github.com/cockroachdb/cockroach@v20.2.0-alpha.1+incompatible/pkg/workload/faker/dict.go (about)

     1  // Copyright 2019 The Cockroach Authors.
     2  //
     3  // Use of this software is governed by the Business Source License
     4  // included in the file licenses/BSL.txt.
     5  //
     6  // As of the Change Date specified in that file, in accordance with
     7  // the Business Source License, use of this software will be governed
     8  // by the Apache License, Version 2.0, included in the file
     9  // licenses/APL.txt.
    10  
    11  package faker
    12  
    13  // The movr workload uses this library and is built into the cockroach binary.
    14  // The common case is that someone won't be using movr, so avoid the allocations
    15  // by using functions instead of static dicts.
    16  
    17  func words() *weightedEntries {
    18  	return makeWeightedEntries(
    19  		`a`, 1.0,
    20  		`ability`, 1.0,
    21  		`able`, 1.0,
    22  		`about`, 1.0,
    23  		`above`, 1.0,
    24  		`accept`, 1.0,
    25  		`according`, 1.0,
    26  		`account`, 1.0,
    27  		`across`, 1.0,
    28  		`act`, 1.0,
    29  		`action`, 1.0,
    30  		`activity`, 1.0,
    31  		`actually`, 1.0,
    32  		`add`, 1.0,
    33  		`address`, 1.0,
    34  		`administration`, 1.0,
    35  		`admit`, 1.0,
    36  		`adult`, 1.0,
    37  		`affect`, 1.0,
    38  		`after`, 1.0,
    39  		`again`, 1.0,
    40  		`against`, 1.0,
    41  		`age`, 1.0,
    42  		`agency`, 1.0,
    43  		`agent`, 1.0,
    44  		`ago`, 1.0,
    45  		`agree`, 1.0,
    46  		`agreement`, 1.0,
    47  		`ahead`, 1.0,
    48  		`air`, 1.0,
    49  		`all`, 1.0,
    50  		`allow`, 1.0,
    51  		`almost`, 1.0,
    52  		`alone`, 1.0,
    53  		`along`, 1.0,
    54  		`already`, 1.0,
    55  		`also`, 1.0,
    56  		`although`, 1.0,
    57  		`always`, 1.0,
    58  		`American`, 1.0,
    59  		`among`, 1.0,
    60  		`amount`, 1.0,
    61  		`analysis`, 1.0,
    62  		`and`, 1.0,
    63  		`animal`, 1.0,
    64  		`another`, 1.0,
    65  		`answer`, 1.0,
    66  		`any`, 1.0,
    67  		`anyone`, 1.0,
    68  		`anything`, 1.0,
    69  		`appear`, 1.0,
    70  		`apply`, 1.0,
    71  		`approach`, 1.0,
    72  		`area`, 1.0,
    73  		`argue`, 1.0,
    74  		`arm`, 1.0,
    75  		`around`, 1.0,
    76  		`arrive`, 1.0,
    77  		`art`, 1.0,
    78  		`article`, 1.0,
    79  		`artist`, 1.0,
    80  		`as`, 1.0,
    81  		`ask`, 1.0,
    82  		`assume`, 1.0,
    83  		`at`, 1.0,
    84  		`attack`, 1.0,
    85  		`attention`, 1.0,
    86  		`attorney`, 1.0,
    87  		`audience`, 1.0,
    88  		`author`, 1.0,
    89  		`authority`, 1.0,
    90  		`available`, 1.0,
    91  		`avoid`, 1.0,
    92  		`away`, 1.0,
    93  		`baby`, 1.0,
    94  		`back`, 1.0,
    95  		`bad`, 1.0,
    96  		`bag`, 1.0,
    97  		`ball`, 1.0,
    98  		`bank`, 1.0,
    99  		`bar`, 1.0,
   100  		`base`, 1.0,
   101  		`be`, 1.0,
   102  		`beat`, 1.0,
   103  		`beautiful`, 1.0,
   104  		`because`, 1.0,
   105  		`become`, 1.0,
   106  		`bed`, 1.0,
   107  		`before`, 1.0,
   108  		`begin`, 1.0,
   109  		`behavior`, 1.0,
   110  		`behind`, 1.0,
   111  		`believe`, 1.0,
   112  		`benefit`, 1.0,
   113  		`best`, 1.0,
   114  		`better`, 1.0,
   115  		`between`, 1.0,
   116  		`beyond`, 1.0,
   117  		`big`, 1.0,
   118  		`bill`, 1.0,
   119  		`billion`, 1.0,
   120  		`bit`, 1.0,
   121  		`black`, 1.0,
   122  		`blood`, 1.0,
   123  		`blue`, 1.0,
   124  		`board`, 1.0,
   125  		`body`, 1.0,
   126  		`book`, 1.0,
   127  		`born`, 1.0,
   128  		`both`, 1.0,
   129  		`box`, 1.0,
   130  		`boy`, 1.0,
   131  		`break`, 1.0,
   132  		`bring`, 1.0,
   133  		`brother`, 1.0,
   134  		`budget`, 1.0,
   135  		`build`, 1.0,
   136  		`building`, 1.0,
   137  		`business`, 1.0,
   138  		`but`, 1.0,
   139  		`buy`, 1.0,
   140  		`by`, 1.0,
   141  		`call`, 1.0,
   142  		`camera`, 1.0,
   143  		`campaign`, 1.0,
   144  		`can`, 1.0,
   145  		`candidate`, 1.0,
   146  		`capital`, 1.0,
   147  		`car`, 1.0,
   148  		`card`, 1.0,
   149  		`care`, 1.0,
   150  		`career`, 1.0,
   151  		`carry`, 1.0,
   152  		`case`, 1.0,
   153  		`catch`, 1.0,
   154  		`cause`, 1.0,
   155  		`cell`, 1.0,
   156  		`center`, 1.0,
   157  		`central`, 1.0,
   158  		`century`, 1.0,
   159  		`certain`, 1.0,
   160  		`certainly`, 1.0,
   161  		`chair`, 1.0,
   162  		`challenge`, 1.0,
   163  		`chance`, 1.0,
   164  		`change`, 1.0,
   165  		`character`, 1.0,
   166  		`charge`, 1.0,
   167  		`check`, 1.0,
   168  		`child`, 1.0,
   169  		`choice`, 1.0,
   170  		`choose`, 1.0,
   171  		`church`, 1.0,
   172  		`citizen`, 1.0,
   173  		`city`, 1.0,
   174  		`civil`, 1.0,
   175  		`claim`, 1.0,
   176  		`class`, 1.0,
   177  		`clear`, 1.0,
   178  		`clearly`, 1.0,
   179  		`close`, 1.0,
   180  		`coach`, 1.0,
   181  		`cold`, 1.0,
   182  		`collection`, 1.0,
   183  		`college`, 1.0,
   184  		`color`, 1.0,
   185  		`commercial`, 1.0,
   186  		`common`, 1.0,
   187  		`community`, 1.0,
   188  		`company`, 1.0,
   189  		`compare`, 1.0,
   190  		`computer`, 1.0,
   191  		`concern`, 1.0,
   192  		`condition`, 1.0,
   193  		`conference`, 1.0,
   194  		`Congress`, 1.0,
   195  		`consider`, 1.0,
   196  		`consumer`, 1.0,
   197  		`contain`, 1.0,
   198  		`continue`, 1.0,
   199  		`control`, 1.0,
   200  		`cost`, 1.0,
   201  		`could`, 1.0,
   202  		`country`, 1.0,
   203  		`couple`, 1.0,
   204  		`course`, 1.0,
   205  		`court`, 1.0,
   206  		`cover`, 1.0,
   207  		`create`, 1.0,
   208  		`crime`, 1.0,
   209  		`cultural`, 1.0,
   210  		`culture`, 1.0,
   211  		`cup`, 1.0,
   212  		`current`, 1.0,
   213  		`customer`, 1.0,
   214  		`cut`, 1.0,
   215  		`dark`, 1.0,
   216  		`data`, 1.0,
   217  		`daughter`, 1.0,
   218  		`day`, 1.0,
   219  		`deal`, 1.0,
   220  		`debate`, 1.0,
   221  		`decade`, 1.0,
   222  		`decide`, 1.0,
   223  		`decision`, 1.0,
   224  		`deep`, 1.0,
   225  		`defense`, 1.0,
   226  		`degree`, 1.0,
   227  		`Democrat`, 1.0,
   228  		`democratic`, 1.0,
   229  		`describe`, 1.0,
   230  		`design`, 1.0,
   231  		`despite`, 1.0,
   232  		`detail`, 1.0,
   233  		`determine`, 1.0,
   234  		`develop`, 1.0,
   235  		`development`, 1.0,
   236  		`difference`, 1.0,
   237  		`different`, 1.0,
   238  		`difficult`, 1.0,
   239  		`dinner`, 1.0,
   240  		`direction`, 1.0,
   241  		`director`, 1.0,
   242  		`discover`, 1.0,
   243  		`discuss`, 1.0,
   244  		`discussion`, 1.0,
   245  		`do`, 1.0,
   246  		`doctor`, 1.0,
   247  		`dog`, 1.0,
   248  		`door`, 1.0,
   249  		`down`, 1.0,
   250  		`draw`, 1.0,
   251  		`dream`, 1.0,
   252  		`drive`, 1.0,
   253  		`drop`, 1.0,
   254  		`drug`, 1.0,
   255  		`during`, 1.0,
   256  		`each`, 1.0,
   257  		`early`, 1.0,
   258  		`east`, 1.0,
   259  		`easy`, 1.0,
   260  		`eat`, 1.0,
   261  		`economic`, 1.0,
   262  		`economy`, 1.0,
   263  		`edge`, 1.0,
   264  		`education`, 1.0,
   265  		`effect`, 1.0,
   266  		`effort`, 1.0,
   267  		`eight`, 1.0,
   268  		`either`, 1.0,
   269  		`election`, 1.0,
   270  		`else`, 1.0,
   271  		`employee`, 1.0,
   272  		`end`, 1.0,
   273  		`energy`, 1.0,
   274  		`enjoy`, 1.0,
   275  		`enough`, 1.0,
   276  		`enter`, 1.0,
