 13 |
Brazil
|
COMMI
|
3810.75
|
0
|
0
|
| 14 |
Brazil
|
FAMIA
|
4107.55003166199
|
0
|
0
|
| 15 |
Brazil
|
GOURL
|
8414.13500213623
|
0
|
0
|
| 16 |
Brazil
|
HANAR
|
32841.3699417114
|
0
|
0
|
| 17 |
Brazil
|
QUEDE
|
6664.80997276306
|
0
|
0
|
| 18 |
Brazil
|
QUEEN
|
25717.4975166321
|
0
|
0
|
| 19 |
Brazil
|
RICAR
|
12450.8000183105
|
0
|
0
|
| 20 |
Brazil
|
TRADH
|
6850.66397094726
|
0
|
0
|
| 21 |
Brazil
|
WELLI
|
6068.19990634918
|
0
|
0
|
| 22 |
Canada
|
|
50196.2903213501
|
0
|
1
|
| 23 |
Canada
|
BOTTM
|
20801.6000213623
|
0
|
0
|
| 24 |
Canada
|
LAUGB
|
522.5
|
0
|
0
|
| 25 |
Canada
|
MEREP
|
28872.1902999878
|
0
|
0
|
| 26 |
Denmark
|
|
32661.0223455429
|
0
|
1
|
| 27 |
Denmark
|
SIMOB
|
16817.0975255966
|
0
|
0
|
| 28 |
Denmark
|
VAFFE
|
15843.9248199463
|
0
|
0
|
| 29 |
Finland
|
|
18810.052570343
|
0
|
1
|
| 30 |
Finland
|
WARTH
|
15648.7025642395
|
0
|
0
|
| 31 |
Finland
|
WILMK
|
3161.35000610352
|
0
|
0
|
| 32 |
France
|
|
81358.322476387
|
0
|
1
|
| 33 |
France
|
BLONP
|
18534.0799789429
|
0
|
0
|
| 34 |
France
|
BONAP
|
21963.2524261475
|
0
|
0
|
| 35 |
France
|
DUMON
|
1615.90000915527
|
0
|
0
|
| 36 |
France
|
FOLIG
|
11666.9000015259
|
0
|
0
|
| 37 |
France
|
FRANR
|
3172.16006469727
|
0
|
0
|
| 38 |
France
|
LACOR
|
1992.04999542236
|
0
|
0
|
| 39 |
France
|
LAMAI
|
9328.20000362396
|
0
|
0
|
| 40 |
France
|
SPECD
|
2423.34999847412
|
0
|
0
|
| 41 |
France
|
VICTE
|
9182.42999076843
|
0
|
0
|
| 42 |
France
|
VINET
|
1480.00000762939
|
0
|
0
|
| 43 |
Germany
|
|
230284.633333206
|
0
|
1
|
| 44 |
Germany
|
ALFKI
|
4272.99999809265
|
0
|
0
|
| 45 |
Germany
|
BLAUS
|
3239.80000305176
|
0
|
0
|
| 46 |
Germany
|
DRACD
|
3763.21001434326
|
0
|
0
|
| 47 |
Germany
|
FRANK
|
26656.559387207
|
0
|
0
|
| 48 |
Germany
|
KOENE
|
30908.3839836121
|
0
|
0
|
| 49 |
Germany
|
LEHMS
|
19261.4100112915
|
0
|
0
|
| 50 |
Germany
|
MORGK
|
5042.19998168945
|
0
|
0
|
| 51 |
Germany
|
OTTIK
|
12496.1999893188
|
0
|
0
|
| 52 |
Germany
|
QUICK
|
110277.304977417
|
0
|
0
|
| 53 |
Germany
|
TOMSP
|
4778.13998413086
|
0
|
0
|
| 54 |
Germany
|
WANDK
|
9588.42500305176
|
0
|
0
|
| 55 |
Ireland
|
|
49979.9050006866
|
0
|
1
|
| 56 |
Ireland
|
HUNGO
|
49979.9050006866
|
0
|
0
|
| 57 |
Italy
|
|
15770.1549053192
|
0
|
1
|
| 58 |
Italy
|
FRANS
|
1545.69999885559
|
0
|
0
|
| 59 |
Italy
|
MAGAA
|
