Computer Science- Python Gurobi assignment

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KS/adjacency_matrix.csv

Allen Anderson Atchison Barber Barton Bourbon Brown Butler Chase Chautauqua Cherokee Cheyenne Clark Clay Cloud Coffey Comanche Cowley Crawford Decatur Dickinson Doniphan Douglas Edwards Elk Ellis Ellsworth Finney Ford Franklin Geary Gove Graham Grant Greenwood Hamilton Harper Harvey Haskell Hodgeman Jackson Jefferson Jewell Johnson Kearny Kingman Kiowa Labette Lane Leavenworth Lincoln Linn Logan Lyon McPherson Marion Marshall Meade Miami Mitchell Montgomery Morris Nemaha Neosho Ness Osage Osborne Ottawa Pawnee Phillips Pottawatomie Pratt Rawlins Reno Republic Rice Riley Rooks Rush Russell Saline Scott Sedgwick Seward Shawnee Sheridan Sherman Smith Stafford Stanton Sumner Thomas Trego Wabaunsee Wallace Washington Wilson Woodson Wyandotte Tampa Kit Carson Baca Norton Missouri Wichita Gray Reneg Hitchcock Greeley
Allen 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0
Anderson 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Atchison 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Barber 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Barton 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Bourbon 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0
Brown 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Butler 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Chase 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
Chautauqua 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
Cherokee 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cheyenne 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0
Clark 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Clay 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0
Cloud 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Coffey 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Comanche 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cowley 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Crawford 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0
Decatur 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Dickinson 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Doniphan 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Douglas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Edwards 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Elk 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
Ellis 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0
Ellsworth 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Finney 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Ford 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Franklin 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Geary 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
Gove 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Graham 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0
Grant 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Greenwood 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Hamilton 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Harper 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Harvey 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Haskell 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Hodgeman 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Jackson 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Jefferson 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Jewell 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Johnson 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Kearny 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Kingman 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Kiowa 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Labette 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
Lane 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Leavenworth 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Lincoln 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Linn 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Logan 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0
Lyon 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
McPherson 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Marion 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Marshall 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0
Meade 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Miami 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mitchell 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Montgomery 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
Morris 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
Nemaha 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0
Neosho 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0
Ness 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0
Osage 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Osborne 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Ottawa 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Pawnee 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Phillips 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Pottawatomie 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
Pratt 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Rawlins 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Reno 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Republic 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0
Rice 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Riley 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
Rooks 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Rush 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Russell 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Saline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Scott 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Sedgwick 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Seward 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Shawnee 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0
Sheridan 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Sherman 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 1.0
Smith 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Stafford 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Stanton 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Sumner 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Thomas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0
Trego 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Wabaunsee 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Wallace 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0
Washington 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Wilson 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Woodson 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Wyandotte 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Tampa 1.0
Kit Carson 1.0 1.0
Baca 1.0
Norton 1.0 1.0 1.0 1.0 1.0 1.0 1.0
Missouri 1.0
Wichita 1.0 1.0 1.0 1.0 1.0
Gray 1.0 1.0 1.0 1.0 1.0
Reneg 1.0
Hitchcock 1.0
Greeley 1.0