   277  		`entire`, 1.0,
   278  		`environment`, 1.0,
   279  		`environmental`, 1.0,
   280  		`especially`, 1.0,
   281  		`establish`, 1.0,
   282  		`even`, 1.0,
   283  		`evening`, 1.0,
   284  		`event`, 1.0,
   285  		`ever`, 1.0,
   286  		`every`, 1.0,
   287  		`everybody`, 1.0,
   288  		`everyone`, 1.0,
   289  		`everything`, 1.0,
   290  		`evidence`, 1.0,
   291  		`exactly`, 1.0,
   292  		`example`, 1.0,
   293  		`executive`, 1.0,
   294  		`exist`, 1.0,
   295  		`expect`, 1.0,
   296  		`experience`, 1.0,
   297  		`expert`, 1.0,
   298  		`explain`, 1.0,
   299  		`eye`, 1.0,
   300  		`face`, 1.0,
   301  		`fact`, 1.0,
   302  		`factor`, 1.0,
   303  		`fall`, 1.0,
   304  		`family`, 1.0,
   305  		`far`, 1.0,
   306  		`fast`, 1.0,
   307  		`father`, 1.0,
   308  		`fear`, 1.0,
   309  		`federal`, 1.0,
   310  		`feel`, 1.0,
   311  		`feeling`, 1.0,
   312  		`few`, 1.0,
   313  		`field`, 1.0,
   314  		`fight`, 1.0,
   315  		`figure`, 1.0,
   316  		`fill`, 1.0,
   317  		`film`, 1.0,
   318  		`final`, 1.0,
   319  		`finally`, 1.0,
   320  		`financial`, 1.0,
   321  		`find`, 1.0,
   322  		`fine`, 1.0,
   323  		`finish`, 1.0,
   324  		`fire`, 1.0,
   325  		`firm`, 1.0,
   326  		`first`, 1.0,
   327  		`fish`, 1.0,
   328  		`five`, 1.0,
   329  		`floor`, 1.0,
   330  		`fly`, 1.0,
   331  		`focus`, 1.0,
   332  		`follow`, 1.0,
   333  		`food`, 1.0,
   334  		`foot`, 1.0,
   335  		`for`, 1.0,
   336  		`force`, 1.0,
   337  		`foreign`, 1.0,
   338  		`forget`, 1.0,
   339  		`form`, 1.0,
   340  		`former`, 1.0,
   341  		`forward`, 1.0,
   342  		`four`, 1.0,
   343  		`free`, 1.0,
   344  		`friend`, 1.0,
   345  		`from`, 1.0,
   346  		`front`, 1.0,
   347  		`full`, 1.0,
   348  		`fund`, 1.0,
   349  		`future`, 1.0,
   350  		`game`, 1.0,
   351  		`garden`, 1.0,
   352  		`gas`, 1.0,
   353  		`general`, 1.0,
   354  		`generation`, 1.0,
   355  		`get`, 1.0,
   356  		`girl`, 1.0,
   357  		`give`, 1.0,
   358  		`glass`, 1.0,
   359  		`go`, 1.0,
   360  		`goal`, 1.0,
   361  		`good`, 1.0,
   362  		`government`, 1.0,
   363  		`great`, 1.0,
   364  		`green`, 1.0,
   365  		`ground`, 1.0,
   366  		`group`, 1.0,
   367  		`grow`, 1.0,
   368  		`growth`, 1.0,
   369  		`guess`, 1.0,
   370  		`gun`, 1.0,
   371  		`guy`, 1.0,
   372  		`hair`, 1.0,
   373  		`half`, 1.0,
   374  		`hand`, 1.0,
   375  		`happen`, 1.0,
   376  		`happy`, 1.0,
   377  		`hard`, 1.0,
   378  		`have`, 1.0,
   379  		`he`, 1.0,
   380  		`head`, 1.0,
   381  		`health`, 1.0,
   382  		`hear`, 1.0,
   383  		`heart`, 1.0,
   384  		`heavy`, 1.0,
   385  		`help`, 1.0,
   386  		`her`, 1.0,
   387  		`here`, 1.0,
   388  		`herself`, 1.0,
   389  		`high`, 1.0,
   390  		`him`, 1.0,
   391  		`himself`, 1.0,
   392  		`his`, 1.0,
   393  		`history`, 1.0,
   394  		`hit`, 1.0,
   395  		`hold`, 1.0,
   396  		`home`, 1.0,
   397  		`hope`, 1.0,
   398  		`hospital`, 1.0,
   399  		`hot`, 1.0,
   400  		`hotel`, 1.0,
   401  		`hour`, 1.0,
   402  		`house`, 1.0,
   403  		`how`, 1.0,
   404  		`however`, 1.0,
   405  		`huge`, 1.0,
   406  		`human`, 1.0,
   407  		`hundred`, 1.0,
   408  		`husband`, 1.0,
   409  		`I`, 1.0,
   410  		`idea`, 1.0,
   411  		`identify`, 1.0,
   412  		`if`, 1.0,
   413  		`image`, 1.0,
   414  		`imagine`, 1.0,
   415  		`impact`, 1.0,
   416  		`important`, 1.0,
   417  		`improve`, 1.0,
   418  		`in`, 1.0,
   419  		`include`, 1.0,
   420  		`including`, 1.0,
   421  		`increase`, 1.0,
   422  		`indeed`, 1.0,
   423  		`indicate`, 1.0,
   424  		`individual`, 1.0,
   425  		`industry`, 1.0,
   426  		`information`, 1.0,
   427  		`inside`, 1.0,
   428  		`instead`, 1.0,
   429  		`institution`, 1.0,
   430  		`interest`, 1.0,
   431  		`interesting`, 1.0,
   432  		`international`, 1.0,
   433  		`interview`, 1.0,
   434  		`into`, 1.0,
   435  		`investment`, 1.0,
   436  		`involve`, 1.0,
   437  		`issue`, 1.0,
   438  		`it`, 1.0,
   439  		`item`, 1.0,
   440  		`its`, 1.0,
   441  		`itself`, 1.0,
   442  		`job`, 1.0,
   443  		`join`, 1.0,
   444  		`just`, 1.0,
   445  		`keep`, 1.0,
   446  		`key`, 1.0,
   447  		`kid`, 1.0,
   448  		`kind`, 1.0,
   449  		`kitchen`, 1.0,
   450  		`know`, 1.0,
   451  		`knowledge`, 1.0,
   452  		`land`, 1.0,
   453  		`language`, 1.0,
   454  		`large`, 1.0,
   455  		`last`, 1.0,
   456  		`late`, 1.0,
   457  		`later`, 1.0,
   458  		`laugh`, 1.0,
   459  		`law`, 1.0,
   460  		`lawyer`, 1.0,
   461  		`lay`, 1.0,
   462  		`lead`, 1.0,
   463  		`leader`, 1.0,
   464  		`learn`, 1.0,
   465  		`least`, 1.0,
   466  		`leave`, 1.0,
   467  		`left`, 1.0,
   468  		`leg`, 1.0,
   469  		`less`, 1.0,
   470  		`let`, 1.0,
   471  		`letter`, 1.0,
   472  		`level`, 1.0,
   473  		`life`, 1.0,
   474  		`light`, 1.0,
   475  		`like`, 1.0,
   476  		`likely`, 1.0,
   477  		`line`, 1.0,
   478  		`list`, 1.0,
   479  		`listen`, 1.0,
   480  		`little`, 1.0,
   481  		`live`, 1.0,
   482  		`local`, 1.0,
   483  		`long`, 1.0,
   484  		`look`, 1.0,
   485  		`lose`, 1.0,
   486  		`loss`, 1.0,
   487  		`lot`, 1.0,
   488  		`low`, 1.0,
   489  		`machine`, 1.0,
   490  		`magazine`, 1.0,
   491  		`main`, 1.0,
   492  		`maintain`, 1.0,
   493  		`major`, 1.0,
   494  		`majority`, 1.0,
   495  		`make`, 1.0,
   496  		`man`, 1.0,
   497  		`manage`, 1.0,
   498  		`management`, 1.0,
   499  		`manager`, 1.0,
   500  		`many`, 1.0,
   501  		`market`, 1.0,
   502  		`marriage`, 1.0,
   503  		`material`, 1.0,
   504  		`matter`, 1.0,
   505  		`may`, 1.0,
   506  		`maybe`, 1.0,
   507  		`me`, 1.0,
   508  		`mean`, 1.0,
   509  		`measure`, 1.0,
   510  		`media`, 1.0,
   511  		`medical`, 1.0,
   512  		`meet`, 1.0,
   513  		`meeting`, 1.0,
   514  		`member`, 1.0,
   515  		`memory`, 1.0,
   516  		`mention`, 1.0,
   517  		`message`, 1.0,
   518  		`method`, 1.0,
   519  		`middle`, 1.0,
   520  		`might`, 1.0,
   521  		`military`, 1.0,
   522  		`million`, 1.0,
   523  		`mind`, 1.0,
   524  		`minute`, 1.0,
   525  		`miss`, 1.0,
   526  		`mission`, 1.0,
   527  		`model`, 1.0,
   528  		`modern`, 1.0,
   529  		`moment`, 1.0,
   530  		`money`, 1.0,
   531  		`month`, 1.0,
   532  		`more`, 1.0,
   533  		`morning`, 1.0,
   534  		`most`, 1.0,
   535  		`mother`, 1.0,
   536  		`mouth`, 1.0,
   537  		`move`, 1.0,
   538  		`movement`, 1.0,
   539  		`movie`, 1.0,
   540  		`Mr`, 1.0,
   541  		`Mrs`, 1.0,
   542  		`much`, 1.0,
   543  		`music`, 1.0,
   544  		`must`, 1.0,
   545  		`my`, 1.0,
   546  		`myself`, 1.0,
   547  		`name`, 1.0,
   548  		`nation`, 1.0,
   549  		`national`, 1.0,
   550  		`natural`, 1.0,
   551  		`nature`, 1.0,
   552  		`near`, 1.0,
   553  		`nearly`, 1.0,
   554  		`necessary`, 1.0,
   555  		`need`, 1.0,
   556  		`network`, 1.0,
   557  		`never`, 1.0,
   558  		`new`, 1.0,
   559  		`news`, 1.0,
   560  		`newspaper`, 1.0,
   561  		`next`, 1.0,
   562  		`nice`, 1.0,
   563  		`night`, 1.0,
   564  		`no`, 1.0,
   565  		`none`, 1.0,
   566  		`nor`, 1.0,
   567  		`north`, 1.0,
   568  		`not`, 1.0,
   569  		`note`, 1.0,
   570  		`nothing`, 1.0,
   571  		`notice`, 1.0,
   572  		`now`, 1.0,
   573  		`number`, 1.0,
   574  		`occur`, 1.0,
   575  		`of`, 1.0,
   576  		`off`, 1.0,
   577  		`offer`, 1.0,
