About c8826024

c8826024 · ‎02-09-2012

Ok, my manager want to change the report template AGAIN. He want to have prior month totle across different region and all region report should be in different worksheet BUT one workbook. Here is my source data: proc_mm country process_dt a1 a2 a7 a9 a11 a_total b1 b2 b7 b9 b11 b_total ab_total realcoamt 1/1/2012 1.NA 1/1/2012 100 200 300 400 1000 100 100 1100 1000 1/1/2012 1.NA 1/2/2012 100 200 300 400 1000 101 101 1101 1000 1/1/2012 1.NA 1/3/2012 100 200 300 400 1000 102 102 1102 1000 1/1/2012 1.NA 1/4/2012 100 200 300 400 1000 103 103 1103 1000 1/1/2012 1.NA 1/5/2012 100 200 300 400 1000 104 104 1104 1000 1/1/2012 1.NA 1/6/2012 100 200 300 400 1000 105 105 1105 1000 1/1/2012 1.NA 1/7/2012 100 200 300 400 1000 106 106 1106 1000 1/1/2012 1.NA 1/8/2012 100 200 300 400 1000 107 107 1107 1000 1/1/2012 1.NA 1/9/2012 100 200 300 400 1000 108 108 1108 1000 1/1/2012 1.NA 1/10/2012 100 200 300 400 1000 109 109 1109 1000 1/1/2012 1.NA 1/11/2012 100 200 300 400 1000 110 110 1110 1000 1/1/2012 1.NA 1/12/2012 100 200 300 400 1000 111 111 1111 1000 1/1/2012 1.NA 1/13/2012 100 200 300 400 1000 112 112 1112 1000 1/1/2012 1.NA 1/14/2012 100 200 300 400 1000 113 113 1113 1000 1/1/2012 1.NA 1/15/2012 100 200 300 400 1000 114 114 1114 1000 1/1/2012 1.NA 1/16/2012 100 200 300 400 1000 115 115 1115 1000 1/1/2012 1.NA 1/17/2012 100 200 300 400 1000 116 116 1116 1000 1/1/2012 1.NA 1/18/2012 100 200 300 400 1000 117 117 1117 1000 1/1/2012 1.NA 1/19/2012 100 200 300 400 1000 118 118 1118 1000 1/1/2012 1.NA 1/20/2012 100 200 300 400 1000 119 119 1119 1000 1/1/2012 1.NA 1/21/2012 100 200 300 400 1000 120 120 1120 1000 1/1/2012 1.NA 1/22/2012 100 200 300 400 1000 121 121 1121 1000 1/1/2012 1.NA 1/23/2012 100 200 300 400 1000 122 122 1122 1000 1/1/2012 1.NA 1/24/2012 100 200 300 400 1000 123 123 1123 1000 1/1/2012 1.NA 1/25/2012 100 200 300 400 1000 124 124 1124 1000 1/1/2012 1.NA 1/26/2012 100 200 300 400 1000 125 125 1125 1000 1/1/2012 1.NA 1/27/2012 100 200 300 400 1000 126 126 1126 1000 1/1/2012 1.NA 1/28/2012 100 200 300 400 1000 127 127 1127 1000 1/1/2012 1.NA 1/29/2012 100 200 300 400 1000 128 128 1128 1000 1/1/2012 1.NA 1/30/2012 100 200 300 400 1000 129 129 1129 1000 1/1/2012 1.NA 1/31/2012 100 200 300 400 1000 130 130 1130 1000 1/1/2012 2.UK 1/1/2012 100 200 300 400 1000 131 131 1131 1000 1/1/2012 2.UK 1/2/2012 100 200 300 400 1000 132 132 1132 1000 1/1/2012 2.UK 1/3/2012 100 200 300 400 1000 133 133 1133 1000 1/1/2012 2.UK 1/4/2012 100 200 300 400 1000 134 134 1134 1000 1/1/2012 2.UK 1/5/2012 100 200 300 400 1000 135 135 1135 1000 1/1/2012 2.UK 1/6/2012 100 200 300 400 1000 136 136 1136 1000 1/1/2012 2.UK 