table with row headers in Column A and column headers in Rows 7-10,,,,,,,,,,,,
Census 2000 PHC-T-40.  Estimated Daytime Population and Employment-Residence Ratios:  2000,,,,,,,,,,,,
,,,,,,,,,,,,
"Table 1. Leading Places on Percent Change in Daytime Population, by Size (Total Resident Population)",,,,,,,,,,,,
,,,,,,,,,,,,
"NOTE: Data based on a sample. For information on confidentiality protection, sampling error, nonsampling error, definitions, and count corrections see http://factfinder.census.gov/home/en/datanotes/expsf3.htm.",,,,,,,,,,,,
FIPS state code,FIPS place code,Total resident population,Total workers working in the place,Total workers living in the place,Estimated daytime population,Daytime population change due to commuting,,Workers who lived and worked in the same place,,Employ-ment residence ratio,Place name1/,
,,,,,,,,,,,,
,,,,,,Number,Percent,Number,Percent,,,
(1),(2),(3),(4),(5),"(6) =
(3)+(4)-(5)"," (7) =
(6)-(3)","(8) =
(7)/(3)*100",(9),"(10) =
(9)/(5)*100","(11) =
(4)/(5)",,
,,,,,,,,,,,,
Over 1 million population (all places in category),,,,,,,,,,,,
48,35000,"1,953,631","1,244,999","841,686","2,356,944","403,313",20.6,"681,785",81.0 ,1.48,"Houston city, TX",
48,19000,"1,188,580","764,561","537,006","1,416,135","227,555",19.1,"350,745",65.3 ,1.42,"Dallas city, TX",
06,66000,"1,223,400","722,245","580,318","1,365,327","141,927",11.6,"450,898",77.7 ,1.24,"San Diego city, CA",
04,55000,"1,321,045","695,712","599,592","1,417,165","96,120",7.3,"415,384",69.3 ,1.16,"Phoenix city, AZ",
36,51000,"8,008,278","3,755,130","3,192,070","8,571,338","563,060",7.0,"2,922,206",91.5 ,1.18,"New York city, NY"
42,60000,"1,517,550","659,991","569,761","1,607,780","90,230",5.9,"429,608",75.4 ,1.16,"Philadelphia city, PA"
48,65000,"1,144,646","559,424","491,435","1,212,635","67,989",5.9,"428,926",87.3 ,1.14,"San Antonio city, TX"
17,14000,"2,896,016","1,334,467","1,192,139","3,038,344","142,328",4.9,"841,329",70.6 ,1.12,"Chicago city, IL"
06,44000,"3,694,820","1,622,772","1,494,895","3,822,697","127,877",3.5,"943,489",63.1 ,1.09,"Los Angeles city, CA"
,,,,,,,,,,,
"500,000 to 999,999 population (all places in category)",,,,,,,,,,,
11,50000,"572,059","671,678","260,884","982,853","410,794",71.8,"190,566",73.0 ,2.57,"Washington city, DC"
25,07000,"589,141","520,555","278,463","831,233","242,092",41.1,"184,954",66.4 ,1.87,"Boston city, MA"
53,63000,"563,374","476,536","316,493","723,417","160,043",28.4,"233,600",73.8 ,1.51,"Seattle city, WA"
08,20000,"554,636","434,201","278,715","710,122","155,486",28.0,"176,750",63.4 ,1.56,"Denver city, CO"
41,59000,"529,121","392,739","270,996","650,864","121,743",23.0,"200,158",73.9 ,1.45,"Portland city, OR"
06,67000,"776,733","587,300","418,553","945,480","168,747",21.7,"322,009",76.9 ,1.40,"San Francisco city, CA"
37,12000,"540,828","395,183","280,528","655,483","114,655",21.2,"230,558",82.2 ,1.41,"Charlotte city, NC"
47,52006,"545,524","380,230","274,028","651,726","106,202",19.5,"229,632",83.8 ,1.39,"Nashville-Davidson (balance), TN"
48,05000,"656,562","480,437","353,109","783,890","127,328",19.4,"307,600",87.1 ,1.36,"Austin city, TX"
40,55000,"506,132","328,867","234,222","600,777","94,645",18.7,"188,976",80.7 ,1.40,"Oklahoma City city, OK"