   578  		`office`, 1.0,
   579  		`officer`, 1.0,
   580  		`official`, 1.0,
   581  		`often`, 1.0,
   582  		`oil`, 1.0,
   583  		`ok`, 1.0,
   584  		`old`, 1.0,
   585  		`on`, 1.0,
   586  		`once`, 1.0,
   587  		`one`, 1.0,
   588  		`only`, 1.0,
   589  		`onto`, 1.0,
   590  		`open`, 1.0,
   591  		`operation`, 1.0,
   592  		`opportunity`, 1.0,
   593  		`option`, 1.0,
   594  		`or`, 1.0,
   595  		`order`, 1.0,
   596  		`organization`, 1.0,
   597  		`other`, 1.0,
   598  		`others`, 1.0,
   599  		`our`, 1.0,
   600  		`out`, 1.0,
   601  		`outside`, 1.0,
   602  		`over`, 1.0,
   603  		`own`, 1.0,
   604  		`owner`, 1.0,
   605  		`page`, 1.0,
   606  		`painting`, 1.0,
   607  		`paper`, 1.0,
   608  		`parent`, 1.0,
   609  		`part`, 1.0,
   610  		`participant`, 1.0,
   611  		`particular`, 1.0,
   612  		`particularly`, 1.0,
   613  		`partner`, 1.0,
   614  		`party`, 1.0,
   615  		`pass`, 1.0,
   616  		`past`, 1.0,
   617  		`pattern`, 1.0,
   618  		`pay`, 1.0,
   619  		`peace`, 1.0,
   620  		`people`, 1.0,
   621  		`per`, 1.0,
   622  		`perform`, 1.0,
   623  		`performance`, 1.0,
   624  		`perhaps`, 1.0,
   625  		`person`, 1.0,
   626  		`personal`, 1.0,
   627  		`phone`, 1.0,
   628  		`physical`, 1.0,
   629  		`pick`, 1.0,
   630  		`picture`, 1.0,
   631  		`piece`, 1.0,
   632  		`place`, 1.0,
   633  		`plan`, 1.0,
   634  		`plant`, 1.0,
   635  		`play`, 1.0,
   636  		`player`, 1.0,
   637  		`PM`, 1.0,
   638  		`point`, 1.0,
   639  		`police`, 1.0,
   640  		`policy`, 1.0,
   641  		`political`, 1.0,
   642  		`politics`, 1.0,
   643  		`poor`, 1.0,
   644  		`popular`, 1.0,
   645  		`population`, 1.0,
   646  		`position`, 1.0,
   647  		`positive`, 1.0,
   648  		`possible`, 1.0,
   649  		`power`, 1.0,
   650  		`practice`, 1.0,
   651  		`prepare`, 1.0,
   652  		`present`, 1.0,
   653  		`president`, 1.0,
   654  		`pressure`, 1.0,
   655  		`pretty`, 1.0,
   656  		`prevent`, 1.0,
   657  		`price`, 1.0,
   658  		`probably`, 1.0,
   659  		`process`, 1.0,
   660  		`produce`, 1.0,
   661  		`product`, 1.0,
   662  		`production`, 1.0,
   663  		`professional`, 1.0,
   664  		`professor`, 1.0,
   665  		`program`, 1.0,
   666  		`project`, 1.0,
   667  		`property`, 1.0,
   668  		`protect`, 1.0,
   669  		`prove`, 1.0,
   670  		`provide`, 1.0,
   671  		`public`, 1.0,
   672  		`pull`, 1.0,
   673  		`purpose`, 1.0,
   674  		`push`, 1.0,
   675  		`put`, 1.0,
   676  		`quality`, 1.0,
   677  		`question`, 1.0,
   678  		`quickly`, 1.0,
   679  		`quite`, 1.0,
   680  		`race`, 1.0,
   681  		`radio`, 1.0,
   682  		`raise`, 1.0,
   683  		`range`, 1.0,
   684  		`rate`, 1.0,
   685  		`rather`, 1.0,
   686  		`reach`, 1.0,
   687  		`read`, 1.0,
   688  		`ready`, 1.0,
   689  		`real`, 1.0,
   690  		`reality`, 1.0,
   691  		`realize`, 1.0,
   692  		`really`, 1.0,
   693  		`reason`, 1.0,
   694  		`receive`, 1.0,
   695  		`recent`, 1.0,
   696  		`recently`, 1.0,
   697  		`recognize`, 1.0,
   698  		`record`, 1.0,
   699  		`red`, 1.0,
   700  		`reduce`, 1.0,
   701  		`reflect`, 1.0,
   702  		`region`, 1.0,
   703  		`relate`, 1.0,
   704  		`relationship`, 1.0,
   705  		`religious`, 1.0,
   706  		`remain`, 1.0,
   707  		`remember`, 1.0,
   708  		`report`, 1.0,
   709  		`represent`, 1.0,
   710  		`Republican`, 1.0,
   711  		`require`, 1.0,
   712  		`research`, 1.0,
   713  		`resource`, 1.0,
   714  		`respond`, 1.0,
   715  		`response`, 1.0,
   716  		`responsibility`, 1.0,
   717  		`rest`, 1.0,
   718  		`result`, 1.0,
   719  		`return`, 1.0,
   720  		`reveal`, 1.0,
   721  		`rich`, 1.0,
   722  		`right`, 1.0,
   723  		`rise`, 1.0,
   724  		`risk`, 1.0,
   725  		`road`, 1.0,
   726  		`rock`, 1.0,
   727  		`role`, 1.0,
   728  		`room`, 1.0,
   729  		`rule`, 1.0,
   730  		`run`, 1.0,
   731  		`safe`, 1.0,
   732  		`same`, 1.0,
   733  		`save`, 1.0,
   734  		`say`, 1.0,
   735  		`scene`, 1.0,
   736  		`school`, 1.0,
   737  		`science`, 1.0,
   738  		`scientist`, 1.0,
   739  		`score`, 1.0,
   740  		`sea`, 1.0,
   741  		`season`, 1.0,
   742  		`seat`, 1.0,
   743  		`second`, 1.0,
   744  		`section`, 1.0,
   745  		`security`, 1.0,
   746  		`see`, 1.0,
   747  		`seek`, 1.0,
   748  		`seem`, 1.0,
   749  		`sell`, 1.0,
   750  		`send`, 1.0,
   751  		`senior`, 1.0,
   752  		`sense`, 1.0,
   753  		`series`, 1.0,
   754  		`serious`, 1.0,
   755  		`serve`, 1.0,
   756  		`service`, 1.0,
   757  		`set`, 1.0,
   758  		`seven`, 1.0,
   759  		`several`, 1.0,
   760  		`shake`, 1.0,
   761  		`share`, 1.0,
   762  		`she`, 1.0,
   763  		`short`, 1.0,
   764  		`should`, 1.0,
   765  		`shoulder`, 1.0,
   766  		`show`, 1.0,
   767  		`side`, 1.0,
   768  		`sign`, 1.0,
   769  		`significant`, 1.0,
   770  		`similar`, 1.0,
   771  		`simple`, 1.0,
   772  		`simply`, 1.0,
   773  		`since`, 1.0,
   774  		`sing`, 1.0,
   775  		`single`, 1.0,
   776  		`sister`, 1.0,
   777  		`sit`, 1.0,
   778  		`site`, 1.0,
   779  		`situation`, 1.0,
   780  		`six`, 1.0,
   781  		`size`, 1.0,
   782  		`skill`, 1.0,
   783  		`skin`, 1.0,
   784  		`small`, 1.0,
   785  		`smile`, 1.0,
   786  		`so`, 1.0,
   787  		`social`, 1.0,
   788  		`society`, 1.0,
   789  		`soldier`, 1.0,
   790  		`some`, 1.0,
   791  		`somebody`, 1.0,
   792  		`someone`, 1.0,
   793  		`something`, 1.0,
   794  		`sometimes`, 1.0,
   795  		`son`, 1.0,
   796  		`song`, 1.0,
   797  		`soon`, 1.0,
   798  		`sort`, 1.0,
   799  		`sound`, 1.0,
   800  		`source`, 1.0,
   801  		`south`, 1.0,
   802  		`southern`, 1.0,
   803  		`space`, 1.0,
   804  		`speak`, 1.0,
   805  		`special`, 1.0,
   806  		`specific`, 1.0,
   807  		`speech`, 1.0,
   808  		`spend`, 1.0,
   809  		`sport`, 1.0,
   810  		`spring`, 1.0,
   811  		`staff`, 1.0,
   812  		`stage`, 1.0,
   813  		`stand`, 1.0,
   814  		`standard`, 1.0,
   815  		`star`, 1.0,
   816  		`start`, 1.0,
   817  		`state`, 1.0,
   818  		`statement`, 1.0,
   819  		`station`, 1.0,
   820  		`stay`, 1.0,
   821  		`step`, 1.0,
   822  		`still`, 1.0,
   823  		`stock`, 1.0,
   824  		`stop`, 1.0,
   825  		`store`, 1.0,
   826  		`story`, 1.0,
   827  		`strategy`, 1.0,
   828  		`street`, 1.0,
   829  		`strong`, 1.0,
   830  		`structure`, 1.0,
   831  		`student`, 1.0,
   832  		`study`, 1.0,
   833  		`stuff`, 1.0,
   834  		`style`, 1.0,
   835  		`subject`, 1.0,
   836  		`success`, 1.0,
   837  		`successful`, 1.0,
   838  		`such`, 1.0,
   839  		`suddenly`, 1.0,
   840  		`suffer`, 1.0,
   841  		`suggest`, 1.0,
   842  		`summer`, 1.0,
   843  		`support`, 1.0,
   844  		`sure`, 1.0,
   845  		`surface`, 1.0,
   846  		`system`, 1.0,
   847  		`table`, 1.0,
   848  		`take`, 1.0,
   849  		`talk`, 1.0,
   850  		`task`, 1.0,
   851  		`tax`, 1.0,
   852  		`teach`, 1.0,
   853  		`teacher`, 1.0,
   854  		`team`, 1.0,
   855  		`technology`, 1.0,
   856  		`television`, 1.0,
   857  		`tell`, 1.0,
   858  		`ten`, 1.0,
   859  		`tend`, 1.0,
   860  		`term`, 1.0,
   861  		`test`, 1.0,
   862  		`than`, 1.0,
   863  		`thank`, 1.0,
   864  		`that`, 1.0,
   865  		`the`, 1.0,
   866  		`their`, 1.0,
   867  		`them`, 1.0,
   868  		`themselves`, 1.0,
   869  		`then`, 1.0,
   870  		`theory`, 1.0,
   871  		`there`, 1.0,
