In the wake of the Great Recession of 2009, there has been a good deal of focus on employment statistics, one of the most important metrics policymakers use to gauge the overall strength of the economy. In the United States, the government measures unemployment using the Current Population Survey (CPS), which collects demographic and employment information from a wide range of Americans each month. In this exercise, we will employ the topics reviewed in the lectures as well as a few new techniques using the September 2013 version of this rich, nationally representative dataset (available online).
The observations in the dataset represent people surveyed in the September 2013 CPS who actually completed a survey. While the full dataset has 385 variables, in this exercise we will use a more compact version of the dataset, CPSData.csv, which has the following variables:
PeopleInHousehold: The number of people in the interviewee’s household.
Region: The census region where the interviewee lives.
State: The state where the interviewee lives.
MetroAreaCode: A code that identifies the metropolitan area in which the interviewee lives (missing if the interviewee does not live in a metropolitan area). The mapping from codes to names of metropolitan areas is provided in the file MetroAreaCodes.csv.
Age: The age, in years, of the interviewee. 80 represents people aged 80-84, and 85 represents people aged 85 and higher.
Married: The marriage status of the interviewee.
Sex: The sex of the interviewee.
Education: The maximum level of education obtained by the interviewee.
Race: The race of the interviewee.
Hispanic: Whether the interviewee is of Hispanic ethnicity.
CountryOfBirthCode: A code identifying the country of birth of the interviewee. The mapping from codes to names of countries is provided in the file CountryCodes.csv.
Citizenship: The United States citizenship status of the interviewee.
EmploymentStatus: The status of employment of the interviewee.
Industry: The industry of employment of the interviewee (only available if they are employed).
Load the dataset from CPSData.csv into a data frame called CPS, and view the dataset with the summary() and str() commands.How many interviewees are in the dataset?
str(CPS)'data.frame': 131302 obs. of 14 variables:
$ PeopleInHousehold : int 1 3 3 3 3 3 3 2 2 2 ...
$ Region : Factor w/ 4 levels "Midwest","Northeast",..: 3 3 3 3 3 3 3 3 3 3 ...
$ State : Factor w/ 51 levels "Alabama","Alaska",..: 1 1 1 1 1 1 1 1 1 1 ...
$ MetroAreaCode : int 26620 13820 13820 13820 26620 26620 26620 33660 33660 26620 ...
$ Age : int 85 21 37 18 52 24 26 71 43 52 ...
$ Married : Factor w/ 5 levels "Divorced","Married",..: 5 3 3 3 5 3 3 1 1 3 ...
$ Sex : Factor w/ 2 levels "Female","Male": 1 2 1 2 1 2 2 1 2 2 ...
$ Education : Factor w/ 8 levels "Associate degree",..: 1 4 4 6 1 2 4 4 4 2 ...
$ Race : Factor w/ 6 levels "American Indian",..: 6 3 3 3 6 6 6 6 6 6 ...
$ Hispanic : int 0 0 0 0 0 0 0 0 0 0 ...
$ CountryOfBirthCode: int 57 57 57 57 57 57 57 57 57 57 ...
$ Citizenship : Factor w/ 3 levels "Citizen, Native",..: 1 1 1 1 1 1 1 1 1 1 ...
$ EmploymentStatus : Factor w/ 5 levels "Disabled","Employed",..: 4 5 1 3 2 2 2 2 3 2 ...
$ Industry : Factor w/ 14 levels "Agriculture, forestry, fishing, and hunting",..: NA 11 NA NA 11 4 14 4 NA 12 ...Among the interviewees with a value reported for the Industry variable, what is the most common industry of employment? Please enter the name exactly how you see it.
sort(table(CPS$Industry))
Armed forces
29
Mining
550
Agriculture, forestry, fishing, and hunting
1307
Information
1328
Public administration
3186
Other services
3224
Transportation and utilities
3260
Financial
4347
Construction
4387
Leisure and hospitality
6364
Manufacturing
6791
Professional and business services
7519
Trade
8933
Educational and health services
15017 Recall from the homework assignment “The Analytical Detective” that you can call the sort() function on the output of the table() function to obtain a sorted breakdown of a variable. For instance, sort(table(CPS$Region)) sorts the regions by the number of interviewees from that region.
Which state has the fewest interviewees?
sort(table(CPS$State))
New Mexico Montana Mississippi
1102 1214 1230
Alabama West Virginia Arkansas
1376 1409 1421
Louisiana Idaho Oklahoma
1450 1518 1523
Arizona Alaska Wyoming
1528 1590 1624
North Dakota South Carolina Tennessee
1645 1658 1784
District of Columbia Kentucky Utah
1791 1841 1842
Nevada Vermont Kansas
1856 1890 1935
Oregon Nebraska Massachusetts
1943 1949 1987
South Dakota Indiana Hawaii
2000 2004 2099
Missouri Rhode Island Delaware
2145 2209 2214
Maine Washington Iowa
2263 2366 2528
New Jersey North Carolina New Hampshire
2567 2619 2662
Wisconsin Georgia Connecticut
2686 2807 2836
Colorado Virginia Michigan
2925 2953 3063
Minnesota Maryland Ohio
3139 3200 3678
Illinois Pennsylvania Florida
3912 3930 5149
New York Texas California
5595 7077 11570 Which state has the largest number of interviewees?
What proportion of interviewees are citizens of the United States?
table(CPS$Citizenship)
Citizen, Native Citizen, Naturalized Non-Citizen
116639 7073 7590 (116639+7073)/(116639+7073+7590)[1] 0.9421943The CPS differentiates between race (with possible values American Indian, Asian, Black, Pacific Islander, White, or Multiracial) and ethnicity. A number of interviewees are of Hispanic ethnicity, as captured by the Hispanic variable. For which races are there at least 250 interviewees in the CPS dataset of Hispanic ethnicity? (Select all that apply.)
table(CPS$Race, CPS$Hispanic)
0 1
American Indian 1129 304
Asian 6407 113
Black 13292 621
Multiracial 2449 448
Pacific Islander 541 77
White 89190 16731Which variables have at least one interviewee with a missing (NA) value? (Select all that apply.)
summary(CPS)
PeopleInHousehold Region State MetroAreaCode
Min. : 1.000 Midwest :30684 California :11570 Min. :10420
1st Qu.: 2.000 Northeast:25939 Texas : 7077 1st Qu.:21780
Median : 3.000 South :41502 New York : 5595 Median :34740
Mean : 3.284 West :33177 Florida : 5149 Mean :35075
3rd Qu.: 4.000 Pennsylvania: 3930 3rd Qu.:41860
Max. :15.000 Illinois : 3912 Max. :79600
(Other) :94069 NA's :34238
Age Married Sex
Min. : 0.00 Divorced :11151 Female:67481
1st Qu.:19.00 Married :55509 Male :63821
Median :39.00 Never Married:30772
Mean :38.83 Separated : 2027
3rd Qu.:57.00 Widowed : 6505
Max. :85.00 NA's :25338
Education Race
High school :30906 American Indian : 1433
Bachelor's degree :19443 Asian : 6520
Some college, no degree:18863 Black : 13913
No high school diploma :16095 Multiracial : 2897
Associate degree : 9913 Pacific Islander: 618
(Other) :10744 White :105921
NA's :25338
Hispanic CountryOfBirthCode Citizenship
Min. :0.0000 Min. : 57.00 Citizen, Native :116639
1st Qu.:0.0000 1st Qu.: 57.00 Citizen, Naturalized: 7073
Median :0.0000 Median : 57.00 Non-Citizen : 7590
Mean :0.1393 Mean : 82.68
3rd Qu.:0.0000 3rd Qu.: 57.00
Max. :1.0000 Max. :555.00
EmploymentStatus Industry
Disabled : 5712 Educational and health services :15017
Employed :61733 Trade : 8933
Not in Labor Force:15246 Professional and business services: 7519
Retired :18619 Manufacturing : 6791
Unemployed : 4203 Leisure and hospitality : 6364
NA's :25789 (Other) :21618
NA's :65060 Often when evaluating a new dataset, we try to identify if there is a pattern in the missing values in the dataset. We will try to determine if there is a pattern in the missing values of the Married variable. The function
is.na(CPS$Married) returns a vector of TRUE/FALSE values for whether the Married variable is missing. We can see the breakdown of whether Married is missing based on the reported value of the Region variable with the function
table(CPS$Region, is.na(CPS$Married))Which is the most accurate:
As mentioned in the variable descriptions, MetroAreaCode is missing if an interviewee does not live in a metropolitan area. Using the same technique as in the previous question, answer the following questions about people who live in non-metropolitan areas.
How many states had all interviewees living in a non-metropolitan area (aka they have a missing MetroAreaCode value)? For this question, treat the District of Columbia as a state (even though it is not technically a state).
table(CPS$State, is.na(CPS$MetroAreaCode))
FALSE TRUE
Alabama 1020 356
Alaska 0 1590
Arizona 1327 201
Arkansas 724 697
California 11333 237
Colorado 2545 380
Connecticut 2593 243
Delaware 1696 518
District of Columbia 1791 0
Florida 4947 202
Georgia 2250 557
Hawaii 1576 523
Idaho 761 757
Illinois 3473 439
Indiana 1420 584
Iowa 1297 1231
Kansas 1234 701
Kentucky 908 933
Louisiana 1216 234
Maine 909 1354
Maryland 2978 222
Massachusetts 1858 129
Michigan 2517 546
Minnesota 2150 989
Mississippi 376 854
Missouri 1440 705
Montana 199 1015
Nebraska 816 1133
Nevada 1609 247
New Hampshire 1148 1514
New Jersey 2567 0
New Mexico 832 270
New York 5144 451
North Carolina 1642 977
North Dakota 432 1213
Ohio 2754 924
Oklahoma 1024 499
Oregon 1519 424
Pennsylvania 3245 685
Rhode Island 2209 0
South Carolina 1139 519
South Dakota 595 1405
Tennessee 1149 635
Texas 6060 1017
Utah 1455 387
Vermont 657 1233
Virginia 2367 586
Washington 1937 429
West Virginia 344 1065
Wisconsin 1882 804
Wyoming 0 1624How many states had all interviewees living in a metropolitan area? Again, treat the District of Columbia as a state.
Which region of the United States has the largest proportion of interviewees living in a non-metropolitan area?
table(CPS$Region, is.na(CPS$MetroAreaCode))
FALSE TRUE
Midwest 20010 10674
Northeast 20330 5609
South 31631 9871
West 25093 808410674/(20010+10674)[1] 0.34786865609/(20330+5609)[1] 0.21623819871/(31631+9871)[1] 0.2378448084/(25093+8084)[1] 0.2436628While we were able to use the table() command to compute the proportion of interviewees from each region not living in a metropolitan area, it was somewhat tedious (it involved manually computing the proportion for each region) and isn’t something you would want to do if there were a larger number of options. It turns out there is a less tedious way to compute the proportion of values that are TRUE. The mean() function, which takes the average of the values passed to it, will treat TRUE as 1 and FALSE as 0, meaning it returns the proportion of values that are true. For instance, mean(c(TRUE, FALSE, TRUE, TRUE)) returns 0.75. Knowing this, use tapply() with the mean function to answer the following questions:
Which state has a proportion of interviewees living in a non-metropolitan area closest to 30%?
tapply(is.na(CPS$MetroAreaCode), CPS$State, mean) Alabama Alaska Arizona
0.25872093 1.00000000 0.13154450
Arkansas California Colorado
0.49049965 0.02048401 0.12991453
Connecticut Delaware District of Columbia
0.08568406 0.23396567 0.00000000
Florida Georgia Hawaii
0.03923092 0.19843249 0.24916627
Idaho Illinois Indiana
0.49868248 0.11221881 0.29141717
Iowa Kansas Kentucky
0.48694620 0.36227390 0.50678979
Louisiana Maine Maryland
0.16137931 0.59832081 0.06937500
Massachusetts Michigan Minnesota
0.06492199 0.17825661 0.31506849
Mississippi Missouri Montana
0.69430894 0.32867133 0.83607908
Nebraska Nevada New Hampshire
0.58132376 0.13308190 0.56874530
New Jersey New Mexico New York
0.00000000 0.24500907 0.08060769
North Carolina North Dakota Ohio
0.37304315 0.73738602 0.25122349
Oklahoma Oregon Pennsylvania
0.32764281 0.21821925 0.17430025
Rhode Island South Carolina South Dakota
0.00000000 0.31302774 0.70250000
Tennessee Texas Utah
0.35594170 0.14370496 0.21009772
Vermont Virginia Washington
0.65238095 0.19844226 0.18131868
West Virginia Wisconsin Wyoming
0.75585522 0.29932986 1.00000000 Which state has the largest proportion of non-metropolitan interviewees, ignoring states where all interviewees were non-metropolitan?