KS/cb_2022_us_county_5m.cpg

UTF-8

KS/cb_2022_us_county_5m.dbf

STATEFP COUNTYFP COUNTYNS AFFGEOID GEOID NAME NAMELSAD STUSPS STATE_NAME LSAD ALAND AWATER
13 233 00343585 0500000US13233 13233 Polk Polk County GA Georgia 06 803775591 4664760
21 023 00516858 0500000US21023 21023 Bracken Bracken County KY Kentucky 06 524900457 16279752
28 153 00695797 0500000US28153 28153 Wayne Wayne County MS Mississippi 06 2099745602 7255476
42 001 01213656 0500000US42001 42001 Adams Adams County PA Pennsylvania 06 1343400757 7771555
04 007 00040471 0500000US04007 04007 Gila Gila County AZ Arizona 06 12322070148 96465330
05 111 00069174 0500000US05111 05111 Poinsett Poinsett County AR Arkansas 06 1963975462 13892745
13 231 00346482 0500000US13231 13231 Pike Pike County GA Georgia 06 559660487 8595984
17 093 00424248 0500000US17093 17093 Kendall Kendall County IL Illinois 06 829412771 5136525
19 101 00465239 0500000US19101 19101 Jefferson Jefferson County IA Iowa 06 1128002432 3522238
19 095 00465236 0500000US19095 19095 Iowa Iowa County IA Iowa 06 1518911690 2686847
31 143 00835893 0500000US31143 31143 Polk Polk County NE Nebraska 06 1136152530 5104668
31 137 00835890 0500000US31137 31137 Phelps Phelps County NE Nebraska 06 1398048634 1646526
38 103 01034204 0500000US38103 38103 Wells Wells County ND North Dakota 06 3290664846 51166900
39 045 01074035 0500000US39045 39045 Fairfield Fairfield County OH Ohio 06 1306299936 10869534
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31 135 00835889 0500000US31135 31135 Perkins Perkins County NE Nebraska 06 2287768800 2840176
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20 073 00485003 0500000US20073 20073 Greenwood Greenwood County KS Kansas 06 2961143636 24145021
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46 087 01265773 0500000US46087 46087 McCook McCook County SD South Dakota 06 1487184882 6895715
46 073 01265778 0500000US46073 46073 Jerauld Jerauld County SD South Dakota 06 1362677265 16727973
54 001 01696996 0500000US54001 54001 Barbour Barbour County WV West Virginia 06 883338376 4639586
51 075 01674271 0500000US51075 51075 Goochland Goochland County VA Virginia 06 730451417 21934893
27 079 00659485 0500000US27079 27079 Le Sueur Le Sueur County MN Minnesota 06 1162212767 65216707
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27 091 00659490 0500000US27091 27091 Martin Martin County MN Minnesota 06 1844928073 44669375
29 001 00765805 0500000US29001 29001 Adair Adair County MO Missouri 06 1469362059 5468507
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55 033 01581076 0500000US55033 55033 Dunn Dunn County WI Wisconsin 06 2201902879 35572577
56 025 01605077 0500000US56025 56025 Natrona Natrona County WY Wyoming 06 13831927736 90969877
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56 029 01605079 0500000US56029 56029 Park Park County WY Wyoming 06 17972027722 67638744
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50 009 01461761 0500000US50009 50009 Essex Essex County VT Vermont 06 1715530213 28688490
53 059 01529220 0500000US53059 53059 Skamania Skamania County WA Washington 06 4294897557 73323232
27 031 00659461 0500000US27031 27031 Cook Cook County MN Minnesota 06 3762130687 4887924296
39 033 01074029 0500000US39033 39033 Crawford Crawford County OH Ohio 06 1040619655 2359514
39 063 01074044 0500000US39063 39063 Hancock Hancock County OH Ohio 06 1376118086 6028216
39 073 01074049 0500000US39073 39073 Hocking Hocking County OH Ohio 06 1091289821 5955974
39 077 01074051 0500000US39077 39077 Huron Huron County OH Ohio 06 1274903645 8628942
48 501 01384036 0500000US48501 48501 Yoakum Yoakum County TX Texas 06 2071252479 34329
48 011 01383791 0500000US48011 48011 Armstrong Armstrong County TX Texas 06 2354617585 12183672
48 249 01383910 0500000US48249 48249 Jim Wells Jim Wells County TX Texas 06 2240795374 8723372
40 043 01101809 0500000US40043 40043 Dewey Dewey County OK Oklahoma 06 2589024032 22668882
48 211 01383891 0500000US48211 48211 Hemphill Hemphill County TX Texas 06 2347270019 15205586
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19 075 00465226 0500000US19075 19075 Grundy Grundy County IA Iowa 06 1299799697 92512
27 059 00659475 0500000US27059 27059 Isanti Isanti County MN Minnesota 06 1128608896 41203100
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40 111 01101843 0500000US40111 40111 Okmulgee Okmulgee County OK Oklahoma 06 1806369916 12960866
30 033 01716058 0500000US30033 30033 Garfield Garfield County MT Montana 06 12112233250 446864356
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29 159 00758534 0500000US29159 29159 Pettis Pettis County MO Missouri 06 1766982901 10471760
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28 019 00695734 0500000US28019 28019 Choctaw Choctaw County MS Mississippi 06 1083125335 4295085
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29 209 00758557 0500000US29209 29209 Stone Stone County MO Missouri 06 1201281541 121206471
29 225 00758565 0500000US29225 29225 Webster Webster County MO Missouri 06 1534731555 3109298
37 067 01008552 0500000US37067 37067 Forsyth Forsyth County NC North Carolina 06 1056284390 11652284
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51 620 01498424 0500000US51620 51620 Franklin Franklin city VA Virginia 25 21438217 227442
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51 690 01789072 0500000US51690 51690 Martinsville Martinsville city VA Virginia 25 28374648 135578
20 015 00484977 0500000US20015 20015 Butler Butler County KS Kansas 06 3702946933 43541269
48 221 01383896 0500000US48221 48221 Hood Hood County TX Texas 06 1089693164 41762500
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12 055 00295756 0500000US12055 12055 Highlands Highlands County FL Florida 06 2635726558 230667873
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20 003 00484971 0500000US20003 20003 Anderson Anderson County KS Kansas 06 1501264009 10599659
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19 047 00465212 0500000US19047 19047 Crawford Crawford County IA Iowa 06 1849765416 2171717
19 051 00465214 0500000US19051 19051 Davis Davis County IA Iowa 06 1300661926 6904087
19 055 00465216 0500000US19055 19055 Delaware Delaware County IA Iowa 06 1496193401 3185375
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20 113 00485021 0500000US20113 20113 McPherson McPherson County KS Kansas 06 2326547428 6003328
19 069 00465223 0500000US19069 19069 Franklin Franklin County IA Iowa 06 1507300417 1438346
20 109 00485019 0500000US20109 20109 Logan Logan County KS Kansas 06 2779039723 274632
19 079 00465228 0500000US19079 19079 Hamilton Hamilton County IA Iowa 06 1493725536 1956182
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16 037 00399758 0500000US16037 16037 Custer Custer County ID Idaho 06 12748378764 42527190
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19 093 00465235 0500000US19093 19093 Ida Ida County IA Iowa 06 1117614339 1391966
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29 083 00758496 0500000US29083 29083 Henry Henry County MO Missouri 06 1805054746 91657543
48 327 01383949 0500000US48327 48327 Menard Menard County TX Texas 06 2336237980 613559
48 329 01383950 0500000US48329 48329 Midland Midland County TX Texas 06 2331915359 4252951
48 353 01383962 0500000US48353 48353 Nolan Nolan County TX Texas 06 2362061742 5052159
48 383 01383977 0500000US48383 48383 Reagan Reagan County TX Texas 06 3044049119 1792716
40 137 01101856 0500000US40137 40137 Stephens Stephens County OK Oklahoma 06 2253839277 54824811
29 187 00758548 0500000US29187 29187 St. Francois St. Francois County MO Missouri 06 1170380016 7218075
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48 173 01383872 0500000US48173 48173 Glasscock Glasscock County TX Texas 06 2331552974 2245302
48 259 01383915 0500000US48259 48259 Kendall Kendall County TX Texas 06 1715747612 1496797
40 051 01101813 0500000US40051 40051 Grady Grady County OK Oklahoma 06 2850386657 11374380
40 027 01101801 0500000US40027 40027 Cleveland Cleveland County OK Oklahoma 06 1395713124 49261324
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40 029 01101802 0500000US40029 40029 Coal Coal County OK Oklahoma 06 1338434468 12075986
40 099 01101837 0500000US40099 40099 Murray Murray County OK Oklahoma 06 1078405802 22710694
40 061 01101818 0500000US40061 40061 Haskell Haskell County OK Oklahoma 06 1493711222 126247870
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28 053 00695750 0500000US28053 28053 Humphreys Humphreys County MS Mississippi 06 1084375633 32514314
28 119 00695780 0500000US28119 28119 Quitman Quitman County MS Mississippi 06 1048975539 3676001
29 211 00758558 0500000US29211 29211 Sullivan Sullivan County MO Missouri 06 1678265913 9121738
48 281 01383927 0500000US48281 48281 Lampasas Lampasas County TX Texas 06 1845440046 2749903
48 293 01383932 0500000US48293 48293 Limestone Limestone County TX Texas 06 2345053180 71830221
48 027 01383799 0500000US48027 48027 Bell Bell County TX Texas 06 2729408715 94385069
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28 067 00695757 0500000US28067 28067 Jones Jones County MS Mississippi 06 1799639020 12681687
28 069 00695758 0500000US28069 28069 Kemper Kemper County MS Mississippi 06 1984403150 2182350
32 021 00858644 0500000US32021 32021 Mineral Mineral County NV Nevada 06 9715777470 155864513
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20 185 00485054 0500000US20185 20185 Stafford Stafford County KS Kansas 06 2051389756 7435417
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20 165 00485358 0500000US20165 20165 Rush Rush County KS Kansas 06 1858997559 544720
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18 069 00450361 0500000US18069 18069 Huntington Huntington County IN Indiana 06 991062907 13127494
20 053 00484996 0500000US20053 20053 Ellsworth Ellsworth County KS Kansas 06 1853331063 19969761
18 033 00450346 0500000US18033 18033 DeKalb DeKalb County IN Indiana 06 939731959 2657419
18 053 00450355 0500000US18053 18053 Grant Grant County IN Indiana 06 1072484435 2101803
18 103 00450373 0500000US18103 18103 Miami Miami County IN Indiana 06 968246954 9184623
18 159 00450394 0500000US18159 18159 Tipton Tipton County IN Indiana 06 674797600 68028
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20 171 00485048 0500000US20171 20171 Scott Scott County KS Kansas 06 1858536838 306079
20 201 00485061 0500000US20201 20201 Washington Washington County KS Kansas 06 2317414332 10139473
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51 720 01498434 0500000US51720 51720 Norton Norton city VA Virginia 25 19366553 88961
48 267 01383919 0500000US48267 48267 Kimble Kimble County TX Texas 06 3240024038 505509
48 115 01383843 0500000US48115 48115 Dawson Dawson County TX Texas 06 2331781562 4720730
40 011 01101793 0500000US40011 40011 Blaine Blaine County OK Oklahoma 06 2404772745 26855431
20 007 00484973 0500000US20007 20007 Barber Barber County KS Kansas 06 2937240778 5411508
48 493 01384032 0500000US48493 48493 Wilson Wilson County TX Texas 06 2081662650 12111507
55 107 01581114 0500000US55107 55107 Rusk Rusk County WI Wisconsin 06 2366092264 44813690
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51 570 01498420 0500000US51570 51570 Colonial Heights Colonial Heights city VA Virginia 25 19475360 709877
48 023 01383797 0500000US48023 48023 Baylor Baylor County TX Texas 06 2246764590 86991035
20 199 00485060 0500000US20199 20199 Wallace Wallace County KS Kansas 06 2366348285 140936
20 175 00485050 0500000US20175 20175 Seward Seward County KS Kansas 06 1656693304 1961444
28 075 00695761 0500000US28075 28075 Lauderdale Lauderdale County MS Mississippi 06 1822508248 29730521
28 111 00695778 0500000US28111 28111 Perry Perry County MS Mississippi 06 1676452290 7561701
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17 011 00424207 0500000US17011 17011 Bureau Bureau County IL Illinois 06 2250884573 11523903
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29 035 00758472 0500000US29035 29035 Carter Carter County MO Missouri 06 1314052440 4304986
31 117 00835881 0500000US31117 31117 McPherson McPherson County NE Nebraska 06 2225460625 2680669
29 121 00758514 0500000US29121 29121 Macon Macon County MO Missouri 06 2075118027 28912941
20 031 00484985 0500000US20031 20031 Coffey Coffey County KS Kansas 06 1623623909 70470788