1/7/2012 100 200 300 400 1000 137 137 1137 1000 1/1/2012 2.UK 1/8/2012 100 200 300 400 1000 138 138 1138 1000 1/1/2012 2.UK 1/9/2012 100 200 300 400 1000 139 139 1139 1000 1/1/2012 2.UK 1/10/2012 100 200 300 400 1000 140 140 1140 1000 1/1/2012 2.UK 1/11/2012 100 200 300 400 1000 141 141 1141 1000 1/1/2012 2.UK 1/12/2012 100 200 300 400 1000 142 142 1142 1000 1/1/2012 2.UK 1/13/2012 100 200 300 400 1000 143 143 1143 1000 1/1/2012 2.UK 1/14/2012 100 200 300 400 1000 144 144 1144 1000 1/1/2012 2.UK 1/15/2012 100 200 300 400 1000 145 145 1145 1000 1/1/2012 2.UK 1/16/2012 100 200 300 400 1000 146 146 1146 1000 1/1/2012 2.UK 1/17/2012 100 200 300 400 1000 147 147 1147 1000 1/1/2012 2.UK 1/18/2012 100 200 300 400 1000 148 148 1148 1000 1/1/2012 2.UK 1/19/2012 100 200 300 400 1000 149 149 1149 1000 1/1/2012 2.UK 1/20/2012 100 200 300 400 1000 150 150 1150 1000 1/1/2012 2.UK 1/21/2012 100 200 300 400 1000 151 151 1151 1000 1/1/2012 2.UK 1/22/2012 100 200 300 400 1000 152 152 1152 1000 1/1/2012 2.UK 1/23/2012 100 200 300 400 1000 153 153 1153 1000 1/1/2012 2.UK 1/24/2012 100 200 300 400 1000 154 154 1154 1000 1/1/2012 2.UK 1/25/2012 100 200 300 400 1000 155 155 1155 1000 1/1/2012 2.UK 1/26/2012 100 200 300 400 1000 156 156 1156 1000 1/1/2012 2.UK 1/27/2012 100 200 300 400 1000 157 157 1157 1000 1/1/2012 2.UK 1/28/2012 100 200 300 400 1000 158 158 1158 1000 1/1/2012 2.UK 1/29/2012 100 200 300 400 1000 159 159 1159 1000 1/1/2012 2.UK 1/30/2012 100 200 300 400 1000 160 160 1160 1000 1/1/2012 2.UK 1/31/2012 100 200 300 400 1000 161 161 1161 1000 1/1/2012 3.DE 1/1/2012 100 200 300 400 1000 162 162 1162 1000 1/1/2012 3.DE 1/2/2012 100 200 300 400 1000 163 163 1163 1000 1/1/2012 3.DE 1/3/2012 100 200 300 400 1000 164 164 1164 1000 1/1/2012 3.DE 1/4/2012 100 200 300 400 1000 165 165 1165 1000 1/1/2012 3.DE 1/5/2012 100 200 300 400 1000 166 166 1166 1000 1/1/2012 3.DE 1/6/2012 100 200 300 400 1000 167 167 1167 1000 1/1/2012 3.DE 1/7/2012 100 200 300 400 1000 168 168 1168 1000 1/1/2012 3.DE 1/8/2012 100 200 300 400 1000 169 169 1169 1000 1/1/2012 3.DE 1/9/2012 100 200 300 400 1000 170 170 1170 1000 1/1/2012 3.DE 1/10/2012 100 200 300 400 1000 171 171 1171 1000 1/1/2012 3.DE 1/11/2012 100 200 300 400 1000 172 172 1172 1000 1/1/2012 3.DE 1/12/2012 100 200 300 400 1000 173 173 1173 1000 1/1/2012 3.DE 1/13/2012 100 200 300 400 1000 174 174 1174 1000 1/1/2012 3.DE 1/14/2012 100 200 300 400 1000 175 175 1175 1000 1/1/2012 3.DE 1/15/2012 100 200 300 400 1000 176 176 1176 1000 1/1/2012 3.DE 1/16/2012 100 200 300 400 1000 177 177 1177 1000 1/1/2012 3.DE 1/17/2012 100 200 300 400 1000 178 178 1178 1000 1/1/2012 3.DE 1/18/2012 100 200 300 400 1000 179 179 1179 