   872  		`these`, 1.0,
   873  		`they`, 1.0,
   874  		`thing`, 1.0,
   875  		`think`, 1.0,
   876  		`third`, 1.0,
   877  		`this`, 1.0,
   878  		`those`, 1.0,
   879  		`though`, 1.0,
   880  		`thought`, 1.0,
   881  		`thousand`, 1.0,
   882  		`threat`, 1.0,
   883  		`three`, 1.0,
   884  		`through`, 1.0,
   885  		`throughout`, 1.0,
   886  		`throw`, 1.0,
   887  		`thus`, 1.0,
   888  		`time`, 1.0,
   889  		`to`, 1.0,
   890  		`today`, 1.0,
   891  		`together`, 1.0,
   892  		`tonight`, 1.0,
   893  		`too`, 1.0,
   894  		`top`, 1.0,
   895  		`total`, 1.0,
   896  		`tough`, 1.0,
   897  		`toward`, 1.0,
   898  		`town`, 1.0,
   899  		`trade`, 1.0,
   900  		`traditional`, 1.0,
   901  		`training`, 1.0,
   902  		`travel`, 1.0,
   903  		`treat`, 1.0,
   904  		`treatment`, 1.0,
   905  		`tree`, 1.0,
   906  		`trial`, 1.0,
   907  		`trip`, 1.0,
   908  		`trouble`, 1.0,
   909  		`true`, 1.0,
   910  		`truth`, 1.0,
   911  		`try`, 1.0,
   912  		`turn`, 1.0,
   913  		`TV`, 1.0,
   914  		`two`, 1.0,
   915  		`type`, 1.0,
   916  		`under`, 1.0,
   917  		`understand`, 1.0,
   918  		`unit`, 1.0,
   919  		`until`, 1.0,
   920  		`up`, 1.0,
   921  		`upon`, 1.0,
   922  		`us`, 1.0,
   923  		`use`, 1.0,
   924  		`usually`, 1.0,
   925  		`value`, 1.0,
   926  		`various`, 1.0,
   927  		`very`, 1.0,
   928  		`view`, 1.0,
   929  		`visit`, 1.0,
   930  		`voice`, 1.0,
   931  		`vote`, 1.0,
   932  		`wait`, 1.0,
   933  		`walk`, 1.0,
   934  		`wall`, 1.0,
   935  		`want`, 1.0,
   936  		`war`, 1.0,
   937  		`watch`, 1.0,
   938  		`water`, 1.0,
   939  		`way`, 1.0,
   940  		`we`, 1.0,
   941  		`wear`, 1.0,
   942  		`week`, 1.0,
   943  		`weight`, 1.0,
   944  		`well`, 1.0,
   945  		`west`, 1.0,
   946  		`western`, 1.0,
   947  		`what`, 1.0,
   948  		`whatever`, 1.0,
   949  		`when`, 1.0,
   950  		`where`, 1.0,
   951  		`whether`, 1.0,
   952  		`which`, 1.0,
   953  		`while`, 1.0,
   954  		`white`, 1.0,
   955  		`who`, 1.0,
   956  		`whole`, 1.0,
   957  		`whom`, 1.0,
   958  		`whose`, 1.0,
   959  		`why`, 1.0,
   960  		`wide`, 1.0,
   961  		`wife`, 1.0,
   962  		`will`, 1.0,
   963  		`win`, 1.0,
   964  		`wind`, 1.0,
   965  		`window`, 1.0,
   966  		`wish`, 1.0,
   967  		`with`, 1.0,
   968  		`within`, 1.0,
   969  		`without`, 1.0,
   970  		`woman`, 1.0,
   971  		`wonder`, 1.0,
   972  		`word`, 1.0,
   973  		`work`, 1.0,
   974  		`worker`, 1.0,
   975  		`world`, 1.0,
   976  		`worry`, 1.0,
   977  		`would`, 1.0,
   978  		`write`, 1.0,
   979  		`writer`, 1.0,
   980  		`wrong`, 1.0,
   981  		`yard`, 1.0,
   982  		`yeah`, 1.0,
   983  		`year`, 1.0,
   984  		`yes`, 1.0,
   985  		`yet`, 1.0,
   986  		`you`, 1.0,
   987  		`young`, 1.0,
   988  		`your`, 1.0,
   989  		`yourself`, 1.0,
   990  	)
   991  }
   992  
   993  func streetSuffix() *weightedEntries {
   994  	return makeWeightedEntries(
   995  		`Alley`, 1.0,
   996  		`Avenue`, 1.0,
   997  		`Branch`, 1.0,
   998  		`Bridge`, 1.0,
   999  		`Brook`, 1.0,
  1000  		`Brooks`, 1.0,
  1001  		`Burg`, 1.0,
  1002  		`Burgs`, 1.0,
  1003  		`Bypass`, 1.0,
  1004  		`Camp`, 1.0,
  1005  		`Canyon`, 1.0,
  1006  		`Cape`, 1.0,
  1007  		`Causeway`, 1.0,
  1008  		`Center`, 1.0,
  1009  		`Centers`, 1.0,
  1010  		`Circle`, 1.0,
  1011  		`Circles`, 1.0,
  1012  		`Cliff`, 1.0,
  1013  		`Cliffs`, 1.0,
  1014  		`Club`, 1.0,
  1015  		`Common`, 1.0,
  1016  		`Corner`, 1.0,
  1017  		`Corners`, 1.0,
  1018  		`Course`, 1.0,
  1019  		`Court`, 1.0,
  1020  		`Courts`, 1.0,
  1021  		`Cove`, 1.0,
  1022  		`Coves`, 1.0,
  1023  		`Creek`, 1.0,
  1024  		`Crescent`, 1.0,
  1025  		`Crest`, 1.0,
  1026  		`Crossing`, 1.0,
  1027  		`Crossroad`, 1.0,
  1028  		`Curve`, 1.0,
  1029  		`Dale`, 1.0,
  1030  		`Dam`, 1.0,
  1031  		`Divide`, 1.0,
  1032  		`Drive`, 1.0,
  1033  		`Drive`, 1.0,
  1034  		`Drives`, 1.0,
  1035  		`Estate`, 1.0,
  1036  		`Estates`, 1.0,
  1037  		`Expressway`, 1.0,
  1038  		`Extension`, 1.0,
  1039  		`Extensions`, 1.0,
  1040  		`Fall`, 1.0,
  1041  		`Falls`, 1.0,
  1042  		`Ferry`, 1.0,
  1043  		`Field`, 1.0,
  1044  		`Fields`, 1.0,
  1045  		`Flat`, 1.0,
  1046  		`Flats`, 1.0,
  1047  		`Ford`, 1.0,
  1048  		`Fords`, 1.0,
  1049  		`Forest`, 1.0,
  1050  		`Forge`, 1.0,
  1051  		`Forges`, 1.0,
  1052  		`Fork`, 1.0,
  1053  		`Forks`, 1.0,
  1054  		`Fort`, 1.0,
  1055  		`Freeway`, 1.0,
  1056  		`Garden`, 1.0,
  1057  		`Gardens`, 1.0,
  1058  		`Gateway`, 1.0,
  1059  		`Glen`, 1.0,
  1060  		`Glens`, 1.0,
  1061  		`Green`, 1.0,
  1062  		`Greens`, 1.0,
  1063  		`Grove`, 1.0,
  1064  		`Groves`, 1.0,
  1065  		`Harbor`, 1.0,
  1066  		`Harbors`, 1.0,
  1067  		`Haven`, 1.0,
  1068  		`Heights`, 1.0,
  1069  		`Highway`, 1.0,
  1070  		`Hill`, 1.0,
  1071  		`Hills`, 1.0,
  1072  		`Hollow`, 1.0,
  1073  		`Inlet`, 1.0,
  1074  		`Inlet`, 1.0,
  1075  		`Island`, 1.0,
  1076  		`Island`, 1.0,
  1077  		`Islands`, 1.0,
  1078  		`Islands`, 1.0,
  1079  		`Isle`, 1.0,
  1080  		`Isle`, 1.0,
  1081  		`Junction`, 1.0,
  1082  		`Junctions`, 1.0,
  1083  		`Key`, 1.0,
  1084  		`Keys`, 1.0,
  1085  		`Knoll`, 1.0,
  1086  		`Knolls`, 1.0,
  1087  		`Lake`, 1.0,
  1088  		`Lakes`, 1.0,
  1089  		`Land`, 1.0,
  1090  		`Landing`, 1.0,
  1091  		`Lane`, 1.0,
  1092  		`Light`, 1.0,
  1093  		`Lights`, 1.0,
  1094  		`Loaf`, 1.0,
  1095  		`Lock`, 1.0,
  1096  		`Locks`, 1.0,
  1097  		`Locks`, 1.0,
  1098  		`Lodge`, 1.0,
  1099  		`Lodge`, 1.0,
  1100  		`Loop`, 1.0,
  1101  		`Mall`, 1.0,
  1102  		`Manor`, 1.0,
  1103  		`Manors`, 1.0,
  1104  		`Meadow`, 1.0,
  1105  		`Meadows`, 1.0,
  1106  		`Mews`, 1.0,
  1107  		`Mill`, 1.0,
  1108  		`Mills`, 1.0,
  1109  		`Mission`, 1.0,
  1110  		`Mission`, 1.0,
  1111  		`Motorway`, 1.0,
  1112  		`Mount`, 1.0,
  1113  		`Mountain`, 1.0,
  1114  		`Mountain`, 1.0,
  1115  		`Mountains`, 1.0,
  1116  		`Mountains`, 1.0,
  1117  		`Neck`, 1.0,
  1118  		`Orchard`, 1.0,
  1119  		`Oval`, 1.0,
  1120  		`Overpass`, 1.0,
  1121  		`Park`, 1.0,
  1122  		`Parks`, 1.0,
  1123  		`Parkway`, 1.0,
  1124  		`Parkways`, 1.0,
  1125  		`Pass`, 1.0,
  1126  		`Passage`, 1.0,
  1127  		`Path`, 1.0,
  1128  		`Pike`, 1.0,
  1129  		`Pine`, 1.0,
  1130  		`Pines`, 1.0,
  1131  		`Place`, 1.0,
  1132  		`Plain`, 1.0,
  1133  		`Plains`, 1.0,
  1134  		`Plains`, 1.0,
  1135  		`Plaza`, 1.0,
  1136  		`Plaza`, 1.0,
  1137  		`Point`, 1.0,
  1138  		`Points`, 1.0,
  1139  		`Port`, 1.0,
  1140  		`Port`, 1.0,
  1141  		`Ports`, 1.0,
  1142  		`Ports`, 1.0,
  1143  		`Prairie`, 1.0,
  1144  		`Prairie`, 1.0,
  1145  		`Radial`, 1.0,
  1146  		`Ramp`, 1.0,
  1147  		`Ranch`, 1.0,
  1148  		`Rapid`, 1.0,
  1149  		`Rapids`, 1.0,
  1150  		`Rest`, 1.0,
  1151  		`Ridge`, 1.0,
  1152  		`Ridges`, 1.0,
  1153  		`River`, 1.0,
  1154  		`Road`, 1.0,
  1155  		`Road`, 1.0,
  1156  		`Roads`, 1.0,
  1157  		`Roads`, 1.0,
  1158  		`Route`, 1.0,
  1159  		`Row`, 1.0,
  1160  		`Rue`, 1.0,
  1161  		`Run`, 1.0,
  1162  		`Shoal`, 1.0,
  1163  		`Shoals`, 1.0,
  1164  		`Shore`, 1.0,
  1165  		`Shores`, 1.0,
  1166  		`Skyway`, 1.0,
  1167  		`Spring`, 1.0,
  1168  		`Springs`, 1.0,
  1169  		`Springs`, 1.0,
  1170  		`Spur`, 1.0,
  1171  		`Spurs`, 1.0,
  1172  		`Square`, 1.0,
  1173  		`Square`, 1.0,
