Example Programs |
data statepop; input State $ CityPop_80 CityPop_90 NonCityPop_80 NonCityPop_90 Region; format region 1.; label citypop_80= '1980 metropolitan pop in millions' noncitypop_80='1980 nonmetropolitan pop in millions' citypop_90= '1990 metropolitan pop in millions' noncitypop_90='1990 nonmetropolitan pop in million' region='Geographic region'; datalines; ME .405 .443 .721 .785 1 NH .535 .659 .386 .450 1 VT .133 .152 .378 .411 1 MA 5.530 5.788 .207 .229 1 RI .886 .938 .061 .065 1 CT 2.982 3.148 .126 .140 1 NY 16.144 16.515 1.414 1.475 1 NJ 7.365 7.730 .A .A 1 PA 10.067 10.083 1.798 1.799 1 DE .496 .553 .098 .113 2 MD 3.920 4.439 .297 .343 2 DC .638 .607 . . 2 VA 3.966 4.773 1.381 1.414 2 WV .796 .748 1.155 1.045 2 NC 3.749 4.376 2.131 2.253 2 SC 2.114 2.423 1.006 1.064 2 GA 3.507 4.352 1.956 2.127 2 FL 9.039 12.023 .708 .915 2 KY 1.735 1.780 1.925 1.906 2 TN 3.045 3.298 1.546 1.579 2 AL 2.560 2.710 1.334 1.331 2 MS .716 .776 1.805 1.798 2 AR .963 1.040 1.323 1.311 2 LA 3.125 3.160 1.082 1.060 2 OK 1.724 1.870 1.301 1.276 2 TX 11.539 14.166 2.686 2.821 2 OH 8.791 8.826 2.007 2.021 3 IN 3.885 3.962 1.605 1.582 3 IL 9.461 9.574 1.967 1.857 3 MI 7.719 7.698 1.543 1.598 3 WI 3.176 3.331 1.530 1.561 3 MN 2.674 3.011 1.402 1.364 3 IA 1.198 1.200 1.716 1.577 3 MO 3.314 3.491 1.603 1.626 3 ND .234 .257 .418 .381 3 SD .194 .221 .497 .475 3 NE .728 .787 .842 .791 3 KS 1.184 1.333 1.180 1.145 3 MT .189 .191 .598 .608 4 ID .257 .296 .687 .711 4 WY .141 .134 .329 .319 4 CO 2.326 2.686 .563 .608 4 NM .675 .842 .628 .673 4 AZ 2.264 3.106 .453 .559 4 UT 1.128 1.336 .333 .387 4 NV .666 1.014 .135 .183 4 WA 3.366 4.036 .776 .830 4 OR 1.799 1.985 .834 .858 4 CA 22.907 28.799 .760 .961 4 AK .174 .226 .227 .324 4 HI .763 .836 .202 .272 4 ;
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