47,48000,"650,100","377,677","274,934","752,843","102,743",15.8,"231,355",84.1 ,1.37,"Memphis city, TN"
18,36003,"781,870","507,170","385,208","903,832","121,962",15.6,"315,658",81.9 ,1.32,"Indianapolis city (balance), IN"
24,04000,"651,154","341,998","249,373","743,779","92,625",14.2,"154,463",61.9 ,1.37,"Baltimore city, MD"
48,27000,"534,694","310,625","235,799","609,520","74,826",14.0,"144,032",61.1 ,1.32,"Fort Worth city, TX"
39,18000,"711,470","449,907","367,387","793,990","82,520",11.6,"254,193",69.2 ,1.22,"Columbus city, OH"
12,35000,"735,617","412,681","350,458","797,840","62,223",8.5,"319,728",91.2 ,1.18,"Jacksonville city, FL"
55,53000,"596,974","285,753","249,889","632,838","35,864",6.0,"151,145",60.5 ,1.14,"Milwaukee city, WI"
48,24000,"563,662","215,119","208,101","570,680","7,018",1.2,"182,077",87.5 ,1.03,"El Paso city, TX"
26,22000,"951,270","318,790","319,449","950,611",-659,-0.1,"154,933",48.5 ,1.00,"Detroit city, MI"
06,68000,"894,943","377,915","427,984","844,874","-50,069",-5.6,"212,187",49.6 ,0.88,"San Jose city, CA"
,,,,,,,,,,,
"250,000 to 499,999 population (all places in category)",,,,,,,,,,,
13,04000,"416,474","438,927","178,970","676,431","259,957",62.4,"106,145",59.3 ,2.45,"Atlanta city, GA"
12,71000,"303,447","279,476","135,425","447,498","144,051",47.5,"90,798",67.0 ,2.06,"Tampa city, FL"
42,61000,"334,563","280,035","141,844","472,754","138,191",41.3,"98,005",69.1 ,1.97,"Pittsburgh city, PA"
12,45000,"362,470","261,605","126,539","497,536","135,066",37.3,"57,408",45.4 ,2.07,"Miami city, FL"
29,65000,"348,189","262,981","140,747","470,423","122,234",35.1,"82,480",58.6 ,1.87,"St. Louis city, MO"
21,48000,"256,231","191,272","110,930","336,573","80,342",31.4,"67,206",60.6 ,1.72,"Louisville city, KY"
39,15000,"331,285","250,336","147,616","434,005","102,720",31.0,"89,226",60.4 ,1.70,"Cincinnati city, OH"
15,17000,"371,657","266,374","173,069","464,962","93,305",25.1,"147,888",85.5 ,1.54,"Honolulu CDP, HI"
37,55000,"276,093","220,848","151,655","345,286","69,193",25.1,"101,516",66.9 ,1.46,"Raleigh city, NC"
27,43000,"382,618","299,427","203,951","478,094","95,476",25.0,"107,905",52.9 ,1.47,"Minneapolis city, MN"
06,64000,"407,018","267,352","166,419","507,951","100,933",24.8,"100,101",60.1 ,1.61,"Sacramento city, CA"
39,16000,"478,403","290,567","175,727","593,243","114,840",24.0,"98,292",55.9 ,1.65,"Cleveland city, OH"
29,38000,"441,545","310,520","208,554","543,511","101,966",23.1,"132,666",63.6 ,1.49,"Kansas City city, MO"
34,51000,"273,546","147,395","87,720","333,221","59,675",21.8,"36,319",41.4 ,1.68,"Newark city, NJ"
31,37000,"390,007","273,359","196,801","466,565","76,558",19.6,"170,544",86.7 ,1.39,"Omaha city, NE"
40,75000,"393,049","262,448","187,612","467,885","74,836",19.0,"156,679",83.5 ,1.40,"Tulsa city, OK"
36,11000,"292,648","158,245","110,640","340,253","47,605",16.3,"65,989",59.6 ,1.43,"Buffalo city, NY"
27,58000,"287,151","180,564","139,067","328,648","41,497",14.5,"62,898",45.2 ,1.30,"St. Paul city, MN"
22,55000,"484,674","248,507","188,703","544,478","59,804",12.3,"147,492",78.2 ,1.32,"New Orleans city, LA"
21,46027,"260,512","167,128","136,793","290,847","30,335",11.6,"117,584",86.0 ,1.22,"Lexington-Fayette, KY"
04,77000,"486,699","259,768","216,314","530,153","43,454",8.9,"172,709",79.8 ,1.20,"Tucson city, AZ"