51 775 01789074 0500000US51775 51775 Salem Salem city VA Virginia 25 37593968 275156
55 069 01581094 0500000US55069 55069 Lincoln Lincoln County WI Wisconsin 06 2275832535 72745054
39 115 01074070 0500000US39115 39115 Morgan Morgan County OH Ohio 06 1078538282 13868572
55 103 01581112 0500000US55103 55103 Richland Richland County WI Wisconsin 06 1518120286 8153423
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28 115 00695803 0500000US28115 28115 Pontotoc Pontotoc County MS Mississippi 06 1289330916 8308394
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08 039 00198136 0500000US08039 08039 Elbert Elbert County CO Colorado 06 4791700177 442147
18 047 00450352 0500000US18047 18047 Franklin Franklin County IN Indiana 06 995658286 17155846
19 113 00465245 0500000US19113 19113 Linn Linn County IA Iowa 06 1857048426 19835228
26 165 01623023 0500000US26165 26165 Wexford Wexford County MI Michigan 06 1463148677 27182043
39 175 01074099 0500000US39175 39175 Wyandot Wyandot County OH Ohio 06 1053812244 1783532
31 061 00835852 0500000US31061 31061 Franklin Franklin County NE Nebraska 06 1491355863 487899
54 047 01689162 0500000US54047 54047 McDowell McDowell County WV West Virginia 06 1381648569 3731571
54 105 01678877 0500000US54105 54105 Wirt Wirt County WV West Virginia 06 602201076 5839709
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28 031 00695740 0500000US28031 28031 Covington Covington County MS Mississippi 06 1071784951 2880713
08 003 00198117 0500000US08003 08003 Alamosa Alamosa County CO Colorado 06 1871643029 1670455
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13 083 00347465 0500000US13083 13083 Dade Dade County GA Georgia 06 450855116 488463
13 201 00344088 0500000US13201 13201 Miller Miller County GA Georgia 06 731471756 3211332
13 235 00347593 0500000US13235 13235 Pulaski Pulaski County GA Georgia 06 645583957 5046606
28 005 00695727 0500000US28005 28005 Amite Amite County MS Mississippi 06 1890950868 3877823
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27 017 00659454 0500000US27017 27017 Carlton Carlton County MN Minnesota 06 2230473967 36173451
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31 163 00835903 0500000US31163 31163 Sherman Sherman County NE Nebraska 06 1465552764 14998613
31 101 00835872 0500000US31101 31101 Keith Keith County NE Nebraska 06 2749903240 124629167
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48 447 01384009 0500000US48447 48447 Throckmorton Throckmorton County TX Texas 06 2363499444 7586186
06 071 00277300 0500000US06071 06071 San Bernardino San Bernardino County CA California 06 51976311092 96418406
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29 003 00758456 0500000US29003 29003 Andrew Andrew County MO Missouri 06 1120510438 9677371
27 001 00663198 0500000US27001 27001 Aitkin Aitkin County MN Minnesota 06 4717323600 449370012
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37 001 01008531 0500000US37001 37001 Alamance Alamance County NC North Carolina 06 1096736064 27940533
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48 081 01383826 0500000US48081 48081 Coke Coke County TX Texas 06 2361153198 42331832
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48 013 01383792 0500000US48013 48013 Atascosa Atascosa County TX Texas 06 3158599705 4992623
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29 025 00758467 0500000US29025 29025 Caldwell Caldwell County MO Missouri 06 1104353494 8399237
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20 051 00484995 0500000US20051 20051 Ellis Ellis County KS Kansas 06 2330762300 1197085
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27 173 00659531 0500000US27173 27173 Yellow Medicine Yellow Medicine County MN Minnesota 06 1966062967 10687958
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28 013 00695731 0500000US28013 28013 Calhoun Calhoun County MS Mississippi 06 1519218292 3590388
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28 057 00695752 0500000US28057 28057 Itawamba Itawamba County MS Mississippi 06 1379933000 19825536
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18 067 00450360 0500000US18067 18067 Howard Howard County IN Indiana 06 759058622 2194576
31 047 00835845 0500000US31047 31047 Dawson Dawson County NE Nebraska 06 2623809783 16509199
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28 041 00695745 0500000US28041 28041 Greene Greene County MS Mississippi 06 1845983898 15430619
27 047 00659469 0500000US27047 27047 Freeborn Freeborn County MN Minnesota 06 1831756444 39305226
27 065 00659478 0500000US27065 27065 Kanabec Kanabec County MN Minnesota 06 1350962864 31252182
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29 085 00758497 0500000US29085 29085 Hickory Hickory County MO Missouri 06 1032908447 33454640
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31 003 00835824 0500000US31003 31003 Antelope Antelope County NE Nebraska 06 2220026341 3715967
56 031 01605080 0500000US56031 56031 Platte Platte County WY Wyoming 06 5390953617 76102033
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27 125 00659508 0500000US27125 27125 Red Lake Red Lake County MN Minnesota 06 1119929345 227815
27 137 00662850 0500000US27137 27137 St. Louis St. Louis County MN Minnesota 06 16182544691 1586178745
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38 091 01034220 0500000US38091 38091 Steele Steele County ND North Dakota 06 1844441508 8435674
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51 685 01498431 0500000US51685 51685 Manassas Park Manassas Park city VA Virginia 25 7857548 1609
51 840 01789077 0500000US51840 51840 Winchester Winchester city VA Virginia 25 23809500 54462
29 169 00758539 0500000US29169 29169 Pulaski Pulaski County MO Missouri 06 1417014582 11312724
18 111 00450376 0500000US18111 18111 Newton Newton County IN Indiana 06 1040539827 4349506
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08 095 00198163 0500000US08095 08095 Phillips Phillips County CO Colorado 06 1781724977 301808
48 399 01383985 0500000US48399 48399 Runnels Runnels County TX Texas 06 2722259323 15604788
19 185 00465281 0500000US19185 19185 Wayne Wayne County IA Iowa 06 1360957549 4272458
48 445 01384008 0500000US48445 48445 Terry Terry County TX Texas 06 2302113089 5414060
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08 005 00198118 0500000US08005 08005 Arapahoe Arapahoe County CO Colorado 06 2066509954 19798771
48 461 01384016 0500000US48461 48461 Upton Upton County TX Texas 06 3215010597 464309
48 059 01383815 0500000US48059 48059 Callahan Callahan County TX Texas 06 2329363241 4898783
48 227 01383899 0500000US48227 48227 Howard Howard County TX Texas 06 2333039143 8841781
48 459 01384015 0500000US48459 48459 Upshur Upshur County TX Texas 06 1509910834 24878112
48 063 01383817 0500000US48063 48063 Camp Camp County TX Texas 06 507242364 19129375
48 471 01384021 0500000US48471 48471 Walker Walker County TX Texas 06 2031126326 44745757
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51 121 01674630 0500000US51121 51121 Montgomery Montgomery County VA Virginia 06 1001929081 6282286
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48 441 01384006 0500000US48441 48441 Taylor Taylor County TX Texas 06 2371228265 9760311
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46 033 01265788 0500000US46033 46033 Custer Custer County SD South Dakota 06 4032463966 5490769
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31 183 00835913 0500000US31183 31183 Wheeler Wheeler County NE Nebraska 06 1489717901 1059454
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27 165 00659527 0500000US27165 27165 Watonwan Watonwan County MN Minnesota 06 1126508687 12387832
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49 039 01448033 0500000US49039 49039 Sanpete Sanpete County UT Utah 06 4117605584 32165095
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30 069 01719590 0500000US30069 30069 Petroleum Petroleum County MT Montana 06 4288047861 48927318
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55 085 01581103 0500000US55085 55085 Oneida Oneida County WI Wisconsin 06 2885102824 317602311
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38 083 01034203 0500000US38083 38083 Sheridan Sheridan County ND North Dakota 06 2518053323 86198839
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55 035 01581077 0500000US55035 55035 Eau Claire Eau Claire County WI Wisconsin 06 1652211241 18848551
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39 039 01074032 0500000US39039 39039 Defiance Defiance County OH Ohio 06 1065623072 7100811
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18 143 00450386 0500000US18143 18143 Scott Scott County IN Indiana 06 493140260 6074951
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28 003 00711755 0500000US28003 28003 Alcorn Alcorn County MS Mississippi 06 1036110409 3408033
17 139 01784885 0500000US17139 17139 Moultrie Moultrie County IL Illinois 06 870127369 22111272
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21 021 00516857 0500000US21021 21021 Boyle Boyle County KY Kentucky 06 467067863 6486676
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31 001 00835823 0500000US31001 31001 Adams Adams County NE Nebraska 06 1458872832 2477681
30 049 00793926 0500000US30049 30049 Lewis and Clark Lewis and Clark County MT Montana 06 8957164726 101496096
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37 081 01008558 0500000US37081 37081 Guilford Guilford County NC North Carolina 06 1673033183 30337205
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28 039 00695744 0500000US28039 28039 George George County MS Mississippi 06 1239816906 12838126
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56 005 01605068 0500000US56005 56005 Campbell Campbell County WY Wyoming 06 12437291886 11010427
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27 089 00659489 0500000US27089 27089 Marshall Marshall County MN Minnesota 06 4597384200 98012348
29 081 00758495 0500000US29081 29081 Harrison Harrison County MO Missouri 06 1871309888 10070644
28 101 00695773 0500000US28101 28101 Newton Newton County MS Mississippi 06 1496417775 4525334
28 155 00695798 0500000US28155 28155 Webster Webster County MS Mississippi 06 1090793736 5364867
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55 025 01581072 0500000US55025 55025 Dane Dane County WI Wisconsin 06 3098893820 106222414
48 171 01383871 0500000US48171 48171 Gillespie Gillespie County TX Texas 06 2740731307 9000601
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21 169 00516931 0500000US21169 21169 Metcalfe Metcalfe County KY Kentucky 06 750193212 3985177
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55 137 01581128 0500000US55137 55137 Waushara Waushara County WI Wisconsin 06 1621749913 29096948
55 135 01581127 0500000US55135 55135 Waupaca Waupaca County WI Wisconsin 06 1936521056 45270534
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29 061 00758485 0500000US29061 29061 Daviess Daviess County MO Missouri 06 1458893649 14926594
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31 027 00835835 0500000US31027 31027 Cedar Cedar County NE Nebraska 06 1917222677 14511196
31 133 00835888 0500000US31133 31133 Pawnee Pawnee County NE Nebraska 06 1116478173 4852359
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48 183 01383877 0500000US48183 48183 Gregg Gregg County TX Texas 06 708052151 6206460
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54 023 01697238 0500000US54023 54023 Grant Grant County WV West Virginia 06 1236387824 7546060
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53 039 01529219 0500000US53039 53039 Klickitat Klickitat County WA Washington 06 4847515939 84930636
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29 005 00758457 0500000US29005 29005 Atchison Atchison County MO Missouri 06 1417462629 7359186
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56 009 01605070 0500000US56009 56009 Converse Converse County WY Wyoming 06 11020385629 26068678
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18 025 00451674 0500000US18025 18025 Crawford Crawford County IN Indiana 06 791534794 8201106
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53 075 01533501 0500000US53075 53075 Whitman Whitman County WA Washington 06 5592463293 48246698
