GIS实验之制作城市联系强度图

一、问题描述

• 数据描述 ：给定某些城市之间的交互强度数据。
• 问题描述 ：基于这些数据制作空间交互地图。
• 形式和内容不限可以采用常规的 GIS 软件分析和实现；也可以使用编程的方式实现。

二、分析所给定的实验数据

• 2.1 将实验数据导入至文件地理数据库中
  

• 2.2 将联系强度数据转为表
  

• 2.3 分别打开属性表查看并初步分析数据

• 2.3.1 打开联系强度表分析
  

• 2.3.2 打开美国州、县面数据和州点数据

• 2.4. 将城市联系强度数据中的city_OD拆分为两列，并进一步分析数据
• 2.4.1 利用ArcGIS属性表中的字段计算器来完成拆分
  • 首先新建两个字段，分布为city_a和city_b，然后分布利用字段计算器利用VBA代码或者Python代码来完成拆分
  • VBA代码：city_a为【left( [city_OD] ,InStr( [city_OD] ,"-" )-1)】；city_b为【Mid( [city_OD] ,InStr( [city_OD] ,"-" )+1)】。
  • Python代码：city_a为【!city_OD!.split(’-’)[0]】；city_b为【!city_OD!.split(’-’)[1]】。

• 2.4.2 利用Excel实现拆分数据

• 2.4.3 利用Python中的pandas模块分析数据

城市联系强度表数据查看分析，结合了美国县(属性表数据导出–表转Excel)的数据进行匹配分析。

import pandas as pd
df = pd.read_excel('OD_dataa_new.xls')
# 查看前5行数据
df.head()

	OBJECTID	city_OD	city_a	city_b	intersect_value
0	1	New York-Los Angeles	New York	Los Angeles	6665
1	2	New York-Chicago	New York	Chicago	6725
2	3	New York-Houston	New York	Houston	1155
3	4	New York-Philadelphia	New York	Philadelphia	1695
4	5	New York-Phoenix	New York	Phoenix	625

# 获取city_a的唯一值
city_a = df['city_a'].unique()
city_a.sort()
print(city_a,len(city_a))

['Albuquerque' 'Anaheim' 'Arlington' 'Atlanta' 'Aurora' 'Austin'
 'Bakersfield' 'Baltimore' 'Baton Rouge' 'Boise' 'Boston' 'Buffalo'
 'Chandler' 'Charlotte' 'Chesapeake' 'Chicago' 'Chula Vista' 'Cincinnati'
 'Cleveland' 'Colorado Springs' 'Columbus' 'Corpus Christi' 'Dallas'
 'Denver' 'Detroit' 'Durham' 'El Paso' 'Fort Wayne' 'Fort Worth' 'Fremont'
 'Fresno' 'Garland' 'Gilbert' 'Glendale' 'Greensboro' 'Henderson'
 'Hialeah' 'Houston' 'Indianapolis' 'Irvine' 'Irving' 'Jacksonville'
 'Jersey City' 'Kansas City' 'Laredo' 'Las Vegas' 'Lexington' 'Lincoln'
 'Long Beach' 'Los Angeles' 'Louisville' 'Lubbock' 'Madison' 'Memphis'
 'Mesa' 'Miami' 'Milwaukee' 'Minneapolis' 'Nashville' 'New Orleans'
 'New York' 'Newark' 'Norfolk' 'North Las Vegas' 'Oakland' 'Oklahoma City'
 'Omaha' 'Orlando' 'Philadelphia' 'Phoenix' 'Pittsburgh' 'Plano'
 'Portland' 'Raleigh' 'Reno' 'Richmond' 'Riverside' 'Sacramento'
 'Saint Paul' 'San Antonio' 'San Bernardino' 'San Diego' 'San Francisco'
 'San Jose' 'Santa Ana' 'Scottsdale' 'Seattle' 'Spokane' 'St Louis'
 'St Petersburg' 'Stockton' 'Tampa' 'Toledo' 'Tucson' 'Tulsa'
 'Virginia Beach' 'Washington' 'Wichita' 'Winston Salem'] 99