7176.21500205994
|
0
|
0
|
| 60 |
Italy
|
REGGC
|
7048.23990440369
|
0
|
0
|
| 61 |
Mexico
|
|
23582.0776252747
|
0
|
1
|
| 62 |
Mexico
|
ANATR
|
1402.95000076294
|
0
|
0
|
| 63 |
Mexico
|
ANTON
|
7023.97755432129
|
0
|
0
|
| 64 |
Mexico
|
CENTC
|
100.799999237061
|
0
|
0
|
| 65 |
Mexico
|
PERIC
|
4242.20002746582
|
0
|
0
|
| 66 |
Mexico
|
TORTU
|
10812.1500434875
|
0
|
0
|
| 67 |
Norway
|
|
5735.14999961853
|
0
|
1
|
| 68 |
Norway
|
SANTG
|
5735.14999961853
|
0
|
0
|
| 69 |
Poland
|
|
3531.94997596741
|
0
|
1
|
| 70 |
Poland
|
WOLZA
|
3531.94997596741
|
0
|
0
|
| 71 |
Portugal
|
|
11472.3626556396
|
0
|
1
|
| 72 |
Portugal
|
FURIB
|
6427.42259216309
|
0
|
0
|
| 73 |
Portugal
|
PRINI
|
5044.94006347656
|
0
|
0
|
| 74 |
Spain
|
|
17983.2001066208
|
0
|
1
|
| 75 |
Spain
|
BOLID
|
4232.85009765625
|
0
|
0
|
| 76 |
Spain
|
GALED
|
836.699996948242
|
0
|
0
|
| 77 |
Spain
|
GODOS
|
11446.3600158691
|
0
|
0
|
| 78 |
Spain
|
ROMEY
|
1467.28999614716
|
0
|
0
|
| 79 |
Sweden
|
|
54495.140045166
|
0
|
1
|
| 80 |
Sweden
|
BERGS
|
24927.5774688721
|
0
|
0
|
| 81 |
Sweden
|
FOLKO
|
29567.5625762939
|
0
|
0
|
| 82 |
Switzerland
|
|
31692.658903122
|
0
|
1
|
| 83 |
Switzerland
|
CHOPS
|
12348.8800125122
|
0
|
0
|
| 84 |
Switzerland
|
RICSU
|
19343.7788906097
|
0
|
0
|
| 85 |
UK
|
|
58971.3100633621
|
0
|
1
|
| 86 |
UK
|
AROUT
|
13390.6500091553
|
0
|
0
|
| 87 |
UK
|
BSBEV
|
6089.89999008179
|
0
|
0
|
| 88 |
UK
|
CONSH
|
1719.10000324249
|
0
|
0
|
| 89 |
UK
|
EASTC
|
14761.0350036621
|
0
|
0
|
| 90 |
UK
|
ISLAT
|
6146.29999542236
|
0
|
0
|
| 91 |
UK
|
NORTS
|
649
|
0
|
0
|
| 92 |
UK
|
SEVES
|
16215.3250617981
|
0
|
0
|
| 93 |
USA
|
|
245584.610227585
|
0
|
1
|
| 94 |
USA
|
GREAL
|
18507.4499664307
|
0
|
0
|
| 95 |
USA
|
HUNGC
|
3063.20000076294
|
0
|
0
|
| 96 |
USA
|
LAZYK
|
357
|
0
|
0
|
| 97 |
USA
|
LETSS
|
3076.47247505188
|
0
|
0
|
| 98 |
USA
|
LONEP
|
4258.60001373291
|
0
|
0
|
| 99 |
USA
|
OLDWO
|
15177.4624938965
|
0
|
0
|
| 100 |
USA
|
RATTC
|
51097.8003330231
|
0
|
0
|
| 101 |
USA
|
SAVEA
|
104361.949920654
|
0
|
0
|
| 102 |
USA
|
SPLIR
|
11441.6299972534
|
0
|
0
|
| 103 |
USA
|
THEBI
|
3361
|
0
|
0
|
| 104 |
USA
|
THECR
|
1947.23999023438
|
0
|
0
|
| 105 |
USA
|
TRAIH
|
1571.19999313354
|
0
|
0
|
| 106 |
USA
|
WHITC
|
27363.6050434113
|
0
|
0
|
| 107 |
Venezuela
|
|
56810.6290016174
|
0
|
1