Codes like MetroAreaCode and CountryOfBirthCode are a compact way to encode factor variables with text as their possible values, and they are therefore quite common in survey datasets. In fact, all but one of the variables in this dataset were actually stored by a numeric code in the original CPS datafile.
When analyzing a variable stored by a numeric code, we will often want to convert it into the values the codes represent. To do this, we will use a dictionary, which maps the the code to the actual value of the variable. We have provided dictionaries MetroAreaCodes.csv and CountryCodes.csv, which respectively map MetroAreaCode and CountryOfBirthCode into their true values. Read these two dictionaries into data frames MetroAreaMap and CountryMap.
How many observations (codes for metropolitan areas) are there in MetroAreaMap?
str(MetroAreaMap)'data.frame': 271 obs. of 2 variables:
$ Code : int 460 3000 3160 3610 3720 6450 10420 10500 10580 10740 ...
$ MetroArea: Factor w/ 271 levels "Akron, OH","Albany, GA",..: 13 92 98 117 122 195 1 2 3 4 ...How many observations (codes for countries) are there in CountryMap?
str(CountryMap)'data.frame': 149 obs. of 2 variables:
$ Code : int 57 66 73 78 96 100 102 103 104 105 ...
$ Country: Factor w/ 149 levels "Afghanistan",..: 140 57 105 135 97 3 11 18 24 37 ...To merge in the metropolitan areas, we want to connect the field MetroAreaCode from the CPS data frame with the field Code in MetroAreaMap. The following command merges the two data frames on these columns, overwriting the CPS data frame with the result:
CPS = merge(CPS, MetroAreaMap, by.x="MetroAreaCode", by.y="Code", all.x=TRUE)The first two arguments determine the data frames to be merged (they are called “x” and “y”, respectively, in the subsequent parameters to the merge function). by.x=“MetroAreaCode” means we’re matching on the MetroAreaCode variable from the “x” data frame (CPS), while by.y=“Code” means we’re matching on the Code variable from the “y” data frame (MetroAreaMap). Finally, all.x=TRUE means we want to keep all rows from the “x” data frame (CPS), even if some of the rows’ MetroAreaCode doesn’t match any codes in MetroAreaMap (for those familiar with database terminology, this parameter makes the operation a left outer join instead of an inner join).
Review the new version of the CPS data frame with the summary() and str() functions. What is the name of the variable that was added to the data frame by the merge() operation?
CPS = merge(CPS, MetroAreaMap, by.x="MetroAreaCode", by.y="Code", all.x=TRUE)
summary(CPS) MetroAreaCode PeopleInHousehold Region State
Min. :10420 Min. : 1.000 Midwest :30684 California :11570
1st Qu.:21780 1st Qu.: 2.000 Northeast:25939 Texas : 7077
Median :34740 Median : 3.000 South :41502 New York : 5595
Mean :35075 Mean : 3.284 West :33177 Florida : 5149
3rd Qu.:41860 3rd Qu.: 4.000 Pennsylvania: 3930
Max. :79600 Max. :15.000 Illinois : 3912
NA's :34238 (Other) :94069
Age Married Sex
Min. : 0.00 Divorced :11151 Female:67481
1st Qu.:19.00 Married :55509 Male :63821
Median :39.00 Never Married:30772
Mean :38.83 Separated : 2027
3rd Qu.:57.00 Widowed : 6505
Max. :85.00 NA's :25338
Education Race
High school :30906 American Indian : 1433
Bachelor's degree :19443 Asian : 6520
Some college, no degree:18863 Black : 13913
No high school diploma :16095 Multiracial : 2897
Associate degree : 9913 Pacific Islander: 618
(Other) :10744 White :105921
NA's :25338
Hispanic CountryOfBirthCode Citizenship
Min. :0.0000 Min. : 57.00 Citizen, Native :116639
1st Qu.:0.0000 1st Qu.: 57.00 Citizen, Naturalized: 7073
Median :0.0000 Median : 57.00 Non-Citizen : 7590
Mean :0.1393 Mean : 82.68
3rd Qu.:0.0000 3rd Qu.: 57.00
Max. :1.0000 Max. :555.00
EmploymentStatus Industry
Disabled : 5712 Educational and health services :15017
Employed :61733 Trade : 8933
Not in Labor Force:15246 Professional and business services: 7519
Retired :18619 Manufacturing : 6791
Unemployed : 4203 Leisure and hospitality : 6364
NA's :25789 (Other) :21618
NA's :65060
MetroArea
New York-Northern New Jersey-Long Island, NY-NJ-PA: 5409
Washington-Arlington-Alexandria, DC-VA-MD-WV : 4177
Los Angeles-Long Beach-Santa Ana, CA : 4102
Philadelphia-Camden-Wilmington, PA-NJ-DE : 2855
Chicago-Naperville-Joliet, IN-IN-WI : 2772
(Other) :77749
NA's :34238 How many interviewees have a missing value for the new metropolitan area variable? Note that all of these interviewees would have been removed from the merged data frame if we did not include the all.x=TRUE parameter.
Which of the following metropolitan areas has the largest number of interviewees?
table(CPS$MetroArea)
Akron, OH
231
Albany, GA
68
Albany-Schenectady-Troy, NY
268
Albuquerque, NM
609
Allentown-Bethlehem-Easton, PA-NJ
334
Altoona, PA
82
Amarillo, TX
88
Anderson, IN
62
Anderson, SC
64
Ann Arbor, MI
85
Anniston-Oxford, AL
61
Appleton,WI
125
Appleton-Oshkosh-Neenah, WI
0
Asheville, NC
116
Athens-Clark County, GA
65
Atlanta-Sandy Springs-Marietta, GA
1552
Atlantic City, NJ
111
Augusta-Richmond County, GA-SC
161
Austin-Round Rock, TX
516
Bakersfield, CA
245
Baltimore-Towson, MD
1483
Bangor, ME
208
Barnstable Town, MA
75
Baton Rouge, LA
262
Beaumont-Port Author, TX
123
Bellingham, WA
70
Bend, OR
140
Billings, MT
199
Binghamton, NY
73
Birmingham-Hoover, AL
392
Bloomington, IN
104
Bloomington-Normal IL
40
Boise City-Nampa, ID
644
Boston-Cambridge-Quincy, MA-NH
2229
Boulder, CO
171
Bowling Green, KY
29
Bremerton-Silverdale, WA
87
Bridgeport-Stamford-Norwalk, CT
730
Brownsville-Harlingen, TX
79
Buffalo-Niagara Falls, NY
344
Burlington-South Burlington, VT
657
Canton-Massillon, OH
118
Cape Coral-Fort Myers, FL
146
Cedar Rapids, IA
196
Champaign-Urbana, IL
122
Charleston, WV
262
Charleston-North Charleston, SC
232
Charlotte-Gastonia-Concord, NC-SC
517
Chattanooga, TN-GA
167
Chicago-Naperville-Joliet, IN-IN-WI
2772
Chico, CA
60
Cincinnati-Middletown, OH-KY-IN
719
Cleveland-Elyria-Mentor, OH
681
Coeur d'Alene, ID
117
Colorado Springs, CO
372
Columbia, MO
47
Columbia, SC
291
Columbus, GA-AL
59
Columbus, OH
551
Corpus Christi, TX
132
Dallas-Fort Worth-Arlington, TX
1863
Danbury, CT
112
Davenport-Moline-Rock Island, IA-IL
240
Dayton, OH
268
Decatur, Al
96
Decatur, IL
81
Deltona-Daytona Beach-Ormond Beach, FL
140
Denver-Aurora, CO
1504
Des Moines, IA
501
Detroit-Warren-Livonia, MI
1354
Dover, DE
456
Duluth, MN-WI
126
Durham, NC
189
Eau Claire, WI
110
El Centro, CA
99
El Paso, TX
244
Erie, PA
87
Eugene-Springfield, OR
196
Evansville, IN-KY
99
Fargo, ND-MN
432
Farmington, NM
64
Fayetteville, NC
77
Fayetteville-Springdale-Rogers, AR-MO
215
Flint, MI
102
Florence, AL
63
Fort Collins-Loveland, CO
206
Fort Smith, AR-OK
105
Fort Walton Beach-Crestview-Destin, FL
80
Fort Wayne, IN
136
Fresno, CA
303
Gainesville, FL
70
Grand Rapids-Muskegon-Holland, MI
0
Grand Rapids-Wyoming, MI
304
Greeley, CO
162
Green Bay, WI
136
Greensboro-High Point, NC
251
Greenville, SC
185
Greenville-Spartanburg-Anderson, SC
0
Gulfport-Biloxi, MS
65
Hagerstown-Martinsburg, MD-WV
86
Harrisburg-Carlisle, PA
174
Harrisonburg, VA
90
Hartford-West Hartford-East Hartford, CT
885
Hickory-Morgantown-Lenoir, NC
57
Hinesville-Fort Stewart, GA
0
Holland-Grand Haven, MI
78
Honolulu, HI
1576
Houston-Baytown-Sugar Land, TX
1649
Huntington-Ashland, WV-KY-OH
82
Huntsville, AL
117
Indianapolis, IN
570
Iowa City, IA
131
Jackson, MI
70
Jackson, MS
222
Jacksonville, FL
393
Jacksonville, NC
63
Jamestown, NY
0
Janesville, WI
99
Johnson City, TN
52
Johnstown, PA
63
Joplin, MO
59
Kalamazoo-Battle Creek, MI
0
Kalamazoo-Portage, MI
127
Kankakee-Bradley, IL
87
Kansas City, MO-KS
962
Killeen-Temple-Fort Hood, TX
101
Kingsport-Bristol, TN-VA
67
Kingston, NY
87
Knoxville, TN
168
La Crosse, WI
114
Lafayette, LA
181
Lake Charles, LA
81
Lakeland-Winter Haven, FL
149
Lancaster, PA
156
Lansing-East Lansing, MI
119
Laredo, TX
89
Las Cruses, NM
107
Las Vegas-Paradise, NV
1299
Lawrence, KS
98
Lawton, OK
97
Leominster-Fitchburg-Gardner, MA
66
Lexington-Fayette, KY
198
Little Rock-North Little Rock, AR
404
Longview, TX
65
Los Angeles-Long Beach-Santa Ana, CA
4102
Louisville, KY-IN
519
Lubbock, TX
63
Lynchburg, VA
73
Macon, GA
65
Madera, CA
57
Madison, WI
284
McAllen-Edinburg-Pharr, TX
195
Medford, OR
82
Memphis, TN-MS-AR
348
Merced, CA
106
Miami-Fort Lauderdale-Miami Beach, FL
1554
Michigan City-La Porte, IN
77
Midland, TX
51
Milwaukee-Waukesha-West Allis, WI
714
Minneapolis-St Paul-Bloomington, MN-WI
1942
Mobile, AL
110
Modesto, CA
158
Monroe, LA
179
Monroe, MI
63
Montgomery, AL
103
Muskegon-Norton Shores, MI
90
Myrtle Beach-Conway-North Myrtle Beach, SC
102
Napa, CA
61
Naples-Marco Island, FL
82
Nashville-Davidson-Murfreesboro, TN
505
New Haven, CT
506
New Orleans-Metairie-Kenner, LA
367
New York-Northern New Jersey-Long Island, NY-NJ-PA
5409
Niles-Benton Harbor, MI
51
Norwich-New London, CT-RI
203
Ocala, FL
76
Ocean City, NJ
30
Ogden-Clearfield, UT
423
Oklahoma City, OK
604
Olympia, WA
99
Omaha-Council Bluffs, NE-IA
957
Orlando, FL
610
Oshkosh-Neenah, WI
85
Oxnard-Thousand Oaks-Ventura, CA
267
Palm Bay-Melbourne-Titusville, FL
168
Panama City-Lynn Haven, FL
59
Pensacola-Ferry Pass-Brent, FL
107
Peoria, IL
112
Philadelphia-Camden-Wilmington, PA-NJ-DE
2855
Phoenix-Mesa-Scottsdale, AZ
971
Pittsburgh, PA
732
Port St. Lucie-Fort Pierce, FL
109
Portland-South Portland, ME
701
Portland-Vancouver-Beaverton, OR-WA
1089
Portsmouth-Rochester, NH-ME
0
Poughkeepsie-Newburgh-Middletown, NY
201
Prescott, AZ
54
Providence-Fall River-Warwick, MA-RI
2284
Provo-Orem, UT
309
Pueblo, CO
130
Punta Gorda, FL
48
Racine, WI
119
Raleigh-Cary, NC
336
Reading, PA
142
Reno-Sparks, NV
310
Richmond, VA
490
Riverside-San Bernardino, CA
1290
Roanoke, VA
66
Rochester, NY
307
Rochester-Dover, NH-ME
262
Rockford, IL
114
Sacramento-Arden-Arcade-Roseville, CA
667
Saginaw-Saginaw Township North, MI
74
Salem, OR
170
Salinas, CA
104
Salisbury, MD
74
Salt Lake City, UT
723
San Antonio, TX
607
San Diego-Carlsbad-San Marcos, CA
907
San Francisco-Oakland-Fremont, CA
1386
San Jose-Sunnyvale-Santa Clara, CA
670
San Luis Obispo-Paso Robles, CA
77
Santa Barbara-Santa Maria-Goleta, CA
132
Santa Fe, NM
52
Santa Rosa-Petaluma, CA
129
Santa-Cruz-Watsonville, CA
66
Sarasota-Bradenton-Venice, FL
192
Savannah, GA
202
Scranton-Wilkes Barre, PA
176
Seattle-Tacoma-Bellevue, WA
1255
Shreveport-Bossier City, LA
146
Sioux Falls, SD
595
South Bend-Mishawaka, IN-MI
81
Spartanburg, SC
99
Spokane, WA
156
Springfield, IL
76
Springfield, MA-CT
155
Springfield, MO
161
Springfield, OH
34
St. Cloud, MN
82
St. Louis, MO-IL
956
Stockton, CA
193
Syracuse, NY
223
Tallahassee, FL
43
Tampa-St. Petersburg-Clearwater, FL
842
Toledo, OH
235
Topeka, KS
182
Trenton-Ewing, NJ
91
Tucson, AZ
302
Tulsa, OK
323
Tuscaloosa, AL
78
Utica-Rome, NY
80
Valdosta, GA
42
Vallejo-Fairfield, CA
133
Vero Beach, FL
79
Victoria, TX
116
Vineland-Millville-Bridgeton, NJ
54
Virginia Beach-Norfolk-Newport News, VA-NC
597
Visalia-Porterville, CA
121
Waco, TX
79
Warner Robins, GA
42
Washington-Arlington-Alexandria, DC-VA-MD-WV
4177
Waterbury, CT
157
Waterloo-Cedar Falls, IA
156
Wausau, WI
96
Wichita, KS
427
Winston-Salem, NC
127
Worcester, MA-CT
144
Yakima, WA
112
York-Hanover, PA
117
Youngstown-Warren-Boardman, OH
153 Which metropolitan area has the highest proportion of interviewees of Hispanic ethnicity? Hint: Use tapply() with mean, as in the previous subproblem. Calling sort() on the output of tapply() could also be helpful here.
