% Contains 110 data sets from the book 'The Statistical Sleuth'
% by Fred Ramsey and Dan Schafer; Duxbury Press, 1997.
% (schafer@stat.orst.edu) [14/Oct/97] (172k)
% 
% Note: description taken from this web site:
%       http://lib.stat.cmu.edu/datasets/
% 
% File: ../data/sleuth/ex1221.asc
% 
% 
% Information about the dataset
% CLASSTYPE: numeric
% CLASSINDEX: none specific
% 
@relation sleuth-ex1221
@attribute river {Adige,Amazon,Caragh,Columbia,Danube,Delaware,Fraser,Ganges,Glaama,Huanghe,Hudson,Kazan_and_Back,Mackenzie,Magdalena,Mekong,Mersey,Meuse,Mississippi,Murray-Darling,Nelson,Niger,Nile,Orange,Orinoco,Parana,Po,Rhine,Rhone,Shannon,St._Lawrence,Stikine,Susquehanna,Tees,Thames,Tiber,Uruguay,Vistula,Volga,Yangtze,Yukon,Zaire,Zambezi}
@attribute country {Argentina,Australia,Canada,Canada/USA,China,Columbia,England,Europe,France,India,Ireland,Italy,NE_Africa,Norway,Nthlnds/Belgium,Poland,Rumania,Russia,SE_Africa,SE_Asia,S_Africa,S_America,USA,Venezuela,W_Africa,Zaire}
@attribute discharge numeric
@attribute runoff numeric
@attribute area numeric
@attribute density numeric
@attribute no3 numeric
@attribute export numeric
@attribute dep numeric
@attribute nprec numeric
@attribute prec numeric

@data
Adige,Italy,223,18.3,1220,102,67.0,1224.7,1237.5,46.0,84.8
Amazon,S_America,175000,24.8,7050000,1,3.0,74.5,120.6,2.1,181.1
Caragh,Ireland,7,45.6,160,7,3.6,164.0,86.5,2.6,104.9
Columbia,USA,7900,11.8,670000,10,26.6,313.6,62.8,2.0,99.1
Danube,Rumania,6500,8.1,805000,90,46.0,371.4,826.4,45.0,57.9
Delaware,USA,336,19.1,17600,100,61.0,1167.2,851.7,25.0,107.4
Fraser,Canada,3550,16.1,220000,2,6.4,103.3,739.7,16.0,145.8
Ganges,India,16000,14.9,1070000,300,91.3,1361.4,294.3,5.8,160.0
Glaama,Norway,706,16.9,41770,12,24.0,405.7,975.0,45.0,68.3
Huanghe,China,1470,2.0,750000,200,139.0,272.6,286.4,28.0,32.3
Hudson,USA,560,16.1,34700,150,47.8,771.4,851.7,25.0,107.4
Kazan_and_Back,Canada,1900,6.1,312000,0,1.1,6.7,60.9,7.0,27.4
Mackenzie,Canada,10600,5.9,1787000,0,5.7,33.8,73.9,7.0,33.3
Magdalena,Columbia,7500,31.3,240000,30,17.0,531.3,87.5,2.6,106.2
Mekong,SE_Asia,15000,19.2,783000,43,17.0,325.7,334.1,7.6,139.2
Mersey,England,21,17.5,1200,200,156.0,2730.0,919.4,28.9,100.3
Meuse,Nthlnds/Belgium,317,9.1,34900,250,230.0,2089.1,742.3,36.0,65.0
Mississippi,USA,16100,5.0,3220000,30,63.0,315.0,691.7,19.0,114.8
Murray-Darling,Australia,318,0.3,1073000,1,15.0,4.4,74.8,4.4,53.6
Nelson,Canada,2370,2.2,1070000,2,5.0,11.1,248.6,21.0,37.3
Niger,W_Africa,7000,6.2,1125000,20,7.0,43.6,555.2,9.6,181.6
Nile,NE_Africa,950,0.3,2960000,50,20.0,6.4,50.9,10.2,15.7
Orange,S_Africa,170,0.2,1020000,20,50.0,8.3,154.9,23.0,18.1
Orinoco,Venezuela,33900,33.9,1000000,2,6.0,203.4,92.5,3.0,97.3
Parana,Argentina,15900,5.7,2800000,10,14.2,80.6,216.2,9.9,75.8
Po,Italy,1470,22.0,66700,232,102.0,2247.3,1237.5,46.0,84.8
Rhine,Europe,2200,11.9,185300,300,286.0,3395.6,1647.9,60.0,86.6
Rhone,France,1700,17.7,96000,100,57.2,1012.9,695.9,30.0,73.2
Shannon,Ireland,190,13.5,14000,35,54.0,727.7,252.8,8.6,92.7
Stikine,Canada/USA,1100,22.0,50000,1,6.1,134.2,76.8,1.0,242.1
St._Lawrence,Canada/USA,10700,10.4,1025000,15,16.0,167.0,673.2,21.0,101.1
Susquehanna,USA,1100,15.1,73000,100,66.0,994.5,821.5,25.0,103.6
Tees,England,50,27.7,1806,100,75.0,2076.5,608.7,33.0,58.2
Thames,England,78,7.8,9950,400,520.0,4076.4,1125.1,61.0,58.2
Tiber,Italy,230,13.5,17000,262,100.0,1352.9,1237.5,46.0,84.8
Uruguay,S_America,3850,10.5,365000,10,29.0,305.9,355.6,13.7,86.1
Vistula,Poland,1100,5.5,200000,120,70.5,387.8,832.8,47.0,55.9
Volga,Russia,8200,6.1,1350000,50,30.0,182.2,151.8,13.0,36.8
Yangtze,China,29000,15.4,1900000,200,58.2,897.0,370.5,10.0,116.8
Yukon,Canada,6180,7.4,831000,0,9.3,69.2,185.4,7.8,78.5
Zaire,Zaire,39730,10.4,3820000,11,6.0,62.4,467.2,10.0,147.3
Zambezi,SE_Africa,3200,2.5,1300000,15,9.3,22.9,138.5,8.4,51.8