# 获取city_a的唯一值
city_b = df['city_b'].unique()
city_b.sort()
print(b,len(city_b))

['Lake of the Woods', 'Ferry', 'Stevens', 'Okanogan', 'Pend Oreille', 'Boundary', 'Lincoln', 'Flathead', 'Glacier', 'Toole', 'Liberty', 'Hill', 'Sheridan', 'Divide', 'Burke', 'Renville', 'Bottineau', 'Rolette', 'Towner', 'Cavalier', 'Pembina', 'Kittson', 'Roseau', 'Blaine', 'Phillips', 'Valley', 'Daniels', 'Whatcom', 'Bonner', 'Ward', 'Koochiching', 'Skagit', 'Williams', 'McHenry', 'St. Louis', 'San Juan', 'Roosevelt', 'Mountrial', 'Marshall', 'Ramsey', 'Walsh', 'Beltrami', 'Pierce', 'Chelan', 'Pondera', 'Clallam', 'Benson', 'Chouteau', 'Snohomish', 'Island', 'Sanders', 'Lake', 'Nelson', 'Grand Forks', 'Polk', 'Pennington', 'Douglas', 'McKenzie', 'Jefferson', 'Richland', 'Teton', 'McCone', 'Shoshone', 'Spokane', 'Clearwater', 'Kootenai', 'Garfield', 'Red Lake', 'Grant', 'Lewis and Clark', 'Kitsap', 'Itasca', 'Wells', 'McLean', 'Eddy', 'Dunn', 'Fergus', 'Dawson', 'King', 'Cascade', 'Griggs', 'Steele', 'Traill', 'Mason', 'Missoula', 'Petroleum', 'Powell', 'Kittitas', 'Foster', 'Mercer', 'Grays Harbor', 'Norman', 'Mahnomen', 'Mineral', 'Cass', 'Aroostook', 'Judith Basin', 'Hubbard', 'Benewah', 'Wibaux', 'Golden Valley', 'Billings', 'Stutsman', 'Kidder', 'Burleigh', 'Oliver', 'Adams', 'Whitman', 'Barnes', 'Prairie', 'Becker', 'Clay', 'Thurston', 'Latah', 'Meagher', 'Yakima', 'Aitkin', 'Stark', 'Morton', 'Bayfield', 'Custer', 'Rosebud', 'Granite', 'Wadena', 'Crow Wing', 'Pacific', 'Lewis', 'Broadwater', 'Carlton', 'Musselshell', 'Wheatland', 'Franklin', 'Benton', 'Otter Tail', 'Fallon', 'Idaho', 'Ravalli', 'Ashland', 'Logan', 'Emmons', 'La Moure', 'Slope', 'Hettinger', 'Ransom', 'Wilkin', 'Nez Perce', 'Columbia', 'Walla Walla', 'Iron', 'Somerset', 'Piscataquis', 'Yellowstone', 'Treasure', 'Asotin', 'Sioux', 'Pine', 'Penobscot', 'Skamania', 'Cowlitz', 'Wahkiakum', 'Todd', 'Morrison', 'McIntosh', 'Dickey', 'Sargent', 'Bowman', 'Deer Lodge', 'Mille Lacs', 'Clatsop', 'Sweet Grass', 'Gallatin', 'Park', 'Silver Bow', 'Washburn', 'Sawyer', 'Burnett', 'Kanabec', 'Carter', 'Stillwater', 'Clark', 'Klickitat', 'Big Horn', 'Traverse', 'Umatilla', 'Wallowa', 'Price', 'Campbell', 'Harding', 'McPherson', 'Perkins', 'Corson', 'Brown', 'Beaverhead', 'Roberts', 'Morrow', 'Union', 'Madison', 'Gilliam', 'Powder River', 'Stearns', 'Tillamook', 'Washington', 'Pope', 'Isanti', 'Chisago', 'Sherman', 'Multnomah', 'Hood River', 'Wasco', 'Lemhi', 'Barron', 'Rusk', 'Carbon', 'Walworth', 'Edmunds', 'Day', 'Big Stone', 'Sherburne', 'Ziebach', 'Dewey', 'Clackamas', 'Wright', 'Yamhill', 'Anoka', 'Kandiyohi', 'Swift', 'Taylor', 'Oxford', 'Meeker', 'Coos', 'Chippewa', 'Marion', 'Lac Qui Parle', 'Potter', 'Faulk', 'Hennepin', 'Spink', 'St. Croix', 'Butte', 'Codington', 'Yellowstone National Park (Part)', 'Baker', 'Wheeler', 'Meade', 'Essex', 'Grand Isle', 'Orleans', 'Clinton', 'Crook', 'McLeod', 'Carver', 'Deuel', 'Dakota', 'Yellow Medicine', 'Sully', 'Hyde', 'Hand', 'Eau Claire', 'Scott', 'Hamlin', 'Lamoille', 'Linn', 'Stanley', 'Caledonia', 'Waldo', 'Haakon', 'Fremont', 'Sibley', 'Chittenden', 'Kennebec', 'Goodhue', 'Redwood', 'Wood', 'Pepin', 'Beadle', 'Lyon', 'Lawrence', 'Buffalo', 'Trempealeau', 'Jackson', 'Johnson', 'Hughes', 'Le Sueur', 'Rice', 'Kingsbury', 'Brookings', 'Gem', 'Androscoggin', 'Nicollet', 'Wabasha', 'Malheur', 'Hancock', 'Grafton', 'Deschutes', 'Knox', 'Boise', 'Addison', 'Carroll', 'Lane', 'Blue Earth', 'Juneau', 'Lyman', 'Orange', 'Waseca', 'Jerauld', 'Moody', 