sort(tapply(CPS$Hispanic, CPS$MetroArea, mean)) Anderson, SC
0.000000000
Ann Arbor, MI
0.000000000
Barnstable Town, MA
0.000000000
Bloomington, IN
0.000000000
Bloomington-Normal IL
0.000000000
Bowling Green, KY
0.000000000
Decatur, IL
0.000000000
Eau Claire, WI
0.000000000
Florence, AL
0.000000000
Hagerstown-Martinsburg, MD-WV
0.000000000
Harrisonburg, VA
0.000000000
Huntington-Ashland, WV-KY-OH
0.000000000
Huntsville, AL
0.000000000
Jackson, MI
0.000000000
Johnstown, PA
0.000000000
Macon, GA
0.000000000
Mobile, AL
0.000000000
Salisbury, MD
0.000000000
Savannah, GA
0.000000000
Warner Robins, GA
0.000000000
Dayton, OH
0.003731343
Monroe, LA
0.005586592
Knoxville, TN
0.005952381
Charleston, WV
0.007633588
Appleton,WI
0.008000000
Jackson, MS
0.009009009
Burlington-South Burlington, VT
0.009132420
Montgomery, AL
0.009708738
Wausau, WI
0.010416667
Portland-South Portland, ME
0.011412268
Oshkosh-Neenah, WI
0.011764706
Altoona, PA
0.012195122
St. Cloud, MN
0.012195122
Holland-Grand Haven, MI
0.012820513
Akron, OH
0.012987013
Springfield, IL
0.013157895
Bellingham, WA
0.014285714
Bangor, ME
0.014423077
Kingsport-Bristol, TN-VA
0.014925373
Cedar Rapids, IA
0.015306122
Gulfport-Biloxi, MS
0.015384615
Duluth, MN-WI
0.015873016
Pittsburgh, PA
0.016393443
Joplin, MO
0.016949153
Charleston-North Charleston, SC
0.017241379
Buffalo-Niagara Falls, NY
0.017441860
La Crosse, WI
0.017543860
Niles-Benton Harbor, MI
0.019607843
Evansville, IN-KY
0.020202020
Spartanburg, SC
0.020202020
Bend, OR
0.021428571
Muskegon-Norton Shores, MI
0.022222222
Erie, PA
0.022988506
Harrisburg-Carlisle, PA
0.022988506
Madison, WI
0.024647887
Lake Charles, LA
0.024691358
Fargo, ND-MN
0.025462963
Coeur d'Alene, ID
0.025641026
Spokane, WA
0.025641026
Saginaw-Saginaw Township North, MI
0.027027027
Lynchburg, VA
0.027397260
Pensacola-Ferry Pass-Brent, FL
0.028037383
Memphis, TN-MS-AR
0.028735632
Springfield, OH
0.029411765
Billings, MT
0.030150754
Janesville, WI
0.030303030
Roanoke, VA
0.030303030
St. Louis, MO-IL
0.030334728
Iowa City, IA
0.030534351
Rochester-Dover, NH-ME
0.030534351
Kalamazoo-Portage, MI
0.031496063
Youngstown-Warren-Boardman, OH
0.032679739
Champaign-Urbana, IL
0.032786885
Toledo, OH
0.034042553
Fort Wayne, IN
0.036764706
Little Rock-North Little Rock, AR
0.037128713
Detroit-Warren-Livonia, MI
0.037666174
Greenville, SC
0.037837838
Baton Rouge, LA
0.038167939
Johnson City, TN
0.038461538
Louisville, KY-IN
0.038535645
Michigan City-La Porte, IN
0.038961039
Flint, MI
0.039215686
Cincinnati-Middletown, OH-KY-IN
0.040333797
Lexington-Fayette, KY
0.040404040
Lawrence, KS
0.040816327
Albany-Schenectady-Troy, NY
0.041044776
Binghamton, NY
0.041095890
Punta Gorda, FL
0.041666667
Sioux Falls, SD
0.042016807
Columbia, MO
0.042553191
York-Hanover, PA
0.042735043
Gainesville, FL
0.042857143
Richmond, VA
0.042857143
Springfield, MO
0.043478261
Columbus, OH
0.043557169
Rockford, IL
0.043859649
Albany, GA
0.044117647
Sarasota-Bradenton-Venice, FL
0.046875000
Valdosta, GA
0.047619048
Anniston-Oxford, AL
0.049180328
South Bend-Mishawaka, IN-MI
0.049382716
Virginia Beach-Norfolk-Newport News, VA-NC
0.050251256
Minneapolis-St Paul-Bloomington, MN-WI
0.052008239
Decatur, Al
0.052083333
Birmingham-Hoover, AL
0.053571429
Palm Bay-Melbourne-Titusville, FL
0.053571429
Winston-Salem, NC
0.055118110
Dover, DE
0.057017544
Bremerton-Silverdale, WA
0.057471264
Rochester, NY
0.058631922
Myrtle Beach-Conway-North Myrtle Beach, SC
0.058823529
Racine, WI
0.058823529
Honolulu, HI
0.059644670
Cleveland-Elyria-Mentor, OH
0.060205580
Asheville, NC
0.060344828
Lafayette, LA
0.060773481
Peoria, IL
0.062500000
Monroe, MI
0.063492063
Anderson, IN
0.064516129
Provo-Orem, UT
0.064724919
Ocean City, NJ
0.066666667
Panama City-Lynn Haven, FL
0.067796610
Kingston, NY
0.068965517
Nashville-Davidson-Murfreesboro, TN
0.069306931
Boston-Cambridge-Quincy, MA-NH
0.069537909
Tallahassee, FL
0.069767442
Omaha-Council Bluffs, NE-IA
0.070010449
Indianapolis, IN
0.071929825
New Haven, CT
0.073122530
Des Moines, IA
0.073852295
Utica-Rome, NY
0.075000000
Greensboro-High Point, NC
0.075697211
Vero Beach, FL
0.075949367
Canton-Massillon, OH
0.076271186
Eugene-Springfield, OR
0.076530612
Chattanooga, TN-GA
0.077844311
Philadelphia-Camden-Wilmington, PA-NJ-DE
0.078458844
Columbia, SC
0.079037801
Syracuse, NY
0.080717489
Shreveport-Bossier City, LA
0.082191781
Baltimore-Towson, MD
0.082265678
Worcester, MA-CT
0.083333333
Lansing-East Lansing, MI
0.084033613
Medford, OR
0.085365854
Milwaukee-Waukesha-West Allis, WI
0.085434174
Atlanta-Sandy Springs-Marietta, GA
0.085695876
Fort Smith, AR-OK
0.085714286
Allentown-Bethlehem-Easton, PA-NJ
0.086826347
Hickory-Morgantown-Lenoir, NC
0.087719298
Seattle-Tacoma-Bellevue, WA
0.088446215
Atlantic City, NJ
0.090090090
Leominster-Fitchburg-Gardner, MA
0.090909091
Jacksonville, FL
0.091603053
Davenport-Moline-Rock Island, IA-IL
0.091666667
Augusta-Richmond County, GA-SC
0.093167702
Boise City-Nampa, ID
0.093167702
Topeka, KS
0.093406593
Portland-Vancouver-Beaverton, OR-WA
0.094582185
Deltona-Daytona Beach-Ormond Beach, FL
0.100000000
Port St. Lucie-Fort Pierce, FL
0.100917431
Lancaster, PA
0.102564103
Tuscaloosa, AL
0.102564103
Norwich-New London, CT-RI
0.103448276
Hartford-West Hartford-East Hartford, CT
0.105084746
Oklahoma City, OK
0.107615894
Waterloo-Cedar Falls, IA
0.108974359
Durham, NC
0.111111111
New Orleans-Metairie-Kenner, LA
0.111716621
Bridgeport-Stamford-Norwalk, CT
0.112328767
Fort Walton Beach-Crestview-Destin, FL
0.112500000
Providence-Fall River-Warwick, MA-RI
0.114273205
Tulsa, OK
0.114551084
Kankakee-Bradley, IL
0.114942529
Chico, CA
0.116666667
Charlotte-Gastonia-Concord, NC-SC
0.117988395
Raleigh-Cary, NC
0.119047619
Colorado Springs, CO
0.120967742
Olympia, WA
0.121212121
Fort Collins-Loveland, CO
0.121359223
Washington-Arlington-Alexandria, DC-VA-MD-WV
0.121378980
Kansas City, MO-KS
0.121621622
Athens-Clark County, GA
0.123076923
Lawton, OK
0.123711340
Green Bay, WI
0.125000000
Jacksonville, NC
0.126984127
Prescott, AZ
0.129629630
Trenton-Ewing, NJ
0.131868132
Wichita, KS
0.133489461
Lakeland-Winter Haven, FL
0.134228188
Scranton-Wilkes Barre, PA
0.136363636
Grand Rapids-Wyoming, MI
0.138157895
Ogden-Clearfield, UT
0.144208038
Boulder, CO
0.146198830
Fayetteville-Springdale-Rogers, AR-MO
0.148837209
Santa-Cruz-Watsonville, CA
0.151515152
Salt Lake City, UT
0.154910097
Fayetteville, NC
0.155844156
Ocala, FL
0.157894737
Tampa-St. Petersburg-Clearwater, FL
0.159144893
Greeley, CO
0.160493827
Chicago-Naperville-Joliet, IN-IN-WI
0.167388167
Naples-Marco Island, FL
0.182926829
Reno-Sparks, NV
0.196774194
San Francisco-Oakland-Fremont, CA
0.199855700
Columbus, GA-AL
0.203389831
Vallejo-Fairfield, CA
0.210526316
Reading, PA
0.211267606
Salem, OR
0.211764706
Orlando, FL
0.213114754
Springfield, MA-CT
0.219354839
Beaumont-Port Author, TX
0.227642276
New York-Northern New Jersey-Long Island, NY-NJ-PA
0.228508042
Napa, CA
0.229508197
Denver-Aurora, CO
0.232047872
Santa Rosa-Petaluma, CA
0.232558140
Farmington, NM
0.234375000
San Luis Obispo-Paso Robles, CA
0.246753247
Waterbury, CT
0.248407643
Las Vegas-Paradise, NV
0.251732102
Phoenix-Mesa-Scottsdale, AZ
0.254376931
Amarillo, TX
0.261363636
Sacramento-Arden-Arcade-Roseville, CA
0.263868066
San Diego-Carlsbad-San Marcos, CA
0.269018743
Poughkeepsie-Newburgh-Middletown, NY
0.273631841
Dallas-Fort Worth-Arlington, TX
0.283950617
Lubbock, TX
0.285714286
Longview, TX
0.292307692
Pueblo, CO
0.307692308
Austin-Round Rock, TX
0.310077519
San Jose-Sunnyvale-Santa Clara, CA
0.316417910
Stockton, CA
0.321243523
Waco, TX
0.329113924
Danbury, CT
0.339285714
Modesto, CA
0.341772152
Midland, TX
0.352941176
Yakima, WA
0.357142857
Houston-Baytown-Sugar Land, TX
0.359005458
Oxnard-Thousand Oaks-Ventura, CA
0.359550562
Killeen-Temple-Fort Hood, TX
0.386138614
Santa Barbara-Santa Maria-Goleta, CA
0.401515152
Vineland-Millville-Bridgeton, NJ
0.407407407
Fresno, CA
0.409240924
Visalia-Porterville, CA
0.438016529
Cape Coral-Fort Myers, FL
0.438356164
Albuquerque, NM
0.441707718
Los Angeles-Long Beach-Santa Ana, CA
0.460263286
Santa Fe, NM
0.461538462
Victoria, TX
0.465517241
Miami-Fort Lauderdale-Miami Beach, FL
0.467824968
Bakersfield, CA
0.489795918
Riverside-San Bernardino, CA
0.502325581
Tucson, AZ
0.506622517
Las Cruses, NM
0.542056075
Salinas, CA
0.557692308
Merced, CA
0.566037736
Corpus Christi, TX
0.606060606
Madera, CA
0.614035088
San Antonio, TX
0.644151565
El Centro, CA
0.686868687
El Paso, TX
0.790983607
Brownsville-Harlingen, TX
0.797468354
McAllen-Edinburg-Pharr, TX
0.948717949
Laredo, TX
0.966292135 Remembering that CPS$Race == “Asian” returns a TRUE/FALSE vector of whether an interviewee is Asian, determine the number of metropolitan areas in the United States from which at least 20% of interviewees are Asian.