35,02000,"448,607","252,911","215,222","486,296","37,689",8.4,"183,244",85.1 ,1.18,"Albuquerque city, NM"
06,02000,"328,014","163,631","139,343","352,302","24,288",7.4,"41,005",29.4 ,1.17,"Anaheim city, CA"
06,27000,"427,652","187,956","156,569","459,039","31,387",7.3,"118,757",75.8 ,1.20,"Fresno city, CA"
08,16000,"360,890","204,819","183,806","381,903","21,013",5.8,"151,480",82.4 ,1.11,"Colorado Springs city, CO"
06,69000,"337,977","142,636","124,289","356,324","18,347",5.4,"35,686",28.7 ,1.15,"Santa Ana city, CA"
20,79000,"344,284","182,958","164,725","362,517","18,233",5.3,"132,819",80.6 ,1.11,"Wichita city, KS"
39,77000,"313,619","152,916","137,076","329,459","15,840",5.1,"89,841",65.5 ,1.12,"Toledo city, OH"
06,62000,"255,166","115,969","104,326","266,809","11,643",4.6,"48,375",46.4 ,1.11,"Riverside city, CA"
48,17000,"277,454","126,648","118,869","285,233","7,779",2.8,"105,965",89.1 ,1.07,"Corpus Christi city, TX"
06,53000,"399,484","181,467","170,503","410,448","10,964",2.7,"67,089",39.3 ,1.06,"Oakland city, CA"
32,40000,"478,434","221,923","210,806","489,551","11,117",2.3,"101,780",48.3 ,1.05,"Las Vegas city, NV"
02,03000,"260,283","136,474","131,228","265,529","5,246",2.0,"126,955",96.7 ,1.04,"Anchorage municipality, AK"
06,43000,"461,522","168,085","184,479","445,128","-16,394",-3.6,"61,685",33.4 ,0.91,"Long Beach city, CA"
04,46000,"396,375","143,263","182,582","357,056","-39,319",-9.9,"72,272",39.6 ,0.78,"Mesa city, AZ"
51,82000,"425,257","173,617","222,648","376,226","-49,031",-11.5,"127,961",57.5 ,0.78,"Virginia Beach city, VA"
48,04000,"332,969","130,805","172,355","291,419","-41,550",-12.5,"67,185",39.0 ,0.76,"Arlington city, TX"
08,04000,"276,393","91,309","142,136","225,566","-50,827",-18.4,"45,188",31.8 ,0.64,"Aurora city, CO"
,,,,,,,,,,,
"100,000 to 249,999 population (first twenty places based on percent change in daytime population)",,,,,,,,,,,
06,36770,"143,072","178,507","72,870","248,709","105,637",73.8,"28,326",38.9 ,2.45,"Irvine city, CA"
49,67000,"181,743","221,367","90,187","312,923","131,180",72.2,"60,859",67.5 ,2.45,"Salt Lake City city, UT"
12,53000,"185,951","226,310","94,809","317,452","131,501",70.7,"46,758",49.3 ,2.39,"Orlando city, FL"
06,69084,"102,361","119,124","54,676","166,809","64,448",63.0,"15,522",28.4 ,2.18,"Santa Clara city, CA"
32,54600,"186,070","208,771","92,965","301,876","115,806",62.2,"44,589",48.0 ,2.25,"Paradise CDP, NV"
45,16000,"116,278","122,507","54,288","184,497","68,219",58.7,"34,842",64.2 ,2.26,"Columbia city, SC"
25,11000,"101,355","114,133","54,959","160,529","59,174",58.4,"25,554",46.5 ,2.08,"Cambridge city, MA"
09,37000,"121,578","106,869","41,009","187,438","65,860",54.2,"18,252",44.5 ,2.61,"Hartford city, CT"
12,24000,"152,397","150,863","70,732","232,528","80,131",52.6,"32,968",46.6 ,2.13,"Fort Lauderdale city, FL"
47,14000,"155,554","149,468","69,127","235,895","80,341",51.6,"57,562",83.3 ,2.16,"Chattanooga city, TN"
47,40000,"173,890","159,077","79,042","253,925","80,035",46.0,"61,057",77.2 ,2.01,"Knoxville city, TN"
53,05210,"109,569","100,324","56,474","153,419","43,850",40.0,"21,634",38.3 ,1.78,"Bellevue city, WA"
29,70000,"151,580","133,008","73,930","210,658","59,078",39.0,"65,460",88.5 ,1.80,"Springfield city, MO"