'Pipestone', 'Dodge', 'Sanborn', 'Murray', 'Cottonwood', 'Olmsted', 'Miner', 'Winona', 'Weston', 'Jones', 'Cumberland', 'Washakie', 'Monroe', 'Payette', 'Hamilton', 'Watonwan', 'Herkimer', 'La Crosse', 'Elmore', 'Hot Springs', 'Harney', 'Sagadahoc', 'Windsor', 'Aurora', 'Brule', 'Canyon', 'Mellette', 'Camas', 'Rutland', 'Faribault', 'Minnehaha', 'Rock', 'Freeborn', 'Nobles', 'Martin', 'Houston', 'Mower', 'Fillmore', 'Davison', 'Hanson', 'McCook', 'York', 'Ada', 'Warren', 'Tripp', 'Belknap', 'Vernon', 'Shannon', 'Owyhee', 'Bonneville', 'Bingham', 'Klamath', 'Merrimack', 'Sullivan', 'Strafford', 'Natrona', 'Gregory', 'Niobrara', 'Charles Mix', 'Turner', 'Worth', 'Mitchell', 'Allamakee', 'Winnebago', 'Winneshiek', 'Converse', 'Osceola', 'Dickinson', 'Kossuth', 'Howard', 'Emmet', 'Hutchinson', 'Fall River', 'Sublette', 'Crawford', 'Saratoga', 'Bennett', 'Bennington', 'Fulton', 'Rockingham', 'Windham', "O'Brien", 'Cerro Gordo', 'Palo Alto', 'Floyd', 'Chickasaw', 'Iowa', 'Hillsborough', 'Gooding', 'Minidoka', 'Cheshire', 'Yankton', 'Bon Homme', 'Power', 'Fayette', 'Clayton', 'Montgomery', 'Caribou', 'Bannock', 'Dawes', 'Keya Paha', 'Boyd', 'Cherry', 'Curry', 'Rensselaer', 'Schenectady', 'Plymouth', 'Cherokee', 'Bremer', 'Butler', 'Buena Vista', 'Twin Falls', 'Pocahontas', 'Humboldt', 'Otsego', 'Holt', 'Cedar', 'Jerome', 'Schoharie', 'Lafayette', 'Albany', 'Josephine', 'Dixon', 'Berkshire', 'Middlesex', 'Worcester', 'Dubuque', 'Cassia', 'Webster', 'Delaware', 'Buchanan', 'Black Hawk', 'Goshen', 'Platte', 'Bear Lake', 'Woodbury', 'Ida', 'Sac', 'Calhoun', 'Hampshire', 'Hardin', 'Grundy', 'Jo Daviess', 'Oneida', 'Greene', 'Suffolk', 'Box Butte', 'Antelope', 'Wayne', 'Hampden', 'Tama', 'Sweetwater', 'Norfolk', 'Monona', 'Boone', 'Story', 'Ulster', 'Cuming', 'Bristol', 'Stanton', 'Loup', 'Hooker', 'Thomas', 'Dutchess', 'Barnstable', 'Burt', 'Litchfield', 'Hartford', 'Tolland', 'Providence', 'Cache', 'Siskiyou', 'Garden', 'Box Elder', 'Rich', 'Scotts Bluff', 'Morrill', 'Del Norte', 'Elko', 'Modoc', 'Washoe', 'Jasper', 'Poweshiek', 'Harrison', 'Guthrie', 'Shelby', 'Audubon', 'Dallas', 'Rock Island', 'Kent', 'Colfax', 'Arthur', 'Greeley', 'Will', 'Lucas', 'Kendall', 'Porter', 'Geauga', 'New London', 'Banner', 'Newport', 'Fairfield', 'Laramie', 'Wyoming', 'New Haven', 'Lackawanna', 'La Salle', 'Elk', 'Cuyahoga', 'Venango', 'Forest', 'Ottawa', 'Cameron', 'Pike', 'Lycoming', 'Muscatine', 'Bureau', 'Henry', 'Uinta', 'Noble', 'De Kalb', 'Putnam', 'Nance', 'Lorain', 'Mahaska', 'Pottawattamie', 'Keokuk', 'Adair', 'Sandusky', 'Trumbull', 'Dukes', 'Saunders', 'Erie', 'Kosciusko', 'Starke', 'Clarion', 'Cheyenne', 'Defiance', 'Weber', 'Louisa', 'Luzerne', 'Merrick', 'Nantucket', 'Keith', 'Kimball', 'Morgan', 'Trinity', 'Westchester', 'Sussex', 'Summit', 'Portage', 'Rockland', 'Kankakee', 'Whitley', 'Huron', 'Allen', 'Medina', 'Centre', 'Clearfield', 'Seneca', 'Paulding', 'Newton', 'Passaic', 'Sarpy', 'Shasta', 'Lassen', 'Northumberland', 'Armstrong', 'Pulaski', 'Montour', 'Mills', 'Clarke', 'Wapello', 'Davis', 'Mahoning', 'Bergen', 'Livingston', 'Tooele', 'Morris', 'Des Moines', 'Henderson', 'Wabash', 'Seward', 'Lancaster', 'Hall', 'Huntington', 'Iroquois', 'Miami', 'Ford', 'Moffat', 'Weld', 'Sedgwick', 'Routt', 'Larimer', 'Daggett', 'Lander', 'Eureka', 'Van Wert', 'Wyandot', 'Peoria', 'Northampton', 'Pershing', 'Schuylkill', 'Woodford', 'Columbiana', 'Bronx', 'White', 'Salt Lake', 'Indiana', 'Page', 'Ringgold', 'Nassau', 'Van Buren', 'Decatur', 