sort(tapply(CPS$Race=="Asian", CPS$MetroArea, mean)) Albany, GA
0.000000000
Altoona, PA
0.000000000
Amarillo, TX
0.000000000
Anderson, IN
0.000000000
Appleton,WI
0.000000000
Asheville, NC
0.000000000
Barnstable Town, MA
0.000000000
Beaumont-Port Author, TX
0.000000000
Billings, MT
0.000000000
Binghamton, NY
0.000000000
Bloomington, IN
0.000000000
Bowling Green, KY
0.000000000
Canton-Massillon, OH
0.000000000
Charleston, WV
0.000000000
Chico, CA
0.000000000
Columbus, GA-AL
0.000000000
Decatur, IL
0.000000000
Durham, NC
0.000000000
Eau Claire, WI
0.000000000
El Paso, TX
0.000000000
Erie, PA
0.000000000
Farmington, NM
0.000000000
Florence, AL
0.000000000
Hagerstown-Martinsburg, MD-WV
0.000000000
Huntsville, AL
0.000000000
Jackson, MI
0.000000000
Jackson, MS
0.000000000
Janesville, WI
0.000000000
Johnson City, TN
0.000000000
Joplin, MO
0.000000000
Kankakee-Bradley, IL
0.000000000
Killeen-Temple-Fort Hood, TX
0.000000000
Kingsport-Bristol, TN-VA
0.000000000
Knoxville, TN
0.000000000
Lafayette, LA
0.000000000
Lansing-East Lansing, MI
0.000000000
Laredo, TX
0.000000000
Leominster-Fitchburg-Gardner, MA
0.000000000
Longview, TX
0.000000000
Lubbock, TX
0.000000000
Lynchburg, VA
0.000000000
Macon, GA
0.000000000
Madera, CA
0.000000000
McAllen-Edinburg-Pharr, TX
0.000000000
Michigan City-La Porte, IN
0.000000000
Midland, TX
0.000000000
Monroe, MI
0.000000000
Muskegon-Norton Shores, MI
0.000000000
Myrtle Beach-Conway-North Myrtle Beach, SC
0.000000000
Niles-Benton Harbor, MI
0.000000000
Ocean City, NJ
0.000000000
Oshkosh-Neenah, WI
0.000000000
Port St. Lucie-Fort Pierce, FL
0.000000000
Poughkeepsie-Newburgh-Middletown, NY
0.000000000
Pueblo, CO
0.000000000
Punta Gorda, FL
0.000000000
Racine, WI
0.000000000
Reading, PA
0.000000000
Roanoke, VA
0.000000000
Rockford, IL
0.000000000
Saginaw-Saginaw Township North, MI
0.000000000
Salem, OR
0.000000000
Salisbury, MD
0.000000000
Santa Fe, NM
0.000000000
Santa-Cruz-Watsonville, CA
0.000000000
Scranton-Wilkes Barre, PA
0.000000000
Shreveport-Bossier City, LA
0.000000000
South Bend-Mishawaka, IN-MI
0.000000000
Spartanburg, SC
0.000000000
Springfield, MA-CT
0.000000000
Springfield, OH
0.000000000
St. Cloud, MN
0.000000000
Tallahassee, FL
0.000000000
Tuscaloosa, AL
0.000000000
Utica-Rome, NY
0.000000000
Valdosta, GA
0.000000000
Vero Beach, FL
0.000000000
Victoria, TX
0.000000000
Vineland-Millville-Bridgeton, NJ
0.000000000
Waco, TX
0.000000000
Waterbury, CT
0.000000000
Wausau, WI
0.000000000
St. Louis, MO-IL
0.002092050
New Orleans-Metairie-Kenner, LA
0.002724796
San Antonio, TX
0.003294893
Charleston-North Charleston, SC
0.004310345
Monroe, LA
0.005586592
Chattanooga, TN-GA
0.005988024
Modesto, CA
0.006329114
Bend, OR
0.007142857
Dayton, OH
0.007462687
Santa Barbara-Santa Maria-Goleta, CA
0.007575758
Santa Rosa-Petaluma, CA
0.007751938
Toledo, OH
0.008510638
Coeur d'Alene, ID
0.008547009
York-Hanover, PA
0.008547009
Yakima, WA
0.008928571
Grand Rapids-Wyoming, MI
0.009868421
Sioux Falls, SD
0.010084034
Evansville, IN-KY
0.010101010
Lawrence, KS
0.010204082
Cleveland-Elyria-Mentor, OH
0.010279001
Lawton, OK
0.010309278
Boise City-Nampa, ID
0.010869565
Harrisburg-Carlisle, PA
0.011494253
Kingston, NY
0.011494253
Louisville, KY-IN
0.011560694
Medford, OR
0.012195122
Greeley, CO
0.012345679
Springfield, MO
0.012422360
Birmingham-Hoover, AL
0.012755102
Waterloo-Cedar Falls, IA
0.012820513
Provo-Orem, UT
0.012944984
Youngstown-Warren-Boardman, OH
0.013071895
Ocala, FL
0.013157895
Allentown-Bethlehem-Easton, PA-NJ
0.014970060
Corpus Christi, TX
0.015151515
Dover, DE
0.015350877
Charlotte-Gastonia-Concord, NC-SC
0.015473888
Sarasota-Bradenton-Venice, FL
0.015625000
Kalamazoo-Portage, MI
0.015748031
Winston-Salem, NC
0.015748031
Johnstown, PA
0.015873016
Colorado Springs, CO
0.016129032
Champaign-Urbana, IL
0.016393443
Napa, CA
0.016393443
Panama City-Lynn Haven, FL
0.016949153
Memphis, TN-MS-AR
0.017241379
Columbus, OH
0.018148820
Prescott, AZ
0.018518519
Las Cruses, NM
0.018691589
Pensacola-Ferry Pass-Brent, FL
0.018691589
Spokane, WA
0.019230769
Fort Collins-Loveland, CO
0.019417476
Flint, MI
0.019607843
Savannah, GA
0.019801980
Tucson, AZ
0.019867550
El Centro, CA
0.020202020
Eugene-Springfield, OR
0.020408163
Davenport-Moline-Rock Island, IA-IL
0.020833333
Deltona-Daytona Beach-Ormond Beach, FL
0.021428571
Topeka, KS
0.021978022
Cincinnati-Middletown, OH-KY-IN
0.022253129
Little Rock-North Little Rock, AR
0.022277228
Albany-Schenectady-Troy, NY
0.022388060
Baton Rouge, LA
0.022900763
Bremerton-Silverdale, WA
0.022988506
Bangor, ME
0.024038462
Naples-Marco Island, FL
0.024390244
Indianapolis, IN
0.024561404
Augusta-Richmond County, GA-SC
0.024844720
Holland-Grand Haven, MI
0.025641026
Fayetteville, NC
0.025974026
Ogden-Clearfield, UT
0.026004728
Rochester-Dover, NH-ME
0.026717557
Virginia Beach-Norfolk-Newport News, VA-NC
0.026800670
Lakeland-Winter Haven, FL
0.026845638
Columbia, SC
0.027491409
Fargo, ND-MN
0.027777778
Bellingham, WA
0.028571429
Montgomery, AL
0.029126214
Omaha-Council Bluffs, NE-IA
0.029258098
Akron, OH
0.030303030
Wichita, KS
0.030444965
Athens-Clark County, GA
0.030769231
Gulfport-Biloxi, MS
0.030769231
Anderson, SC
0.031250000
Denver-Aurora, CO
0.031914894
Greenville, SC
0.032432432
Philadelphia-Camden-Wilmington, PA-NJ-DE
0.032924694
Harrisonburg, VA
0.033333333
Cape Coral-Fort Myers, FL
0.034246575
Kansas City, MO-KS
0.034303534
Worcester, MA-CT
0.034722222
Oklahoma City, OK
0.034768212
Hickory-Morgantown-Lenoir, NC
0.035087719
Lexington-Fayette, KY
0.035353535
Miami-Fort Lauderdale-Miami Beach, FL
0.035392535
Palm Bay-Melbourne-Titusville, FL
0.035714286
Salt Lake City, UT
0.035961272
Mobile, AL
0.036363636
Huntington-Ashland, WV-KY-OH
0.036585366
Richmond, VA
0.036734694
Fort Wayne, IN
0.036764706
Fort Walton Beach-Crestview-Destin, FL
0.037500000
Des Moines, IA
0.037924152
Phoenix-Mesa-Scottsdale, AZ
0.038105046
Pittsburgh, PA
0.038251366
Bridgeport-Stamford-Norwalk, CT
0.038356164
Providence-Fall River-Warwick, MA-RI
0.038966725
Tampa-St. Petersburg-Clearwater, FL
0.039192399
Duluth, MN-WI
0.039682540
Syracuse, NY
0.040358744
Albuquerque, NM
0.041050903
Decatur, Al
0.041666667
Portland-South Portland, ME
0.042796006
Gainesville, FL
0.042857143
Detroit-Warren-Livonia, MI
0.043574594
Trenton-Ewing, NJ
0.043956044
New Haven, CT
0.047430830
Jacksonville, NC
0.047619048
Milwaukee-Waukesha-West Allis, WI
0.047619048
Jacksonville, FL
0.048346056
Burlington-South Burlington, VT
0.048706240
Anniston-Oxford, AL
0.049180328
Tulsa, OK
0.049535604
Raleigh-Cary, NC
0.050595238
Orlando, FL
0.050819672
Fayetteville-Springdale-Rogers, AR-MO
0.051162791
San Luis Obispo-Paso Robles, CA
0.051948052
Boston-Cambridge-Quincy, MA-NH
0.052041274
Austin-Round Rock, TX
0.052325581
Buffalo-Niagara Falls, NY
0.052325581
Springfield, IL
0.052631579
Iowa City, IA
0.053435115
Peoria, IL
0.053571429
Madison, WI
0.056338028
Merced, CA
0.056603774
Fort Smith, AR-OK
0.057142857
Nashville-Davidson-Murfreesboro, TN
0.057425743
Lancaster, PA
0.057692308
Baltimore-Towson, MD
0.057990560
Reno-Sparks, NV
0.058064516
Chicago-Naperville-Joliet, IN-IN-WI
0.058441558
Boulder, CO
0.058479532
Houston-Baytown-Sugar Land, TX
0.061249242
Riverside-San Bernardino, CA
0.062015504
Danbury, CT
0.062500000
Dallas-Fort Worth-Arlington, TX
0.062801932
Columbia, MO
0.063829787
Rochester, NY
0.065146580
Cedar Rapids, IA
0.066326531
Hartford-West Hartford-East Hartford, CT
0.066666667
Portland-Vancouver-Beaverton, OR-WA
0.069788797
Washington-Arlington-Alexandria, DC-VA-MD-WV
0.070624850
Atlanta-Sandy Springs-Marietta, GA
0.072809278
Norwich-New London, CT-RI
0.073891626
Lake Charles, LA
0.074074074
Oxnard-Thousand Oaks-Ventura, CA
0.074906367
Bloomington-Normal IL
0.075000000
Brownsville-Harlingen, TX
0.075949367
Minneapolis-St Paul-Bloomington, MN-WI
0.076725026
Las Vegas-Paradise, NV
0.078521940
Greensboro-High Point, NC
0.079681275
Bakersfield, CA
0.081632653
Ann Arbor, MI
0.082352941
La Crosse, WI
0.087719298
Green Bay, WI
0.088235294
Visalia-Porterville, CA
0.090909091
Seattle-Tacoma-Bellevue, WA
0.099601594
New York-Northern New Jersey-Long Island, NY-NJ-PA
0.104270660
Salinas, CA
0.125000000
Olympia, WA
0.131313131
Los Angeles-Long Beach-Santa Ana, CA
0.135056070
San Diego-Carlsbad-San Marcos, CA
0.142227122
Sacramento-Arden-Arcade-Roseville, CA
0.142428786
Atlantic City, NJ
0.144144144
Stockton, CA
0.155440415
Warner Robins, GA
0.166666667
Fresno, CA
0.184818482
Vallejo-Fairfield, CA
0.203007519
San Jose-Sunnyvale-Santa Clara, CA
0.241791045
San Francisco-Oakland-Fremont, CA
0.246753247
Honolulu, HI
0.501903553 Normally, we would look at the sorted proportion of interviewees from each metropolitan area who have not received a high school diploma with the command:
sort(tapply(CPS$Education == "No high school diploma", CPS$MetroArea, mean))However, none of the interviewees aged 14 and younger have an education value reported, so the mean value is reported as NA for each metropolitan area. To get mean (and related functions, like sum) to ignore missing values, you can pass the parameter na.rm=TRUE. Passing na.rm=TRUE to the tapply function, determine which metropolitan area has the smallest proportion of interviewees who have received no high school diploma.