  1174  		`Squares`, 1.0,
  1175  		`Squares`, 1.0,
  1176  		`Station`, 1.0,
  1177  		`Station`, 1.0,
  1178  		`Stravenue`, 1.0,
  1179  		`Stravenue`, 1.0,
  1180  		`Stream`, 1.0,
  1181  		`Stream`, 1.0,
  1182  		`Street`, 1.0,
  1183  		`Street`, 1.0,
  1184  		`Streets`, 1.0,
  1185  		`Summit`, 1.0,
  1186  		`Summit`, 1.0,
  1187  		`Terrace`, 1.0,
  1188  		`Throughway`, 1.0,
  1189  		`Trace`, 1.0,
  1190  		`Track`, 1.0,
  1191  		`Trafficway`, 1.0,
  1192  		`Trail`, 1.0,
  1193  		`Trail`, 1.0,
  1194  		`Tunnel`, 1.0,
  1195  		`Tunnel`, 1.0,
  1196  		`Turnpike`, 1.0,
  1197  		`Turnpike`, 1.0,
  1198  		`Underpass`, 1.0,
  1199  		`Union`, 1.0,
  1200  		`Unions`, 1.0,
  1201  		`Valley`, 1.0,
  1202  		`Valleys`, 1.0,
  1203  		`Via`, 1.0,
  1204  		`Viaduct`, 1.0,
  1205  		`View`, 1.0,
  1206  		`Views`, 1.0,
  1207  		`Village`, 1.0,
  1208  		`Village`, 1.0,
  1209  		`Villages`, 1.0,
  1210  		`Ville`, 1.0,
  1211  		`Vista`, 1.0,
  1212  		`Vista`, 1.0,
  1213  		`Walk`, 1.0,
  1214  		`Walks`, 1.0,
  1215  		`Wall`, 1.0,
  1216  		`Way`, 1.0,
  1217  		`Ways`, 1.0,
  1218  		`Well`, 1.0,
  1219  		`Wells`, 1.0,
  1220  	)
  1221  }
  1222  
  1223  // Top 200 names of the decade from the 60's-90's from,
  1224  // https,//www.ssa.gov/OACT/babynames/decades/names1960s.html
  1225  // Weightings derived from total number on each name
  1226  
  1227  func firstNameFemale() *weightedEntries {
  1228  	return makeWeightedEntries(
  1229  		`April`, 0.004529083,
  1230  		`Abigail`, 0.002043839,
  1231  		`Adriana`, 0.000488767,
  1232  		`Adrienne`, 0.000622931,
  1233  		`Aimee`, 0.000424727,
  1234  		`Alejandra`, 0.000415754,
  1235  		`Alexa`, 0.000663005,
  1236  		`Alexandra`, 0.002835711,
  1237  		`Alexandria`, 0.000964993,
  1238  		`Alexis`, 0.003446735,
  1239  		`Alice`, 0.000589904,
  1240  		`Alicia`, 0.003766845,
  1241  		`Alisha`, 0.000475942,
  1242  		`Alison`, 0.001506047,
  1243  		`Allison`, 0.003740866,
  1244  		`Alyssa`, 0.00324341,
  1245  		`Amanda`, 0.015360768,
  1246  		`Amber`, 0.006928794,
  1247  		`Amy`, 0.012860314,
  1248  		`Ana`, 0.000853679,
  1249  		`Andrea`, 0.006747028,
  1250  		`Angel`, 0.001161117,
  1251  		`Angela`, 0.011954085,
  1252  		`Angelica`, 0.001102746,
  1253  		`Angie`, 0.00030166,
  1254  		`Anita`, 0.001383767,
  1255  		`Ann`, 0.002627483,
  1256  		`Anna`, 0.004691502,
  1257  		`Anne`, 0.002089582,
  1258  		`Annette`, 0.001487399,
  1259  		`Ariana`, 0.000412668,
  1260  		`Ariel`, 0.000615774,
  1261  		`Ashlee`, 0.000696534,
  1262  		`Ashley`, 0.014773009,
  1263  		`Audrey`, 0.001139165,
  1264  		`Autumn`, 0.000918594,
  1265  		`Bailey`, 0.000691916,
  1266  		`Barbara`, 0.004839169,
  1267  		`Becky`, 0.000960944,
  1268  		`Belinda`, 0.000502227,
  1269  		`Beth`, 0.002246113,
  1270  		`Bethany`, 0.001249385,
  1271  		`Betty`, 0.000840241,
  1272  		`Beverly`, 0.000990272,
  1273  		`Bianca`, 0.000624835,
  1274  		`Bonnie`, 0.001351901,
  1275  		`Brandi`, 0.002077216,
  1276  		`Brandy`, 0.002177499,
  1277  		`Breanna`, 0.000876003,
  1278  		`Brenda`, 0.005737124,
  1279  		`Briana`, 0.00093665,
  1280  		`Brianna`, 0.002543549,
  1281  		`Bridget`, 0.000787232,
  1282  		`Brittany`, 0.007258404,
  1283  		`Brittney`, 0.001566147,
  1284  		`Brooke`, 0.002410152,
  1285  		`Caitlin`, 0.001808319,
  1286  		`Caitlyn`, 0.000481194,
  1287  		`Candace`, 0.000550662,
  1288  		`Candice`, 0.000653199,
  1289  		`Carla`, 0.00195185,
  1290  		`Carly`, 0.000498725,
  1291  		`Carmen`, 0.000891783,
  1292  		`Carol`, 0.002972719,
  1293  		`Caroline`, 0.001198127,
  1294  		`Carolyn`, 0.002647225,
  1295  		`Carrie`, 0.002934659,
  1296  		`Casey`, 0.001177707,
  1297  		`Cassandra`, 0.002501243,
  1298  		`Cassidy`, 0.000452129,
  1299  		`Cassie`, 0.000344886,
  1300  		`Catherine`, 0.004460622,
  1301  		`Cathy`, 0.001413248,
  1302  		`Charlene`, 0.000538865,
  1303  		`Charlotte`, 0.000530417,
  1304  		`Chelsea`, 0.00280043,
  1305  		`Chelsey`, 0.000368501,
  1306  		`Cheryl`, 0.004166447,
  1307  		`Cheyenne`, 0.000696907,
  1308  		`Chloe`, 0.000565807,
  1309  		`Christie`, 0.000397873,
  1310  		`Christina`, 0.008735669,
  1311  		`Christine`, 0.007488758,
  1312  		`Christy`, 0.00141861,
  1313  		`Cindy`, 0.003360109,
  1314  		`Claire`, 0.000553835,
  1315  		`Claudia`, 0.00096055,
  1316  		`Colleen`, 0.001836203,
  1317  		`Connie`, 0.001821845,
  1318  		`Courtney`, 0.00484939,
  1319  		`Cristina`, 0.000328734,
  1320  		`Crystal`, 0.006365045,
  1321  		`Cynthia`, 0.007655379,
  1322  		`Daisy`, 0.000437443,
  1323  		`Dana`, 0.003395805,
  1324  		`Danielle`, 0.006671783,
  1325  		`Darlene`, 0.000952737,
  1326  		`Dawn`, 0.005014983,
  1327  		`Deanna`, 0.002049026,
  1328  		`Debbie`, 0.001842922,
  1329  		`Deborah`, 0.005386088,
  1330  		`Debra`, 0.004123572,
  1331  		`Denise`, 0.004592291,
  1332  		`Desiree`, 0.000991497,
  1333  		`Destiny`, 0.001055515,
  1334  		`Diamond`, 0.000331732,
  1335  		`Diana`, 0.003699348,
  1336  		`Diane`, 0.003058996,
  1337  		`Dominique`, 0.000847857,
  1338  		`Donna`, 0.00570819,
  1339  		`Doris`, 0.000398026,
  1340  		`Dorothy`, 0.000722426,
  1341  		`Ebony`, 0.000399624,
  1342  		`Eileen`, 0.000544271,
  1343  		`Elaine`, 0.000601175,
  1344  		`Elizabeth`, 0.014954075,
  1345  		`Ellen`, 0.000747267,
  1346  		`Emily`, 0.009100581,
  1347  		`Emma`, 0.001272059,
  1348  		`Erica`, 0.004344471,
  1349  		`Erika`, 0.002105537,
  1350  		`Erin`, 0.005450719,
  1351  		`Evelyn`, 0.000825095,
  1352  		`Faith`, 0.000427113,
  1353  		`Felicia`, 0.001717294,
  1354  		`Frances`, 0.000546897,
  1355  		`Gabriela`, 0.000526937,
  1356  		`Gabriella`, 0.00044123,
  1357  		`Gabrielle`, 0.001090096,
  1358  		`Gail`, 0.00071934,
  1359  		`Gina`, 0.002841095,
  1360  		`Glenda`, 0.000384982,
  1361  		`Gloria`, 0.001155623,
  1362  		`Grace`, 0.00087202,
  1363  		`Gwendolyn`, 0.000407831,
  1364  		`Hailey`, 0.000662917,
  1365  		`Haley`, 0.001557939,
  1366  		`Hannah`, 0.004189822,
  1367  		`Hayley`, 0.000478305,
  1368  		`Heather`, 0.010945254,
  1369  		`Heidi`, 0.002239941,
  1370  		`Helen`, 0.000636675,
  1371  		`Holly`, 0.003487028,
  1372  		`Isabel`, 0.000352305,
  1373  		`Isabella`, 0.000410282,
  1374  		`Jackie`, 0.000566748,
  1375  		`Jaclyn`, 0.00047708,
  1376  		`Jacqueline`, 0.004811242,
  1377  		`Jade`, 0.000446264,
  1378  		`Jaime`, 0.000853175,
  1379  		`Jamie`, 0.005067663,
  1380  		`Jane`, 0.0009486,
  1381  		`Janet`, 0.002489993,
  1382  		`Janice`, 0.001593308,
  1383  		`Jasmin`, 0.000333374,
  1384  		`Jasmine`, 0.003025422,
  1385  		`Jean`, 0.000815969,
  1386  		`Jeanette`, 0.000767293,
  1387  		`Jeanne`, 0.000515381,
  1388  		`Jenna`, 0.001804052,
  1389  		`Jennifer`, 0.029218839,
  1390  		`Jenny`, 0.000932667,
  1391  		`Jessica`, 0.020047608,
  1392  		`Jill`, 0.003253018,
  1393  		`Jillian`, 0.000988587,
  1394  		`Jo`, 0.000442083,
  1395  		`Joan`, 0.000802793,
  1396  		`Joann`, 0.000544336,
  1397  		`Joanna`, 0.001176284,
  1398  		`Joanne`, 0.000729824,
  1399  		`Jocelyn`, 0.000456878,
  1400  		`Jodi`, 0.001252405,
  1401  		`Jody`, 0.000741861,
  1402  		`Jordan`, 0.001653057,
  1403  		`Joy`, 0.000916515,
  1404  		`Joyce`, 0.001009488,