|
| 108 |
Venezuela
|
GROSR
|
1488.69999694824
|
0
|
0
|
| 109 |
Venezuela
|
HILAA
|
22768.7639884949
|
0
|
0
|
| 110 |
Venezuela
|
LILAS
|
16076.5999908447
|
0
|
0
|
| 111 |
Venezuela
|
LINOD
|
16476.5650253296
|
0
|
0
|
2. Usage of GROUPING to Total sales with CUBE
SQL Server Query 3
SELECT
o.ShipCountry,
c.CustomerID,
SUM(od.Quantity * od.UnitPrice * (1 - od.Discount)) AS TotalSales,
GROUPING(o.ShipCountry) AS CountryGrouping,
GROUPING(c.CustomerID) AS CustomerGrouping
FROM Orders AS o
JOIN Customers AS c ON o.CustomerID = c.CustomerID
JOIN [Order Details] AS od ON o.OrderID = od.OrderID
GROUP BY ROLLUP (o.ShipCountry, c.CustomerID) -- Using CUBE
ORDER BY o.ShipCountry, c.CustomerID;
Create SQL query with SqlQueryBuilder 3
var (sql3, parameters3) = new SqlQueryBuilder()
.Select()
.Columns("o.ShipCountry","c.CustomerID")
.Column(new SUM(new ColumnArithmatic("od.Quantity").MULTIPLY("od.UnitPrice").MULTIPLY()
.StartBracket(1).SUBTRACT("od.Discount").EndBracket()), "TotalSales")
.Column(new GROUPING(new Column("o.ShipCountry")), "CountryGrouping")
.Column(new GROUPING(new Column("c.CustomerID")), "CustomerGrouping")
.From("Orders","o")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Customers", "c")
.On(new Column("o.CustomerID").Equale(new Column("c.CustomerID"))),
new INNERJOIN().TableName("[Order Details]", "od")
.On(new Column("o.OrderID").Equale(new Column("od.OrderID")))
})
.GroupBy(new GroupBy("o.ShipCountry","c.CustomerID").WithCube())
.OrderBy(new OrderBy()
.SetColumnAscending("o.ShipCountry")
.SetColumnAscending("c.CustomerID"))
.Build();
Query build by SqlQueryBuilder 3
SELECT o.ShipCountry,
c.CustomerID,
SUM(od.Quantity * od.UnitPrice * (@pMAIN_2512060920282083490 - od.Discount)) AS TotalSales,
GROUPING(o.ShipCountry) AS CountryGrouping,
GROUPING(c.CustomerID) AS CustomerGrouping
FROM Orders AS o
INNER JOIN
Customers AS c
ON o.CustomerID = c.CustomerID
INNER JOIN
[Order Details] AS od
ON o.OrderID = od.OrderID
GROUP BY CUBE(o.ShipCountry, c.CustomerID)
ORDER BY o.ShipCountry ASC, c.CustomerID ASC;
Parameters (If used)
| Name |
Value |
| @pMAIN_2512060920282083490 |
1 |
Query Results 3:
| |
SHipCountry |
CustomerID |
TotalSales |
CountryGrouping |
CustomerGrouping |
| 1 |
|
|
1265793.03961849
|
1
|
1
|
| 2 |
|
ALFKI
|
4272.99999809265
|
1
|
0
|
| 3 |
|
ANATR
|
1402.95000076294