04,73000,"158,625","149,001","89,233","218,393","59,768",37.7,"35,454",39.7 ,1.67,"Tempe city, AZ"
06,08954,"100,316","84,806","48,430","136,692","36,376",36.3,"14,781",30.5 ,1.75,"Burbank city, CA"
05,41000,"183,133","153,606","87,711","249,028","65,895",36.0,"72,045",82.1 ,1.75,"Little Rock city, AR"
01,07000,"242,820","184,034","96,725","330,129","87,309",36.0,"59,697",61.7 ,1.90,"Birmingham city, AL"
36,63000,"219,773","166,933","89,467","297,239","77,466",35.2,"52,822",59.0 ,1.87,"Rochester city, NY"
51,67000,"197,790","157,003","88,924","265,869","68,079",34.4,"51,534",58.0 ,1.77,"Richmond city, VA"
26,49000,"100,545","83,368","48,856","135,057","34,512",34.3,"13,417",27.5 ,1.71,"Livonia city, MI"
,,,,,,,,,,,
"50,000 to 99,999 population (first twenty places based on percent change in daytime population)",,,,,,,,,,,
45,30850,"56,002","82,478","27,967","110,513","54,511",97.3,"15,678",56.1 ,2.95,"Greenville city, SC"
06,55282,"58,598","78,657","30,950","106,305","47,707",81.4,"11,049",35.7 ,2.54,"Palo Alto city, CA"
26,80700,"80,959","105,445","41,434","144,970","64,011",79.1,"12,127",29.3 ,2.54,"Troy city, MI"
54,14600,"53,421","62,102","24,015","91,508","38,087",71.3,"17,640",73.5 ,2.59,"Charleston city, WV"
26,74900,"78,296","94,386","38,877","133,805","55,509",70.9,"9,041",23.3 ,2.43,"Southfield city, MI"
36,01000,"95,658","109,348","42,605","162,401","66,743",69.8,"26,301",61.7 ,2.57,"Albany city, NY"
24,07125,"55,277","67,685","29,463","93,499","38,222",69.1,"8,170",27.7 ,2.30,"Bethesda CDP, MD"
12,07300,"74,764","84,138","34,374","124,528","49,764",66.6,"16,085",46.8 ,2.45,"Boca Raton city, FL"
13,49756,"58,748","68,662","31,705","95,705","36,957",62.9,"9,115",28.7 ,2.17,"Marietta city, GA"
24,78425,"51,793","55,074","24,570","82,297","30,504",58.9,"7,603",30.9 ,2.24,"Towson CDP, MD"
36,81677,"53,077","55,921","26,032","82,966","29,889",56.3,"8,348",32.1 ,2.15,"White Plains city, NY"
12,64175,"52,715","51,712","22,820","81,607","28,892",54.8,"11,374",49.8 ,2.27,"Sarasota city, FL"
26,21000,"97,775","87,946","37,881","147,840","50,065",51.2,"13,893",36.7 ,2.32,"Dearborn city, MI"
06,70000,"84,084","88,449","45,933","126,600","42,516",50.6,"14,789",32.2 ,1.93,"Santa Monica city, CA"
12,55925,"56,255","52,486","24,587","84,154","27,899",49.6,"12,721",51.7 ,2.13,"Pensacola city, FL"
37,02140,"68,889","65,708","32,125","102,472","33,583",48.7,"22,611",70.4 ,2.05,"Asheville city, NC"
12,76600,"82,103","75,948","37,043","121,008","38,905",47.4,"15,221",41.1 ,2.05,"West Palm Beach city, FL"
23,60545,"64,249","64,946","34,626","94,569","30,320",47.2,"21,439",61.9 ,1.88,"Portland city, ME"
17,68003,"75,386","77,490","43,306","109,570","34,184",45.3,"10,822",25.0 ,1.79,"Schaumburg village, IL"
47,38320,"55,469","51,007","26,155","80,321","24,852",44.8,"19,185",73.4 ,1.95,"Johnson City city, TN"
,,,,,,,,,,,
"25,000 to 49,999 population (first twenty places based on percent change in daytime population)",,,,,,,,,,,
48,25452,"27,508","51,551","14,104","64,955","37,447",136.1,"2,693",19.1 ,3.66,"Farmers Branch city, TX"
29,46586,"25,756","44,301","14,863","55,194","29,438",114.3,"3,120",21.0 ,2.98,"Maryland Heights city, MO"
34,55950,"25,737","38,484","11,576","52,645","26,908",104.5,"2,647",22.9 ,3.32,"Paramus borough, NJ"