sort(tapply(CPS$Education == "No high school diploma", CPS$MetroArea, mean, na.rm="TRUE")) Iowa City, IA
0.02912621
Bowling Green, KY
0.03703704
Kalamazoo-Portage, MI
0.05050505
Champaign-Urbana, IL
0.05154639
Bremerton-Silverdale, WA
0.05405405
Lawrence, KS
0.05952381
Bloomington-Normal IL
0.06060606
Jacksonville, NC
0.06122449
Eau Claire, WI
0.06250000
Palm Bay-Melbourne-Titusville, FL
0.06666667
Salisbury, MD
0.06779661
Gainesville, FL
0.06896552
Fort Collins-Loveland, CO
0.06936416
Altoona, PA
0.07142857
Madison, WI
0.07423581
Tallahassee, FL
0.07500000
Fargo, ND-MN
0.07902736
Albany-Schenectady-Troy, NY
0.07929515
Ocean City, NJ
0.08000000
Lakeland-Winter Haven, FL
0.08130081
Billings, MT
0.08280255
Coeur d'Alene, ID
0.08333333
Burlington-South Burlington, VT
0.08394161
Akron, OH
0.08421053
Ann Arbor, MI
0.08695652
Asheville, NC
0.08695652
Pensacola-Ferry Pass-Brent, FL
0.08695652
Oshkosh-Neenah, WI
0.08823529
Rochester-Dover, NH-ME
0.08928571
Knoxville, TN
0.08965517
Pittsburgh, PA
0.09060403
Barnstable Town, MA
0.09090909
Bridgeport-Stamford-Norwalk, CT
0.09563758
Johnstown, PA
0.09615385
Austin-Round Rock, TX
0.09629630
La Crosse, WI
0.09677419
Boulder, CO
0.09701493
Charleston-North Charleston, SC
0.09890110
Fort Wayne, IN
0.09900990
Roanoke, VA
0.10169492
Prescott, AZ
0.10204082
Santa Rosa-Petaluma, CA
0.10280374
Evansville, IN-KY
0.10389610
Spokane, WA
0.10434783
Poughkeepsie-Newburgh-Middletown, NY
0.10559006
Tampa-St. Petersburg-Clearwater, FL
0.10579710
Grand Rapids-Wyoming, MI
0.10612245
Portland-South Portland, ME
0.10638298
Honolulu, HI
0.10739300
Michigan City-La Porte, IN
0.10769231
Eugene-Springfield, OR
0.11038961
Boston-Cambridge-Quincy, MA-NH
0.11080485
Bend, OR
0.11111111
Vero Beach, FL
0.11428571
Sarasota-Bradenton-Venice, FL
0.11464968
Fort Walton Beach-Crestview-Destin, FL
0.11475410
Flint, MI
0.11538462
Cedar Rapids, IA
0.11564626
Minneapolis-St Paul-Bloomington, MN-WI
0.11638204
Portland-Vancouver-Beaverton, OR-WA
0.11657143
Washington-Arlington-Alexandria, DC-VA-MD-WV
0.11683748
Mobile, AL
0.11702128
Scranton-Wilkes Barre, PA
0.11724138
Topeka, KS
0.11724138
Colorado Springs, CO
0.11764706
Olympia, WA
0.11764706
Reno-Sparks, NV
0.11764706
Appleton,WI
0.11827957
Santa Fe, NM
0.11904762
Virginia Beach-Norfolk-Newport News, VA-NC
0.11909651
Allentown-Bethlehem-Easton, PA-NJ
0.11929825
Rochester, NY
0.12132353
Seattle-Tacoma-Bellevue, WA
0.12168793
Kansas City, MO-KS
0.12172775
Napa, CA
0.12244898
Duluth, MN-WI
0.12264151
New Haven, CT
0.12354312
Canton-Massillon, OH
0.12371134
Fayetteville, NC
0.12500000
San Luis Obispo-Paso Robles, CA
0.12500000
Worcester, MA-CT
0.12605042
Philadelphia-Camden-Wilmington, PA-NJ-DE
0.12717253
Davenport-Moline-Rock Island, IA-IL
0.12727273
Waterloo-Cedar Falls, IA
0.12800000
Pueblo, CO
0.12844037
Baton Rouge, LA
0.12871287
Racine, WI
0.12903226
Des Moines, IA
0.12944162
Detroit-Warren-Livonia, MI
0.12964642
Omaha-Council Bluffs, NE-IA
0.12972973
Richmond, VA
0.12990196
Savannah, GA
0.13013699
Danbury, CT
0.13043478
Bloomington, IN
0.13095238
Valdosta, GA
0.13157895
Wausau, WI
0.13157895
Deltona-Daytona Beach-Ormond Beach, FL
0.13178295
Tulsa, OK
0.13178295
Harrisburg-Carlisle, PA
0.13286713
Las Vegas-Paradise, NV
0.13307985
Myrtle Beach-Conway-North Myrtle Beach, SC
0.13333333
Provo-Orem, UT
0.13366337
Anderson, IN
0.13461538
Chico, CA
0.13461538
St. Louis, MO-IL
0.13461538
Niles-Benton Harbor, MI
0.13513514
Ogden-Clearfield, UT
0.13571429
Baltimore-Towson, MD
0.13583333
Buffalo-Niagara Falls, NY
0.13684211
Milwaukee-Waukesha-West Allis, WI
0.13693694
Chicago-Naperville-Joliet, IN-IN-WI
0.13737734
Louisville, KY-IN
0.13785047
Lynchburg, VA
0.13793103
Peoria, IL
0.13829787
Sioux Falls, SD
0.13832200
Ocala, FL
0.13888889
Leominster-Fitchburg-Gardner, MA
0.14035088
Oklahoma City, OK
0.14137214
San Diego-Carlsbad-San Marcos, CA
0.14188267
Jacksonville, FL
0.14244186
Atlantic City, NJ
0.14285714
Holland-Grand Haven, MI
0.14285714
Medford, OR
0.14285714
Naples-Marco Island, FL
0.14285714
Punta Gorda, FL
0.14285714
Victoria, TX
0.14285714
Winston-Salem, NC
0.14285714
Salt Lake City, UT
0.14338235
Atlanta-Sandy Springs-Marietta, GA
0.14421553
Decatur, IL
0.14516129
Springfield, IL
0.14516129
Monroe, MI
0.14545455
Denver-Aurora, CO
0.14574558
Hartford-West Hartford-East Hartford, CT
0.14574899
Greeley, CO
0.14615385
San Francisco-Oakland-Fremont, CA
0.14651368
Boise City-Nampa, ID
0.14653465
Greenville, SC
0.14666667
Birmingham-Hoover, AL
0.14678899
Saginaw-Saginaw Township North, MI
0.14754098
Santa-Cruz-Watsonville, CA
0.14814815
Trenton-Ewing, NJ
0.14814815
Lexington-Fayette, KY
0.14838710
San Jose-Sunnyvale-Santa Clara, CA
0.14922481
Bellingham, WA
0.15000000
Norwich-New London, CT-RI
0.15060241
Lubbock, TX
0.15094340
Huntington-Ashland, WV-KY-OH
0.15151515
St. Cloud, MN
0.15151515
Jackson, MS
0.15168539
Dayton, OH
0.15207373
Chattanooga, TN-GA
0.15217391
Syracuse, NY
0.15428571
New York-Northern New Jersey-Long Island, NY-NJ-PA
0.15573586
Columbia, SC
0.15600000
Columbus, OH
0.15617716
Memphis, TN-MS-AR
0.15714286
Orlando, FL
0.16108787
Warner Robins, GA
0.16216216
Cleveland-Elyria-Mentor, OH
0.16250000
Columbia, MO
0.16279070
Durham, NC
0.16326531
Miami-Fort Lauderdale-Miami Beach, FL
0.16356589
Indianapolis, IN
0.16371681
Albuquerque, NM
0.16424116
Cape Coral-Fort Myers, FL
0.16528926
Amarillo, TX
0.16666667
Anniston-Oxford, AL
0.16666667
Athens-Clark County, GA
0.16666667
Binghamton, NY
0.16666667
Phoenix-Mesa-Scottsdale, AZ
0.16687737
Green Bay, WI
0.16831683
Bangor, ME
0.16860465
Providence-Fall River-Warwick, MA-RI
0.16915688
Muskegon-Norton Shores, MI
0.16923077
Tuscaloosa, AL
0.16949153
Rockford, IL
0.17021277
Las Cruses, NM
0.17283951
Gulfport-Biloxi, MS
0.17307692
Huntsville, AL
0.17391304
Utica-Rome, NY
0.17391304
Fort Smith, AR-OK
0.17441860
Charlotte-Gastonia-Concord, NC-SC
0.17444717
El Centro, CA
0.17567568
Erie, PA
0.17567568
Jackson, MI
0.17741935
Cincinnati-Middletown, OH-KY-IN
0.17773788
Springfield, MA-CT
0.17829457
Reading, PA
0.17857143
Vallejo-Fairfield, CA
0.17924528
Salem, OR
0.17985612
Nashville-Davidson-Murfreesboro, TN
0.18112245
Johnson City, TN
0.18181818
Wichita, KS
0.18181818
York-Hanover, PA
0.18181818
Janesville, WI
0.18292683
Lansing-East Lansing, MI
0.18348624
Greensboro-High Point, NC
0.18357488
Decatur, Al
0.18421053
Albany, GA
0.18604651
Augusta-Richmond County, GA-SC
0.18796992
Charleston, WV
0.18834081
Shreveport-Bossier City, LA
0.18918919
Raleigh-Cary, NC
0.18959108
Toledo, OH
0.18965517
Spartanburg, SC
0.18987342
Dallas-Fort Worth-Arlington, TX
0.19077135
Sacramento-Arden-Arcade-Roseville, CA
0.19136961
Santa Barbara-Santa Maria-Goleta, CA
0.19191919
Monroe, LA
0.19205298
Dover, DE
0.19220056
South Bend-Mishawaka, IN-MI
0.19354839
Fayetteville-Springdale-Rogers, AR-MO
0.19393939
Columbus, GA-AL
0.19607843
Kingston, NY
0.19696970
Port St. Lucie-Fort Pierce, FL
0.19767442
Waterbury, CT
0.19852941
Little Rock-North Little Rock, AR
0.19939577
Springfield, MO
0.20000000
Modesto, CA
0.20325203
Houston-Baytown-Sugar Land, TX
0.20439739
Oxnard-Thousand Oaks-Ventura, CA
0.20657277
Anderson, SC
0.20689655
Midland, TX
0.21052632
New Orleans-Metairie-Kenner, LA
0.21088435
Fresno, CA
0.21120690
Lake Charles, LA
0.21739130
Visalia-Porterville, CA
0.21782178
San Antonio, TX
0.22004357
Hagerstown-Martinsburg, MD-WV
0.22222222
Yakima, WA
0.22222222
Hickory-Morgantown-Lenoir, NC
0.22448980
Los Angeles-Long Beach-Santa Ana, CA
0.22882883
Panama City-Lynn Haven, FL
0.22916667
Harrisonburg, VA
0.23287671
Kankakee-Bradley, IL
0.23437500
Beaumont-Port Author, TX
0.23469388
Youngstown-Warren-Boardman, OH
0.23622047
Riverside-San Bernardino, CA
0.23780488
Farmington, NM
0.23913043
Killeen-Temple-Fort Hood, TX
0.24050633
Waco, TX
0.24074074
Montgomery, AL
0.24137931
Tucson, AZ
0.24603175
Lafayette, LA
0.24822695
Joplin, MO
0.25000000
Stockton, CA
0.25333333
Brownsville-Harlingen, TX
0.25396825
Lancaster, PA
0.26771654
Bakersfield, CA
0.27218935
Vineland-Millville-Bridgeton, NJ
0.27500000
Lawton, OK
0.28000000
Merced, CA
0.28358209
Corpus Christi, TX
0.29702970
El Paso, TX
0.30219780
Springfield, OH
0.31034483
Florence, AL
0.32075472
Madera, CA
0.33333333
Salinas, CA
0.34090909
Laredo, TX
0.34426230
Kingsport-Bristol, TN-VA
0.36363636
Longview, TX
0.38297872
McAllen-Edinburg-Pharr, TX
0.38297872
Macon, GA
0.40816327 Just as we did with the metropolitan area information, merge in the country of birth information from the CountryMap data frame, replacing the CPS data frame with the result. If you accidentally overwrite CPS with the wrong values, remember that you can restore it by re-loading the data frame from CPSData.csv and then merging in the metropolitan area information using the command provided in the previous subproblem.