|
1
|
0
|
| 4 |
|
ANTON
|
7023.97755432129
|
1
|
0
|
| 5 |
|
AROUT
|
13390.6500091553
|
1
|
0
|
| 6 |
|
BERGS
|
24927.5774688721
|
1
|
0
|
| 7 |
|
BLAUS
|
3239.80000305176
|
1
|
0
|
| 8 |
|
BLONP
|
18534.0799789429
|
1
|
0
|
| 9 |
|
BOLID
|
4232.85009765625
|
1
|
0
|
| 10 |
|
BONAP
|
21963.2524261475
|
1
|
0
|
| 11 |
|
BOTTM
|
20801.6000213623
|
1
|
0
|
| 12 |
|
BSBEV
|
6089.89999008179
|
1
|
0
|
| 13 |
|
CACTU
|
1814.79998779297
|
1
|
0
|
| 14 |
|
CENTC
|
100.799999237061
|
1
|
0
|
| 15 |
|
CHOPS
|
12348.8800125122
|
1
|
0
|
| 16 |
|
COMMI
|
3810.75
|
1
|
0
|
| 17 |
|
CONSH
|
1719.10000324249
|
1
|
0
|
| 18 |
|
DRACD
|
3763.21001434326
|
1
|
0
|
| 19 |
|
DUMON
|
1615.90000915527
|
1
|
0
|
| 20 |
|
EASTC
|
14761.0350036621
|
1
|
0
|
| 21 |
|
ERNSH
|
104874.978713989
|
1
|
0
|
| 22 |
|
FAMIA
|
4107.55003166199
|
1
|
0
|
| 23 |
|
FOLIG
|
11666.9000015259
|
1
|
0
|
| 24 |
|
FOLKO
|
29567.5625762939
|
1
|
0
|
| 25 |
|
FRANK
|
26656.559387207
|
1
|
0
|
| 26 |
|
FRANR
|
3172.16006469727
|
1
|
0
|
| 27 |
|
FRANS
|
1545.69999885559
|
1
|
0
|
| 28 |
|
FURIB
|
6427.42259216309
|
1
|
0
|
| 29 |
|
GALED
|
836.699996948242
|
1
|
0
|
| 30 |
|
GODOS
|
11446.3600158691
|
1
|
0
|
| 31 |
|
GOURL
|
8414.13500213623
|
1
|
0
|
| 32 |
|
GREAL
|
18507.4499664307
|
1
|
0
|
| 33 |
|
GROSR
|
1488.69999694824
|
1
|
0
|
| 34 |
|
HANAR
|
32841.3699417114
|
1
|
0
|
| 35 |
|
HILAA
|
22768.7639884949
|
1
|
0
|
| 36 |
|
HUNGC
|
3063.20000076294
|
1
|
0
|
| 37 |
|
HUNGO
|
49979.9050006866
|
1
|
0
|
| 38 |
|
ISLAT
|
6146.29999542236
|
1
|
0
|
| 39 |
|
KOENE
|
30908.3839836121
|
1
|
0
|
| 40 |
|
LACOR
|
1992.04999542236
|
1
|
0
|
| 41 |
|
LAMAI
|
9328.20000362396
|
1
|
0
|
| 42 |
|
LAUGB
|
522.5
|
1
|
0
|
| 43 |
|
LAZYK
|
357
|
1
|
0
|
| 44 |
|
LEHMS
|
19261.4100112915
|
1
|
0
|
| 45 |
|
LETSS
|
3076.47247505188
|
1
|
0
|
| 46 |
|
LILAS
|
16076.5999908447
|
1
|
0
|
| 47 |
|
LINOD
|
16476.5650253296
|
1
|
0
|
| 48 |
|
LONEP
|
4258.60001373291
|
1
|
0
|
| 49 |
|
MAGAA
|
7176.21500205994
|
1
|
0
|
| 50 |
|
MAISD
|
9736.07500457764
|
1
|
0
|
| 51 |
|
MEREP
|
28872.1902999878
|
1
|
0
|
| 52 |
|
MORGK
|
5042.19998168945
|
1
|
0
|
| 53 |
|
NORTS
|
649
|
1
|
0
|
| 54 |
|
OCEAN
|
3460.19999694824
|
1
|
0
|
| 55 |
|
OLDWO
|
15177.4624938965
|
1
|
0
|
| 56 |
|
OTTIK
|
12496.1999893188
|
1
|
0
|
| 57 |
|
PERIC
|
4242.20002746582