'Appanoose', 'Snyder', 'New York', 'Uintah', 'Beaver', 'Mifflin', 'Duchesne', 'Hudson', 'Lee', 'Queens', 'Otoe', 'Lehigh', 'Hunterdon', 'Tazewell', 'Blair', 'Huntingdon', 'Kings', 'Cambria', 'Saline', 'Juniata', 'Hayes', 'Chase', 'Frontier', 'Gosper', 'Auglaize', 'Kearney', 'Wasatch', 'Phelps', 'Berks', 'Westmoreland', 'Allegheny', 'Holmes', 'Dauphin', 'Tuscarawas', 'Richmond', 'McDonough', 'Perry', 'Bucks', 'Scotland', 'Schuyler', 'Blackford', 'Atchison', 'Jay', 'Utah', 'Nodaway', 'Tippecanoe', 'Nemaha', 'Lebanon', 'Gage', 'Vermilion', 'Grand', 'Coshocton', 'Tehama', 'Monmouth', 'Plumas', 'Yuma', 'Tipton', 'Champaign', 'Brooke', 'Gentry', 'Fountain', 'Darke', 'Thayer', 'Dundy', 'Nuckolls', 'Hitchcock', 'Harlan', 'Furnas', 'Red Willow', 'Bedford', 'Randolph', 'Piatt', 'De Witt', 'Licking', 'Richardson', 'Pawnee', 'Boulder', 'Chester', 'Rio Blanco', 'Guernsey', 'Ohio', 'Burlington', 'Vermillion', 'Menard', 'Belmont', 'Ocean', 'Muskingum', 'Daviess', 'Philadelphia', 'Andrew', 'White Pine', 'Macon', 'Juab', 'Churchill', 'Norton', 'Rawlins', 'Republic', 'Doniphan', 'Mendocino', 'Smith', 'Jewell', 'Camden', 'Sangamon', 'Parke', 'Hendricks', 'Gilpin', 'Preble', 'Eagle', 'Edgar', 'Gloucester', 'Clear Creek', 'New Castle', 'Christian', 'Sanpete', 'Pickaway', 'Denver', 'Glenn', 'Moultrie', 'Rush', 'Caldwell', 'Salem', 'Sierra', 'Arapahoe', 'Atlantic', 'Allegany', 'Cecil', 'Garrett', 'Harford', 'Monongalia', 'Preston', 'Baltimore', 'Wetzel', 'Frederick', 'Chariton', 'Emery', 'Coles', 'Ralls', 'Hocking', 'Cloud', 'Yuba', 'Storey', 'Berkeley', 'Vigo', 'Tyler', 'Kit Carson', 'Elbert', 'Riley', 'Rooks', 'Osborne', 'Pottawatomie', 'Graham', 'Athens', 'Millard', 'Macoupin', 'Ray', 'Nevada', 'Ross', 'Pleasants', 'Owen', 'Doddridge', 'Colusa', 'Leavenworth', 'Ritchie', 'Vinton', 'Highland', 'Baltimore City', 'Mesa', 'Pitkin', 'Audrain', 'Bartholomew', 'Cape May', 'Loudoun', 'Dearborn', 'Placer', 'Ripley', 'Sutter', 'Barbour', 'Queen Annes', 'Tucker', 'Clermont', 'Carson City', 'Jersey', 'Gunnison', 'Hardy', 'Anne Arundel', 'Geary', 'Shawnee', 'Effingham', 'Delta', 'Wabaunsee', 'Winchester', 'Meigs', 'Wyandotte', 'Jennings', 'Wirt', 'Nye', 'Caroline', 'Trego', 'Ellis', 'Gove', 'Prince Georges', 'Wallace', 'Russell', 'El Paso', 'Teller', 'Upshur', 'Gilmer', 'Shenandoah', 'Kenton', 'Callaway', 'El Dorado', 'Fairfax', 'Cooper', 'Chaffee', 'Sevier', 'Gallia', 'Bond', 'Scioto', 'Fauquier', 'St. Charles', 'Pendleton', 'Talbot', 'Roane', 'Pettis', 'Prince William', 'Arlington', 'Switzerland', 'Yolo', 'Alpine', 'Moniteau', 'Braxton', 'Falls Chruch', 'Fairfax City', 'Osage', 'Ellsworth', 'Rappahannock', 'Napa', 'Sonoma', 'Alexandria', 'Bracken', 'St. Louis City', 'Manassas Park City', 'Manassas City', 'Calvert', 'Greenup', 'Trimble', 'Sacramento', 'Cole', 'Gasconade', 'Charles', 'Mono', 'Dorchester', 'Culpeper', 'Amador', 'Wichita', 'Ness', 'Barton', 'Montrose', 'St. Clair', 'Kanawha', 'Kiowa', 'Robertson', 'Stafford', 'Cabell', 'Edwards', 'Nicholas', 'Wicomico', 'Oldham', 'Fleming', 'Gibson', 'Dubois', 'Pueblo', 'Crowley', 'St. Marys', 'Piute', 'Calaveras', 'Augusta', 'Bates', 'Harrisonburg', 'Saguache', 'Esmeralda', 'Tuolumne', 'Coffey', 'Miller', 'Rowan', 'Anderson', 'Spotsylvania', 'King George', 'Bourbon', 'Ouray', 'Marin', 'Fredericksburg', 'Bath', 'San Joaquin', 'Maries', 'Albemarle', 'Elliott', 'Greenbrier', 'Prowers', 'Bent', 'Kearny', 'Otero', 'Finney', 'Hodgeman', 'Warrick', 'Posey', 'Spencer', 'Staunton', 'Vanderburgh', 'Harvey', 'Reno', 