What is the name of the variable added to the CPS data frame by this merge operation?
CPS = merge(CPS, CountryMap, by.x = "CountryOfBirthCode", by.y = "Code", all.x = TRUE)
summary(CPS) CountryOfBirthCode MetroAreaCode PeopleInHousehold Region
Min. : 57.00 Min. :10420 Min. : 1.000 Midwest :30684
1st Qu.: 57.00 1st Qu.:21780 1st Qu.: 2.000 Northeast:25939
Median : 57.00 Median :34740 Median : 3.000 South :41502
Mean : 82.68 Mean :35075 Mean : 3.284 West :33177
3rd Qu.: 57.00 3rd Qu.:41860 3rd Qu.: 4.000
Max. :555.00 Max. :79600 Max. :15.000
NA's :34238
State Age Married Sex
California :11570 Min. : 0.00 Divorced :11151 Female:67481
Texas : 7077 1st Qu.:19.00 Married :55509 Male :63821
New York : 5595 Median :39.00 Never Married:30772
Florida : 5149 Mean :38.83 Separated : 2027
Pennsylvania: 3930 3rd Qu.:57.00 Widowed : 6505
Illinois : 3912 Max. :85.00 NA's :25338
(Other) :94069
Education Race
High school :30906 American Indian : 1433
Bachelor's degree :19443 Asian : 6520
Some college, no degree:18863 Black : 13913
No high school diploma :16095 Multiracial : 2897
Associate degree : 9913 Pacific Islander: 618
(Other) :10744 White :105921
NA's :25338
Hispanic Citizenship EmploymentStatus
Min. :0.0000 Citizen, Native :116639 Disabled : 5712
1st Qu.:0.0000 Citizen, Naturalized: 7073 Employed :61733
Median :0.0000 Non-Citizen : 7590 Not in Labor Force:15246
Mean :0.1393 Retired :18619
3rd Qu.:0.0000 Unemployed : 4203
Max. :1.0000 NA's :25789
Industry
Educational and health services :15017
Trade : 8933
Professional and business services: 7519
Manufacturing : 6791
Leisure and hospitality : 6364
(Other) :21618
NA's :65060
MetroArea
New York-Northern New Jersey-Long Island, NY-NJ-PA: 5409
Washington-Arlington-Alexandria, DC-VA-MD-WV : 4177
Los Angeles-Long Beach-Santa Ana, CA : 4102
Philadelphia-Camden-Wilmington, PA-NJ-DE : 2855
Chicago-Naperville-Joliet, IN-IN-WI : 2772
(Other) :77749
NA's :34238
Country
United States:115063
Mexico : 3921
Philippines : 839
India : 770
China : 581
(Other) : 9952
NA's : 176 How many interviewees have a missing value for the new country of birth variable?
Among all interviewees born outside of North America, which country was the most common place of birth?
sort(table(CPS$Country))
Cyprus Kosovo
0 0
Oceania, not specified Other U. S. Island Areas
0 0
Wales Northern Ireland
0 2
Tanzania Azerbaijan
2 3
Czechoslovakia St. Kitts--Nevis
3 3
Georgia Barbados
5 6
Denmark Latvia
6 6
Samoa Senegal
6 6
Singapore Slovakia
6 6
Tonga Zimbabwe
6 6
South America, not specified St. Lucia
7 7
Algeria Americas, not specified
9 9
Belize Fiji
9 9
St. Vincent and the Grenadines Bahamas
9 10
Finland Kuwait
10 10
Lithuania Czech Republic
10 11
Dominica Paraguay
11 11
Croatia Macedonia
12 12
Moldova Antigua and Barbuda
12 13
Belgium Bermuda
13 13
Bolivia Grenada
13 13
Sudan Cape Verde
13 15
Eritrea Sierra Leone
15 15
Uganda Austria
15 17
Morocco Sri Lanka
17 17
U. S. Virgin Islands Uruguay
17 17
Albania Norway
18 18
Europe, not specified Uzbekistan
19 19
West Indies, not specified Malaysia
19 20
Serbia Azores
20 22
USSR New Zealand
22 23
Switzerland Yemen
23 23
Belarus Scotland
24 24
Yugoslavia Hungary
24 25
Afghanistan Indonesia
26 26
Netherlands Sweden
28 28
Bulgaria Costa Rica
29 29
Saudi Arabia Guam
29 31
Cameroon Syria
32 32
Armenia Jordan
35 36
Chile Asia, not specified
37 39
Ireland Spain
39 41
Bangladesh Australia
42 43
Nepal Panama
44 44
Lebanon Myanmar (Burma)
45 45
South Africa Turkey
48 48
Cambodia Liberia
49 52
Kenya Romania
55 55
Greece Israel
56 57
Trinidad and Tobago Bosnia & Herzegovina
60 61
Venezuela Argentina
61 64
Hong Kong Portugal
64 64
Egypt Somalia
65 72
France South Korea
73 73
Ghana Nicaragua
76 76
Ethiopia Elsewhere
80 81
Nigeria Iraq
85 97
Laos Taiwan
98 102
Ukraine Guyana
104 109
Pakistan United Kingdom
109 111
Thailand Africa, not specified
128 129
Ecuador Peru
136 136
Iran Italy
144 149
Brazil Poland
159 162
Haiti Russia
167 173
England Japan
179 187
Honduras Columbia
189 206
Jamaica Guatemala
217 309
Dominican Republic Korea
330 334
Canada Cuba
410 426
Germany Vietnam
438 458
El Salvador Puerto Rico
477 518
China India
581 770
Philippines Mexico
839 3921
United States
115063 What proportion of the interviewees from the “New York-Northern New Jersey-Long Island, NY-NJ-PA” metropolitan area have a country of birth that is not the United States? For this computation, don’t include people from this metropolitan area who have a missing country of birth.
table(CPS$MetroArea == "New York-Northern New Jersey-Long Island, NY-NJ-PA", CPS$Country != "United States")
FALSE TRUE
FALSE 78757 12744
TRUE 3736 16681668/(1688+3736)[1] 0.3075221Which metropolitan area has the largest number (note – not proportion) of interviewees with a country of birth in India? Hint – remember to include na.rm=TRUE if you are using tapply() to answer this question.