|
1
|
0
|
| 58 |
|
PICCO
|
23128.8600311279
|
1
|
0
|
| 59 |
|
PRINI
|
5044.94006347656
|
1
|
0
|
| 60 |
|
QUEDE
|
6664.80997276306
|
1
|
0
|
| 61 |
|
QUEEN
|
25717.4975166321
|
1
|
0
|
| 62 |
|
QUICK
|
110277.304977417
|
1
|
0
|
| 63 |
|
RANCH
|
2844.09999084473
|
1
|
0
|
| 64 |
|
RATTC
|
51097.8003330231
|
1
|
0
|
| 65 |
|
REGGC
|
7048.23990440369
|
1
|
0
|
| 66 |
|
RICAR
|
12450.8000183105
|
1
|
0
|
| 67 |
|
RICSU
|
19343.7788906097
|
1
|
0
|
| 68 |
|
ROMEY
|
1467.28999614716
|
1
|
0
|
| 69 |
|
SANTG
|
5735.14999961853
|
1
|
0
|
| 70 |
|
SAVEA
|
104361.949920654
|
1
|
0
|
| 71 |
|
SEVES
|
16215.3250617981
|
1
|
0
|
| 72 |
|
SIMOB
|
16817.0975255966
|
1
|
0
|
| 73 |
|
SPECD
|
2423.34999847412
|
1
|
0
|
| 74 |
|
SPLIR
|
11441.6299972534
|
1
|
0
|
| 75 |
|
SUPRD
|
24088.7799758911
|
1
|
0
|
| 76 |
|
THEBI
|
3361
|
1
|
0
|
| 77 |
|
THECR
|
1947.23999023438
|
1
|
0
|
| 78 |
|
TOMSP
|
4778.13998413086
|
1
|
0
|
| 79 |
|
TORTU
|
10812.1500434875
|
1
|
0
|
| 80 |
|
TRADH
|
6850.66397094726
|
1
|
0
|
| 81 |
|
TRAIH
|
1571.19999313354
|
1
|
0
|
| 82 |
|
VAFFE
|
15843.9248199463
|
1
|
0
|
| 83 |
|
VICTE
|
9182.42999076843
|
1
|
0
|
| 84 |
|
VINET
|
1480.00000762939
|
1
|
0
|
| 85 |
|
WANDK
|
9588.42500305176
|
1
|
0
|
| 86 |
|
WARTH
|
15648.7025642395
|
1
|
0
|
| 87 |
|
WELLI
|
6068.19990634918
|
1
|
0
|
| 88 |
|
WHITC
|
27363.6050434113
|
1
|
0
|
| 89 |
|
WILMK
|
3161.35000610352
|
1
|
0
|
| 90 |
|
WOLZA
|
3531.94997596741
|
1
|
0
|
| 91 |
Argentina
|
|
8119.09997558594
|
0
|
1
|
| 92 |
Argentina
|
CACTU
|
1814.79998779297
|
0
|
0
|
| 93 |
Argentina
|
OCEAN
|
3460.19999694824
|
0
|
0
|
| 94 |
Argentina
|
RANCH
|
2844.09999084473
|
0
|
0
|
| 95 |
Austria
|
|
128003.838745117
|
0
|
1
|
| 96 |
Austria
|
ERNSH
|
104874.978713989
|
0
|
0
|
| 97 |
Austria
|
PICCO
|
23128.8600311279
|
0
|
0
|
| 98 |
Belgium
|
|
33824.8549804688
|
0
|
1
|
| 99 |
Belgium
|
MAISD
|
9736.07500457764
|
0
|
0
|
| 100 |
Belgium
|
SUPRD
|
24088.7799758911
|
0
|
0
|
| 101 |
Brazil
|
|
106925.776360512
|
0
|
1
|
| 102 |
Brazil
|
COMMI
|
3810.75
|
0
|
0
|
| 103 |
Brazil
|
FAMIA
|
4107.55003166199
|
0
|
0
|
| 104 |
Brazil
|
GOURL
|
8414.13500213623
|
0
|
0
|
| 105 |
Brazil
|
HANAR
|
32841.3699417114
|
0
|
0
|
| 106 |
Brazil
|
QUEDE
|
6664.80997276306
|
0
|
0
|
| 107 |
Brazil
|
QUEEN
|
25717.4975166321
|
0
|
0
|
| 108 |
