How do I divide data into regions?

madisongaw — Thu, 12 Nov 2020 00:42:13 GMT

How do I divide this data into regions (Northeast, Midwest, South, and West)? How do I create a box-plot with these regions?

Here is my data:

Rank2012	City	State	Estimate2012	Census2010	Change
1	New York	New York	8,336,697	8,175,133	1.98%
2	Los Angeles	California	3,857,799	3,792,621	1.72%
3	Chicago	Illinois	2,714,856	2,695,598	0.71%
4	Houston	Texas	2,160,821	2,100,263	2.88%
5	Philadelphia	Pennsylvania	1,547,607	1,526,006	1.42%
6	Phoenix	Arizona	1,488,750	1,445,632	2.98%
7	San Antonio	Texas	1,382,951	1,327,407	4.18%
8	San Diego	California	1,338,348	1,307,402	2.37%
9	Dallas	Texas	1,241,162	1,197,816	3.62%
10	San Jose	California	982,765	945,942	3.89%
11	Austin	Texas	842,592	790,390	6.60%
12	Jacksonville	Florida	836,507	821,784	1.79%
13	Indianapolis	Indiana	834,852	820,445	1.76%
14	San Francisco	California	825,863	805,235	2.56%
15	Columbus	Ohio	809,798	787,033	2.89%
16	Fort Worth	Texas	777,992	741,206	4.96%
17	Charlotte	North Carolina	775,202	731,424	5.99%
18	Detroit	Michigan	701,475	713,777	(1.72%)
19	El Paso	Texas	672,538	649,121	3.61%
20	Memphis	Tennessee	655,155	646,889	1.28%
21	Boston	Massachusetts	636,479	617,594	3.06%
22	Seattle	Washington	634,535	608,660	4.25%
23	Denver	Colorado	634,265	600,158	5.68%
24	Washington	District of Columbia	632,323	601,723	5.09%
25	Nashville	Tennessee	624,496	601,222	3.87%
26	Baltimore	Maryland	621,342	620,961	0.06%
27	Louisville	Kentucky	605,110	597,337	1.30%
28	Portland	Oregon	603,106	583,776	3.31%
29	Oklahoma City	Oklahoma	599,199	579,999	3.31%
30	Milwaukee	Wisconsin	598,916	594,833	0.69%
31	Las Vegas	Nevada	596,424	583,756	2.17%
32	Albuquerque	New Mexico	555,417	545,852	1.75%
33	Tucson	Arizona	524,295	520,116	0.80%
34	Fresno	California	505,882	494,665	2.27%
35	Sacramento	California	475,516	466,488	1.94%
36	Long Beach	California	467,892	462,257	1.22%
37	Kansas City	Missouri	464,310	459,787	0.98%
38	Mesa	Arizona	452,084	439,041	2.97%
39	Virginia Beach	Virginia	447,021	437,994	2.06%
40	Atlanta	Georgia	443,775	420,003	5.66%
41	Colorado Springs	Colorado	431,834	416,427	3.70%
42	Raleigh	North Carolina	423,179	403,892	4.78%
43	Omaha	Nebraska	421,570	408,958	3.08%
44	Miami	Florida	413,892	399,457	3.61%
45	Oakland	California	400,740	390,724	2.56%
46	Tulsa	Oklahoma	393,987	391,906	0.53%
47	Minneapolis	Minnesota	392,880	382,578	2.69%
48	Cleveland	Ohio	390,928	396,815	(1.48%)
49	Wichita	Kansas	385,577	382,368	0.84%
50	Arlington	Texas	375,600	365,438	2.78%
51	New Orleans	Louisiana	369,250	343,829	7.39%
52	Bakersfield	California	358,597	347,483	3.20%
53	Tampa	Florida	347,645	335,709	3.56%
54	Honolulu	Hawaii	345,610	337,256	2.48%
55	Anaheim	California	343,248	336,265	2.08%
56	Aurora	Colorado	339,030	325,078	4.29%
57	Santa Ana	California	330,920	324,528	1.97%
58	St. Louis	Missouri	318,172	319,294	(0.35%)
59	Riverside	California	313,673	303,871	3.23%
60	Corpus Christi	Texas	312,195	305,215	2.29%
61	Pittsburgh	Pennsylvania	306,211	305,704	0.17%
62	Lexington	Kentucky	310,573	295,803	4.99%
63	Anchorage	Alaska	298,610	291,826	2.32%
64	Stockton	California	297,984	291,707	2.15%
65	Cincinnati	Ohio	296,550	296,943	(0.13%)
66	Saint Paul	Minnesota	290,770	285,068	2.00%
67	Toledo	Ohio	284,012	287,208	(1.11%)
68	Newark	New Jersey	277,727	277,140	0.21%
69	Greensboro	North Carolina	277,080	269,666	2.75%
70	Plano	Texas	272,068	259,841	4.71%
71	Henderson	Nevada	265,679	257,729	3.08%
72	Lincoln	Nebraska	265,404	258,379	2.72%
73	Buffalo	New York	259,384	261,310	(0.74%)
74	Fort Wayne	Indiana	254,555	253,691	0.34%
75	Jersey City	New Jersey	254,441	247,597	2.76%
76	Chula Vista	California	252,422	243,916	3.49%
77	Orlando	Florida	249,562	238,300	4.73%
78	St. Petersburg	Florida	246,541	244,769	0.72%
79	Norfolk	Virginia	245,782	242,803	1.23%
80	Chandler	Arizona	245,628	236,123	4.03%
81	Laredo	Texas	244,731	236,091	3.66%
82	Madison	Wisconsin	240,323	233,209	3.05%
83	Durham	North Carolina	239,358	228,330	4.83%
84	Lubbock	Texas	236,065	229,573	2.83%
85	Winston–Salem	North Carolina	234,349	229,617	2.06%
86	Garland	Texas	233,564	226,876	2.95%
87	Glendale	Arizona	232,143	226,721	2.39%
88	Hialeah	Florida	231,941	224,669	3.24%
89	Reno	Nevada	231,027	225,221	2.58%
90	Baton Rouge	Louisiana	230,058	229,493	0.25%
91	Irvine	California	229,985	212,375	8.29%
92	Chesapeake	Virginia	228,417	222,209	2.79%
93	Irving	Texas	225,427	216,290	4.22%
94	Scottsdale	Arizona	223,514	217,385	2.82%
95	North Las Vegas	Nevada	223,491	216,961	3.01%
96	Fremont	California	221,986	214,089	3.69%
97	Gilbert	Arizona	221,140	208,453	6.09%
98	San Bernardino	California	213,295	209,924	1.61%
99	Boise	Idaho	212,303	205,671	3.22%
100	Birmingham	Alabama	212,038	212,237	(0.09%)

Re: How do I divide data into regions?

ballardw — Thu, 12 Nov 2020 01:48:07 GMT

Box plot of what?

What is your definition of a region. Likely the easiest for use and construction is to create a custom format.

That would look something like:

Proc format;
value $region
"New York", "Pennsylvania" <list the rest comma delimited> = "Northeast"
"Ohio","Indiana" <the rest> ="Midwest"
<repeat for other regions>
run;

Then you would use state as the Group variable on a VBOX or HBOX statement in Proc Sgplot.

Assign the format to the state with a statement like: Format state $region.; in the proc.

topic Re: How do I divide data into regions? in SAS Programming

How do I divide data into regions?

Re: How do I divide data into regions?