sort(tapply(CPS$Country=="India", CPS$MetroArea, sum, na.rm=TRUE)) Akron, OH
0
Albany, GA
0
Albany-Schenectady-Troy, NY
0
Allentown-Bethlehem-Easton, PA-NJ
0
Altoona, PA
0
Amarillo, TX
0
Anderson, IN
0
Ann Arbor, MI
0
Anniston-Oxford, AL
0
Appleton,WI
0
Asheville, NC
0
Athens-Clark County, GA
0
Augusta-Richmond County, GA-SC
0
Bangor, ME
0
Barnstable Town, MA
0
Baton Rouge, LA
0
Beaumont-Port Author, TX
0
Bellingham, WA
0
Bend, OR
0
Billings, MT
0
Binghamton, NY
0
Bloomington, IN
0
Boulder, CO
0
Bowling Green, KY
0
Bremerton-Silverdale, WA
0
Buffalo-Niagara Falls, NY
0
Canton-Massillon, OH
0
Cape Coral-Fort Myers, FL
0
Cedar Rapids, IA
0
Champaign-Urbana, IL
0
Charleston, WV
0
Chattanooga, TN-GA
0
Chico, CA
0
Coeur d'Alene, ID
0
Colorado Springs, CO
0
Columbia, MO
0
Columbus, GA-AL
0
Columbus, OH
0
Corpus Christi, TX
0
Danbury, CT
0
Davenport-Moline-Rock Island, IA-IL
0
Dayton, OH
0
Decatur, Al
0
Decatur, IL
0
Denver-Aurora, CO
0
Dover, DE
0
Duluth, MN-WI
0
Durham, NC
0
Eau Claire, WI
0
El Centro, CA
0
El Paso, TX
0
Erie, PA
0
Eugene-Springfield, OR
0
Evansville, IN-KY
0
Fargo, ND-MN
0
Farmington, NM
0
Fayetteville, NC
0
Flint, MI
0
Florence, AL
0
Fort Collins-Loveland, CO
0
Fort Smith, AR-OK
0
Fort Walton Beach-Crestview-Destin, FL
0
Gainesville, FL
0
Grand Rapids-Wyoming, MI
0
Greeley, CO
0
Green Bay, WI
0
Greensboro-High Point, NC
0
Gulfport-Biloxi, MS
0
Hagerstown-Martinsburg, MD-WV
0
Harrisonburg, VA
0
Hickory-Morgantown-Lenoir, NC
0
Holland-Grand Haven, MI
0
Huntington-Ashland, WV-KY-OH
0
Huntsville, AL
0
Jackson, MI
0
Jackson, MS
0
Jacksonville, NC
0
Janesville, WI
0
Johnson City, TN
0
Johnstown, PA
0
Joplin, MO
0
Kalamazoo-Portage, MI
0
Kankakee-Bradley, IL
0
Killeen-Temple-Fort Hood, TX
0
Kingsport-Bristol, TN-VA
0
Kingston, NY
0
Knoxville, TN
0
La Crosse, WI
0
Lafayette, LA
0
Lake Charles, LA
0
Lakeland-Winter Haven, FL
0
Lancaster, PA
0
Lansing-East Lansing, MI
0
Laredo, TX
0
Las Cruses, NM
0
Lawton, OK
0
Leominster-Fitchburg-Gardner, MA
0
Lexington-Fayette, KY
0
Longview, TX
0
Louisville, KY-IN
0
Lubbock, TX
0
Lynchburg, VA
0
Macon, GA
0
Madera, CA
0
McAllen-Edinburg-Pharr, TX
0
Medford, OR
0
Merced, CA
0
Michigan City-La Porte, IN
0
Midland, TX
0
Mobile, AL
0
Modesto, CA
0
Monroe, LA
0
Monroe, MI
0
Montgomery, AL
0
Muskegon-Norton Shores, MI
0
Myrtle Beach-Conway-North Myrtle Beach, SC
0
Napa, CA
0
Niles-Benton Harbor, MI
0
Ocala, FL
0
Ocean City, NJ
0
Oshkosh-Neenah, WI
0
Palm Bay-Melbourne-Titusville, FL
0
Panama City-Lynn Haven, FL
0
Pensacola-Ferry Pass-Brent, FL
0
Port St. Lucie-Fort Pierce, FL
0
Portland-South Portland, ME
0
Poughkeepsie-Newburgh-Middletown, NY
0
Prescott, AZ
0
Pueblo, CO
0
Punta Gorda, FL
0
Racine, WI
0
Raleigh-Cary, NC
0
Reading, PA
0
Richmond, VA
0
Riverside-San Bernardino, CA
0
Roanoke, VA
0
Rockford, IL
0
Saginaw-Saginaw Township North, MI
0
Salem, OR
0
Salinas, CA
0
Salisbury, MD
0
San Antonio, TX
0
San Luis Obispo-Paso Robles, CA
0
Santa Barbara-Santa Maria-Goleta, CA
0
Santa Fe, NM
0
Santa Rosa-Petaluma, CA
0
Santa-Cruz-Watsonville, CA
0
Sarasota-Bradenton-Venice, FL
0
Savannah, GA
0
Scranton-Wilkes Barre, PA
0
Shreveport-Bossier City, LA
0
Sioux Falls, SD
0
South Bend-Mishawaka, IN-MI
0
Spartanburg, SC
0
Spokane, WA
0
Springfield, MA-CT
0
Springfield, MO
0
Springfield, OH
0
St. Cloud, MN
0
St. Louis, MO-IL
0
Stockton, CA
0
Tallahassee, FL
0
Toledo, OH
0
Topeka, KS
0
Tuscaloosa, AL
0
Utica-Rome, NY
0
Valdosta, GA
0
Vallejo-Fairfield, CA
0
Vero Beach, FL
0
Victoria, TX
0
Vineland-Millville-Bridgeton, NJ
0
Virginia Beach-Norfolk-Newport News, VA-NC
0
Waco, TX
0
Waterbury, CT
0
Waterloo-Cedar Falls, IA
0
Wausau, WI
0
Wichita, KS
0
Worcester, MA-CT
0
Yakima, WA
0
York-Hanover, PA
0
Youngstown-Warren-Boardman, OH
0
Anderson, SC
1
Bloomington-Normal IL
1
Boise City-Nampa, ID
1
Cincinnati-Middletown, OH-KY-IN
1
Columbia, SC
1
Greenville, SC
1
Harrisburg-Carlisle, PA
1
Jacksonville, FL
1
Lawrence, KS
1
Naples-Marco Island, FL
1
New Orleans-Metairie-Kenner, LA
1
Olympia, WA
1
Provo-Orem, UT
1
Syracuse, NY
1
Tucson, AZ
1
Atlantic City, NJ
2
Bakersfield, CA
2
Birmingham-Hoover, AL
2
Burlington-South Burlington, VT
2
Charleston-North Charleston, SC
2
Cleveland-Elyria-Mentor, OH
2
Deltona-Daytona Beach-Ormond Beach, FL
2
Fort Wayne, IN
2
Las Vegas-Paradise, NV
2
Memphis, TN-MS-AR
2
Miami-Fort Lauderdale-Miami Beach, FL
2
Nashville-Davidson-Murfreesboro, TN
2
Ogden-Clearfield, UT
2
Oklahoma City, OK
2
Oxnard-Thousand Oaks-Ventura, CA
2
Phoenix-Mesa-Scottsdale, AZ
2
Rochester, NY
2
Salt Lake City, UT
2
Springfield, IL
2
Winston-Salem, NC
2
Albuquerque, NM
3
Iowa City, IA
3
Madison, WI
3
Norwich-New London, CT-RI
3
Reno-Sparks, NV
3
Visalia-Porterville, CA
3
Charlotte-Gastonia-Concord, NC-SC
4
Indianapolis, IN
4
Omaha-Council Bluffs, NE-IA
4
Peoria, IL
4
Rochester-Dover, NH-ME
4
San Diego-Carlsbad-San Marcos, CA
4
Trenton-Ewing, NJ
4
Tulsa, OK
4
Orlando, FL
5
Seattle-Tacoma-Bellevue, WA
5
Austin-Round Rock, TX
6
Brownsville-Harlingen, TX
6
Des Moines, IA
6
Little Rock-North Little Rock, AR
6
New Haven, CT
6
Portland-Vancouver-Beaverton, OR-WA
6
Warner Robins, GA
6
Tampa-St. Petersburg-Clearwater, FL
7
Fayetteville-Springdale-Rogers, AR-MO
8
Sacramento-Arden-Arcade-Roseville, CA
8
Honolulu, HI
9
Boston-Cambridge-Quincy, MA-NH
11
Kansas City, MO-KS
11
Bridgeport-Stamford-Norwalk, CT
12
Milwaukee-Waukesha-West Allis, WI
12
Providence-Fall River-Warwick, MA-RI
14
Houston-Baytown-Sugar Land, TX
15
Baltimore-Towson, MD
16
Fresno, CA
16
Pittsburgh, PA
16
Dallas-Fort Worth-Arlington, TX
18
Los Angeles-Long Beach-Santa Ana, CA
19
San Jose-Sunnyvale-Santa Clara, CA
19
Minneapolis-St Paul-Bloomington, MN-WI
23
Hartford-West Hartford-East Hartford, CT
26
Atlanta-Sandy Springs-Marietta, GA
27
San Francisco-Oakland-Fremont, CA
27
Detroit-Warren-Livonia, MI
30
Chicago-Naperville-Joliet, IN-IN-WI
31
Philadelphia-Camden-Wilmington, PA-NJ-DE
32
Washington-Arlington-Alexandria, DC-VA-MD-WV
50
New York-Northern New Jersey-Long Island, NY-NJ-PA
96 In Brazil?
sort(tapply(CPS$Country=="Brazil", CPS$MetroArea, sum, na.rm=TRUE)) Albany, GA
0
Albany-Schenectady-Troy, NY
0
Allentown-Bethlehem-Easton, PA-NJ
0
Altoona, PA
0
Amarillo, TX
0
Anderson, IN
0
Anderson, SC
0
Ann Arbor, MI
0
Anniston-Oxford, AL
0
Appleton,WI
0
Asheville, NC
0
Athens-Clark County, GA
0
Atlantic City, NJ
0
Augusta-Richmond County, GA-SC
0
Austin-Round Rock, TX
0
Bakersfield, CA
0
Baltimore-Towson, MD
0
Bangor, ME
0
Baton Rouge, LA
0
Beaumont-Port Author, TX
0
Bellingham, WA
0
Bend, OR
0
Billings, MT
0
Binghamton, NY
0
Birmingham-Hoover, AL
0
Bloomington, IN
0
Bloomington-Normal IL
0
Boise City-Nampa, ID
0
Boulder, CO
0
Bowling Green, KY
0
Brownsville-Harlingen, TX
0
Buffalo-Niagara Falls, NY
0
Burlington-South Burlington, VT
0
Cedar Rapids, IA
0
Champaign-Urbana, IL
0
Charleston, WV
0
Charleston-North Charleston, SC
0
Chattanooga, TN-GA
0
Cleveland-Elyria-Mentor, OH
0
Coeur d'Alene, ID
0
Colorado Springs, CO
0
Columbia, MO
0
Columbus, GA-AL
0
Columbus, OH
0
Corpus Christi, TX
0
Dayton, OH
0
Decatur, Al
0
Decatur, IL
0
Deltona-Daytona Beach-Ormond Beach, FL
0
Des Moines, IA
0
Detroit-Warren-Livonia, MI
0
Dover, DE
0
Duluth, MN-WI
0
Durham, NC
0
Eau Claire, WI
0
El Centro, CA
0
El Paso, TX
0
Erie, PA
0
Eugene-Springfield, OR
0
Evansville, IN-KY
0
Fargo, ND-MN
0
Farmington, NM
0
Fayetteville, NC
0
Fayetteville-Springdale-Rogers, AR-MO
0
Flint, MI
0
Florence, AL
0
Fort Collins-Loveland, CO
0
Fort Smith, AR-OK
0
Fort Walton Beach-Crestview-Destin, FL
0
Fort Wayne, IN
0
Fresno, CA
0
Gainesville, FL
0
Grand Rapids-Wyoming, MI
0
Greeley, CO
0
Green Bay, WI
0
Greensboro-High Point, NC
0
Greenville, SC
0
Gulfport-Biloxi, MS
0
Hagerstown-Martinsburg, MD-WV
0
Harrisburg-Carlisle, PA
0
Harrisonburg, VA
0
Hickory-Morgantown-Lenoir, NC
0
Holland-Grand Haven, MI
0
Honolulu, HI
0
Houston-Baytown-Sugar Land, TX
0
Huntington-Ashland, WV-KY-OH
0
Huntsville, AL
0
Indianapolis, IN
0
Iowa City, IA
0
Jackson, MI
0
Jackson, MS
0
Jacksonville, NC
0
Janesville, WI
0
Johnson City, TN
0
Johnstown, PA
0
Joplin, MO
0
Kalamazoo-Portage, MI
0
Kankakee-Bradley, IL
0
Killeen-Temple-Fort Hood, TX
0
Kingsport-Bristol, TN-VA
0
Kingston, NY
0
Knoxville, TN
0
La Crosse, WI
0
Lafayette, LA
0
Lake Charles, LA
0
Lakeland-Winter Haven, FL
0
Lancaster, PA
0
Lansing-East Lansing, MI
0
Laredo, TX
0
Las Cruses, NM
0
Las Vegas-Paradise, NV
0
Lawrence, KS
0
Lawton, OK
0
Lexington-Fayette, KY
0
Little Rock-North Little Rock, AR
0
Longview, TX
0
Lubbock, TX
0
Lynchburg, VA
0
Macon, GA
0
Madera, CA
0
Madison, WI
0
McAllen-Edinburg-Pharr, TX
0
Medford, OR
0
Memphis, TN-MS-AR
0
Merced, CA
0
Michigan City-La Porte, IN
0
Midland, TX
0
Milwaukee-Waukesha-West Allis, WI
0
Mobile, AL
0
Modesto, CA
0
Monroe, MI
0
Muskegon-Norton Shores, MI
0
Myrtle Beach-Conway-North Myrtle Beach, SC
0
Napa, CA
0
Naples-Marco Island, FL
0
Nashville-Davidson-Murfreesboro, TN
0
New Haven, CT
0
New Orleans-Metairie-Kenner, LA
0
Niles-Benton Harbor, MI
0
Norwich-New London, CT-RI