Brazil
|
RICAR
|
12450.8000183105
|
0
|
0
|
| 109 |
Brazil
|
TRADH
|
6850.66397094726
|
0
|
0
|
| 110 |
Brazil
|
WELLI
|
6068.19990634918
|
0
|
0
|
| 111 |
Canada
|
|
50196.2903213501
|
0
|
1
|
| 112 |
Canada
|
BOTTM
|
20801.6000213623
|
0
|
0
|
| 113 |
Canada
|
LAUGB
|
522.5
|
0
|
0
|
| 114 |
Canada
|
MEREP
|
28872.1902999878
|
0
|
0
|
| 115 |
Denmark
|
|
32661.0223455429
|
0
|
1
|
| 116 |
Denmark
|
SIMOB
|
16817.0975255966
|
0
|
0
|
| 117 |
Denmark
|
VAFFE
|
15843.9248199463
|
0
|
0
|
| 118 |
Finland
|
|
18810.052570343
|
0
|
1
|
| 119 |
Finland
|
WARTH
|
15648.7025642395
|
0
|
0
|
| 120 |
Finland
|
WILMK
|
3161.35000610352
|
0
|
0
|
| 121 |
France
|
|
81358.322476387
|
0
|
1
|
| 122 |
France
|
BLONP
|
18534.0799789429
|
0
|
0
|
| 123 |
France
|
BONAP
|
21963.2524261475
|
0
|
0
|
| 124 |
France
|
DUMON
|
1615.90000915527
|
0
|
0
|
| 125 |
France
|
FOLIG
|
11666.9000015259
|
0
|
0
|
| 126 |
France
|
FRANR
|
3172.16006469727
|
0
|
0
|
| 127 |
France
|
LACOR
|
1992.04999542236
|
0
|
0
|
| 128 |
France
|
LAMAI
|
9328.20000362396
|
0
|
0
|
| 129 |
France
|
SPECD
|
2423.34999847412
|
0
|
0
|
| 130 |
France
|
VICTE
|
9182.42999076843
|
0
|
0
|
| 131 |
France
|
VINET
|
1480.00000762939
|
0
|
0
|
| 132 |
Germany
|
|
230284.633333206
|
0
|
1
|
| 133 |
Germany
|
ALFKI
|
4272.99999809265
|
0
|
0
|
| 134 |
Germany
|
BLAUS
|
3239.80000305176
|
0
|
0
|
| 135 |
Germany
|
DRACD
|
3763.21001434326
|
0
|
0
|
| 136 |
Germany
|
FRANK
|
26656.559387207
|
0
|
0
|
| 137 |
Germany
|
KOENE
|
30908.3839836121
|
0
|
0
|
| 138 |
Germany
|
LEHMS
|
19261.4100112915
|
0
|
0
|
| 139 |
Germany
|
MORGK
|
5042.19998168945
|
0
|
0
|
| 140 |
Germany
|
OTTIK
|
12496.1999893188
|
0
|
0
|
| 141 |
Germany
|
QUICK
|
110277.304977417
|
0
|
0
|
| 142 |
Germany
|
TOMSP
|
4778.13998413086
|
0
|
0
|
| 143 |
Germany
|
WANDK
|
9588.42500305176
|
0
|
0
|
| 144 |
Ireland
|
|
49979.9050006866
|
0
|
1
|
| 145 |
Ireland
|
HUNGO
|
49979.9050006866
|
0
|
0
|
| 146 |
Italy
|
|
15770.1549053192
|
0
|
1
|
| 147 |
Italy
|
FRANS
|
1545.69999885559
|
0
|
0
|
| 148 |
Italy
|
MAGAA
|
7176.21500205994
|
0
|
0
|
| 149 |
Italy
|
REGGC
|
7048.23990440369
|
0
|
0
|
| 150 |
Mexico
|
|
23582.0776252747
|
0
|
1
|
| 151 |
Mexico
|
ANATR
|
1402.95000076294
|
0
|
0
|
| 152 |
Mexico
|
ANTON
|
7023.97755432129
|
0
|
0
|
| 153 |
Mexico
|
CENTC
|
100.799999237061