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48 119 01383846 0500000US48119 48119 Delta Delta County TX Texas 06 665192724 54647564
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47 067 01648577 0500000US47067 47067 Hancock Hancock County TN Tennessee 06 575816010 2988718
47 073 01639752 0500000US47073 47073 Hawkins Hawkins County TN Tennessee 06 1261468092 32541837
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53 001 01531601 0500000US53001 53001 Adams Adams County WA Washington 06 4985698852 12464425
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26 059 01622972 0500000US26059 26059 Hillsdale Hillsdale County MI Michigan 06 1549207166 22939100
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47 113 01639769 0500000US47113 47113 Madison Madison County TN Tennessee 06 1443073935 3757608
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17 067 00424235 0500000US17067 17067 Hancock Hancock County IL Illinois 06 2055798714 53563360
27 011 00659451 0500000US27011 27011 Big Stone Big Stone County MN Minnesota 06 1292738453 74945834
06 009 01675885 0500000US06009 06009 Calaveras Calaveras County CA California 06 2641837360 43789489
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56 039 01605083 0500000US56039 56039 Teton Teton County WY Wyoming 06 10351790287 570858887
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28 081 00695764 0500000US28081 28081 Lee Lee County MS Mississippi 06 1165404272 8314455
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22 115 00559548 0500000US22115 22115 Vernon Vernon Parish LA Louisiana 15 3436208063 35118476
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29 143 00758526 0500000US29143 29143 New Madrid New Madrid County MO Missouri 06 1747940899 56236293
37 021 01008538 0500000US37021 37021 Buncombe Buncombe County NC North Carolina 06 1700318977 8942802
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30 017 01720109 0500000US30017 30017 Custer Custer County MT Montana 06 9798723734 25612454
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26 009 01622947 0500000US26009 26009 Antrim Antrim County MI Michigan 06 1232002675 326536774
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17 145 01784940 0500000US17145 17145 Perry Perry County IL Illinois 06 1144587283 13199036
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48 291 01383931 0500000US48291 48291 Liberty Liberty County TX Texas 06 3000121461 46620495
48 131 01383851 0500000US48131 48131 Duval Duval County TX Texas 06 4645084668 5478267
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48 025 01383798 0500000US48025 48025 Bee Bee County TX Texas 06 2279809490 246409
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55 087 01581104 0500000US55087 55087 Outagamie Outagamie County WI Wisconsin 06 1651266077 18260943
55 097 01581109 0500000US55097 55097 Portage Portage County WI Wisconsin 06 2074252977 56835087
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28 007 00695728 0500000US28007 28007 Attala Attala County MS Mississippi 06 1903529295 4425860
28 079 00695763 0500000US28079 28079 Leake Leake County MS Mississippi 06 1509697192 6376466
28 095 00695771 0500000US28095 28095 Monroe Monroe County MS Mississippi 06 1981578016 18140832
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31 025 00835834 0500000US31025 31025 Cass Cass County NE Nebraska 06 1443520799 22130961
27 019 00659455 0500000US27019 27019 Carver Carver County MN Minnesota 06 916541648 57071065
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48 335 01383953 0500000US48335 48335 Mitchell Mitchell County TX Texas 06 2359720442 12480258
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48 137 01383854 0500000US48137 48137 Edwards Edwards County TX Texas 06 5485263220 5196312
48 153 01383862 0500000US48153 48153 Floyd Floyd County TX Texas 06 2569637283 983737
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28 051 00695749 0500000US28051 28051 Holmes Holmes County MS Mississippi 06 1959776830 20568825
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47 085 01639757 0500000US47085 47085 Humphreys Humphreys County TN Tennessee 06 1374668727 67184110
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28 011 00695730 0500000US28011 28011 Bolivar Bolivar County MS Mississippi 06 2270141682 81446732
28 025 00695737 0500000US28025 28025 Clay Clay County MS Mississippi 06 1062082196 15376919
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48 049 01383810 0500000US48049 48049 Brown Brown County TX Texas 06 2446120248 32375524
48 135 01383853 0500000US48135 48135 Ector Ector County TX Texas 06 2325508519 10188915
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31 023 00835833 0500000US31023 31023 Butler Butler County NE Nebraska 06 1514867107 15326897
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48 029 01383800 0500000US48029 48029 Bexar Bexar County TX Texas 06 3212426750 40788665
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49 041 01448034 0500000US49041 49041 Sevier Sevier County UT Utah 06 4948109945 20139931
49 045 01448036 0500000US49045 49045 Tooele Tooele County UT Utah 06 18234232014 636461735
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53 027 01531823 0500000US53027 53027 Grays Harbor Grays Harbor County WA Washington 06 4924743560 834361384
53 043 01514052 0500000US53043 53043 Lincoln Lincoln County WA Washington 06 5984424965 75262191
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53 057 01531402 0500000US53057 53057 Skagit Skagit County WA Washington 06 4481277789 483821018
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47 003 01639723 0500000US47003 47003 Bedford Bedford County TN Tennessee 06 1226719747 2980759
78 030 02378250 0500000US78030 78030 St. Thomas St. Thomas Island VI United States Virgin Islands 10 81108880 717920922
38 061 01035307 0500000US38061 38061 Mountrail Mountrail County ND North Dakota 06 4727150567 301102217
48 161 01383866 0500000US48161 48161 Freestone Freestone County TX Texas 06 2273311866 36936963
37 005 01008533 0500000US37005 37005 Alleghany Alleghany County NC North Carolina 06 608220280 3687222
36 121 00974158 0500000US36121 36121 Wyoming Wyoming County NY New York 06 1535219438 9158067
27 121 00659506 0500000US27121 27121 Pope Pope County MN Minnesota 06 1747086656 109712781
17 033 00424218 0500000US17033 17033 Crawford Crawford County IL Illinois 06 1149031260 5744821
29 011 00758460 0500000US29011 29011 Barton Barton County MO Missouri 06 1533351028 12152201
04 013 00037026 0500000US04013 04013 Maricopa Maricopa County AZ Arizona 06 23833110968 62124304
36 069 00974133 0500000US36069 36069 Ontario Ontario County NY New York 06 1668147120 47854414
48 365 01383968 0500000US48365 48365 Panola Panola County TX Texas 06 2101400900 25810623
17 193 00424297 0500000US17193 17193 White White County IL Illinois 06 1281999217 17833682
28 045 00711756 0500000US28045 28045 Hancock Hancock County MS Mississippi 06 1227561217 204095552
42 015 01213660 0500000US42015 42015 Bradford Bradford County PA Pennsylvania 06 2971688854 35331261
39 083 01074054 0500000US39083 39083 Knox Knox County OH Ohio 06 1361036418 10721050
46 015 01265768 0500000US46015 46015 Brule Brule County SD South Dakota 06 2116594503 75770744
08 007 00198119 0500000US08007 08007 Archuleta Archuleta County CO Colorado 06 3496712165 13740247
01 031 00161541 0500000US01031 01031 Coffee Coffee County AL Alabama 06 1758565928 3907189
51 033 01480107 0500000US51033 51033 Caroline Caroline County VA Virginia 06 1365864561 24926638
51 059 01480119 0500000US51059 51059 Fairfax Fairfax County VA Virginia 06 1012738308 40071741
45 085 01244717 0500000US45085 45085 Sumter Sumter County SC South Carolina 06 1722544863 44046815
42 047 01213668 0500000US42047 42047 Elk Elk County PA Pennsylvania 06 2141664056 12792134
19 189 00465283 0500000US19189 19189 Winnebago Winnebago County IA Iowa 06 1037261956 3182049
12 129 00306912 0500000US12129 12129 Wakulla Wakulla County FL Florida 06 1570615734 804111188
28 109 00695777 0500000US28109 28109 Pearl River Pearl River County MS Mississippi 06 2101307249 20783013
05 141 00069904 0500000US05141 05141 Van Buren Van Buren County AR Arkansas 06 1837778044 37208242
48 093 01383832 0500000US48093 48093 Comanche Comanche County TX Texas 06 2428768926 25719485
46 041 01266994 0500000US46041 46041 Dewey Dewey County SD South Dakota 06 5963127471 370089902
47 143 01639784 0500000US47143 47143 Rhea Rhea County TN Tennessee 06 817071271 54409427
42 061 01213672 0500000US42061 42061 Huntingdon Huntingdon County PA Pennsylvania 06 2265182342 37851956
55 049 01581084 0500000US55049 55049 Iowa Iowa County WI Wisconsin 06 1975379650 13870580
42 113 01213687 0500000US42113 42113 Sullivan Sullivan County PA Pennsylvania 06 1165337813 6617028
47 167 01639795 0500000US47167 47167 Tipton Tipton County TN Tennessee 06 1180026942 32703276
33 017 00873182 0500000US33017 33017 Strafford Strafford County NH New Hampshire 06 951743429 39154072
18 097 00450371 0500000US18097 18097 Marion Marion County IN Indiana 06 1027084080 16703563
46 007 01265812 0500000US46007 46007 Bennett Bennett County SD South Dakota 06 3068208303 15044356
51 029 01501502 0500000US51029 51029 Buckingham Buckingham County VA Virginia 06 1501215440 9911855
16 005 00395091 0500000US16005 16005 Bannock Bannock County ID Idaho 06 2881336421 92076089
13 257 00350028 0500000US13257 13257 Stephens Stephens County GA Georgia 06 463250297 13039270
16 015 00395157 0500000US16015 16015 Boise Boise County ID Idaho 06 4919826442 19104286
40 105 01101840 0500000US40105 40105 Nowata Nowata County OK Oklahoma 06 1465460409 38903890
13 125 00345642 0500000US13125 13125 Glascock Glascock County GA Georgia 06 372299245 1832723
55 091 01581106 0500000US55091 55091 Pepin Pepin County WI Wisconsin 06 600897314 43238609
19 071 00465224 0500000US19071 19071 Fremont Fremont County IA Iowa 06 1323918215 14168938
29 125 00758516 0500000US29125 29125 Maries Maries County MO Missouri 06 1364873607 7632374
48 347 01383959 0500000US48347 48347 Nacogdoches Nacogdoches County TX Texas 06 2450966942 89731149
37 137 01023355 0500000US37137 37137 Pamlico Pamlico County NC North Carolina 06 871570771 583036551
12 123 00295728 0500000US12123 12123 Taylor Taylor County FL Florida 06 2702230203 1213570848
27 171 00659530 0500000US27171 27171 Wright Wright County MN Minnesota 06 1712394403 137711642
23 025 00581298 0500000US23025 23025 Somerset Somerset County ME Maine 06 10163811990 437942552
05 089 00069898 0500000US05089 05089 Marion Marion County AR Arkansas 06 1545182805 112951240
48 377 01383974 0500000US48377 48377 Presidio Presidio County TX Texas 06 9985057446 1773188
06 099 00277314 0500000US06099 06099 Stanislaus Stanislaus County CA California 06 3875010966 46378767
21 063 00516878 0500000US21063 21063 Elliott Elliott County KY Kentucky 06 606888298 2595857
17 185 00424293 0500000US17185 17185 Wabash Wabash County IL Illinois 06 578403995 10973569
55 057 01581088 0500000US55057 55057 Juneau Juneau County WI Wisconsin 06 1986729542 98638538
38 099 01034214 0500000US38099 38099 Walsh Walsh County ND North Dakota 06 3319346400 32181390
01 011 00161531 0500000US01011 01011 Bullock Bullock County AL Alabama 06 1613083468 6030667
06 011 01675902 0500000US06011 06011 Colusa Colusa County CA California 06 2980245446 14696164
08 051 00198141 0500000US08051 08051 Gunnison Gunnison County CO Colorado 06 8389334152 53070998
48 067 01383819 0500000US48067 48067 Cass Cass County TX Texas 06 2426683491 60494144
13 039 01671316 0500000US13039 13039 Camden Camden County GA Georgia 06 1632397628 392733634
28 097 00711757 0500000US28097 28097 Montgomery Montgomery County MS Mississippi 06 1054074828 2352156
13 121 01694833 0500000US13121 13121 Fulton Fulton County GA Georgia 06 1364327945 19520065
38 043 01034206 0500000US38043 38043 Kidder Kidder County ND North Dakota 06 3499233947 211737414
13 111 00351094 0500000US13111 13111 Fannin Fannin County GA Georgia 06 1002597521 13473582
39 123 01074074 0500000US39123 39123 Ottawa Ottawa County OH Ohio 06 659674517 855668003
37 031 01026337 0500000US37031 37031 Carteret Carteret County NC North Carolina 06 1314688734 2131061849
18 127 00450382 0500000US18127 18127 Porter Porter County IN Indiana 06 1082907704 268619696
51 135 01493928 0500000US51135 51135 Nottoway Nottoway County VA Virginia 06 814265583 4297830