0
Ocala, FL
0
Ocean City, NJ
0
Ogden-Clearfield, UT
0
Oklahoma City, OK
0
Olympia, WA
0
Omaha-Council Bluffs, NE-IA
0
Oshkosh-Neenah, WI
0
Palm Bay-Melbourne-Titusville, FL
0
Panama City-Lynn Haven, FL
0
Peoria, IL
0
Pittsburgh, PA
0
Port St. Lucie-Fort Pierce, FL
0
Portland-South Portland, ME
0
Portland-Vancouver-Beaverton, OR-WA
0
Poughkeepsie-Newburgh-Middletown, NY
0
Prescott, AZ
0
Provo-Orem, UT
0
Pueblo, CO
0
Punta Gorda, FL
0
Raleigh-Cary, NC
0
Reading, PA
0
Reno-Sparks, NV
0
Richmond, VA
0
Riverside-San Bernardino, CA
0
Roanoke, VA
0
Rochester-Dover, NH-ME
0
Rockford, IL
0
Saginaw-Saginaw Township North, MI
0
Salinas, CA
0
Salisbury, MD
0
San Antonio, TX
0
San Diego-Carlsbad-San Marcos, CA
0
San Luis Obispo-Paso Robles, CA
0
Santa Barbara-Santa Maria-Goleta, CA
0
Santa Fe, NM
0
Santa Rosa-Petaluma, CA
0
Santa-Cruz-Watsonville, CA
0
Sarasota-Bradenton-Venice, FL
0
Savannah, GA
0
Scranton-Wilkes Barre, PA
0
Shreveport-Bossier City, LA
0
Sioux Falls, SD
0
South Bend-Mishawaka, IN-MI
0
Spartanburg, SC
0
Spokane, WA
0
Springfield, IL
0
Springfield, MA-CT
0
Springfield, MO
0
Springfield, OH
0
St. Cloud, MN
0
St. Louis, MO-IL
0
Stockton, CA
0
Syracuse, NY
0
Tallahassee, FL
0
Toledo, OH
0
Topeka, KS
0
Tucson, AZ
0
Tulsa, OK
0
Tuscaloosa, AL
0
Utica-Rome, NY
0
Valdosta, GA
0
Vallejo-Fairfield, CA
0
Vero Beach, FL
0
Victoria, TX
0
Vineland-Millville-Bridgeton, NJ
0
Visalia-Porterville, CA
0
Waco, TX
0
Warner Robins, GA
0
Waterloo-Cedar Falls, IA
0
Wausau, WI
0
Winston-Salem, NC
0
Worcester, MA-CT
0
Yakima, WA
0
York-Hanover, PA
0
Youngstown-Warren-Boardman, OH
0
Akron, OH
1
Albuquerque, NM
1
Atlanta-Sandy Springs-Marietta, GA
1
Bremerton-Silverdale, WA
1
Cape Coral-Fort Myers, FL
1
Chico, CA
1
Cincinnati-Middletown, OH-KY-IN
1
Denver-Aurora, CO
1
Hartford-West Hartford-East Hartford, CT
1
Kansas City, MO-KS
1
Leominster-Fitchburg-Gardner, MA
1
Louisville, KY-IN
1
Minneapolis-St Paul-Bloomington, MN-WI
1
Monroe, LA
1
Montgomery, AL
1
Oxnard-Thousand Oaks-Ventura, CA
1
Pensacola-Ferry Pass-Brent, FL
1
Racine, WI
1
Rochester, NY
1
Salem, OR
1
San Jose-Sunnyvale-Santa Clara, CA
1
Seattle-Tacoma-Bellevue, WA
1
Tampa-St. Petersburg-Clearwater, FL
1
Trenton-Ewing, NJ
1
Virginia Beach-Norfolk-Newport News, VA-NC
1
Waterbury, CT
1
Wichita, KS
1
Barnstable Town, MA
2
Charlotte-Gastonia-Concord, NC-SC
2
Chicago-Naperville-Joliet, IN-IN-WI
2
Columbia, SC
2
Dallas-Fort Worth-Arlington, TX
2
Jacksonville, FL
2
Orlando, FL
2
Sacramento-Arden-Arcade-Roseville, CA
2
Canton-Massillon, OH
3
Phoenix-Mesa-Scottsdale, AZ
3
Providence-Fall River-Warwick, MA-RI
3
Salt Lake City, UT
3
Davenport-Moline-Rock Island, IA-IL
4
Philadelphia-Camden-Wilmington, PA-NJ-DE
4
Danbury, CT
5
San Francisco-Oakland-Fremont, CA
6
Bridgeport-Stamford-Norwalk, CT
7
New York-Northern New Jersey-Long Island, NY-NJ-PA
7
Washington-Arlington-Alexandria, DC-VA-MD-WV
8
Los Angeles-Long Beach-Santa Ana, CA
9
Miami-Fort Lauderdale-Miami Beach, FL
16
Boston-Cambridge-Quincy, MA-NH
18 In Somalia?
sort(tapply(CPS$Country=="Somalia", CPS$MetroArea, sum, na.rm=TRUE)) Akron, OH
0
Albany, GA
0
Albany-Schenectady-Troy, NY
0
Albuquerque, NM
0
Allentown-Bethlehem-Easton, PA-NJ
0
Altoona, PA
0
Amarillo, TX
0
Anderson, IN
0
Anderson, SC
0
Ann Arbor, MI
0
Anniston-Oxford, AL
0
Appleton,WI
0
Asheville, NC
0
Athens-Clark County, GA
0
Atlanta-Sandy Springs-Marietta, GA
0
Atlantic City, NJ
0
Augusta-Richmond County, GA-SC
0
Austin-Round Rock, TX
0
Bakersfield, CA
0
Baltimore-Towson, MD
0
Bangor, ME
0
Barnstable Town, MA
0
Baton Rouge, LA
0
Beaumont-Port Author, TX
0
Bellingham, WA
0
Bend, OR
0
Billings, MT
0
Binghamton, NY
0
Birmingham-Hoover, AL
0
Bloomington, IN
0
Bloomington-Normal IL
0
Boise City-Nampa, ID
0
Boston-Cambridge-Quincy, MA-NH
0
Boulder, CO
0
Bowling Green, KY
0
Bremerton-Silverdale, WA
0
Bridgeport-Stamford-Norwalk, CT
0
Brownsville-Harlingen, TX
0
Buffalo-Niagara Falls, NY
0
Canton-Massillon, OH
0
Cape Coral-Fort Myers, FL
0
Cedar Rapids, IA
0
Champaign-Urbana, IL
0
Charleston, WV
0
Charleston-North Charleston, SC
0
Charlotte-Gastonia-Concord, NC-SC
0
Chattanooga, TN-GA
0
Chicago-Naperville-Joliet, IN-IN-WI
0
Chico, CA
0
Cincinnati-Middletown, OH-KY-IN
0
Cleveland-Elyria-Mentor, OH
0
Coeur d'Alene, ID
0
Colorado Springs, CO
0
Columbia, MO
0
Columbia, SC
0
Columbus, GA-AL
0
Corpus Christi, TX
0
Dallas-Fort Worth-Arlington, TX
0
Danbury, CT
0
Davenport-Moline-Rock Island, IA-IL
0
Decatur, Al
0
Decatur, IL
0
Deltona-Daytona Beach-Ormond Beach, FL
0
Denver-Aurora, CO
0
Des Moines, IA
0
Detroit-Warren-Livonia, MI
0
Dover, DE
0
Duluth, MN-WI
0
Durham, NC
0
Eau Claire, WI
0
El Centro, CA
0
El Paso, TX
0
Erie, PA
0
Eugene-Springfield, OR
0
Evansville, IN-KY
0
Farmington, NM
0
Fayetteville, NC
0
Fayetteville-Springdale-Rogers, AR-MO
0
Flint, MI
0
Florence, AL
0
Fort Collins-Loveland, CO
0
Fort Smith, AR-OK
0
Fort Walton Beach-Crestview-Destin, FL
0
Fort Wayne, IN
0
Fresno, CA
0
Gainesville, FL
0
Grand Rapids-Wyoming, MI
0
Greeley, CO
0
Green Bay, WI
0
Greensboro-High Point, NC
0
Greenville, SC
0
Gulfport-Biloxi, MS
0
Hagerstown-Martinsburg, MD-WV
0
Harrisburg-Carlisle, PA
0
Harrisonburg, VA
0
Hartford-West Hartford-East Hartford, CT
0
Hickory-Morgantown-Lenoir, NC
0
Holland-Grand Haven, MI
0
Honolulu, HI
0
Huntington-Ashland, WV-KY-OH
0
Huntsville, AL
0
Indianapolis, IN
0
Iowa City, IA
0
Jackson, MI
0
Jackson, MS
0
Jacksonville, FL
0
Jacksonville, NC
0
Janesville, WI
0
Johnson City, TN
0
Johnstown, PA
0
Joplin, MO
0
Kalamazoo-Portage, MI
0
Kankakee-Bradley, IL
0
Kansas City, MO-KS
0
Killeen-Temple-Fort Hood, TX
0
Kingsport-Bristol, TN-VA
0
Kingston, NY
0
Knoxville, TN
0
La Crosse, WI
0
Lafayette, LA
0
Lake Charles, LA
0
Lakeland-Winter Haven, FL
0
Lancaster, PA
0
Lansing-East Lansing, MI
0
Laredo, TX
0
Las Cruses, NM
0
Las Vegas-Paradise, NV
0
Lawrence, KS
0
Lawton, OK
0
Leominster-Fitchburg-Gardner, MA
0
Lexington-Fayette, KY
0
Little Rock-North Little Rock, AR
0
Longview, TX
0
Los Angeles-Long Beach-Santa Ana, CA
0
Louisville, KY-IN
0
Lubbock, TX
0
Lynchburg, VA
0
Macon, GA
0
Madera, CA
0
Madison, WI
0
McAllen-Edinburg-Pharr, TX
0
Medford, OR
0
Memphis, TN-MS-AR
0
Merced, CA
0
Miami-Fort Lauderdale-Miami Beach, FL
0
Michigan City-La Porte, IN
0
Midland, TX
0
Milwaukee-Waukesha-West Allis, WI
0
Mobile, AL
0
Modesto, CA
0
Monroe, LA
0
Monroe, MI
0
Montgomery, AL
0
Muskegon-Norton Shores, MI
0
Myrtle Beach-Conway-North Myrtle Beach, SC
0
Napa, CA
0
Naples-Marco Island, FL
0
Nashville-Davidson-Murfreesboro, TN
0
New Haven, CT
0
New Orleans-Metairie-Kenner, LA
0
New York-Northern New Jersey-Long Island, NY-NJ-PA
0
Niles-Benton Harbor, MI
0
Norwich-New London, CT-RI
0
Ocala, FL
0
Ocean City, NJ
0
Ogden-Clearfield, UT
0
Oklahoma City, OK
0
Olympia, WA
0
Omaha-Council Bluffs, NE-IA
0
Orlando, FL
0
Oshkosh-Neenah, WI
0
Oxnard-Thousand Oaks-Ventura, CA
0
Palm Bay-Melbourne-Titusville, FL
0
Panama City-Lynn Haven, FL
0
Pensacola-Ferry Pass-Brent, FL
0
Peoria, IL
0
Philadelphia-Camden-Wilmington, PA-NJ-DE
0
Pittsburgh, PA
0
Port St. Lucie-Fort Pierce, FL
0
Poughkeepsie-Newburgh-Middletown, NY
0
Prescott, AZ
0
Providence-Fall River-Warwick, MA-RI
0
Provo-Orem, UT
0
Pueblo, CO
0
Punta Gorda, FL
0
Racine, WI
0
Raleigh-Cary, NC
0
Reading, PA
0
Reno-Sparks, NV
0
Riverside-San Bernardino, CA
0
Roanoke, VA
0
Rochester, NY
0
Rochester-Dover, NH-ME
0
Rockford, IL
0
Sacramento-Arden-Arcade-Roseville, CA
0
Saginaw-Saginaw Township North, MI
0
Salem, OR
0
Salinas, CA
0
Salisbury, MD
0
Salt Lake City, UT
0
San Antonio, TX
0
San Diego-Carlsbad-San Marcos, CA
0
San Francisco-Oakland-Fremont, CA
0
San Jose-Sunnyvale-Santa Clara, CA
0
San Luis Obispo-Paso Robles, CA
0
Santa Barbara-Santa Maria-Goleta, CA
0
Santa Fe, NM
0
Santa Rosa-Petaluma, CA
0
Santa-Cruz-Watsonville, CA
0
Sarasota-Bradenton-Venice, FL
0
Savannah, GA
0
Scranton-Wilkes Barre, PA
0
Shreveport-Bossier City, LA
0
South Bend-Mishawaka, IN-MI
0
Spartanburg, SC
0
Spokane, WA
0
Springfield, IL
0
Springfield, MA-CT
0
Springfield, MO
0
Springfield, OH
0
St. Louis, MO-IL
0
Stockton, CA
0
Syracuse, NY
0
Tallahassee, FL
0
Tampa-St. Petersburg-Clearwater, FL
0
Toledo, OH
0
Topeka, KS
0
Trenton-Ewing, NJ
0
Tucson, AZ
0
Tulsa, OK
0
Tuscaloosa, AL
0
Utica-Rome, NY
0
Valdosta, GA
0
Vallejo-Fairfield, CA
0
Vero Beach, FL
0
Victoria, TX
0
Vineland-Millville-Bridgeton, NJ
0
Virginia Beach-Norfolk-Newport News, VA-NC
0
Visalia-Porterville, CA
0
Waco, TX
0
Warner Robins, GA
0
Washington-Arlington-Alexandria, DC-VA-MD-WV
0
Waterbury, CT
0
Waterloo-Cedar Falls, IA
0
Wausau, WI
0
Wichita, KS
0
Winston-Salem, NC
0
Worcester, MA-CT
0
Yakima, WA
0
York-Hanover, PA
0
Youngstown-Warren-Boardman, OH
0
Dayton, OH
1
Richmond, VA
1
Houston-Baytown-Sugar Land, TX
2
Sioux Falls, SD
2
Burlington-South Burlington, VT
3
Portland-South Portland, ME
3
Portland-Vancouver-Beaverton, OR-WA
3
Columbus, OH
5
Fargo, ND-MN
5
Phoenix-Mesa-Scottsdale, AZ
7
Seattle-Tacoma-Bellevue, WA
7
St. Cloud, MN
7
Minneapolis-St Paul-Bloomington, MN-WI
17