'Greenwood', 'Solano', 'San Miguel', 'Hinsdale', 'Ste. Genevieve', 'Bullitt', 'Contra Costa', 'Waynesboro', 'Rockbridge', 'St. Francois', 'Stanislaus', 'Hickory', 'Charlottesville', 'Menifee', 'Breckinridge', 'Woodson', 'Accomack', 'Hanover', 'Fluvanna', 'Huerfano', 'Jessamine', 'Gray', 'Raleigh', 'Mingo', 'King and Queen', 'Alleghany', 'King William', 'Goochland', 'Dolores', 'Alameda', 'Mariposa', 'Magoffin', 'Laclede', 'Williamson', 'Summers', 'Wolfe', 'Clifton Forge', 'Estill', 'Rio Grande', 'Garrard', 'Pratt', 'Amherst', 'San Francisco', 'Covington', 'Las Animas', 'Lexington', 'Botetourt', 'Buckingham', 'Dent', 'Madera', 'Alamosa', 'Haskell', 'Larue', 'Wilson', 'Neosho', 'Kingman', 'Boyle', 'Henrico', 'San Mateo', 'Breathitt', 'Powhatan', 'Craig', 'Baca', 'Costilla', 'Montezuma', 'La Plata', 'New Kent', 'Merced', 'Grayson', 'Richmond City', 'Texas', 'Reynolds', 'Bollinger', 'Cape Girardeau', 'Dade', 'Fresno', 'Hopkins', 'Chesterfield', 'Appomattox', 'Casey', 'McDowell', 'Crittenden', 'Kane', 'Owsley', 'Rockcastle', 'Knott', 'Mathews', 'Amelia', 'Charles City', 'Santa Clara', 'Giles', 'Sumner', 'Cowley', 'Lynchburg', 'Green', 'Barber', 'James City', 'Inyo', 'Hart', 'Archuleta', 'Muhlenberg', 'Roanoke', 'Prince Edward', 'Conejos', 'Harper', 'Labette', 'Comanche', 'Bedford City', 'Massac', 'Alexander', 'Edmonson', 'Laurel', 'Prince George', 'Roanoke City', 'Hopewell', 'Leslie', 'Bland', 'Dickenson', 'Chautauqua', 'Nottoway', 'Colonial Heights', 'Williamsburg', 'Santa Cruz', 'Dinwiddie', 'Letcher', 'Charlotte', 'Surry', 'Petersburg', 'Newport News', 'Ballard', 'McCracken', 'Wise', 'Metcalfe', 'Poquoson City', 'Barren', 'Radford', 'Isle of Wight', 'Pittsylvania', 'Stoddard', 'Lunenburg', 'Hampton', 'Mississippi', 'Wythe', 'Howell', 'Halifax', 'Brunswick', 'Smyth', 'Trigg', 'Navajo', 'Coconino', 'Nowata', 'Kay', 'Rio Arriba', 'Alfalfa', 'Cimarron', 'Woods', 'Mohave', 'Southampton', 'Apache', 'Taos', 'Stone', 'San Benito', 'Carlisle', 'McCreary', 'Bell', 'Graves', 'Virginia Beach', 'Barry', 'Monterey', 'Greensville', 'Mecklenburg', 'Simpson', 'Oregon', 'Patrick', 'New Madrid', 'Chesapeake', 'Portsmouth', 'Taney', 'Woodward', 'Ozark', 'Hickman', 'McDonald', 'Calloway', 'Tulare', 'Emporia', 'Martinsville', 'South Boston', 'Galax', 'Franklin City', 'Stewart', 'Danville', 'Dunklin', 'Pickett', 'Rogers', 'Claiborne', 'Hawkins', 'Ashe', 'Fentress', 'Currituck', 'Hertford', 'Gates', 'Stokes', 'Caswell', 'Granville', 'Person', 'Vance', 'Overton', 'Mayes', 'Major', 'Pasquotank', 'Obion', 'Weakley', 'Trousdale', 'Lipscomb', 'Dallam', 'Hansford', 'Baxter', 'Sharp', 'Ochiltree', 'Cheatham', 'Tulsa', 'Wilkes', 'Pemiscot', 'Grainger', 'Davidson', 'Watauga', 'Perquimans', 'Hamblen', 'Chowan', 'Dickson', 'Avery', 'Yadkin', 'Mora', 'Izard', 'Unicoi', 'Forsyth', 'Payne', 'Humphreys', 'Guilford', 'Alamance', 'Bertie', 'Durham', 'Sandoval', 'Dyer', 'Nash', 'Cocke', 'Creek', 'Kingfisher', 'Wagoner', 'Edgecombe', 'Searcy', 'Rutherford', 'Yancey', 'Wake', 'Hemphill', 'Hartley', 'Moore', 'Iredell', 'Davie', 'Roger Mills', 'Santa Fe', 'McKinley', 'Crockett', 'Craighead', 'Los Alamos', 'Cannon', 'Tyrrell', 'Lauderdale', 'Independence', 'Loudon', 'Blount', 'Chatham', 'Muskogee', 'Okmulgee', 'Maury', 'Rhea', 'Pitt', 'Catawba', 'Haywood', 'Buncombe', 'Johnston', 'Kern', 'San Bernardino', 'San Luis Obispo', 'Bledsoe', 'Dare', 'Quay', 'Beaufort', 'Canadian', 'Oklahoma', 'Cleburne', 'Coffee', 'Poinsett', 'Swain', 'McMinn', 'Okfuskee', 'Sequoyah', 'Carson', 'Harnett', 