|
0
|
0
|
| 154 |
Mexico
|
PERIC
|
4242.20002746582
|
0
|
0
|
| 155 |
Mexico
|
TORTU
|
10812.1500434875
|
0
|
0
|
| 156 |
Norway
|
|
5735.14999961853
|
0
|
1
|
| 157 |
Norway
|
SANTG
|
5735.14999961853
|
0
|
0
|
| 158 |
Poland
|
|
3531.94997596741
|
0
|
1
|
| 159 |
Poland
|
WOLZA
|
3531.94997596741
|
0
|
0
|
| 160 |
Portugal
|
|
11472.3626556396
|
0
|
1
|
| 161 |
Portugal
|
FURIB
|
6427.42259216309
|
0
|
0
|
| 162 |
Portugal
|
PRINI
|
5044.94006347656
|
0
|
0
|
| 163 |
Spain
|
|
17983.2001066208
|
0
|
1
|
| 164 |
Spain
|
BOLID
|
4232.85009765625
|
0
|
0
|
| 165 |
Spain
|
GALED
|
836.699996948242
|
0
|
0
|
| 166 |
Spain
|
GODOS
|
11446.3600158691
|
0
|
0
|
| 167 |
Spain
|
ROMEY
|
1467.28999614716
|
0
|
0
|
| 168 |
Sweden
|
|
54495.140045166
|
0
|
1
|
| 169 |
Sweden
|
BERGS
|
24927.5774688721
|
0
|
0
|
| 170 |
Sweden
|
FOLKO
|
29567.5625762939
|
0
|
0
|
| 171 |
Switzerland
|
|
31692.658903122
|
0
|
1
|
| 172 |
Switzerland
|
CHOPS
|
12348.8800125122
|
0
|
0
|
| 173 |
Switzerland
|
RICSU
|
19343.7788906097
|
0
|
0
|
| 174 |
UK
|
|
58971.3100633621
|
0
|
1
|
| 175 |
UK
|
AROUT
|
13390.6500091553
|
0
|
0
|
| 176 |
UK
|
BSBEV
|
6089.89999008179
|
0
|
0
|
| 177 |
UK
|
CONSH
|
1719.10000324249
|
0
|
0
|
| 178 |
UK
|
EASTC
|
14761.0350036621
|
0
|
0
|
| 179 |
UK
|
ISLAT
|
6146.29999542236
|
0
|
0
|
| 180 |
UK
|
NORTS
|
649
|
0
|
0
|
| 181 |
UK
|
SEVES
|
16215.3250617981
|
0
|
0
|
| 182 |
USA
|
|
245584.610227585
|
0
|
1
|
| 183 |
USA
|
GREAL
|
18507.4499664307
|
0
|
0
|
| 184 |
USA
|
HUNGC
|
3063.20000076294
|
0
|
0
|
| 185 |
USA
|
LAZYK
|
357
|
0
|
0
|
| 186 |
USA
|
LETSS
|
3076.47247505188
|
0
|
0
|
| 187 |
USA
|
LONEP
|
4258.60001373291
|
0
|
0
|
| 188 |
USA
|
OLDWO
|
15177.4624938965
|
0
|
0
|
| 189 |
USA
|
RATTC
|
51097.8003330231
|
0
|
0
|
| 190 |
USA
|
SAVEA
|
104361.949920654
|
0
|
0
|
| 191 |
USA
|
SPLIR
|
11441.6299972534
|
0
|
0
|
| 192 |
USA
|
THEBI
|
3361
|
0
|
0
|
| 193 |
USA
|
THECR
|
1947.23999023438
|
0
|
0
|
| 194 |
USA
|
TRAIH
|
1571.19999313354
|
0
|
0
|
| 195 |
USA
|
WHITC
|
27363.6050434113
|
0
|
0
|
| 196 |
Venezuela
|
|
56810.6290016174
|
0
|
1
|
| 197 |
Venezuela
|
GROSR
|
1488.69999694824
|
0
|
0
|
| 198 |
Venezuela
|
HILAA
|
22768.7639884949
|
0
|
0
|
| 199 |
Venezuela
|
LILAS
|
16076.5999908447
|
0
|
0
|
| 200 |
Venezuela
|
LINOD
|
16476.5650253296
|
0
|
0
|