1000 1/1/2012 3.DE 1/19/2012 100 200 300 400 1000 180 180 1180 1000 1/1/2012 3.DE 1/20/2012 100 200 300 400 1000 181 181 1181 1000 1/1/2012 3.DE 1/21/2012 100 200 300 400 1000 182 182 1182 1000 1/1/2012 3.DE 1/22/2012 100 200 300 400 1000 183 183 1183 1000 1/1/2012 3.DE 1/23/2012 100 200 300 400 1000 184 184 1184 1000 1/1/2012 3.DE 1/24/2012 100 200 300 400 1000 185 185 1185 1000 1/1/2012 3.DE 1/25/2012 100 200 300 400 1000 186 186 1186 1000 1/1/2012 3.DE 1/26/2012 100 200 300 400 1000 187 187 1187 1000 1/1/2012 3.DE 1/27/2012 100 200 300 400 1000 188 188 1188 1000 1/1/2012 3.DE 1/28/2012 100 200 300 400 1000 189 189 1189 1000 1/1/2012 3.DE 1/29/2012 100 200 300 400 1000 190 190 1190 1000 1/1/2012 3.DE 1/30/2012 100 200 300 400 1000 191 191 1191 1000 1/1/2012 3.DE 1/31/2012 100 200 300 400 1000 192 192 1192 1000 1/1/2012 8.Global Total 1/1/2012 300 600 900 0 1200 3000 0 0 394 0 0 394 3394 1000 1/1/2012 8.Global Total 1/2/2012 300 600 900 0 1200 3000 0 0 397 0 0 397 3397 1000 1/1/2012 8.Global Total 1/3/2012 300 600 900 0 1200 3000 0 0 400 0 0 400 3400 1000 1/1/2012 8.Global Total 1/4/2012 300 600 900 0 1200 3000 0 0 403 0 0 403 3403 1000 1/1/2012 8.Global Total 1/5/2012 300 600 900 0 1200 3000 0 0 406 0 0 406 3406 1000 1/1/2012 8.Global Total 1/6/2012 300 600 900 0 1200 3000 0 0 409 0 0 409 3409 1000 1/1/2012 8.Global Total 1/7/2012 300 600 900 0 1200 3000 0 0 412 0 0 412 3412 1000 1/1/2012 8.Global Total 1/8/2012 300 600 900 0 1200 3000 0 0 415 0 0 415 3415 1000 1/1/2012 8.Global Total 1/9/2012 300 600 900 0 1200 3000 0 0 418 0 0 418 3418 1000 1/1/2012 8.Global Total 1/10/2012 300 600 900 0 1200 3000 0 0 421 0 0 421 3421 1000 1/1/2012 8.Global Total 1/11/2012 300 600 900 0 1200 3000 0 0 424 0 0 424 3424 1000 1/1/2012 8.Global Total 1/12/2012 300 600 900 0 1200 3000 0 0 427 0 0 427 3427 1000 1/1/2012 8.Global Total 1/13/2012 300 600 900 0 1200 3000 0 0 430 0 0 430 3430 1000 1/1/2012 8.Global Total 1/14/2012 300 600 900 0 1200 3000 0 0 433 0 0 433 3433 1000 1/1/2012 8.Global Total 1/15/2012 300 600 900 0 1200 3000 0 0 436 0 0 436 3436 1000 1/1/2012 8.Global Total 1/16/2012 300 600 900 0 1200 3000 0 0 439 0 0 439 3439 1000 1/1/2012 8.Global Total 1/17/2012 300 600 900 0 1200 3000 0 0 442 0 0 442 3442 1000 1/1/2012 8.Global Total 1/18/2012 300 600 900 0 1200 3000 0 0 445 0 0 445 3445 1000 1/1/2012 8.Global Total 1/19/2012 300 600 900 0 1200 3000 0 0 448 0 0 448 3448 1000 1/1/2012 8.Global Total 1/20/2012 300 600 900 0 1200 3000 0 0 451 0 0 451 3451 1000 1/1/2012 8.Global Total 1/21/2012 300 600 900 0 1200 3000 0 0 454 0 0 454 3454 1000 1/1/2012 8.Global Total 1/22/2012 300 600 900 0 1200 3000 0 0 457 0 0 457 3457 1000 1/1/2012 