3 # AT_SETUP([CTABLES parsing])
4 # AT_DATA([ctables.sps],
5 # [[DATA LIST LIST NOTABLE /x y z.
6 # CTABLES /TABLE=(x + y) > z.
7 # CTABLES /TABLE=(x[c] + y[c]) > z.
8 # CTABLES /TABLE=(x + y) > z[c].
9 # CTABLES /TABLE=x BY y BY z.
10 # CTABLES /TABLE=x[c] [ROWPCT.COUNT] > y[c].
11 # CTABLES /TABLE=x[c] > y[c] [ROWPCT.COUNT].
13 # AT_CHECK([pspp ctables.sps])
16 AT_SETUP([CTABLES one categorical variable])
17 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
18 AT_DATA([ctables.sps],
21 CTABLES /TABLE BY qn1.
22 CTABLES /TABLE BY BY qn1.
24 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
26 ╭────────────────────────────────────────────────────────────────────────┬─────╮
28 ├────────────────────────────────────────────────────────────────────────┼─────┤
29 │ 1. How often do you usually drive a car or other Every day │ 4667│
30 │motor vehicle? Several days a week │ 1274│
31 │ Once a week or less │ 361│
32 │ Only certain times a │ 130│
35 ╰────────────────────────────────────────────────────────────────────────┴─────╯
38 ╭──────────────────────────────────────────────────────────────────────────────╮
39 │ 1. How often do you usually drive a car or other motor vehicle? │
40 ├─────────┬──────────────────┬──────────────────┬────────────────────────┬─────┤
41 │ │ Several days a │ Once a week or │ Only certain times a │ │
42 │Every day│ week │ less │ year │Never│
43 ├─────────┼──────────────────┼──────────────────┼────────────────────────┼─────┤
44 │ Count │ Count │ Count │ Count │Count│
45 ├─────────┼──────────────────┼──────────────────┼────────────────────────┼─────┤
46 │ 4667│ 1274│ 361│ 130│ 540│
47 ╰─────────┴──────────────────┴──────────────────┴────────────────────────┴─────╯
59 AT_SETUP([CTABLES one scale variable])
60 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
61 AT_DATA([ctables.sps],
63 CTABLES /TABLE qnd1[COUNT, MEAN, STDDEV, MINIMUM, MAXIMUM].
64 CTABLES /TABLE BY qnd1.
65 CTABLES /TABLE BY BY qnd1.
67 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
69 ╭──────────────────────────┬─────┬────┬─────────────┬───────┬───────╮
70 │ │Count│Mean│Std Deviation│Minimum│Maximum│
71 ├──────────────────────────┼─────┼────┼─────────────┼───────┼───────┤
72 │D1. AGE: What is your age?│ 6930│ 48│ 19│ 16│ 86│
73 ╰──────────────────────────┴─────┴────┴─────────────┴───────┴───────╯
76 ╭──────────────────────────╮
77 │D1. AGE: What is your age?│
78 ├──────────────────────────┤
80 ├──────────────────────────┤
82 ╰──────────────────────────╯
85 D1. AGE: What is your age?
94 AT_SETUP([CTABLES simple stacking])
95 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
96 AT_DATA([ctables.sps],
98 CTABLES /TABLE qn105ba + qn105bb + qn105bc + qn105bd BY qns3a [COLPCT PCT8.0].
100 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
102 ╭───────────────────────────────────────────────────────────────┬──────────────╮
109 ├───────────────────────────────────────────────────────────────┼──────┼───────┤
110 │105b. How likely is it that drivers who have had Almost │ 10%│ 11%│
111 │too much to drink to drive safely will A. Get certain │ │ │
112 │stopped by the police? Very likely │ 21%│ 22%│
113 │ Somewhat │ 38%│ 42%│
115 │ Somewhat │ 21%│ 18%│
119 ├───────────────────────────────────────────────────────────────┼──────┼───────┤
120 │105b. How likely is it that drivers who have had Almost │ 14%│ 18%│
121 │too much to drink to drive safely will B. Have an certain │ │ │
122 │accident? Very likely │ 36%│ 45%│
123 │ Somewhat │ 39%│ 32%│
129 ├───────────────────────────────────────────────────────────────┼──────┼───────┤
130 │105b. How likely is it that drivers who have had Almost │ 18%│ 16%│
131 │too much to drink to drive safely will C. Be certain │ │ │
132 │convicted for drunk driving? Very likely │ 32%│ 28%│
133 │ Somewhat │ 27%│ 32%│
135 │ Somewhat │ 15%│ 15%│
139 ├───────────────────────────────────────────────────────────────┼──────┼───────┤
140 │105b. How likely is it that drivers who have had Almost │ 16%│ 16%│
141 │too much to drink to drive safely will D. Be certain │ │ │
142 │arrested for drunk driving? Very likely │ 26%│ 27%│
143 │ Somewhat │ 32%│ 35%│
145 │ Somewhat │ 17%│ 15%│
149 ╰───────────────────────────────────────────────────────────────┴──────┴───────╯
154 AT_SETUP([CTABLES simple nesting])
155 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
156 AT_DATA([ctables.sps],
158 CTABLES /TABLE (qn105ba + qn105bb + qn105bc + qn105bd) > qns3a [TABLEPCT PCT8.0]
159 /CATEGORIES VARIABLES=qns3a TOTAL=NO.
160 CTABLES /TABLE qns3a > (qn105ba + qn105bb + qn105bc + qn105bd) [TABLEPCT PCT8.0]
161 /CATEGORIES VARIABLES=qns3a TOTAL=NO
162 /CLABELS ROW=OPPOSITE.
