Computing County Dissimilarity Indexes (g16)

dissim.py output

Checking shares in 20 random counties:

              total  white  nonwhite
state county                        
01    017       1.0    1.0       1.0
55    045       1.0    1.0       1.0
13    083       1.0    1.0       1.0
37    189       1.0    1.0       1.0
09    003       1.0    1.0       1.0
53    009       1.0    1.0       1.0
28    097       1.0    1.0       1.0
04    003       1.0    1.0       1.0
17    071       1.0    1.0       1.0
21    091       1.0    1.0       1.0
13    259       1.0    1.0       1.0
27    121       1.0    1.0       1.0
26    109       1.0    1.0       1.0
20    071       1.0    1.0       1.0
37    087       1.0    1.0       1.0
22    095       1.0    1.0       1.0
37    145       1.0    1.0       1.0
36    117       1.0    1.0       1.0
51    005       1.0    1.0       1.0
46    123       1.0    1.0       1.0

Total population:

total       326.289971
white       237.188538
nonwhite     89.101433
dtype: float64

Population and population share for large counties:

total       255.819425
white       176.872385
nonwhite     78.947040
dtype: float64
total       78.402479
white       74.570376
nonwhite    88.603558
dtype: float64

Checking merge of county names:

both          621
left_only       0
right_only      0
Name: _merge, dtype: int64

NY counties from lowest dissimilarity to highest:

    state county    total  ...  num_bg  dissim                          NAME
366    36    091   227377  ...     139   34.96     Saratoga County, New York
361    36    079    99070  ...      69   36.52       Putnam County, New York
370    36    109   102962  ...      64   39.57     Tompkins County, New York
371    36    111   179303  ...     152   39.68       Ulster County, New York
350    36    027   293894  ...     248   41.96     Dutchess County, New York
360    36    071   378227  ...     276   43.07       Orange County, New York
347    36    005  1437872  ...    1154   43.43        Bronx County, New York
372    36    119   968815  ...     704   45.65  Westchester County, New York
352    36    045   114448  ...      96   46.62    Jefferson County, New York
364    36    085   474101  ...     338   46.80     Richmond County, New York
369    36    105    75211  ...      78   46.87     Sullivan County, New York
348    36    007   194402  ...     204   47.52       Broome County, New York
365    36    087   323686  ...     203   47.55     Rockland County, New York
346    36    001   307426  ...     235   47.64       Albany County, New York
368    36    103  1487901  ...     999   47.74      Suffolk County, New York
349    36    015    85740  ...      87   49.45      Chemung County, New York
362    36    081  2298513  ...    1746   50.46       Queens County, New York
356    36    061  1632480  ...    1170   51.39     New York County, New York
357    36    063   211704  ...     176   51.66      Niagara County, New York
354    36    055   744248  ...     609   52.68       Monroe County, New York
367    36    093   154883  ...     138   53.03  Schenectady County, New York
363    36    083   159431  ...     125   53.63   Rensselaer County, New York
359    36    067   464242  ...     380   54.03     Onondaga County, New York
353    36    047  2600747  ...    2085   54.60        Kings County, New York
355    36    059  1356564  ...    1143   54.96       Nassau County, New York
358    36    065   230782  ...     187   57.10       Oneida County, New York
351    36    029   919866  ...     779   64.48         Erie County, New York

[27 rows x 8 columns]

Population by bin:

           total      white   nonwhite
bin                                   
20.0    2.990831   2.167590   0.823241
30.0   62.857616  47.304714  15.552902
40.0  103.393883  70.803236  32.590647
50.0   63.073961  42.940927  20.133034
60.0   21.405450  12.557002   8.848448
70.0    1.917457   1.030620   0.886837
80.0    0.108705   0.051934   0.056771
90.0    0.071522   0.016362   0.055160

Percent of population by bin:

          total      white   nonwhite
bin                                  
20.0   1.169118   1.225511   1.042776
30.0  24.571088  26.745110  19.700424
40.0  40.416744  40.030690  41.281658
50.0  24.655657  24.277915  25.501949
60.0   8.367406   7.099470  11.208081
70.0   0.749535   0.582691   1.123332
80.0   0.042493   0.029362   0.071910
90.0   0.027958   0.009251   0.069870
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Peter J Wilcoxen, The Maxwell School, Syracuse University
Revised 03/14/2022