  1405  		`Judith`, 0.000870706,
  1406  		`Judy`, 0.001101586,
  1407  		`Julia`, 0.003301891,
  1408  		`Julie`, 0.008211731,
  1409  		`Kaitlin`, 0.000674473,
  1410  		`Kaitlyn`, 0.001478623,
  1411  		`Kara`, 0.001549119,
  1412  		`Karen`, 0.009643845,
  1413  		`Kari`, 0.000794323,
  1414  		`Karina`, 0.000494764,
  1415  		`Karla`, 0.000387696,
  1416  		`Katelyn`, 0.001476128,
  1417  		`Katherine`, 0.006581479,
  1418  		`Kathleen`, 0.00503549,
  1419  		`Kathryn`, 0.004177806,
  1420  		`Kathy`, 0.002710214,
  1421  		`Katie`, 0.003056216,
  1422  		`Katrina`, 0.001565446,
  1423  		`Kayla`, 0.004621465,
  1424  		`Kaylee`, 0.000551734,
  1425  		`Kelli`, 0.000932163,
  1426  		`Kellie`, 0.000299187,
  1427  		`Kelly`, 0.009342929,
  1428  		`Kelsey`, 0.002470383,
  1429  		`Kendra`, 0.001401079,
  1430  		`Kerri`, 0.000316215,
  1431  		`Kerry`, 0.000352984,
  1432  		`Kiara`, 0.000390037,
  1433  		`Kim`, 0.002518642,
  1434  		`Kimberly`, 0.015594077,
  1435  		`Kirsten`, 0.000369486,
  1436  		`Krista`, 0.001266872,
  1437  		`Kristen`, 0.004345587,
  1438  		`Kristi`, 0.001022926,
  1439  		`Kristie`, 0.000380189,
  1440  		`Kristin`, 0.003613728,
  1441  		`Kristina`, 0.002316281,
  1442  		`Kristine`, 0.000977709,
  1443  		`Kristy`, 0.001097734,
  1444  		`Krystal`, 0.001238113,
  1445  		`Kylie`, 0.00049739,
  1446  		`Lacey`, 0.00045469,
  1447  		`Latasha`, 0.00032904,
  1448  		`Latoya`, 0.000646371,
  1449  		`Laura`, 0.010815096,
  1450  		`Lauren`, 0.007015421,
  1451  		`Laurie`, 0.002200786,
  1452  		`Leah`, 0.001997571,
  1453  		`Leslie`, 0.003606134,
  1454  		`Linda`, 0.006437751,
  1455  		`Lindsay`, 0.002185466,
  1456  		`Lindsey`, 0.002646153,
  1457  		`Lisa`, 0.01872729,
  1458  		`Loretta`, 0.000482945,
  1459  		`Lori`, 0.006040316,
  1460  		`Lorraine`, 0.000486753,
  1461  		`Lydia`, 0.000370274,
  1462  		`Lynn`, 0.001522308,
  1463  		`Mackenzie`, 0.000761056,
  1464  		`Madeline`, 0.000808921,
  1465  		`Madison`, 0.002011184,
  1466  		`Makayla`, 0.000439391,
  1467  		`Mallory`, 0.000688633,
  1468  		`Mandy`, 0.000355566,
  1469  		`Marcia`, 0.000403213,
  1470  		`Margaret`, 0.003839968,
  1471  		`Maria`, 0.006593123,
  1472  		`Mariah`, 0.00097598,
  1473  		`Marie`, 0.001520229,
  1474  		`Marilyn`, 0.000590889,
  1475  		`Marisa`, 0.000339983,
  1476  		`Marissa`, 0.001582627,
  1477  		`Martha`, 0.001290028,
  1478  		`Mary`, 0.014288466,
  1479  		`Maureen`, 0.000753855,
  1480  		`Mckenzie`, 0.000334512,
  1481  		`Meagan`, 0.000729999,
  1482  		`Megan`, 0.007686786,
  1483  		`Meghan`, 0.001481578,
  1484  		`Melanie`, 0.003400117,
  1485  		`Melinda`, 0.002078113,
  1486  		`Melissa`, 0.014890692,
  1487  		`Melody`, 0.000404264,
  1488  		`Mercedes`, 0.000334643,
  1489  		`Meredith`, 0.000766987,
  1490  		`Mia`, 0.000319935,
  1491  		`Michaela`, 0.000506998,
  1492  		`Michele`, 0.003519551,
  1493  		`Michelle`, 0.01527423,
  1494  		`Mikayla`, 0.000410195,
  1495  		`Mindy`, 0.000306891,
  1496  		`Miranda`, 0.001421193,
  1497  		`Misty`, 0.001564614,
  1498  		`Molly`, 0.001710641,
  1499  		`Monica`, 0.004324095,
  1500  		`Monique`, 0.001272125,
  1501  		`Morgan`, 0.002527025,
  1502  		`Nancy`, 0.005023343,
  1503  		`Natalie`, 0.003658398,
  1504  		`Natasha`, 0.001739815,
  1505  		`Nichole`, 0.001001237,
  1506  		`Nicole`, 0.011156655,
  1507  		`Nina`, 0.000298115,
  1508  		`Norma`, 0.000470754,
  1509  		`Olivia`, 0.001967609,
  1510  		`Paige`, 0.001106313,
  1511  		`Pam`, 0.000374454,
  1512  		`Pamela`, 0.005816222,
  1513  		`Patricia`, 0.008349353,
  1514  		`Patty`, 0.000383493,
  1515  		`Paula`, 0.002478284,
  1516  		`Peggy`, 0.000810606,
  1517  		`Penny`, 0.000836564,
  1518  		`Phyllis`, 0.000562437,
  1519  		`Priscilla`, 0.000350226,
  1520  		`Rachael`, 0.001098128,
  1521  		`Rachel`, 0.00876108,
  1522  		`Raven`, 0.000404855,
  1523  		`Rebecca`, 0.010563161,
  1524  		`Rebekah`, 0.000858581,
  1525  		`Regina`, 0.001941739,
  1526  		`Renee`, 0.00257883,
  1527  		`Rhonda`, 0.002879221,
  1528  		`Rita`, 0.000719187,
  1529  		`Roberta`, 0.000461715,
  1530  		`Robin`, 0.00409199,
  1531  		`Robyn`, 0.00032138,
  1532  		`Rose`, 0.000697125,
  1533  		`Ruth`, 0.001041946,
  1534  		`Sabrina`, 0.001920969,
  1535  		`Sally`, 0.000532912,
  1536  		`Samantha`, 0.008186124,
  1537  		`Sandra`, 0.006473426,
  1538  		`Sandy`, 0.000497106,
  1539  		`Sara`, 0.005619879,
  1540  		`Sarah`, 0.014434273,
  1541  		`Savannah`, 0.000978344,
  1542  		`Selena`, 0.000329106,
  1543  		`Shannon`, 0.005952552,
  1544  		`Shari`, 0.000449043,
  1545  		`Sharon`, 0.004796469,
  1546  		`Shawna`, 0.000354209,
  1547  		`Sheena`, 0.000355763,
  1548  		`Sheila`, 0.00220129,
  1549  		`Shelby`, 0.001575601,
  1550  		`Shelia`, 0.000403673,
  1551  		`Shelley`, 0.000922227,
  1552  		`Shelly`, 0.001339469,
  1553  		`Sheri`, 0.000913166,
  1554  		`Sherri`, 0.001285038,
  1555  		`Sherry`, 0.002445235,
  1556  		`Sheryl`, 0.00057025,
  1557  		`Shirley`, 0.000833259,
  1558  		`Sierra`, 0.000954816,
  1559  		`Sonia`, 0.000332739,
  1560  		`Sonya`, 0.000914085,
  1561  		`Sophia`, 0.000535976,
  1562  		`Stacey`, 0.002836761,
  1563  		`Stacie`, 0.0003903,
  1564  		`Stacy`, 0.00311717,
  1565  		`Stefanie`, 0.00034644,
  1566  		`Stephanie`, 0.013595762,
  1567  		`Sue`, 0.000472877,
  1568  		`Summer`, 0.000411508,
  1569  		`Susan`, 0.0088973,
  1570  		`Suzanne`, 0.001943577,
  1571  		`Sydney`, 0.001220101,
  1572  		`Sylvia`, 0.000625798,
  1573  		`Tabitha`, 0.000428404,
  1574  		`Tamara`, 0.00212948,
  1575  		`Tami`, 0.000403651,
  1576  		`Tammie`, 0.00042337,
  1577  		`Tammy`, 0.006493584,
  1578  		`Tanya`, 0.002039024,
  1579  		`Tara`, 0.00316834,
  1580  		`Tasha`, 0.000355807,
  1581  		`Taylor`, 0.003996871,
  1582  		`Teresa`, 0.005060003,
  1583  		`Terri`, 0.001823903,
  1584  		`Terry`, 0.00060494,
  1585  		`Theresa`, 0.003492762,
  1586  		`Tiffany`, 0.006594283,
  1587  		`Tina`, 0.005186419,
  1588  		`Toni`, 0.000891695,
  1589  		`Tonya`, 0.002404133,
  1590  		`Tracey`, 0.001511146,
  1591  		`Traci`, 0.00086193,
  1592  		`Tracie`, 0.000301901,
  1593  		`Tracy`, 0.00498572,
  1594  		`Tricia`, 0.000449196,
  1595  		`Valerie`, 0.003218022,
  1596  		`Vanessa`, 0.003779189,
  1597  		`Veronica`, 0.003017805,
  1598  		`Vicki`, 0.00088653,
  1599  		`Vickie`, 0.000695199,
  1600  		`Victoria`, 0.005237677,
  1601  		`Virginia`, 0.001496482,
  1602  		`Wanda`, 0.001336186,
  1603  		`Wendy`, 0.004058263,
  1604  		`Whitney`, 0.001690768,
  1605  		`Yesenia`, 0.000331951,
  1606  		`Yolanda`, 0.001213819,
  1607  		`Yvette`, 0.000483427,
  1608  		`Yvonne`, 0.001005483,
  1609  		`Zoe`, 0.000367407,
  1610  	)
  1611  }
  1612  
  1613  func firstNameMale() *weightedEntries {
  1614  	return makeWeightedEntries(
  1615  		`Aaron`, 0.006741589,
  1616  		`Adam`, 0.007124922,
  1617  		`Adrian`, 0.001521889,
  1618  		`Alan`, 0.002344657,
  1619  		`Albert`, 0.001316595,
  1620  		`Alec`, 0.000442958,
  1621  		`Alejandro`, 0.000862489,
  1622  		`Alex`, 0.002111833,
  1623  		`Alexander`, 0.005215733,
  1624  		`Alexis`, 0.000277915,
  1625  		`Alfred`, 0.000318919,
  1626  		`Allen`, 0.001679613,
  1627  		`Alvin`, 0.00024794,
  1628  		`Andre`, 0.001400621,