8.Global Total 1/23/2012 300 600 900 0 1200 3000 0 0 460 0 0 460 3460 1000 1/1/2012 8.Global Total 1/24/2012 300 600 900 0 1200 3000 0 0 463 0 0 463 3463 1000 1/1/2012 8.Global Total 1/25/2012 300 600 900 0 1200 3000 0 0 466 0 0 466 3466 1000 1/1/2012 8.Global Total 1/26/2012 300 600 900 0 1200 3000 0 0 469 0 0 469 3469 1000 1/1/2012 8.Global Total 1/27/2012 300 600 900 0 1200 3000 0 0 472 0 0 472 3472 1000 1/1/2012 8.Global Total 1/28/2012 300 600 900 0 1200 3000 0 0 475 0 0 475 3475 1000 1/1/2012 8.Global Total 1/29/2012 300 600 900 0 1200 3000 0 0 478 0 0 478 3478 1000 1/1/2012 8.Global Total 1/30/2012 300 600 900 0 1200 3000 0 0 481 0 0 481 3481 1000 1/1/2012 8.Global Total 1/31/2012 300 600 900 0 1200 3000 0 0 484 0 0 484 3484 1000 2/1/2012 1.NA 2/1/2012 100 200 300 400 1000 224 224 1224 1000 2/1/2012 1.NA 2/2/2012 100 200 300 400 1000 225 225 1225 1000 2/1/2012 1.NA 2/3/2012 100 200 300 400 1000 226 226 1226 1000 2/1/2012 1.NA 2/4/2012 100 200 300 400 1000 227 227 1227 1000 2/1/2012 1.NA 2/5/2012 100 200 300 400 1000 228 228 1228 1000 2/1/2012 1.NA 2/6/2012 100 200 300 400 1000 229 229 1229 1000 2/1/2012 1.NA 2/7/2012 100 200 300 400 1000 230 230 1230 1000 2/1/2012 2.UK 2/1/2012 100 200 300 400 1000 231 231 1231 1000 2/1/2012 2.UK 2/2/2012 100 200 300 400 1000 232 232 1232 1000 2/1/2012 2.UK 2/3/2012 100 200 300 400 1000 233 233 1233 1000 2/1/2012 2.UK 2/4/2012 100 200 300 400 1000 234 234 1234 1000 2/1/2012 2.UK 2/5/2012 100 200 300 400 1000 235 235 1235 1000 2/1/2012 2.UK 2/6/2012 100 200 300 400 1000 236 236 1236 1000 2/1/2012 2.UK 2/7/2012 100 200 300 400 1000 237 237 1237 1000 2/1/2012 3.DE 2/1/2012 100 200 300 400 1000 238 238 1238 1000 2/1/2012 3.DE 2/2/2012 100 200 300 400 1000 239 239 1239 1000 2/1/2012 3.DE 2/3/2012 100 200 300 400 1000 240 240 1240 1000 2/1/2012 3.DE 2/4/2012 100 200 300 400 1000 241 241 1241 1000 2/1/2012 3.DE 2/5/2012 100 200 300 400 1000 242 242 1242 1000 2/1/2012 3.DE 2/6/2012 100 200 300 400 1000 243 243 1243 1000 2/1/2012 3.DE 2/7/2012 100 200 300 400 1000 244 244 1244 1000 2/1/2012 8.Global Total 2/1/2012 300 600 900 0 1800 3000 0 0 693 0 0 693 3693 3000 2/1/2012 8.Global Total 2/2/2012 300 600 900 0 1800 3000 0 0 696 0 0 696 3696 3000 2/1/2012 8.Global Total 2/3/2012 300 600 900 0 1800 3000 0 0 699 0 0 699 3699 3000 2/1/2012 8.Global Total 2/4/2012 300 600 900 0 1800 3000 0 0 702 0 0 702 3702 3000 2/1/2012 8.Global Total 2/5/2012 300 600 900 0 1800 3000 0 0 705 0 0 705 3705 3000 2/1/2012 8.Global Total 2/6/2012 300 600 900 0 1800 3000 0 0 708 0 0 708 3708 3000 2/1/2012 8.Global Total 2/7/2012 300 600 900 0 1800 3000 0 0 711 0 0 711 3711 3000 The code provided seems not working. Any idea?