'Sequatchie', 'Cleveland', 'Caddo', 'Yavapai', 'Cabarrus', 'Beckham', 'Stanly', 'Washita', 'Conway', 'Seminole', 'Sebastian', 'Cross', 'Woodruff', 'Hardeman', 'Lenoir', 'Transylvania', 'Gaston', 'Le Flore', 'McNairy', 'Grady', 'Faulkner', 'Bradley', 'Cibola', 'McClain', 'Sampson', 'Pittsburg', 'Pamlico', 'Yell', 'Bernalillo', 'Guadalupe', 'Greenville', 'Anson', 'Hoke', 'Spartanburg', 'Duplin', 'Randall', 'Collingsworth', 'Donley', 'Deaf Smith', 'St. Francis', 'Greer', 'Pickens', 'Lonoke', 'Latimer', 'Craven', 'Oconee', 'Torrance', 'Harmon', 'Limestone', 'Alcorn', 'Tishomingo', 'Tippah', 'De Soto', 'Rabun', 'Whitfield', 'Catoosa', 'Walker', 'Towns', 'Fannin', 'Onslow', 'Pontotoc', 'Valencia', 'Robeson', 'Colbert', 'Ventura', 'Tunica', 'Carteret', 'Garvin', 'Bladen', 'Habersham', 'Marlboro', 'Tate', 'Laurens', 'Garland', 'De Baca', 'Coal', 'Prentiss', 'Parmer', 'Castro', 'Swisher', 'Briscoe', 'Childress', 'Pender', 'Lumpkin', 'Pushmataha', 'Atoka', 'Stephens', 'Tillman', 'Gordon', 'Dillon', 'Kershaw', 'Catron', 'Chattooga', 'Socorro', 'Arkansas', 'Panola', 'Coahoma', 'Darlington', 'Newberry', 'Gila', 'Quitman', 'Hot Spring', 'McCurtain', 'Cotton', 'Banks', 'Abbeville', 'Columbus', 'Itawamba', 'Wilbarger', 'Bartow', 'New Hanover', 'La Paz', 'Motley', 'Cullman', 'Cottle', 'Winston', 'Hale', 'Lamb', 'Bailey', 'Florence', 'Horry', 'Foard', 'Etowah', 'Yalobusha', 'Saluda', 'Gwinnett', 'Tallahatchie', 'Bryan', 'Choctaw', 'Sumter', 'Barrow', 'Desha', 'Bolivar', 'Cobb', 'Chaves', 'Riverside', 'McCormick', 'Love', 'Lamar', 'Oglethorpe', 'Maricopa', 'Santa Barbara', 'Hempstead', 'Sunflower', 'Montague', 'Edgefield', 'Red River', 'Cooke', 'Little River', 'Clarendon', 'Walton', 'Haralson', 'Grenada', 'Aiken', 'Dickens', 'Crosby', 'Lubbock', 'Archer', 'Hockley', 'Baylor', 'Cochran', 'Ouachita', 'Leflore', 'Drew', 'Rockdale', 'Greenlee', 'Georgetown', 'Lowndes', 'Taliaferro', 'Orangeburg', 'Bowie', 'Talladega', 'McDuffie', 'Tuscaloosa', 'Oktibbeha', 'Lea', 'Chicot', 'Coweta', 'San Diego', 'Barnwell', 'Los Angeles', 'Pinal', 'Jack', 'Butts', 'Imperial', 'Denton', 'Bamberg', 'Heard', 'Hunt', 'Collin', 'Ashley', 'Titus', 'Throckmorton', 'Young', 'Stonewall', 'Garza', 'Lynn', 'Terry', 'Yoakum', 'Spalding', 'Glascock', 'Attala', 'Noxubee', 'Bibb', 'Meriwether', 'Troup', 'Baldwin', 'Colleton', 'Allendale', 'Chambers', 'Tallapoosa', 'Coosa', 'Sharkey', 'Camp', 'Chilton', 'Dona Ana', 'Screven', 'Yazoo', 'Charleston', 'Bossier', 'Issaquena', 'Morehouse', 'West Carroll', 'East Carroll', 'Wilkinson', 'Palo Pinto', 'Upson', 'Parker', 'Tarrant', 'Rockwall', 'Rains', 'Shackelford', 'Fisher', 'Scurry', 'Borden', 'Gaines', 'Jenkins', 'Neshoba', 'Leake', 'Kemper', 'Twiggs', 'Harris', 'Kaufman', 'Van Zandt', 'Emanuel', 'Hidalgo', 'Autauga', 'Peach', 'Gregg', 'Bulloch', 'Luna', 'Muscogee', 'Rankin', 'Bienville', 'Bleckley', 'Hinds', 'Hood', 'Candler', 'Marengo', 'Chattahoochee', 'Pima', 'Eastland', 'Callahan', 'Andrews', 'Nolan', 'Erath', 'Treutlen', 'Cochise', 'Schley', 'Toombs', 'Navarro', 'Somervell', 'Bullock', 'Tattnall', 'Dooly', 'Wilcox', 'Evans', 'Tensas', 'Bosque', 'Winn', 'Natchitoches', 'Telfair', 'Sterling', 'Glasscock', 'Midland', 'Coke', 'Winkler', 'Ector', 'Runnels', 'Coleman', 'Crenshaw', 'Copiah', 'Crisp', 'Freestone', 'Long', 'Culberson', 'Reeves', 'Loving', 'Hudspeth', 'Catahoula', 'Jeff Davis', 'Appling', 'Terrell', 'McLennan', 'Nacogdoches', 'Sabine', 'Ben Hill', 'Jefferson Davis', 'Irwin', 'Concordia', 'Conecuh', 'Coryell', 'Bacon', 