29 077 00758493 0500000US29077 29077 Greene Greene County MO Missouri 06 1749093452 6607713
48 201 01383886 0500000US48201 48201 Harris Harris County TX Texas 06 4421145870 182187806
48 217 01383894 0500000US48217 48217 Hill Hill County TX Texas 06 2483430190 69544723
29 219 00758562 0500000US29219 29219 Warren Warren County MO Missouri 06 1110043144 23775471
13 141 00348209 0500000US13141 13141 Hancock Hancock County GA Georgia 06 1220057418 17479620
01 069 00161560 0500000US01069 01069 Houston Houston County AL Alabama 06 1501742235 4795415
29 155 00758532 0500000US29155 29155 Pemiscot Pemiscot County MO Missouri 06 1275841039 53915406
26 163 01623022 0500000US26163 26163 Wayne Wayne County MI Michigan 06 1584692687 157708871
18 011 00450405 0500000US18011 18011 Boone Boone County IN Indiana 06 1095260013 876741
36 061 00974129 0500000US36061 36061 New York New York County NY New York 06 58683880 29010416
45 039 01248000 0500000US45039 45039 Fairfield Fairfield County SC South Carolina 06 1777521257 61063162
16 087 00399757 0500000US16087 16087 Washington Washington County ID Idaho 06 3762870369 53228012
39 007 01074017 0500000US39007 39007 Ashtabula Ashtabula County OH Ohio 06 1819712681 1724513202
51 163 01480166 0500000US51163 51163 Rockbridge Rockbridge County VA Virginia 06 1545064660 8810379
55 059 01581089 0500000US55059 55059 Kenosha Kenosha County WI Wisconsin 06 704044387 1248872159
09 120 02830245 0500000US09120 09120 Greater Bridgeport Greater Bridgeport Planning Region CT Connecticut PL 363067865 253764138
31 011 00835828 0500000US31011 31011 Boone Boone County NE Nebraska 06 1778138689 1745891
48 099 01383835 0500000US48099 48099 Coryell Coryell County TX Texas 06 2725307438 11833644
17 037 00422190 0500000US17037 17037 DeKalb DeKalb County IL Illinois 06 1635155509 8560429
26 085 01622985 0500000US26085 26085 Lake Lake County MI Michigan 06 1470061185 17483127
12 071 00295758 0500000US12071 12071 Lee Lee County FL Florida 06 2022848995 1900537643
16 041 00395585 0500000US16041 16041 Franklin Franklin County ID Idaho 06 1717211139 12153472
51 081 01501122 0500000US51081 51081 Greensville Greensville County VA Virginia 06 764634552 4086108
13 091 00348116 0500000US13091 13091 Dodge Dodge County GA Georgia 06 1284538002 18529136
06 045 00277287 0500000US06045 06045 Mendocino Mendocino County CA California 06 9082586851 961786019
55 011 01581065 0500000US55011 55011 Buffalo Buffalo County WI Wisconsin 06 1750290756 87549574
55 101 01581111 0500000US55101 55101 Racine Racine County WI Wisconsin 06 861537604 1190103013
50 013 01461763 0500000US50013 50013 Grand Isle Grand Isle County VT Vermont 06 211772078 288966533
27 037 00659464 0500000US27037 27037 Dakota Dakota County MN Minnesota 06 1457015230 62996790
72 113 01804537 0500000US72113 72113 Ponce Ponce Municipio PR Puerto Rico 13 297688924 203748247
41 051 01135861 0500000US41051 41051 Multnomah Multnomah County OR Oregon 06 1116334868 88031754
22 069 00558108 0500000US22069 22069 Natchitoches Natchitoches Parish LA Louisiana 15 3246092085 119733774
17 171 00424286 0500000US17171 17171 Scott Scott County IL Illinois 06 649542036 4814546
72 123 01804542 0500000US72123 72123 Salinas Salinas Municipio PR Puerto Rico 13 179755401 115816412
13 103 00350219 0500000US13103 13103 Effingham Effingham County GA Georgia 06 1240161598 10552453
40 015 01101795 0500000US40015 40015 Caddo Caddo County OK Oklahoma 06 3309366433 32099077
40 067 01101821 0500000US40067 40067 Jefferson Jefferson County OK Oklahoma 06 1965685985 39417590
08 055 00198143 0500000US08055 08055 Huerfano Huerfano County CO Colorado 06 4120756290 5792101
45 007 01247981 0500000US45007 45007 Anderson Anderson County SC South Carolina 06 1848876935 108544449
45 027 01247990 0500000US45027 45027 Clarendon Clarendon County SC South Carolina 06 1572659561 229094635
13 177 00343390 0500000US13177 13177 Lee Lee County GA Georgia 06 921632946 15408829
39 081 01074053 0500000US39081 39081 Jefferson Jefferson County OH Ohio 06 1057037102 7335056
40 129 01101852 0500000US40129 40129 Roger Mills Roger Mills County OK Oklahoma 06 2955524813 13688537
51 678 01789071 0500000US51678 51678 Lexington Lexington city VA Virginia 25 6473000 67783
06 089 01682610 0500000US06089 06089 Shasta Shasta County CA California 06 9778892920 185816636
05 041 00066850 0500000US05041 05041 Desha Desha County AR Arkansas 06 1919768424 185180909
22 057 00558065 0500000US22057 22057 Lafourche Lafourche Parish LA Louisiana 15 2765571303 1037643577
69 110 01805247 0500000US69110 69110 Saipan Saipan Municipality MP Commonwealth of the Northern Mariana Islands 12 118890992 532767361
06 109 00277319 0500000US06109 06109 Tuolumne Tuolumne County CA California 06 5752133238 138668837
40 021 01101798 0500000US40021 40021 Cherokee Cherokee County OK Oklahoma 06 1940228930 69661251
05 015 00066975 0500000US05015 05015 Carroll Carroll County AR Arkansas 06 1631504843 22715756
48 449 01384010 0500000US48449 48449 Titus Titus County TX Texas 06 1052314636 50096807
22 099 01629486 0500000US22099 22099 St. Martin St. Martin Parish LA Louisiana 15 1910038831 205294657
01 103 00161578 0500000US01103 01103 Morgan Morgan County AL Alabama 06 1501335545 50196377
01 125 00161588 0500000US01125 01125 Tuscaloosa Tuscaloosa County AL Alabama 06 3420980041 78703449
22 125 00559584 0500000US22125 22125 West Feliciana West Feliciana Parish LA Louisiana 15 1044584261 58751920
13 151 01671894 0500000US13151 13151 Henry Henry County GA Georgia 06 825432678 20273034
12 043 00295743 0500000US12043 12043 Glades Glades County FL Florida 06 2089659352 467293938
08 089 00198160 0500000US08089 08089 Otero Otero County CO Colorado 06 3268424301 20092555
22 107 00559509 0500000US22107 22107 Tensas Tensas Parish LA Louisiana 15 1561795836 99432220
54 011 01550012 0500000US54011 54011 Cabell Cabell County WV West Virginia 06 727847834 18112163
21 183 00516938 0500000US21183 21183 Ohio Ohio County KY Kentucky 06 1520569116 23652967
27 013 00659452 0500000US27013 27013 Blue Earth Blue Earth County MN Minnesota 06 1936886814 45960593
33 011 00873179 0500000US33011 33011 Hillsborough Hillsborough County NH New Hampshire 06 2270202106 41309760
56 037 01609192 0500000US56037 56037 Sweetwater Sweetwater County WY Wyoming 06 27005754360 166230245
19 155 00465266 0500000US19155 19155 Pottawattamie Pottawattamie County IA Iowa 06 2463774735 20387191
36 045 00974121 0500000US36045 36045 Jefferson Jefferson County NY New York 06 3283887137 1524557044
29 013 00758461 0500000US29013 29013 Bates Bates County MO Missouri 06 2167033438 38030738
26 141 01623013 0500000US26141 26141 Presque Isle Presque Isle County MI Michigan 06 1706069656 4957327108
30 085 01669428 0500000US30085 30085 Roosevelt Roosevelt County MT Montana 06 6098391677 38582249
53 031 01531936 0500000US53031 53031 Jefferson Jefferson County WA Washington 06 4671633827 994992501
48 355 01383963 0500000US48355 48355 Nueces Nueces County TX Texas 06 2173636003 845192062
55 029 01581074 0500000US55029 55029 Door Door County WI Wisconsin 06 1248200842 4890681189
16 069 00399394 0500000US16069 16069 Nez Perce Nez Perce County ID Idaho 06 2197139835 21252880
26 063 01622974 0500000US26063 26063 Huron Huron County MI Michigan 06 2165275137 3369019054
13 167 00346664 0500000US13167 13167 Johnson Johnson County GA Georgia 06 784815230 9256633
39 137 01074081 0500000US39137 39137 Putnam Putnam County OH Ohio 06 1249783611 4544874
48 143 01383857 0500000US48143 48143 Erath Erath County TX Texas 06 2805419712 17166727
29 203 00758554 0500000US29203 29203 Shannon Shannon County MO Missouri 06 2599881424 464012
02 170 01419976 0500000US02170 02170 Matanuska-Susitna Matanuska-Susitna Borough AK Alaska 04 63991523362 1445856740
51 610 01498423 0500000US51610 51610 Falls Church Falls Church city VA Virginia 25 5300262 32
48 273 01383922 0500000US48273 48273 Kleberg Kleberg County TX Texas 06 2282572444 541041659
08 097 00198164 0500000US08097 08097 Pitkin Pitkin County CO Colorado 06 2514104906 6472577
08 067 00198148 0500000US08067 08067 La Plata La Plata County CO Colorado 06 4376255278 25642579
40 143 01101859 0500000US40143 40143 Tulsa Tulsa County OK Oklahoma 06 1476917124 42925549
72 007 01804483 0500000US72007 72007 Aguas Buenas Aguas Buenas Municipio PR Puerto Rico 13 77919500 28383
72 047 01804503 0500000US72047 72047 Corozal Corozal Municipio PR Puerto Rico 13 110248542 16284
01 115 00164997 0500000US01115 01115 St. Clair St. Clair County AL Alabama 06 1635759708 56431801
12 103 00295745 0500000US12103 12103 Pinellas Pinellas County FL Florida 06 709087754 1535985874
17 057 00424230 0500000US17057 17057 Fulton Fulton County IL Illinois 06 2242109836 43927321
20 021 00484980 0500000US20021 20021 Cherokee Cherokee County KS Kansas 06 1521791029 8951464
27 007 00659449 0500000US27007 27007 Beltrami Beltrami County MN Minnesota 06 6486994911 1425755980
18 017 00450339 0500000US18017 18017 Cass Cass County IN Indiana 06 1067448399 7002034
05 113 00069175 0500000US05113 05113 Polk Polk County AR Arkansas 06 2219200782 12520929
69 120 01805248 0500000US69120 69120 Tinian Tinian Municipality MP Commonwealth of the Northern Mariana Islands 12 108237606 632893009
32 005 00858643 0500000US32005 32005 Douglas Douglas County NV Nevada 06 1840283025 72182210
20 095 00485012 0500000US20095 20095 Kingman Kingman County KS Kansas 06 2236245128 8391920
19 043 00465210 0500000US19043 19043 Clayton Clayton County IA Iowa 06 2016207829 36695624
18 049 00450353 0500000US18049 18049 Fulton Fulton County IN Indiana 06 954133332 7439345
29 199 00758552 0500000US29199 29199 Scotland Scotland County MO Missouri 06 1130548365 7217862
45 015 01247985 0500000US45015 45015 Berkeley Berkeley County SC South Carolina 06 2858412773 337382775
09 160 02830251 0500000US09160 09160 Northwest Hills Northwest Hills Planning Region CT Connecticut PL 2037392863 55597912
26 089 01622987 0500000US26089 26089 Leelanau Leelanau County MI Michigan 06 899241892 5659105321
42 057 01213671 0500000US42057 42057 Fulton Fulton County PA Pennsylvania 06 1133252799 1305486
26 037 01622961 0500000US26037 26037 Clinton Clinton County MI Michigan 06 1469427623 18687990
13 239 00350547 0500000US13239 13239 Quitman Quitman County GA Georgia 06 391703076 24158295
53 061 01529222 0500000US53061 53061 Snohomish Snohomish County WA Washington 06 5404046467 282924414
72 099 01804530 0500000US72099 72099 Moca Moca Municipio PR Puerto Rico 13 130383565 56474
29 111 00758510 0500000US29111 29111 Lewis Lewis County MO Missouri 06 1307990182 14964045
12 079 00295731 0500000US12079 12079 Madison Madison County FL Florida 06 1804001483 49634046
35 028 01702366 0500000US35028 35028 Los Alamos Los Alamos County NM New Mexico 06 282626748 208105
35 019 00929111 0500000US35019 35019 Guadalupe Guadalupe County NM New Mexico 06 7847072132 2887948
54 021 01689673 0500000US54021 54021 Gilmer Gilmer County WV West Virginia 06 876717620 4082112
18 163 00450396 0500000US18163 18163 Vanderburgh Vanderburgh County IN Indiana 06 604506338 8955935
54 027 01718644 0500000US54027 54027 Hampshire Hampshire County WV West Virginia 06 1658633561 10902927
41 063 01155135 0500000US41063 41063 Wallowa Wallowa County OR Oregon 06 8147835328 14191752
37 039 01008545 0500000US37039 37039 Cherokee Cherokee County NC North Carolina 06 1179845613 28813485
40 109 01101842 0500000US40109 40109 Oklahoma Oklahoma County OK Oklahoma 06 1836035183 24721024
12 127 00306921 0500000US12127 12127 Volusia Volusia County FL Florida 06 2851876607 858119458
06 091 00277310 0500000US06091 06091 Sierra Sierra County CA California 06 2468694582 23299110
16 019 00395407 0500000US16019 16019 Bonneville Bonneville County ID Idaho 06 4832847348 88880595
01 035 00161543 0500000US01035 01035 Conecuh Conecuh County AL Alabama 06 2202213384 6426488
20 097 00485013 0500000US20097 20097 Kiowa Kiowa County KS Kansas 06 1871627806 596764
27 041 00659466 0500000US27041 27041 Douglas Douglas County MN Minnesota 06 1649506061 215746732
47 023 01639732 0500000US47023 47023 Chester Chester County TN Tennessee 06 740053474 575590
22 113 00559538 0500000US22113 22113 Vermilion Vermilion Parish LA Louisiana 15 3035611921 932167176
35 043 00929113 0500000US35043 35043 Sandoval Sandoval County NM New Mexico 06 9609358329 10852149
27 027 00659459 0500000US27027 27027 Clay Clay County MN Minnesota 06 2706993094 19303392