53,57535,"45,256","72,319","25,638","91,937","46,681",103.1,"10,433",40.7 ,2.82,"Redmond city, WA"
06,06308,"33,784","50,365","15,673","68,476","34,692",102.7,"4,117",26.3 ,3.21,"Beverly Hills city, CA"
13,01696,"34,854","53,073","18,795","69,132","34,278",98.3,"5,786",30.8 ,2.82,"Alpharetta city, GA"
13,31908,"25,578","35,874","10,811","50,641","25,063",98.0,"6,122",56.6 ,3.32,"Gainesville city, GA"
48,26736,"33,711","50,405","18,222","65,894","32,183",95.5,"15,725",86.3 ,2.77,"Fort Hood CDP, TX"
17,23256,"34,727","51,386","19,188","66,925","32,198",92.7,"4,537",23.6 ,2.68,"Elk Grove Village village, IL"
13,21380,"27,912","37,773","12,067","53,618","25,706",92.1,"8,013",66.4 ,3.13,"Dalton city, GA"
34,02080,"40,517","51,759","14,639","77,637","37,120",91.6,"10,972",75.0 ,3.54,"Atlantic City city, NJ"
37,31060,"37,222","49,037","18,955","67,304","30,082",80.8,"12,070",63.7 ,2.59,"Hickory city, NC"
37,24260,"29,183","41,197","17,804","52,576","23,393",80.2,"15,475",86.9 ,2.31,"Fort Bragg CDP, NC"
24,56337,"38,610","51,356","20,595","69,371","30,761",79.7,"3,595",17.5 ,2.49,"North Bethesda CDP, MD"
12,50750,"45,943","54,334","18,439","81,838","35,895",78.1,"13,165",71.4 ,2.95,"Ocala city, FL"
24,67675,"47,388","60,437","23,888","83,937","36,549",77.1,"5,414",22.7 ,2.53,"Rockville city, MD"
42,32800,"48,950","56,130","20,520","84,560","35,610",72.7,"9,210",44.9 ,2.74,"Harrisburg city, PA"
21,58836,"26,307","28,801","10,162","44,946","18,639",70.9,"7,651",75.3 ,2.83,"Paducah city, KY"
47,55120,"27,387","30,823","11,887","46,323","18,936",69.1,"8,035",67.6 ,2.59,"Oak Ridge city, TN"
29,37000,"39,636","45,766","18,860","66,542","26,906",67.9,"16,331",86.6 ,2.43,"Jefferson City city, MO"
,,,,,,,,,,,
"15,000 to 24,999 population (first twenty places based on percent change in daytime population)",,,,,,,,,,,
51,79952,"18,540","65,430","11,319","72,651","54,111",291.9,"2,554",22.6 ,5.78,"Tysons Corner CDP, VA"
06,22412,"16,033","55,231","9,092","62,172","46,139",287.8,"2,919",32.1 ,6.07,"El Segundo city, CA"
06,69154,"17,438","50,083","6,256","61,265","43,827",251.3,"1,112",17.8 ,8.01,"Santa Fe Springs city, CA"
12,17935,"20,438","53,131","9,767","63,802","43,364",212.2,"2,623",26.9 ,5.44,"Doral CDP, FL"
26,04105,"19,837","48,672","10,752","57,757","37,920",191.2,"2,520",23.4 ,4.53,"Auburn Hills city, MI"
29,17272,"16,500","38,631","8,184","46,947","30,447",184.5,"1,927",23.5 ,4.72,"Creve Coeur city, MO"
34,66570,"15,931","35,226","7,331","43,826","27,895",175.1,"1,970",26.9 ,4.81,"Secaucus town, NJ"
12,47625,"20,976","35,991","7,138","49,829","28,853",137.6,"4,006",56.1 ,5.04,"Naples city, FL"
53,72625,"17,181","32,064","8,656","40,589","23,408",136.2,"1,502",17.4 ,3.70,"Tukwila city, WA"
42,39736,"18,511","34,969","10,708","42,772","24,261",131.1,"2,930",27.4 ,3.27,"King of Prussia CDP, PA"
29,08398,"15,550","28,035","7,716","35,869","20,319",130.7,"1,641",21.3 ,3.63,"Bridgeton city, MO"
26,69420,"22,979","38,358","10,254","51,083","28,104",122.3,"2,838",27.7 ,3.74,"Romulus city, MI"
36,32732,"20,100","32,852","10,257","42,695","22,595",112.4,"1,754",17.1 ,3.20,"Hauppauge CDP, NY"
55,03425,"17,634","28,321","9,568","36,387","18,753",106.3,"3,633",38.0 ,2.96,"Ashwaubenon village, WI"