'Tom Green', 'Dougherty', 'San Augustine', 'Crane', 'Upton', 'Reagan', 'Leon', 'Dale', 'Tift', 'Concho', 'Irion', 'Angelina', 'Falls', 'Early', 'Rapides', 'McCulloch', 'San Saba', 'Berrien', 'Ware', 'Lampasas', 'Glynn', 'Forrest', 'Atkinson', 'Pecos', 'Brantley', 'Amite', 'Walthall', 'Cook', 'Avoyelles', 'Colquitt', 'Escambia', 'Geneva', 'Lanier', 'Clinch', 'Mobile', 'Milam', 'Schleicher', 'Brooks', 'Charlton', 'Burnet', 'Pointe Coupee', 'Pearl River', 'Tangipahoa', 'St. Helena', 'East Feliciana', 'George', 'West Feliciana', 'Evangeline', 'Brazos', 'Llano', 'San Jacinto', 'Beauregard', 'Grimes', 'Echols', 'St. Landry', 'Burleson', 'East Baton Rouge', 'Kimble', 'Gadsden', 'St. Tammany', 'Sutton', 'Brewster', 'West Baton Rouge', 'Presidio', 'Travis', 'Duval', 'Bay', 'Gillespie', 'Blanco', 'St. Martin', 'Iberville', 'Calcasieu', 'Acadia', 'Suwannee', 'Bastrop', 'Okaloosa', 'Santa Rosa', 'Ascension', 'Hays', 'St. John the Baptist', 'Wakulla', 'Val Verde', 'Kerr', 'Waller', 'St. Johns', 'Gulf', 'St. James', 'Bradford', 'Austin', 'Real', 'Assumption', 'St. Bernard', 'Comal', 'Colorado', 'St. Mary', 'Alachua', 'Gilchrist', 'LaFourche', 'Bandera', 'Plaquemines', 'Dixie', 'Fort Bend', 'Gonzales', 'Bexar', 'Flagler', 'Iberia', 'Lavaca', 'Wharton', 'Uvalde', 'Kinney', 'Brazoria', 'Levy', 'Galveston', 'Volusia', 'Terrebonne', 'Atascosa', 'Matagorda', 'Karnes', 'Victoria', 'Zavala', 'Frio', 'Maverick', 'Citrus', 'Goliad', 'Live Oak', 'Bee', 'Hernando', 'McMullen', 'Dimmit', 'Brevard', 'Refugio', 'Pasco', 'Webb', 'Pinellas', 'San Patricio', 'Aransas', 'Jim Wells', 'Indian River', 'Nueces', 'Hardee', 'Highlands', 'Manatee', 'Okeechobee', 'Kleberg', 'St. Lucie', 'Sarasota', 'Jim Hogg', 'Zapata', 'Glades', 'Kenedy', 'Palm Beach', 'Hendry', 'Starr', 'Willacy', 'Collier', 'Broward', 'Keweenaw', 'Houghton', 'Ontonagon', 'Baraga', 'Marquette', 'Gogebic', 'Luce', 'Alger', 'Schoolcraft', 'Vilas', 'Mackinac', 'Menominee', 'Marinette', 'Cheboygan', 'Presque Isle', 'Langlade', 'Oconto', 'Charlevoix', 'Door', 'Alpena', 'Antrim', 'Montmorency', 'Leelanau', 'Marathon', 'Shawano', 'St. Lawrence', 'Kalkaska', 'Alcona', 'Grand Traverse', 'Oscoda', 'Benzie', 'Kewaunee', 'Waupaca', 'Outagamie', 'Manistee', 'Iosco', 'Wexford', 'Missaukee', 'Roscommon', 'Ogemaw', 'Manitowoc', 'Waushara', 'Calumet', 'Arenac', 'Clare', 'Gladwin', 'Green Lake', 'Fond Du Lac', 'Sheboygan', 'Oceana', 'Isabella', 'Newaygo', 'Mecosta', 'Tuscola', 'Oswego', 'Sanilac', 'Sauk', 'Saginaw', 'Ozaukee', 'Muskegon', 'Montcalm', 'Gratiot', 'Cayuga', 'Niagara', 'Lapeer', 'Dane', 'Onondaga', 'Genesee', 'Waukesha', 'Milwaukee', 'Shiawassee', 'Ionia', 'Ontario', 'Macomb', 'Oakland', 'Racine', 'Cortland', 'Ingham', 'Allegan', 'Eaton', 'Yates', 'Chenango', 'Kenosha', 'Tompkins', 'Steuben', 'Cattaraugus', 'Stephenson', 'Washtenaw', 'Kalamazoo', 'Broome', 'Tioga', 'Chemung', 'Ogle', 'Lenawee', 'Hillsdale', 'Branch', 'St. Joseph', 'Susquehanna', 'McKean', 'Du Page', 'Ashtabula', 'Whiteside', 'La Porte', 'Elkhart', 'Lagrange', 'North Slope', 'Northwest Arctic', 'Fairbanks North Star', 'Bristol Bay', 'Yukon-Koyukuk', 'Southeast Fairbanks', 'Nome', 'Matanuska-Susitna', 'Wade Hampton', 'Bethel', 'Anchorage', 'Kenai Peninsula', 'Dillingham', 'Lake and Peninsula', 'Valdez-Cordova', 'Haines', 'Kodiak Island', 'Skagway-Yakutat-Angoon', 'Sitka', 'Wrangell-Petersburg', 'Ketchikan Gateway', 'Prince of Wales-Outer Ketchikan', 'Aleutians East', 'Aleutians West', 'Kalawao', 'Kauai', 'Honolulu', 'Maui', 'Hawaii'] 99