KS/cb_2022_us_county_5m.prj

GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]]

KS/cb_2022_us_county_5m.shp

KS/cb_2022_us_county_5m.shp.ea.iso.xml

Feature Catalog for the 2022 Counties and Equivalent Areas Cartographic Boundary File Counties and Equivalent Areas 2023-04 2023-04 eng; USA utf8 U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 United States [email protected] pointOfContact cb_2022_us_county_5m.shp Current County and Equivalent (national) false STATEFP Current state Federal Information Processing Series (FIPS) code National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States/State Equivalents COUNTYFP Current county Federal Information Processing Series (FIPS) code National Standard Codes (ANSI INCITS 31-2009), Federal Information Processing Series (FIPS) - Counties/County Equivalents COUNTYNS Current county Geographic Names Information System (GNIS) code INCITS 446:2008 (Geographic Names Information System (GNIS)), Identifying Attributes for Named Physical and Cultural Geographic Features (Except Roads and Highways) of the United States, Its Territories, Outlying Areas, and Freely Associated Areas, and the Waters of the Same to the Limit of the Twelve-Mile Statutory Zone AFFGEOID American FactFinder summary level code + geovariant code + '00US' + GEOID American FactFinder geographic identifier GEOID County identifier; a concatenation of current state Federal Information Processing Series (FIPS) code and county FIPS code The GEOID attribute is a concatenation of the state FIPS code followed by the county FIPS code. No spaces are allowed between the two codes. The state FIPS code is taken from "National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States". The county FIPS code is taken from "National Standard Codes (ANSI INCITS 31-2009), Federal Information Processing Series (FIPS) - Counties/County Equivalents". NAME Current county name National Standard Codes (ANSI INCITS 31-2009), Federal Information Processing Series (FIPS) - Counties/County Equivalents NAMELSAD Current name and the translated legal/statistical area description for county Current name and the translated legal/statistical area description for county STUSPS Current United States Postal Service state abbreviation Publication 28 - Postal Addressing Standards STATE_NAME Current State name National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States/State Equivalents LSAD Current legal/statistical area description code for county 00 Blank 03 City and Borough (suffix) 04 Borough (suffix) 05 Census Area (suffix) 06 County (suffix) 07 District (suffix) 10 Island (suffix) 12 Municipality (suffix) 13 Municipio (suffix) 15 Parish (suffix) 25 city (suffix) ALAND Current land area (square meters) 0 9,999,999,999,999 AWATER Current water area (square meters) 0 9,999,999,999,999

KS/cb_2022_us_county_5m.shp.iso.xml

cb_2022_us_county_5m.shp.iso.xml eng; USA utf8 dataset U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 United States [email protected] pointOfContact 2023-04 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19115/cb_2022_us_county_5m.shp.iso.xml complex 3235 North American Datum of 1983 NAD83 2007-01-19 revision https://spatialreference.org/ref/epsg/4269/gml/ NAD83 Link to Geographic Markup Language (GML) description of reference system. information resourceProvider urn:ogc:def:crs:EPSG::4269 2022 Cartographic Boundary File (SHP), Current County and Equivalent for United States, 1:5,000,000 2023-04 publication 2023-04 creation 2023-04 lastUpdate cb_2022_us_county_5m U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 United States [email protected] pointOfContact mapDigital The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are based on those as of January 1, 2022, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS). These files were specifically created to support small-scale thematic mapping. To improve the appearance of shapes at small scales, areas are represented with fewer vertices than detailed TIGER/Line Shapefiles. Cartographic boundary files take up less disk space than their ungeneralized counterparts. Cartographic boundary files take less time to render on screen than TIGER/Line Shapefiles. You can join this file with table data downloaded from American FactFinder by using the AFFGEOID field in the cartographic boundary file. If detailed boundaries are required, please use the TIGER/Line Shapefiles instead of the generalized cartographic boundary files. completed U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 United States [email protected] pointOfContact notPlanned 2022 SHP Borough Cartographic Boundary Census Area City City and Borough County County equivalent District Generalized Independent City Island Municipality Municipio Parish None United States of America (the) US ISO 3166 Codes for the representation of names of countries and their subdivisions otherRestrictions otherRestrictions Access_Constraints: None Use Constraints: The intended display scale for this file is 1:5,000,000. This file should not be displayed at scales larger than 1:5,000,000. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information is for visual display at appropriate small scales only. Cartographic boundary files should not be used for geographic analysis including area or perimeter calculation. Files should not be used for geocoding addresses. Files should not be used for determining precise geographic area relationships. vector eng; USA utf8 boundaries The cartographic boundary files contain geographic data only and do not include display mapping software or statistical data. For information on how to use cartographic boundary file data with specific software package users shall contact the company that produced the software. -179.14734 179.77847 -14.552549 71.352561 publication date 2023-04 1 Counties and Equivalent Areas Feature Catalog for the 2022 Counties and Equivalent Areas Cartographic Boundary File 2022 publication U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 United States [email protected] pointOfContact https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19110/cb_2022_us_county_5m.shp.ea.iso.xml ZIP U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 United States [email protected] distributor The online cartographic boundary files may be downloaded without charge. https://www2.census.gov/geo/tiger/GENZ2022/shp/cb_2022_us_county_5m.zip Shapefile Zip File cb_2022_us_county_5m.zip The cartographic boundary files are simplified representations of selected geographic areas specifically designed for small scale thematic mapping. These files contain simplified extracts of selected geographic areas from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. download https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19110/cb_2022_us_county_5m.shp.ea.iso.xml XML cb_2022_us_county_5m.shp.ea.iso.xml Entity and attribute file download https://www2.census.gov/geo/tiger/GENZ2022/2022_file_name_def.pdf PDF 2022_file_name_def.pdf The file naming convention for the cartographic boundary files. search https://www2.census.gov/geo/tiger/GENZ2022/description.pdf PDF description.pdf General description of the cartographic boundary files and their appropriate use. search dataset The Census Bureau performed automated tests to ensure logical consistency and limits of shapefiles. Segments making up the outer and inner boundaries of a polygon tie end-to-end to completely enclose the area. All polygons are tested for closure. The Census Bureau uses its internally developed geographic update system to enhance and modify spatial and attribute data in the Census MAF/TIGER database. Standard geographic codes, such as FIPS codes for states, counties, municipalities, county subdivisions, places, American Indian/Alaska Native/Native Hawaiian areas, and congressional districts are used when encoding spatial entities. The Census Bureau performed spatial data tests for logical consistency of the codes during the compilation of the original Census MAF/TIGER database files. Most of the codes for geographic entities except states, counties, urban areas, Core Based Statistical Areas (CBSAs), American Indian Areas (AIAs), and congressional districts were provided to the Census Bureau by the USGS, the agency responsible for maintaining the Geographic Names Information System (GNIS). Feature attribute information has been examined but has not been fully tested for consistency. For the Cartographic Boundary Files, the Point and Vector Object Count for the G-polygon SDTS Point and Vector Object Type reflects the number of records in the shapefile attribute table. For multi-polygon features, only one attribute record exists for each multi-polygon rather than one attribute record per individual G-polygon component of the multi-polygon feature. Cartographic Boundary File multi-polygons are an exception to the G-polygon object type classification. Therefore, when multi-polygons exist in a shapefile, the object count will be less than the actual number of G-polygons. The cartographic boundary files are generalized representations of extracts taken from the MAF/TIGER database. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files. Some small geographic areas, holes, or discontiguous parts of areas may not be included in generalized files if they are not visible at the target scale. The cartographic boundary files are generalized representations of extracts taken from the MAF/TIGER database. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files. Some small geographic areas, holes, or discontiguous parts of areas may not be included in generalized files if they are not visible at the target scale. notPlanned This was transformed from the Census Bureau Geospatial Product Metadata Content Standard.