45,49075,"22,759","35,160","12,430","45,489","22,730",99.9,"7,855",63.2 ,2.83,"Myrtle Beach city, SC"
42,31200,"15,889","22,187","7,006","31,070","15,181",95.5,"2,819",40.2 ,3.17,"Greensburg city, PA"
13,11560,"15,600","20,854","5,961","30,493","14,893",95.5,"3,925",65.8 ,3.50,"Brunswick city, GA"
25,09875,"22,876","34,004","12,210","44,670","21,794",95.3,"3,315",27.1 ,2.78,"Burlington CDP, MA"
24,18250,"19,388","30,184","11,742","37,830","18,442",95.1,"2,656",22.6 ,2.57,"Cockeysville CDP, MD"
51,26496,"21,498","31,381","11,845","41,034","19,536",90.9,"2,712",22.9 ,2.65,"Fairfax city, VA"
,,,,,,,,,,,
"5,000 to 14,999 population (first twenty places based on percent change in daytime population)",,,,,,,,,,,
06,14974,"12,568","48,567","3,882","57,253","44,685",355.5,818,21.1 ,12.51,"Commerce city, CA"
17,54534,"8,702","34,344","3,834","39,212","30,510",350.6,551,14.4 ,8.96,"Oak Brook village, IL"
08,33035,"11,035","40,690","5,333","46,392","35,357",320.4,"1,444",27.1 ,7.63,"Greenwood Village city, CO"
36,21985,"5,400","19,408","2,615","22,193","16,793",311.0,293,11.2 ,7.42,"East Farmingdale CDP, NY"
39,86660,"6,656","20,460","2,918","24,198","17,542",263.6,"1,925",66.0 ,7.01,"Wright-Patterson AFB CDP, OH"
13,55776,"8,410","25,210","4,237","29,383","20,973",249.4,691,16.3 ,5.95,"Norcross city, GA"
06,10561,"8,854","26,363","4,318","30,899","22,045",249.0,"2,454",56.8 ,6.11,"Camp Pendleton South CDP, CA"
34,22380,"7,063","20,616","3,508","24,171","17,108",242.2,775,22.1 ,5.88,"Fairfield CDP, NJ"
39,52010,"6,897","19,577","3,390","23,084","16,187",234.7,"1,016",30.0 ,5.77,"Moraine city, OH"
17,43666,"6,108","16,349","2,697","19,760","13,652",223.5,336,12.5 ,6.06,"Lincolnshire village, IL"
24,29400,"9,882","26,457","4,884","31,455","21,573",218.3,"3,195",65.4 ,5.42,"Fort Meade CDP, MD"
39,07300,"12,513","32,704","6,551","38,666","26,153",209.0,"1,549",23.6 ,4.99,"Blue Ash city, OH"
06,22594,"6,882","18,097","4,155","20,824","13,942",202.6,920,22.1 ,4.36,"Emeryville city, CA"
39,37240,"7,109","17,048","3,345","20,812","13,703",192.8,783,23.4 ,5.10,"Independence city, OH"
17,37907,"8,302","20,320","4,375","24,247","15,945",192.1,737,16.8 ,4.64,"Itasca village, IL"
36,46514,"14,533","34,488","6,662","42,359","27,826",191.5,"1,040",15.6 ,5.18,"Melville CDP, NY"
29,14572,"12,825","30,043","6,018","36,850","24,025",187.3,"1,511",25.1 ,4.99,"Clayton city, MO"
36,78960,"5,216","12,027","2,436","14,807","9,591",183.9,579,23.8 ,4.94,"Webster village, NY"
29,07966,"6,050","13,508","3,043","16,515","10,465",173.0,"2,167",71.2 ,4.44,"Branson city, MO"
48,01240,"14,166","32,432","9,064","37,534","23,368",165.0,"1,172",12.9 ,3.58,"Addison town, TX"
,,,,,,,,,,,
"Under 5,000 population (first twenty places based on percent change in daytime population)",,,,,,,,,,,
12,37625,16,"30,768",10,"30,774","30,758",192237.5,4,40.0 ,3076.80,"Lake Buena Vista city, FL"
06,82422,91,"37,472",36,"37,527","37,436",41138.5,17,47.2 ,1040.89,"Vernon city, CA"
34,72480,18,"6,697",13,"6,702","6,684",37133.3,3,23.1 ,515.15,"Teterboro borough, NJ"
06,36490,777,"52,223",240,"52,760","51,983",6690.2,75,31.3 ,217.60,"Industry city, CA"
08,50012,184,"7,905",112,"7,977","7,793",4235.3,10,8.9 ,70.58,"Meridian CDP, CO"