• 美国县数据查看分析

import pandas as pd
dfx = pd.read_excel('美国县.xls')
# 查看前5行数据
dfx.head()

	OBJECTID_1	OBJECTID	NAME	STATE_NAME	STATE_FIPS	CNTY_FIPS	FIPS	AREA	POP1990	POP2000	POP90_SQMI	Shape_Leng	Shape_Length	Shape_Area
0	1	1	Lake of the Woods	Minnesota	27	77	27077	1784.0634	4076	4651	2	375147.267550	375147.267353	4.620986e+09
1	2	2	Ferry	Washington	53	19	53019	2280.2319	6295	7199	3	372231.202858	372231.202772	5.905464e+09
2	3	3	Stevens	Washington	53	65	53065	2529.9794	30948	40652	12	462471.138865	462471.138943	6.552176e+09
3	4	4	Okanogan	Washington	53	47	53047	5306.1800	33350	38640	6	581636.386735	581636.386959	1.373762e+10
4	5	5	Pend Oreille	Washington	53	51	53051	1445.0286	8915	11752	6	307729.184493	307729.184524	3.742470e+09

# 提取美国县的所有名称
c = dfx['NAME'].unique()
c = c.tolist()
c.sort()
print(c[:100],len(c))

['Abbeville', 'Acadia', 'Accomack', 'Ada', 'Adair', 'Adams', 'Addison', 'Aiken', 'Aitkin', 'Alachua', 'Alamance', 'Alameda', 'Alamosa', 'Albany', 'Albemarle', 'Alcona', 'Alcorn', 'Aleutians East', 'Aleutians West', 'Alexander', 'Alexandria', 'Alfalfa', 'Alger', 'Allamakee', 'Allegan', 'Allegany', 'Alleghany', 'Allegheny', 'Allen', 'Allendale', 'Alpena', 'Alpine', 'Amador', 'Amelia', 'Amherst', 'Amite', 'Anchorage', 'Anderson', 'Andrew', 'Andrews', 'Androscoggin', 'Angelina', 'Anne Arundel', 'Anoka', 'Anson', 'Antelope', 'Antrim', 'Apache', 'Appanoose', 'Appling', 'Appomattox', 'Aransas', 'Arapahoe', 'Archer', 'Archuleta', 'Arenac', 'Arkansas', 'Arlington', 'Armstrong', 'Aroostook', 'Arthur', 'Ascension', 'Ashe', 'Ashland', 'Ashley', 'Ashtabula', 'Asotin', 'Assumption', 'Atascosa', 'Atchison', 'Athens', 'Atkinson', 'Atlantic', 'Atoka', 'Attala', 'Audrain', 'Audubon', 'Auglaize', 'Augusta', 'Aurora', 'Austin', 'Autauga', 'Avery', 'Avoyelles', 'Baca', 'Bacon', 'Bailey', 'Baker', 'Baldwin', 'Ballard', 'Baltimore', 'Baltimore City', 'Bamberg', 'Bandera', 'Banks', 'Banner', 'Bannock', 'Baraga', 'Barber', 'Barbour'] 1833

# 提取美国州的所有名称
d = dfx['STATE_NAME'].unique()
d = d.tolist()
d.sort()
print(d,len(d))

['Alabama', 'Alaska', 'Arizona', 'Arkansas', 'California', 'Colorado', 'Connecticut', 'Delaware', 'District of Columbia', 'Florida', 'Georgia', 'Hawaii', 'Idaho', 'Illinois', 'Indiana', 'Iowa', 'Kansas', 'Kentucky', 'Louisiana', 'Maine', 'Maryland', 'Massachusetts', 'Michigan', 'Minnesota', 'Mississippi', 'Missouri', 'Montana', 'Nebraska', 'Nevada', 'New Hampshire', 'New Jersey', 'New Mexico', 'New York', 'North Carolina', 'North Dakota', 'Ohio', 'Oklahoma', 'Oregon', 'Pennsylvania', 'Rhode Island', 'South Carolina', 'South Dakota', 'Tennessee', 'Texas', 'Utah', 'Vermont', 'Virginia', 'Washington', 'West Virginia', 'Wisconsin', 'Wyoming'] 51

• 查看city_a与美国县、州名的匹配情况

count = 0
p_name = []
for i in city_a:
    if i in c:
        p_name.append(i)
        count += 1
print('一共匹配%d个县'%count)
print('匹配的县名为：',p_name)

一共匹配44个县
匹配的县名为： ['Arlington', 'Aurora', 'Austin', 'Baltimore', 'Boise', 'Buffalo', 'Charlotte', 'Chesapeake', 'Cleveland', 'Columbus', 'Dallas', 'Denver', 'Durham', 'El Paso', 'Fremont', 'Fresno', 'Garland', 'Henderson', 'Houston', 'Lexington', 'Lincoln', 'Los Angeles', 'Lubbock', 'Madison', 'Mesa', 'Miami', 'Milwaukee', 'New York', 'Norfolk', 'Oakland', 'Philadelphia', 'Raleigh', 'Reno', 'Richmond', 'Riverside', 'Sacramento', 'San Bernardino', 'San Diego', 'San Francisco', 'Spokane', 'Tulsa', 'Virginia Beach', 'Washington', 'Wichita']

count = 0
p_name = []
for i in city_a:
    if i in d:
        p_name.append(i)
        count += 1
print('一共匹配%d个州'%count)
print('匹配的州名为：',p_name)

一共匹配2个州
匹配的州名为： ['New York', 'Washington']

• 查看city_a与美国县、州名的匹配情况

count = 0
p_name = []
for i in city_b:
    if i in c:
        p_name.append(i)
        count += 1
print('一共匹配%d个县'%count)
print('匹配的县名为：',p_name)

一共匹配43个县
匹配的县名为： ['Arlington', 'Aurora', 'Austin', 'Baltimore', 'Boise', 'Buffalo', 'Charlotte', 'Chesapeake', 'Cleveland', 'Columbus', 'Dallas', 'Denver', 'Durham', 'El Paso', 'Fremont', 'Fresno', 'Garland', 'Henderson', 'Houston', 'Lexington', 'Lincoln', 'Los Angeles', 'Lubbock', 'Madison', 'Mesa', 'Miami', 'Milwaukee', 'Norfolk', 'Oakland', 'Philadelphia', 'Raleigh', 'Reno', 'Richmond', 'Riverside', 'Sacramento', 'San Bernardino', 'San Diego', 'San Francisco', 'Spokane', 'Tulsa', 'Virginia Beach', 'Washington', 'Wichita']

count = 0
p_name = []
for i in city_b:
    if i in d:
        p_name.append(i)
        count += 1
print('一共匹配%d个州'%count)
print('匹配的州名为：',p_name)

一共匹配1个州
匹配的州名为： ['Washington']

• 综上所述，可以看出分别与美国县数据的州匹配的数量最多，因此在ArcGIS实验中应选用美国县名称来进行表格连接。

三、ArcMap制作城市关系强度图

• 3.1 利用美国县的数据结合计算几何工具计算出县中心位置的坐标

• 3.2 将属性表数据导出，同时删除不需要的字段

在次将此次删除字段的结果导出，因为需要对city_a与city_b匹配坐标，因此需要连接两次，所以就再次导出数据。然后再将这两次导出的结果，结果1删除X2、Y2字段，结果1删除X1、Y1字段。

• 3.3 在城市联系强度表(OD)中连接上述得出的两个表，分别以NAME字段连接

• 3.4 XY转线工具完成城市强度分析

• 3.5 制图

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【参考一】使用ArcGIS制作城市关系强度图
【参考二】迁徙图？流向图？城市关系强度图？【微信公众号：码上GIS】
【参考三】ArcGIS制作城市空间经济联系强度图

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