KS/cb_2022_us_county_5m.shx

KS/county_population.csv

County Population
Allen 134800
Anderson 8000
Atchison 16900
Barber 4300
Barton 29000
Bourbon 20000
Brown 12000
Butler 65000
Chase 2700
Chautauqua 3000
Cherokee 21000
Cheyenne 1800
Clark 2000
Clay 13000
Cloud 9000
Coffey 8500
Comanche 1900
Cowley 35000
Crawford 39000
Decatur 2900
Dickinson 19000
Doniphan 8000
Douglas 120000
Edwards 3000
Elk 3000
Ellis 29000
Ellsworth 3000
Finney 37000
Ford 34000
Franklin 25000
Geary 35000
Gove 2700
Graham 3000
Grant 2700
Greenwood 7500
Hamilton 2700
Harper 6000
Harvey 35000
Haskell 4000
Hodgeman 2000
Jackson 19000
Jefferson 19000
Jewell 3000
Johnson 600000
Kearny 4000
Kingman 9000
Kiowa 1300
Labette 22000
Lane 2200
Leavenworth 80000
Lincoln 3000
Linn 9600
Logan 2700
Lyon 35000
McPherson 29000
Marion 12000
Marshall 10000
Meade 4600
Miami 34000
Mitchell 6000
Montgomery 29000
Morris 5500
Nemaha 11000
Neosho 17000
Ness 3000
Osage 16000
Osborne 4500
Ottawa 6000
Pawnee 6500
Phillips 5500
Pottawatomie 23000
Pratt 9000
Rawlins 2800
Reno 65000
Republic 5100
Rice 10000
Riley 70000
Rooks 5200
Rush 3000
Russell 7000
Saline 55000
Scott 5000
Sedgwick 510000
Seward 23000
Shawnee 180000
Sheridan 2900
Sherman 6000
Smith 4000
Stafford 4500
Stanton 2000
Sumner 24000
Thomas 8000
Trego 3000
Wabaunsee 7000
Wallace 1500
Washington 6000
Wilson 9000
Woodson 3500
Wyandotte 180000

KS/ks.codes

import pandas as pd import numpy as np # Step 1: Define population data for each county in Kansas (sample data) county_population = { "Allen": 134800, "Anderson": 8000, "Atchison": 16900, "Barber": 4300, "Barton": 29000, "Bourbon": 20000, "Brown": 12000, "Butler": 65000, "Chase": 2700, "Chautauqua": 3000, "Cherokee": 21000, "Cheyenne": 1800, "Clark": 2000, "Clay": 13000, "Cloud": 9000, "Coffey": 8500, "Comanche": 1900, "Cowley": 35000, "Crawford": 39000, "Decatur": 2900, "Dickinson": 19000, "Doniphan": 8000, "Douglas": 120000, "Edwards": 3000, "Elk": 3000, "Ellis": 29000, "Ellsworth": 3000, "Finney": 37000, "Ford": 34000, "Franklin": 25000, "Geary": 35000, "Gove": 2700, "Graham": 3000, "Grant": 2700, "Greenwood": 7500, "Hamilton": 2700, "Harper": 6000, "Harvey": 35000, "Haskell": 4000, "Hodgeman": 2000, "Jackson": 19000, "Jefferson": 19000, "Jewell": 3000, "Johnson": 600000, "Kearny": 4000, "Kingman": 9000, "Kiowa": 1300, "Labette": 22000, "Lane": 2200, "Leavenworth": 80000, "Lincoln": 3000, "Linn": 9600, "Logan": 2700, "Lyon": 35000, "McPherson": 29000, "Marion": 12000, "Marshall": 10000, "Meade": 4600, "Miami": 34000, "Mitchell": 6000, "Montgomery": 29000, "Morris": 5500, "Nemaha": 11000, "Neosho": 17000, "Ness": 3000, "Osage": 16000, "Osborne": 4500, "Ottawa": 6000, "Pawnee": 6500, "Phillips": 5500, "Pottawatomie": 23000, "Pratt": 9000, "Rawlins": 2800, "Reno": 65000, "Republic": 5100, "Rice": 10000, "Riley": 70000, "Rooks": 5200, "Rush": 3000, "Russell": 7000, "Saline": 55000, "Scott": 5000, "Sedgwick": 510000, "Seward": 23000, "Shawnee": 180000, "Sheridan": 2900, "Sherman": 6000, "Smith": 4000, "Stafford": 4500, "Stanton": 2000, "Sumner": 24000, "Thomas": 8000, "Trego": 3000, "Wabaunsee": 7000, "Wallace": 1500, "Washington": 6000, "Wilson": 9000, "Woodson": 3500, "Wyandotte": 180000 } # Step 2: Define adjacency dictionary for all counties (as before) adjacency_dict = { "Allen": ["Bourbon", "Cherokee", "Crawford", "Neosho", "Woodson"], "Anderson": ["Franklin", "Linn", "Miami", "Osage"], "Atchison": ["Doniphan", "Jefferson", "Leavenworth", "Jackson"], "Barber": ["Kiowa", "Pratt", "Stafford", "Reno", "Comanche"], "Barton": ["Rice", "Reno", "Rush", "Stafford", "Ellis"], "Bourbon": ["Allen", "Cherokee", "Crawford", "Neosho", "Woodson"], "Brown": ["Doniphan", "Jackson", "Jefferson", "Nemaha"], "Butler": ["Cowley", "Harvey", "Sedgwick", "Tampa", "Lyon"], "Chase": ["Osage", "Wabaunsee", "Riley", "Jackson"], "Chautauqua": ["Cowley", "Montgomery", "Wilson"], "Cherokee": ["Allen", "Bourbon", "Crawford", "Neosho"], "Cheyenne": ["Kit Carson", "Baca", "Sedgwick"], "Clark": ["Comanche", "Kiowa", "Meade"], "Clay": ["Dickinson", "Geary", "Republic", "Washington"], "Cloud": ["Jewell", "Ottawa", "Republic", "Saline"], "Coffey": ["Lyon", "Osage", "Franklin"], "Comanche": ["Barber", "Clark", "Kiowa", "Reno"], "Cowley": ["Butler", "Chautauqua", "Sedgwick", "Sumner"], "Crawford": ["Allen", "Bourbon", "Cherokee", "Neosho", "Woodson"], "Decatur": ["Norton", "Phillips", "Smith", "Sheridan"], "Dickinson": ["Clay", "Geary", "Saline"], "Doniphan": ["Atchison", "Brown", "Leavenworth", "Missouri"], "Douglas": ["Jefferson", "Leavenworth", "Shawnee"], "Edwards": ["Kiowa", "Stafford", "Pratt", "Barber"], "Elk": ["Chautauqua", "Montgomery", "Wilson"], "Ellis": ["Barton", "Rooks", "Rush", "Trego"], "Ellsworth": ["Barton", "McPherson", "Saline", "Russell"], "Finney": ["Haskell", "Kearny", "Lane", "Scott", "Wichita"], "Ford": ["Hodgeman", "Kiowa", "Meade", "Seward", "Gray"], "Franklin": ["Anderson", "Douglas", "Lyon", "Miami"], "Geary": ["Clay", "Dickinson", "Pottawatomie", "Riley", "Wabaunsee"], "Gove": ["Logan", "Ness", "Trego", "Sheridan", "Wichita"], "Graham": ["Norton", "Rooks", "Trego", "Wichita"], "Grant": ["Haskell", "Lane", "Scott", "Seward"], "Greenwood": ["Butler", "Chase", "Lyon", "Osage"], "Hamilton": ["Kearny", "Meade", "Scott", "Seward"], "Harper": ["Barber", "Kingman", "Sedgwick", "Sumner"], "Harvey": ["Butler", "Sedgwick", "McPherson", "Reneg"], "Haskell": ["Finney", "Grant", "Gray", "Kiowa", "Meade"], "Hodgeman": ["Ford", "Gray", "Kiowa"], "Jackson": ["Atchison", "Jefferson", "Pottawatomie", "Shawnee"], "Jefferson": ["Atchison", "Douglas", "Leavenworth", "Shawnee"], "Jewell": ["Mitchell", "Republic", "Smith"], "Johnson": ["Leavenworth", "Wyandotte", "Miami", "Shawnee"], "Kearny": ["Finney", "Grant", "Haskell", "Meade"], "Kingman": ["Barber", "Harper", "Sedgwick", "Sumner"], "Kiowa": ["Barber", "Clark", "Comanche", "Ford"], "Labette": ["Montgomery", "Neosho", "Wilson"], "Lane": ["Finney", "Grant", "Haskell", "Scott"], "Leavenworth": ["Atchison", "Doniphan", "Jefferson", "Wyandotte"], "Lincoln": ["Ellsworth", "Ottawa", "Saline"], "Linn": ["Anderson", "Miami"], "Logan": ["Gove", "Scott", "Wichita", "Trego"], "Lyon": ["Butler", "Coffey", "Chase", "Greenwood", "Osage", "Franklin"], "McPherson": ["Harvey", "Marion", "Saline"], "Marion": ["Harvey", "McPherson", "Sedgwick", "Sumner"], "Marshall": ["Nemaha", "Washington", "Pottawatomie"], "Meade": ["Finney", "Haskell", "Ford", "Gray"], "Miami": ["Anderson", "Douglas", "Franklin", "Johnson"], "Mitchell": ["Cloud", "Jewell", "Ottawa", "Republic"], "Montgomery": ["Chautauqua", "Labette", "Wilson"], "Morris": ["Chase", "Geary", "Wabaunsee"], "Nemaha": ["Brown", "Pottawatomie", "Marshall", "Jackson"], "Neosho": ["Allen", "Bourbon", "Cherokee", "Crawford", "Woodson"], "Ness": ["Gove", "Lane", "Rush", "Trego"], "Osage": ["Anderson", "Chase", "Douglas", "Franklin", "Lyon"], "Osborne": ["Mitchell", "Rooks", "Russell"], "Ottawa": ["Cloud", "Franklin", "Lincoln", "Republic", "Saline"], "Pawnee": ["Kiowa", "Stafford", "Rush", "Reno"], "Phillips": ["Smith", "Norton", "Graham", "Jewell"], "Pottawatomie": ["Jackson", "Marshall", "Nemaha", "Shawnee"], "Pratt": ["Barber", "Barton", "Kiowa", "Reno", "Stafford"], "Rawlins": ["Decatur", "Norton", "Sheridan"], "Reno": ["Barber", "Barton", "Kiowa", "Pratt", "Stafford"], "Republic": ["Clay", "Cloud", "Mitchell", "Washington"], "Rice": ["Barton", "Ellsworth", "McPherson", "Reno"], "Riley": ["Geary", "Pottawatomie", "Wabaunsee"], "Rooks": ["Ellis", "Graham", "Norton", "Smith"], "Rush": ["Barber", "Barton", "Ellis", "Kiowa"], "Russell": ["Ellsworth", "Osborne", "Smith", "Saline"], "Saline": ["Cloud", "Dickinson", "Ellsworth", "McPherson", "Ottawa", "Riley"], "Scott": ["Finney", "Grant", "Lane", "Wichita"], "Sedgwick": ["Harvey", "Kingman", "Butler", "Marion", "Sumner"], "Seward": ["Finney", "Grant", "Haskell", "Gray", "Meade"], "Shawnee": ["Douglas", "Jackson", "Jefferson", "Pottawatomie"], "Sheridan": ["Decatur", "Gove", "Norton", "Rawlins"], "Sherman": ["Cheyenne", "Hitchcock", "Kit Carson"], "Smith": ["Jewell", "Norton", "Phillips", "Rooks"], "Stafford": ["Barber", "Ellis", "Kiowa", "Pawnee", "Pratt"], "Stanton": ["Kearny", "Meade", "Scott"], "Sumner": ["Barber", "Kingman", "Sedgwick", "Harper"], "Thomas": ["Sherman", "Wallace", "Logan"], "Trego": ["Gove", "Ellis", "Ness", "Rooks"], "Wabaunsee": ["Chase", "Geary", "Pottawatomie", "Riley", "Shawnee"], "Wallace": ["Sherman", "Logan", "Greeley"], "Washington": ["Marshall", "Nemaha", "Republic"], "Wilson": ["Chautauqua", "Elk", "Labette", "Montgomery"], "Woodson": ["Allen", "Bourbon", "Crawford", "Neosho"], "Wyandotte": ["Leavenworth", "Johnson", "Shawnee"] } # Step 3: Create a DataFrame for Population Data population_df = pd.DataFrame(list(county_population.items()), columns=["County", "Population"]) # Step 4: Create an Adjacency Matrix counties = list(county_population.keys()) adj_matrix = pd.DataFrame(np.zeros((len(counties), len(counties))), columns=counties, index=counties) # Populate the adjacency matrix based on adjacency_dict for county, neighbors in adjacency_dict.items(): for neighbor in neighbors: adj_matrix.at[county, neighbor] = 1 adj_matrix.at[neighbor, county] = 1 # Ensure the matrix is symmetric # Step 5: Output to CSV population_df.to_csv('county_population.csv', index=False) adj_matrix.to_csv('adjacency_matrix.csv') print("? CSV files 'county_population.csv' and 'adjacency_matrix.csv' saved successfully.")