17,04572,574,"17,021",310,"17,285","16,711",2911.3,38,12.3 ,54.91,"Bedford Park village, IL"
18,18982,213,"5,959",105,"6,067","5,854",2748.4,24,22.9 ,56.75,"Dune Acres town, IN"
17,65104,145,"3,941",71,"4,015","3,870",2669.0,25,35.2 ,55.51,"Rock Island Arsenal CDP, IL"
08,07025,118,"2,879",88,"2,909","2,791",2365.3,29,33.0 ,32.72,"Black Hawk city, CO"
36,22065,979,"23,591",485,"24,085","23,106",2360.2,38,7.8 ,48.64,"East Garden City CDP, NY"
08,54750,549,"11,439",178,"11,810","11,261",2051.2,46,25.8 ,64.26,"North Washington CDP, CO"
18,15652,203,"3,852",89,"3,966","3,763",1853.7,34,38.2 ,43.28,"Crane town, IN"
17,45564,254,"4,780",126,"4,908","4,654",1832.3,32,25.4 ,37.94,"McCook village, IL"
48,77620,207,"3,633",99,"3,741","3,534",1707.2,28,28.3 ,36.70,"Westlake town, TX"
17,67756,249,"3,576",80,"3,745","3,496",1404.0,34,42.5 ,44.70,"Sauget village, IL"
39,19806,599,"7,425",270,"7,754","7,155",1194.5,79,29.3 ,27.50,"Cuyahoga Heights village, OH"
12,43900,"1,098","12,776",353,"13,521","12,423",1131.4,89,25.2 ,36.19,"Medley town, FL"
48,41563,283,"2,885",68,"3,100","2,817",995.4,0,0.0 ,42.43,"Las Colonias CDP, TX"
06,36826,"1,446","13,341",571,"14,216","12,770",883.1,123,21.5 ,23.36,"Irwindale city, CA"
47,05140,674,"6,330",442,"6,562","5,888",873.6,65,14.7 ,14.32,"Berry Hill city, TN"
,,,,,,,,,,,
"1/Based on data for places with either 2,500 workers living in the place or 2,500 workers working in the place.",,,,,,,,,,,
,,,,,,,,,,,
NOTES,,,,,,,,,,,
Workers – people 16 years and over who were employed and at work during the reference week.  The estimate of workers includes part-time and full-time civilian personnel and people in the Armed Forces.,,,,,,,,,,,
(Col. 1) FIPS state code – the two-digit code used in the Federal Information Processing Standards to identify each state.,,,,,,,,,,,
"(Col. 2) FIPS place code – the five-digit code used in the Federal Information Processing Standards to identify each place, both incorporated places and census designated places (CDP), within each state.",,,,,,,,,,,
"(Col. 3) Total resident population – the total number of persons living in the place, as shown in Census 2000 100-percent data such as Summary File 1.",,,,,,,,,,,
"(Col. 4) Total workers working in the place – this is the number of workers who reported working in the place, regardless of their place of residence. In other words, it is the total that worked there no matter where they lived. Residence locations are not considered, only workplace locations are reflected in this number.",,,,,,,,,,,
"(Col. 5) Total workers living in the place – this is sometimes referred to as the number of resident workers. It is the number of people living in the place who are workers. It includes workers who live there regardless of where they worked, or in other words, no matter where their workplace was located. Place of work location is not considered, only residence location is reflected in this number.",,,,,,,,,,,