  1629  		`Andres`, 0.000335574,
  1630  		`Andrew`, 0.013475074,
  1631  		`Angel`, 0.000902262,
  1632  		`Anthony`, 0.013783357,
  1633  		`Antonio`, 0.002392535,
  1634  		`Arthur`, 0.001342637,
  1635  		`Austin`, 0.003785615,
  1636  		`Barry`, 0.001102751,
  1637  		`Benjamin`, 0.006535474,
  1638  		`Bernard`, 0.000298691,
  1639  		`Bill`, 0.000430013,
  1640  		`Billy`, 0.001749806,
  1641  		`Blake`, 0.001218155,
  1642  		`Bob`, 0.000235731,
  1643  		`Bobby`, 0.001666977,
  1644  		`Brad`, 0.000984544,
  1645  		`Bradley`, 0.003845018,
  1646  		`Brady`, 0.000277522,
  1647  		`Brandon`, 0.009518346,
  1648  		`Brendan`, 0.000736758,
  1649  		`Brent`, 0.001889131,
  1650  		`Brett`, 0.002248371,
  1651  		`Brian`, 0.01597677,
  1652  		`Bruce`, 0.001883335,
  1653  		`Bryan`, 0.00456454,
  1654  		`Bryce`, 0.000457406,
  1655  		`Caleb`, 0.001485861,
  1656  		`Calvin`, 0.001168738,
  1657  		`Cameron`, 0.00180755,
  1658  		`Carl`, 0.002011802,
  1659  		`Carlos`, 0.00266638,
  1660  		`Casey`, 0.001440035,
  1661  		`Cesar`, 0.000304898,
  1662  		`Chad`, 0.003858817,
  1663  		`Charles`, 0.010889881,
  1664  		`Chase`, 0.000971942,
  1665  		`Chris`, 0.001389507,
  1666  		`Christian`, 0.003097779,
  1667  		`Christopher`, 0.02783596,
  1668  		`Clarence`, 0.000299289,
  1669  		`Clayton`, 0.000662222,
  1670  		`Clifford`, 0.00053078,
  1671  		`Clinton`, 0.000579307,
  1672  		`Cody`, 0.00353482,
  1673  		`Cole`, 0.000578811,
  1674  		`Colin`, 0.00078508,
  1675  		`Collin`, 0.000406057,
  1676  		`Colton`, 0.000520845,
  1677  		`Connor`, 0.000981073,
  1678  		`Corey`, 0.002476612,
  1679  		`Cory`, 0.001813005,
  1680  		`Craig`, 0.00338161,
  1681  		`Cristian`, 0.000333847,
  1682  		`Curtis`, 0.002140235,
  1683  		`Dakota`, 0.000797614,
  1684  		`Dale`, 0.001171354,
  1685  		`Dalton`, 0.000615113,
  1686  		`Damon`, 0.00034308,
  1687  		`Dan`, 0.000388496,
  1688  		`Daniel`, 0.018881874,
  1689  		`Danny`, 0.001873879,
  1690  		`Darin`, 0.000234962,
  1691  		`Darius`, 0.000336189,
  1692  		`Darrell`, 0.001218582,
  1693  		`Darren`, 0.001253738,
  1694  		`Darryl`, 0.00067019,
  1695  		`Daryl`, 0.000260918,
  1696  		`Dave`, 0.000269673,
  1697  		`David`, 0.031073833,
  1698  		`Dean`, 0.000965375,
  1699  		`Dennis`, 0.003318992,
  1700  		`Derek`, 0.003095299,
  1701  		`Derrick`, 0.001955921,
  1702  		`Devin`, 0.001312474,
  1703  		`Devon`, 0.000485877,
  1704  		`Dillon`, 0.000558361,
  1705  		`Dominic`, 0.000438221,
  1706  		`Don`, 0.000378322,
  1707  		`Donald`, 0.005689572,
  1708  		`Douglas`, 0.004513687,
  1709  		`Drew`, 0.000596868,
  1710  		`Duane`, 0.00061855,
  1711  		`Dustin`, 0.003088938,
  1712  		`Dwayne`, 0.000711382,
  1713  		`Dylan`, 0.002329096,
  1714  		`Earl`, 0.000348347,
  1715  		`Eddie`, 0.0007944,
  1716  		`Edgar`, 0.000379536,
  1717  		`Eduardo`, 0.000465358,
  1718  		`Edward`, 0.005702242,
  1719  		`Edwin`, 0.001117833,
  1720  		`Elijah`, 0.000592183,
  1721  		`Eric`, 0.012024659,
  1722  		`Erik`, 0.001997096,
  1723  		`Ernest`, 0.000746556,
  1724  		`Ethan`, 0.001143978,
  1725  		`Eugene`, 0.000784243,
  1726  		`Evan`, 0.001570691,
  1727  		`Fernando`, 0.000557608,
  1728  		`Francis`, 0.000330837,
  1729  		`Francisco`, 0.001084335,
  1730  		`Frank`, 0.003276449,
  1731  		`Franklin`, 0.000237561,
  1732  		`Fred`, 0.000396618,
  1733  		`Frederick`, 0.001104188,
  1734  		`Gabriel`, 0.001906504,
  1735  		`Garrett`, 0.001124861,
  1736  		`Gary`, 0.005023109,
  1737  		`Gavin`, 0.000295373,
  1738  		`Gene`, 0.00023426,
  1739  		`Geoffrey`, 0.000425978,
  1740  		`George`, 0.004423984,
  1741  		`Gerald`, 0.00165841,
  1742  		`Gilbert`, 0.000246726,
  1743  		`Glen`, 0.000374338,
  1744  		`Glenn`, 0.001111421,
  1745  		`Gordon`, 0.00027075,
  1746  		`Grant`, 0.00068322,
  1747  		`Greg`, 0.000623492,
  1748  		`Gregg`, 0.000235885,
  1749  		`Gregory`, 0.007676443,
  1750  		`Guy`, 0.000262645,
  1751  		`Harold`, 0.000929467,
  1752  		`Harry`, 0.000586934,
  1753  		`Hayden`, 0.000279454,
  1754  		`Hector`, 0.000798691,
  1755  		`Henry`, 0.001856232,
  1756  		`Herbert`, 0.000234226,
  1757  		`Howard`, 0.000712921,
  1758  		`Hunter`, 0.001034679,
  1759  		`Ian`, 0.001863192,
  1760  		`Isaac`, 0.001001951,
  1761  		`Isaiah`, 0.000625441,
  1762  		`Ivan`, 0.000350433,
  1763  		`Jack`, 0.001839748,
  1764  		`Jackson`, 0.000403253,
  1765  		`Jacob`, 0.007845384,
  1766  		`Jaime`, 0.000421378,
  1767  		`Jake`, 0.000565782,
  1768  		`James`, 0.029601617,
  1769  		`Jamie`, 0.00093552,
  1770  		`Jared`, 0.002538802,
  1771  		`Jason`, 0.01520513,
  1772  		`Javier`, 0.000625202,
  1773  		`Jay`, 0.001411462,
  1774  		`Jeff`, 0.001271436,
  1775  		`Jeffery`, 0.002627873,
  1776  		`Jeffrey`, 0.01225709,
  1777  		`Jeremiah`, 0.001209605,
  1778  		`Jeremy`, 0.006336079,
  1779  		`Jermaine`, 0.000450156,
  1780  		`Jerome`, 0.000634299,
  1781  		`Jerry`, 0.003150273,
  1782  		`Jesse`, 0.003884552,
  1783  		`Jesus`, 0.001628965,
  1784  		`Jim`, 0.000567714,
  1785  		`Jimmy`, 0.001607489,
  1786  		`Joe`, 0.001621544,
  1787  		`Joel`, 0.002537742,
  1788  		`John`, 0.028683008,
  1789  		`Johnathan`, 0.000840448,
  1790  		`Johnny`, 0.002117065,
  1791  		`Jon`, 0.001561184,
  1792  		`Jonathan`, 0.009963971,
  1793  		`Jonathon`, 0.000701157,
  1794  		`Jordan`, 0.003451546,
  1795  		`Jorge`, 0.001180553,
  1796  		`Jose`, 0.005368207,
  1797  		`Joseph`, 0.018604763,
  1798  		`Joshua`, 0.014808101,
  1799  		`Juan`, 0.003233598,
  1800  		`Julian`, 0.000693736,
  1801  		`Justin`, 0.010197889,
  1802  		`Karl`, 0.000362437,
  1803  		`Keith`, 0.004622866,
  1804  		`Kelly`, 0.000775283,
  1805  		`Kenneth`, 0.008318145,
  1806  		`Kent`, 0.000329418,
  1807  		`Kerry`, 0.000261448,
  1808  		`Kevin`, 0.014324157,
  1809  		`Kirk`, 0.0003801,
  1810  		`Kristopher`, 0.000580692,
  1811  		`Kurt`, 0.000716375,
  1812  		`Kyle`, 0.006350049,
  1813  		`Lance`, 0.001048495,
  1814  		`Larry`, 0.003658807,
  1815  		`Lawrence`, 0.001670294,
  1816  		`Lee`, 0.001223883,
  1817  		`Leon`, 0.000236347,
  1818  		`Leonard`, 0.000756713,
  1819  		`Leroy`, 0.000260234,
  1820  		`Leslie`, 0.000234637,
  1821  		`Levi`, 0.000347184,
  1822  		`Logan`, 0.001325812,
  1823  		`Lonnie`, 0.000258576,
  1824  		`Louis`, 0.001212255,
  1825  		`Lucas`, 0.001098237,
  1826  		`Luis`, 0.002427777,
  1827  		`Luke`, 0.001221455,
  1828  		`Malik`, 0.000306813,
  1829  		`Manuel`, 0.001331369,
  1830  		`Marc`, 0.001431947,
  1831  		`Marco`, 0.000290586,
  1832  		`Marcus`, 0.002604122,
  1833  		`Mario`, 0.001229337,
  1834  		`Mark`, 0.014382277,
  1835  		`Martin`, 0.002085226,
  1836  		`Marvin`, 0.000732962,
  1837  		`Mason`, 0.000562037,
  1838  		`Mathew`, 0.000605555,
  1839  		`Matthew`, 0.020425018,
  1840  		`Maurice`, 0.000777078,
  1841  		`Max`, 0.000311276,
  1842  		`Maxwell`, 0.000357478,
  1843  		`Melvin`, 0.00061932,
  1844  		`Michael`, 0.045602241,
  1845  		`Micheal`, 0.001273847,
  1846  		`Miguel`, 0.001416267,
  1847  		`Mike`, 0.001221797,
  1848  		`Mitchell`, 0.001747788,
  1849  		`Nathan`, 0.005039405,
  1850  		`Nathaniel`, 0.001887558,
  1851  		`Neil`, 0.000240331,
  1852  		`Nicholas`, 0.010021219,
  1853  		`Nicolas`, 0.000362522,