c8826024 · ‎01-24-2012

I add DSD and LRECL option. The error message is gone. Thanks Scott and Art.

c8826024 · ‎01-23-2012

I try to productionize my program for a batch production. So selecting Export from the file menu is out of my option.

c8826024 · ‎01-23-2012

Sorry, I forgot one requirement: the first row need to have the variable name.

c8826024 · ‎01-23-2012

Somebody might answer this question. But I can't find it. Somehow, the PROC EXPORT, for some reasons, is just not working in my company's server. Are there any neat solution? Thanks.

c8826024 · ‎12-01-2011

That's quick and neat. One more question, if I know each location where the patience was treated. But I only need the first location AFTER hospital date: id Hospital_dt T1_date T2_date T3_date T4_date T5_date Location1 Location2 Location3 first_Treatment_dt location 1 3/4/2011 1/1/2011 3/2/3011 3/5/2011 a b c 3/5/2011 c 2 1/1/2011 1/1/2011 2/1/2011 b d 1/1/2011 b 3 2/15/2011 4 10/1/2010 8/1/2010 9/1/2010 a b

c8826024 · ‎12-01-2011

I have a dataset like this: id Hospital_dt T1_date T2_date T3_date T4_date T5_date 1 3/4/2011 1/1/2011 3/2/3011 3/5/2011 2 1/1/2011 1/1/2011 2/1/2011 3 2/15/2011 4 10/1/2010 8/1/2010 9/1/2010 I want to create a new variable which will show the data of the first treatment AFTER hospital date. It will look like this: id Hospital_dt T1_date T2_date T3_date T4_date T5_date first_Treatment_dt 1 3/4/2011 1/1/2011 3/2/3011 3/5/2011 3/5/2011 2 1/1/2011 1/1/2011 2/1/2011 1/1/2011 3 2/15/2011 4 10/1/2010 8/1/2010 9/1/2010

c8826024 · ‎11-30-2011

The solution is elegant. But if I have additional variable, called hospital_date, which is date when the patience first admitted into the hospital. I want to know 120 days's (not a month) treatment for each patience: id date1 date2 date3 dosage1 dosage2 dosage3 hospital_dt 1 1/2 1/5 10 20 12/1/2010 2 1/10 30 11/1/2010 3 1/2 1/5 1/31 10 20 30 1/1/2011 4 4/1/2011 I try to modify your code but it is not working. Thanks.

c8826024 · ‎11-28-2011

But some may have the treatment every day, not necessarily 3 days.

c8826024 · ‎11-28-2011

Hi, I have a dataset like this: id date1 date2 date3 dosage1 dosage2 dosage3 1 1/2 1/5 10 20 2 1/10 30 3 1/2 1/5 1/31 10 20 30 4 The final dataset I wants looks like this: id cumdosage1 cumdosage2 cumdosage3.... cumdosage5.... cumdosage10.... cumdosage31 1 0 10 10 30 30 30 2 30 30 30 30 3 0 0 0 0 10 10 4 0 0 0 0 0 0 So, cumdosage1 - cumdosage31 are corresponding to total days of the month and will be the cumulative dosages month-to-date. Do you know how I can re-construct my dataset? Thanks.

c8826024 · ‎11-21-2011

Thanks everybody. I like KSHARP's solution because I am a "DATA STEP" guy. I always believe DATA STEP gives programmers more flexibilities than PROCEDURE. But sometimes PROCEDURE is easier to get your job done if the task is simple. Thanks again.

c8826024 · ‎11-18-2011

Thanks for the response. What about multiple variables are needed to be transposed? Say, in my original dataset, I have variables called location and dose, which will be different every patience visit.PROC TRANSPOSE seems to be only able to handle one variable transpose.

c8826024 · ‎11-18-2011

Bear with me if this question has been resolved but I can't find my answer by searching this forum. I have a dataset like this: id visit_date 001 1/1/2011 001 3/20/2011 001 4/15/2011 002 8/1/2011 002 9/2/2011 003 1/23/2011 003 2/2/2011 003 2/15/2011 003 3/8/2011 003 3/15/2011 003 3/28/2011 003 3/29/2011 003 3/31/2011 ......... The final dataset I want is like this: id visit1 visit2 visit3 visit4 visit5 visit6 visit7 visit8 visit9 visit10.... 001 1/1/11 3/20/11 4/15/11 002 8/1/11 9/2/11 003 1/23/11 2/2/11 2/15/11 3/8/11 3/15/11 3/28/11 3/29/11 3/31/2011 ... I don't know how many times the patiences have been visit. But I just want to have one record/patience with all the visit dates populated. I know I should use ARRAY but I don't know how to impletment it. Can anyone help? Thanks.

c8826024 · ‎10-27-2011

Thanks. Got it. I was figuring somebody might already post the solution somewhere. But I was in a hurry. Thanks again.

c8826024 · ‎10-27-2011

I use tagset to generate a report and convert the report to an Excel spreadsheet. But there is a character variable, which is 19 digit. When the report convert to excel, it is automatically set the last 4 digit to 0000. Anybody know how to fix it? Sample data: country account # US 1234567891234567899 UK 9876543219876543219 .... wrong output in Excel: country account # US 1234567891234560000 UK 9876543219876540000 Code: ods tagsets.excelxp path='/path/' file="myreport.xls"; ods tagsets.excelxp options(sheet_interval='bygroup'); proc report data=mydata by country; column account#; define account#/display 'Account #' f=$char19. style(column)={tagattr="###################"}; run;

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