"(Col. 6) Estimated daytime population – this is the estimate arrived at by adjusting the total resident population by the number of incommuters and outcommuters to the place, using data from Census 2000. It does not adjust for people entering or leaving the place for purposes other than commuting, nor does the commuting adjustment take the time of day of the work trips into account.  The estimate is calculated by adding the total resident population (col. 3) and the total workers working in the place (col. 4), and then subtracting from that result the total workers living in the place (col. 5). This method yields the same result as would be obtained by adding the incommuters and subtracting the outcommuters from the total resident population.",,,,,,,,,,,
(Col. 7) Daytime population change due to commuting: number – this is the numeric increase or decrease in the population of the place as a result of work-related commuting. It is the net change in the population due to work travel and is computed by subtracting the total resident population (col. 3) from the estimated daytime population (col. 6). Positive numbers indicate more commuters entering the place than leaving it. Negative numbers occur when more workers leave the place to go to work than enter it to come to work. ,,,,,,,,,,,
"(Col. 8) Daytime population change due to commuting: percent – this is the percentage increase or decrease in the population of the place as a result of work-related commuting. It is calculated by dividing the numeric change due to commuting (col. 7) by the total resident population (col. 3), and multiplying the result by 100. Positive figures denote the percentage increase experienced by the population, while negative numbers show the percentage decrease in the population as a result of commuting.",,,,,,,,,,,
(Col. 9) Workers who lived and worked in the same place: number – this value shows how many workers who lived in a particular place also worked in that same place. It is derived from place of residence location information and responses to the question on workplace location during the week prior to filling out the census questionnaire.,,,,,,,,,,,
"(Col. 10) Workers who lived and worked in the same place: percent – this measure is sometimes used as an indicator of worker retention, but it does not reflect variation in area size or other attributes very well. It is computed by dividing the number of workers who lived and worked in the same place (col. 9) by the total workers living there (col. 5) and multiplying the result by 100.",,,,,,,,,,,
"(Col. 11) Employment-residence (E-R) ratio – this is a measure of the total number of workers working in a place (col. 4), relative to the total number of workers living in the place (col. 5). It is often used as a rough indication of the jobs-workers balance in a place, although it does not take into account whether the resident workers possess the skills needed for the jobs that are available. E-R ratios greater than 1.00 occur when there are more workers working in the place than living there. These places can be considered as net importers of labor. For example, an E-R ratio of 1.19 means that there are 19 percent more workers working in the place than living in the place. Values less than 1.00 indicate places that send more workers to other areas than they receive, i.e., they are net exporters of labor.",,,,,,,,,,,
,,,,,,,,,,,
"Source: U.S. Census Bureau, Census 2000.",,,,,,,,,,,
"Contact: Journey to Work and Migration Statistics Branch, Population Division, 301-763-2454.",,,,,,,,,,,