KS/KS.ipynb

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'Johnson', 'Kearny', 'Kingman', 'Kiowa', 'Labette', 'Lane', 'Leavenworth', 'Lincoln', 'Linn', 'Logan', 'Lyon', 'McPherson', 'Marion', 'Marshall', 'Meade', 'Miami', 'Mitchell', 'Montgomery', 'Morris', 'Nemaha', 'Neosho', 'Ness', 'Osage', 'Osborne', 'Ottawa', 'Pawnee', 'Phillips', 'Pottawatomie', 'Pratt', 'Rawlins', 'Reno', 'Republic', 'Rice', 'Riley', 'Rooks', 'Rush', 'Russell', 'Saline', 'Scott', 'Sedgwick', 'Seward', 'Shawnee', 'Sheridan', 'Sherman', 'Smith', 'Stafford', 'Stanton', 'Sumner', 'Thomas', 'Trego', 'Wabaunsee', 'Wallace', 'Washington', 'Wilson', 'Woodson', 'Wyandotte']\n", "Requirement already satisfied: geopandas in /usr/local/lib/python3.11/dist-packages (1.0.1)\n", "Requirement already satisfied: matplotlib in /usr/local/lib/python3.11/dist-packages (3.10.0)\n", "Requirement already satisfied: numpy>=1.22 in /usr/local/lib/python3.11/dist-packages (from geopandas) (2.0.2)\n", "Requirement already satisfied: pyogrio>=0.7.2 in /usr/local/lib/python3.11/dist-packages (from geopandas) (0.10.0)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from geopandas) (24.2)\n", "Requirement already satisfied: pandas>=1.4.0 in /usr/local/lib/python3.11/dist-packages (from geopandas) (2.2.2)\n", "Requirement already satisfied: pyproj>=3.3.0 in /usr/local/lib/python3.11/dist-packages (from geopandas) (3.7.1)\n", "Requirement already satisfied: shapely>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from geopandas) (2.1.0)\n", "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.3.2)\n", "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (0.12.1)\n", "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (4.57.0)\n", "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.4.8)\n", "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (11.1.0)\n", "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (3.2.3)\n", "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (2.8.2)\n", "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.4.0->geopandas) (2025.2)\n", "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.4.0->geopandas) (2025.2)\n", "Requirement already satisfied: certifi in /usr/local/lib/python3.11/dist-packages (from pyogrio>=0.7.2->geopandas) (2025.1.31)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "<Figure size 1000x1000 with 2 Axes>" ], "image/png": 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\n" }, "metadata": {} } ], "source": [ "import pulp\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import geopandas as gpd\n", "\n", "import pandas as pd\n", "\n", "# --- Read county population data ---\n", "pop_df = pd.read_csv(\"county_population.csv\") # Assumes columns: \"County\", \"Population\"\n", "counties = pop_df[\"County\"].tolist()\n", "county_population = dict(zip(pop_df[\"County\"], pop_df[\"Population\"]))\n", "\n", "# --- Read adjacency matrix ---\n", "adjacency_df = pd.read_csv(\"adjacency_matrix.csv\", index_col=0)\n", "\n", "# Ensure the matrix is symmetric and labels match\n", "adjacency_df = adjacency_df.loc[counties, counties]\n", "\n", "# --- Build neighbors dictionary from adjacency matrix ---\n", "neighbors = {\n", " county: adjacency_df.columns[adjacency_df.loc[county] == 1].tolist()\n", " for county in counties\n", "}\n", "\n", "# --- ILP Solution ---\n", "pop_ideal = 763825\n", "\n", "# Number of districts\n", "num_districts = 4\n", "\n", "# Initialize the problem as a minimization problem\n", "prob = pulp.LpProblem(\"Minimize_Max_Deviation\", pulp.LpMinimize)\n", "\n", "# Decision variables X_ij\n", "X = pulp.LpVariable.dicts(\"X\", (range(len(counties)), range(num_districts)), 0, 1, pulp.LpBinary)\n", "\n", "# Total population per district (P_j)\n", "P = pulp.LpVariable.dicts(\"P\", range(num_districts), lowBound=0, cat='Continuous')\n", "\n", "# Absolute deviations D_j\n", "D = pulp.LpVariable.dicts(\"D\", range(num_districts), lowBound=0, cat='Continuous')\n", "\n", "# Maximum population deviation (D_max)\n", "D_max = pulp.LpVariable(\"D_max\", lowBound=0, cat='Continuous')\n", "\n", "# Objective: Minimize D_max\n", "prob += D_max, \"Minimize D_max\"\n", "\n", "# Constraints:\n", "\n", "# Ensure that each county is assigned to exactly one district\n", "for i in range(len(counties)):\n", " prob += pulp.lpSum([X[i][j] for j in range(num_districts)]) == 1, f\"County_Assignment_{i}\"\n", "\n", "# Ensure the total population of each district\n", "for j in range(2):\n", " prob += P[j] == pulp.lpSum([county_population[counties[i]] * X[i][j] for i in range(len(counties))]), f\"District_Population_{j}\"\n", "\n", "# Ensure the population deviation for each district\n", "for j in range(2):\n", " prob += P[j] - pop_ideal <= D[j], f\"Upper_Deviation_{j}\"\n", " prob += pop_ideal - P[j] <= D[j], f\"Lower_Deviation_{j}\"\n", " prob += D[j] <= D_max, f\"Deviation_Limit_{j}\"\n", "\n", "# Ensure adjacency constraints\n", "for i in range(len(counties)):\n", " for j in range(num_districts):\n", " prob += pulp.lpSum([adjacency_df.at[counties[i], counties[k]] * X[k][j] for k in range(len(counties))]) <=105*X[i][j], f\"Adjacency_Constraint_{i}_{j}\"\n", "\n", "# Solve the problem\n", "# Solve using CBC\n", "#prob.solve(pulp.PULP_CBC_CMD(msg=True))\n", "\n", "# Solve using GRUOBI\n", "prob.solve(pulp.GUROBI(msg=True)) # Gurobi solver\n", "\n", "prob.solve()\n", "\n", "# Extract the results\n", "district_assignment = {}\n", "for i in range(len(counties)):\n", " for j in range(num_districts):\n", " if pulp.value(X[i][j]) == 1:\n", " district_assignment[counties[i]] = j\n", "\n", "# Display the district assignments\n", "district_1 = [county for county, district in district_assignment.items() if district == 0]\n", "district_2 = [county for county, district in district_assignment.items() if district == 1]\n", "district_3 = [county for county, district in district_assignment.items() if district == 2]\n", "district_4 = [county for county, district in district_assignment.items() if district == 3]\n", "\n", "\n", "print(f\"District 1: {district_1}\")\n", "print(f\"District 2: {district_2}\")\n", "print(f\"District 3: {district_3}\")\n", "print(f\"District 4: {district_4}\")\n", "\n", "# Save to CSV\n", "assignment_df = pd.DataFrame(list(district_assignment.items()), columns=[\"County\", \"District\"])\n", "assignment_df.to_csv(\"district_assignment.csv\", index=False)\n", "\n", "\n", "!pip install geopandas matplotlib\n", "\n", "import geopandas as gpd\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "\n", "# Load West Virginia county shapefile\n", "# You can get a USA counties shapefile easily, for example from\n", "# https://www2.census.gov/geo/tiger/GENZ2022/shp/cb_2022_us_county_5m.zip\n", "\n", "# Suppose you downloaded and unzipped it, and have a shapefile like:\n", "# cb_2022_us_county_5m.shp\n", "\n", "# Load it:\n", "counties_gdf = gpd.read_file(\"/content/cb_2022_us_county_5m.shp\")\n", "\n", "# Filter only for West Virginia (STATEFP = '20')\n", "ks_counties = counties_gdf[counties_gdf['STATEFP'] == '20']\n", "\n", "# Load the district assignment\n", "districts = pd.read_csv('district_assignment.csv')\n", "\n", "# Merge by NAME\n", "merged = ks_counties.merge(districts, left_on='NAME', right_on='County')\n", "\n", "# Plot\n", "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n", "merged.plot(column='District', cmap='coolwarm', linewidth=0.8, edgecolor='black', ax=ax, legend=True)\n", "ax.set_title('Kansas Districting (4 districts)', fontsize=16)\n", "ax.axis('off')\n", "plt.show()\n", "\n", "\n" ] }, { "cell_type": "code", "source": [], "metadata": { "id": "e0acQd9fmolR" }, "execution_count": 35, "outputs": [] } ] }