# spaeth2_07.txt
#
#  Discussion:
#
#    Data matrix with 89 rows and 3 columns
#
#    This data represents, for each of 89 postal zones in Bavaria,
#
#      x1, the area of each zone,
#      x2, the population of each zone,
#      x3, the population density of each zone, that is, x2 / x1.
#
#    The districts are listed below in order, corresponding to the
#    data.  We list the index, the postal code, and the name of the
#    district:
#
#     1  800  Muenchen
#     2  801  Muenchen-Land Ost
#     3  802  Muenchen-Land Sued
#     4  803  Muenchen-Land West
#     5  804  Muenchen-Land Nord
#     6  805  Freising
#     7  806  Dachau
#     8  807  Ingolstadt
#     9  808  Fuerstenfeldbruck
#    10  809  Wasserburg
#    11  810  Garmisch-Partenkirchen
#    12  811  Murnau
#    13  812  Weilheim
#    14  813  Starnberg
#    15  815  Holzkirchen
#    16  816  Miesbach
#    17  817  Bad Toelz
#    18  818  Tegernsee
#    19  819  Wolfratshausen
#    20  820  Rosenheim
#    21  821  Prien
#    22  822  Traunstein
#    23  823  Bad Reichenhall
#    24  824  Berchtesgaden
#    25  825  Dorfen
#    26  826  Muehldorf
#    27  830  Landshut
#    28  831  Landshut
#    29  833  Eggenfelden
#    30  834  Pfarrkirchen
#    31  835  Plattling
#    32  836  Deggendorf
#    33  837  Regen
#    34  836  Landau (Isar)
#    35  839  Passau
#    36  840  Regensburg
#    37  841  Regensburg
#    38  842  Kelheim
#    39  843  Neumarkt
#    40  844  Straubing
#    41  845  Amberg
#    42  846  Schwandorf
#    43  847  Nabburg
#    44  848  Weiden
#    45  849  Cham
#    46  850  Nuernberg
#    47  851  Fuerth
#    48  852  Erlangen
#    49  853  Neustadt (Aisch)
#    50  854  Schwabach
#    51  855  Forchheim
#    52  856  Lauf
#    53  857  Pegnitz
#    54  858  Bayreuth
#    55  859  Marktredwitz
#    56  860  Bamberg
#    57  862  Lichtenfels
#    58  863  Coburg
#    59  864  Kronach
#    60  865  Kulmbach
#    61  866  Muenchberg
#    62  867  Hof
#    63  870  Wuerzburg
#    64  871  Kitzingen
#    65  872  Schweinfurt
#    66  873  Bad Kissingen
#    67  874  Bad Neustadt (Saale)
#    68  875  Aschaffenburg
#    69  876  Miltenberg
#    70  877  Lohr
#    71  878  Gemuenden
#    72  880  Ansbach
#    73  882  Gunzenhausen
#    74  883  Treuchtlingen
#    75  885  Donauwoerth
#    76  886  Noerdlingen
#    77  887  Guenzburg
#    78  888  Dillingen
#    79  889  Aichach
#    80  890  Augsburg
#    81  891  Landsberg
#    82  892  Schongau
#    83  893  Schwabmuenchen
#    84  894  Memmingen
#    85  895  Kaufbeuren
#    86  896  Kempten
#    87  897  Immenstadt
#    88  898  Oberstdorf
#    89  899  Lindau
#
#  Modified:
#
#    02 May 2002
#
#  Reference:
#
#    Helmut Spaeth,
#    Cluster Analysis Algorithms 
#    for Data Reduction and Classification of Objects,
#    Ellis Horwood, 1980, pages 91-92.
#
 330.93  1306024  3946.5
 759.12   138706   182.1
 209.38    55749   266.3
 315.05   135167   429.0
 181.65    40366   272.2
1085.39   131198   120.9
1019.17   121499   119.2
 576.91   141663   245.6
 365.02    54456   149.2
 568.54    47490    83.5
 568.70    53483    94.0
 459.37    27026    58.8
 582.19    60539   104.0
 229.36    38607   168.3
 322.42    23234    72.1
 347.73    30889    88.8
 671.30    36300    54.1
 271.42    21515    79.3
 261.44    42482   162.5
 961.91   154739   160.9
 441.50    39590    89.7
1085.09   135459   124.8
  97.93    23578   240.8
 125.10    24836   198.5
 505.88    38568    76.2
1207.38   174628   144.6
1336.79   152268   113.9
1055.09    79532    75.4
 456.25    33033    72.4
 474.83    37083    78.1
1692.89   156557    92.5
  24.49    20087   820.2
 858.06    74383    86.7
 528.88    40814    77.2
1744.45   202356   116.0
 679.88   188916   277.9
1123.26   109480    97.5
 744.65    67574    90.7
1114.27    91987    82.6
 973.13   106762   109.7
1199.54   136177   113.5
 593.69    61065   102.9
 653.04    46071    70.5
1053.85   142163   134.9
1191.14   102431    86.0
 984.24   685783   696.6
  55.61    97563  1754.4
 310.62   145511   468.5
 889.59    68424    76.9
 757.54   104125   137.5
 747.97    98102   131.2
 528.02    75965   143.9
 432.77    41756    96.5
 939.95   150127   159.7
 887.22   123161   138.8
1726.77   225552   130.6
 538.57    89989   167.1
 453.58   110799   244.3
 489.63    74806   152.8
 520.87    72111   138.4
 223.60    35439   158.5
 900.46   190239   211.3
1282.67   270471   210.9
 658.07    81060   123.2
1515.92   224789   148.3
 504.19    66731   132.4
 870.41    77400    88.9
 710.54   238722   336.0
 410.80    57350   139.6
 446.85    60078   134.4
 859.52    77689    90.4
1672.24   174620   104.4
 641.85    53229    82.9
1209.98   102429    84.7
1415.78   135007    95.4
 539.99    51216    94.8
 477.40    71767   150.3
 561.72    62753   111.7
 713.16    61575    86.3
1511.03   467367   309.3
 577.75    60277   104.3
 396.82    38152    96.1
 717.49    72692   101.3
1026.50   123112   119.9
1048.81   120165   114.6
 771.94   115852   150.1
 592.27    58453    98.7
 319.08    13348    41.8
 323.48    69094   213.6