  1854  		`Noah`, 0.000960947,
  1855  		`Norman`, 0.000389043,
  1856  		`Omar`, 0.000639052,
  1857  		`Oscar`, 0.000946583,
  1858  		`Parker`, 0.000277522,
  1859  		`Patrick`, 0.007153255,
  1860  		`Paul`, 0.009272953,
  1861  		`Pedro`, 0.000275726,
  1862  		`Perry`, 0.000258644,
  1863  		`Peter`, 0.004340385,
  1864  		`Philip`, 0.002262956,
  1865  		`Phillip`, 0.00280273,
  1866  		`Preston`, 0.000292022,
  1867  		`Ralph`, 0.000836891,
  1868  		`Randall`, 0.001614722,
  1869  		`Randy`, 0.003021926,
  1870  		`Ray`, 0.000379451,
  1871  		`Raymond`, 0.003493952,
  1872  		`Reginald`, 0.00095108,
  1873  		`Ricardo`, 0.001197276,
  1874  		`Richard`, 0.014131961,
  1875  		`Rick`, 0.000440016,
  1876  		`Rickey`, 0.00023833,
  1877  		`Ricky`, 0.001856882,
  1878  		`Riley`, 0.000322031,
  1879  		`Robert`, 0.026938092,
  1880  		`Roberto`, 0.000906024,
  1881  		`Rodney`, 0.002180555,
  1882  		`Roger`, 0.002038032,
  1883  		`Ronald`, 0.00576775,
  1884  		`Ronnie`, 0.000905938,
  1885  		`Ross`, 0.00026863,
  1886  		`Roy`, 0.001311346,
  1887  		`Ruben`, 0.000774821,
  1888  		`Russell`, 0.002096221,
  1889  		`Ryan`, 0.01128178,
  1890  		`Samuel`, 0.00498019,
  1891  		`Scott`, 0.010580999,
  1892  		`Sean`, 0.005593456,
  1893  		`Sergio`, 0.000568518,
  1894  		`Seth`, 0.001537416,
  1895  		`Shane`, 0.002530218,
  1896  		`Shannon`, 0.000421583,
  1897  		`Shaun`, 0.000748761,
  1898  		`Shawn`, 0.004474546,
  1899  		`Spencer`, 0.000912094,
  1900  		`Stanley`, 0.000739032,
  1901  		`Stephen`, 0.007675365,
  1902  		`Steve`, 0.001407564,
  1903  		`Steven`, 0.013292898,
  1904  		`Stuart`, 0.000238826,
  1905  		`Tanner`, 0.000639292,
  1906  		`Taylor`, 0.00133036,
  1907  		`Terrance`, 0.000203311,
  1908  		`Terrence`, 0.000203704,
  1909  		`Terry`, 0.002873624,
  1910  		`Theodore`, 0.000596561,
  1911  		`Thomas`, 0.0143364,
  1912  		`Tim`, 0.000711126,
  1913  		`Timothy`, 0.012632608,
  1914  		`Todd`, 0.00414612,
  1915  		`Tom`, 0.000499283,
  1916  		`Tommy`, 0.000778737,
  1917  		`Tony`, 0.002511563,
  1918  		`Tracy`, 0.000728259,
  1919  		`Travis`, 0.004022458,
  1920  		`Trevor`, 0.001692523,
  1921  		`Tristan`, 0.000408759,
  1922  		`Troy`, 0.002695415,
  1923  		`Tyler`, 0.005962323,
  1924  		`Tyrone`, 0.000587207,
  1925  		`Vernon`, 0.000246401,
  1926  		`Victor`, 0.002340621,
  1927  		`Vincent`, 0.002494515,
  1928  		`Walter`, 0.001525891,
  1929  		`Warren`, 0.000317414,
  1930  		`Wayne`, 0.00160966,
  1931  		`Wesley`, 0.001733835,
  1932  		`William`, 0.020025989,
  1933  		`Willie`, 0.001379247,
  1934  		`Wyatt`, 0.000306591,
  1935  		`Xavier`, 0.000415222,
  1936  		`Zachary`, 0.005918634,
  1937  	)
  1938  }
  1939  
  1940  // Top 1000 US surnames from US Census data
  1941  // Weighted by number of occurrences
  1942  // By way of http,//names.mongabay.com/data/1000.html on 2/10/2016
  1943  
  1944  func lastName() *weightedEntries {
  1945  	return makeWeightedEntries(
  1946  		`Smith`, 0.021712045,
  1947  		`Johnson`, 0.01696938,
  1948  		`Williams`, 0.014016962,
  1949  		`Brown`, 0.012610763,
  1950  		`Jones`, 0.012451866,
  1951  		`Miller`, 0.010305045,
  1952  		`Davis`, 0.009798219,
  1953  		`Garcia`, 0.007842422,
  1954  		`Rodriguez`, 0.007348561,
  1955  		`Wilson`, 0.007154951,
  1956  		`Martinez`, 0.007082045,
  1957  		`Anderson`, 0.006966203,
  1958  		`Taylor`, 0.006582218,
  1959  		`Thomas`, 0.006493824,
  1960  		`Hernandez`, 0.006454314,
  1961  		`Moore`, 0.006383948,
  1962  		`Martin`, 0.006146745,
  1963  		`Jackson`, 0.006086567,
  1964  		`Thompson`, 0.005887767,
  1965  		`White`, 0.005843424,
  1966  		`Lopez`, 0.005679145,
  1967  		`Lee`, 0.005535909,
  1968  		`Gonzalez`, 0.005461513,
  1969  		`Harris`, 0.005423356,
  1970  		`Clark`, 0.005010598,
  1971  		`Lewis`, 0.00465937,
  1972  		`Robinson`, 0.004596305,
  1973  		`Walker`, 0.004580579,
  1974  		`Perez`, 0.00446375,
  1975  		`Hall`, 0.004327121,
  1976  		`Young`, 0.004257495,
  1977  		`Allen`, 0.00423392,
  1978  		`Sanchez`, 0.004031749,
  1979  		`Wright`, 0.004023754,
  1980  		`King`, 0.004011135,
  1981  		`Scott`, 0.003838487,
  1982  		`Green`, 0.003778053,
  1983  		`Baker`, 0.003776901,
  1984  		`Adams`, 0.00377448,
  1985  		`Nelson`, 0.003766713,
  1986  		`Hill`, 0.003762455,
  1987  		`Ramirez`, 0.003554281,
  1988  		`Campbell`, 0.003398636,
  1989  		`Mitchell`, 0.003357336,
  1990  		`Roberts`, 0.003346207,
  1991  		`Carter`, 0.0033127,
  1992  		`Phillips`, 0.003214932,
  1993  		`Evans`, 0.003127113,
  1994  		`Turner`, 0.003067045,
  1995  		`Torres`, 0.002971158,
  1996  		`Parker`, 0.002962725,
  1997  		`Collins`, 0.002904264,
  1998  		`Edwards`, 0.002897155,
  1999  		`Stewart`, 0.002859044,
  2000  		`Flores`, 0.002856449,
  2001  		`Morris`, 0.002848582,
  2002  		`Nguyen`, 0.002833697,
  2003  		`Murphy`, 0.00274576,
  2004  		`Rivera`, 0.002736275,
  2005  		`Cook`, 0.002693623,
  2006  		`Rogers`, 0.002690041,
  2007  		`Morgan`, 0.002525543,
  2008  		`Peterson`, 0.002513125,
  2009  		`Cooper`, 0.00246795,
  2010  		`Reed`, 0.0024437,
  2011  		`Bailey`, 0.002429747,
  2012  		`Bell`, 0.002419112,
  2013  		`Gomez`, 0.002408494,
  2014  		`Kelly`, 0.002379209,
  2015  		`Howard`, 0.002327986,
  2016  		`Ward`, 0.002321973,
  2017  		`Cox`, 0.002318775,
  2018  		`Diaz`, 0.00230051,
  2019  		`Richardson`, 0.002280051,
  2020  		`Wood`, 0.002259639,
  2021  		`Watson`, 0.002215168,
  2022  		`Brooks`, 0.002199808,
  2023  		`Bennett`, 0.002184311,
  2024  		`Gray`, 0.002162912,
  2025  		`James`, 0.002131032,
  2026  		`Reyes`, 0.002124517,
  2027  		`Cruz`, 0.002111304,
  2028  		`Hughes`, 0.002095999,
  2029  		`Price`, 0.002090206,
  2030  		`Myers`, 0.002054278,
  2031  		`Long`, 0.002042126,
  2032  		`Foster`, 0.002019703,
  2033  		`Sanders`, 0.002018442,
  2034  		`Ross`, 0.002009844,
  2035  		`Morales`, 0.001988655,
  2036  		`Powell`, 0.001978704,
  2037  		`Sullivan`, 0.001970362,
  2038  		`Russell`, 0.001968461,
  2039  		`Ortiz`, 0.001961617,
  2040  		`Jenkins`, 0.001952974,
  2041  		`Gutierrez`, 0.001945371,
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  2476  		`Weiss`, 0.000513085,
  2477  		`Wilkins`, 0.000512309,
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  2481  		`Short`, 0.000510801,
  2482  		`Carson`, 0.000510052,
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  2918  		`Gay`, 0.000298533,
  2919  		`Riddle`, 0.000298369,
  2920  		`Haney`, 0.000298277,
  2921  		`Kaiser`, 0.000297574,
  2922  		`Holder`, 0.000296651,
  2923  		`Chaney`, 0.000296349,
  2924  		`Mcknight`, 0.00029592,
  2925  		`Gamble`, 0.000295838,
  2926  		`Vang`, 0.000295435,
  2927  		`Cooley`, 0.000295015,
  2928  		`Carney`, 0.000294969,
  2929  		`Cowan`, 0.000294604,
  2930  		`Forbes`, 0.000294476,
  2931  		`Ferrell`, 0.000293983,
  2932  		`Davies`, 0.0002939,
  2933  		`Barajas`, 0.000293736,
  2934  		`Shea`, 0.000293023,
  2935  		`Osborn`, 0.000292795,
  2936  		`Bright`, 0.000292777,
  2937  		`Cuevas`, 0.00029253,
  2938  		`Bolton`, 0.000292347,
  2939  		`Murillo`, 0.000292064,
  2940  		`Lutz`, 0.000291845,
  2941  		`Duarte`, 0.000291442,
  2942  		`Kidd`, 0.000291351,
  2943  		`Key`, 0.000291315,
  2944  		`Cooke`, 0.000291114,
  2945  	)
  2946  }