164 dnl XXX With TOTAL=YES above, the totals get included in the denominator so that
165 dnl the percentages are about half of the correct values.
166 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
168 ╭───────────────────────────────────────────────────────────────────────┬──────╮
171 ├───────────────────────────────────────────────────────────────────────┼──────┤
172 │105b. How likely is it that drivers who Almost S3a. Male │ 4%│
173 │have had too much to drink to drive safely certain GENDER: Female│ 6%│
174 │will A. Get stopped by the police? ╶───────────────────────────┼──────┤
175 │ Very likely S3a. Male │ 10%│
176 │ GENDER: Female│ 12%│
177 │ ╶───────────────────────────┼──────┤
178 │ Somewhat S3a. Male │ 17%│
179 │ likely GENDER: Female│ 23%│
180 │ ╶───────────────────────────┼──────┤
181 │ Somewhat S3a. Male │ 9%│
182 │ unlikely GENDER: Female│ 10%│
183 │ ╶───────────────────────────┼──────┤
184 │ Very S3a. Male │ 5%│
185 │ unlikely GENDER: Female│ 4%│
186 ├───────────────────────────────────────────────────────────────────────┼──────┤
187 │105b. How likely is it that drivers who Almost S3a. Male │ 6%│
188 │have had too much to drink to drive safely certain GENDER: Female│ 10%│
189 │will B. Have an accident? ╶───────────────────────────┼──────┤
190 │ Very likely S3a. Male │ 16%│
191 │ GENDER: Female│ 25%│
192 │ ╶───────────────────────────┼──────┤
193 │ Somewhat S3a. Male │ 17%│
194 │ likely GENDER: Female│ 18%│
195 │ ╶───────────────────────────┼──────┤
196 │ Somewhat S3a. Male │ 4%│
197 │ unlikely GENDER: Female│ 2%│
198 │ ╶───────────────────────────┼──────┤
199 │ Very S3a. Male │ 1%│
200 │ unlikely GENDER: Female│ 1%│
201 ├───────────────────────────────────────────────────────────────────────┼──────┤
202 │105b. How likely is it that drivers who Almost S3a. Male │ 8%│
203 │have had too much to drink to drive safely certain GENDER: Female│ 9%│
204 │will C. Be convicted for drunk driving? ╶───────────────────────────┼──────┤
205 │ Very likely S3a. Male │ 14%│
206 │ GENDER: Female│ 15%│
207 │ ╶───────────────────────────┼──────┤
208 │ Somewhat S3a. Male │ 12%│
209 │ likely GENDER: Female│ 18%│
210 │ ╶───────────────────────────┼──────┤
211 │ Somewhat S3a. Male │ 7%│
212 │ unlikely GENDER: Female│ 8%│
213 │ ╶───────────────────────────┼──────┤
214 │ Very S3a. Male │ 4%│
215 │ unlikely GENDER: Female│ 5%│
216 ├───────────────────────────────────────────────────────────────────────┼──────┤
217 │105b. How likely is it that drivers who Almost S3a. Male │ 7%│
218 │have had too much to drink to drive safely certain GENDER: Female│ 9%│
219 │will D. Be arrested for drunk driving? ╶───────────────────────────┼──────┤
220 │ Very likely S3a. Male │ 12%│
221 │ GENDER: Female│ 15%│
222 │ ╶───────────────────────────┼──────┤
223 │ Somewhat S3a. Male │ 14%│
224 │ likely GENDER: Female│ 19%│
225 │ ╶───────────────────────────┼──────┤
226 │ Somewhat S3a. Male │ 8%│
227 │ unlikely GENDER: Female│ 8%│
228 │ ╶───────────────────────────┼──────┤
229 │ Very S3a. Male │ 4%│
230 │ unlikely GENDER: Female│ 4%│
231 ╰───────────────────────────────────────────────────────────────────────┴──────╯
234 ╭─────────────────────────────────┬────────┬──────┬─────────┬─────────┬────────╮
235 │ │ Almost │ Very │ Somewhat│ Somewhat│ Very │
236 │ │ certain│likely│ likely │ unlikely│unlikely│
237 │ ├────────┼──────┼─────────┼─────────┼────────┤
239 │ │ Table %│ % │ Table % │ Table % │ Table %│
240 ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
241 │S3a. Male 105b. How likely │ 4%│ 10%│ 17%│ 9%│ 5%│
242 │GENDER: is it that drivers│ │ │ │ │ │
243 │ who have had too │ │ │ │ │ │
244 │ much to drink to │ │ │ │ │ │
245 │ drive safely will │ │ │ │ │ │
246 │ A. Get stopped by │ │ │ │ │ │
247 │ the police? │ │ │ │ │ │
248 │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
249 │ Female 105b. How likely │ 6%│ 12%│ 23%│ 10%│ 4%│
250 │ is it that drivers│ │ │ │ │ │
251 │ who have had too │ │ │ │ │ │
252 │ much to drink to │ │ │ │ │ │
253 │ drive safely will │ │ │ │ │ │
254 │ A. Get stopped by │ │ │ │ │ │
255 │ the police? │ │ │ │ │ │
256 ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
257 │S3a. Male 105b. How likely │ 6%│ 16%│ 17%│ 4%│ 1%│
258 │GENDER: is it that drivers│ │ │ │ │ │
259 │ who have had too │ │ │ │ │ │
260 │ much to drink to │ │ │ │ │ │
261 │ drive safely will │ │ │ │ │ │
262 │ B. Have an │ │ │ │ │ │
263 │ accident? │ │ │ │ │ │
264 │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
265 │ Female 105b. How likely │ 10%│ 25%│ 18%│ 2%│ 1%│
266 │ is it that drivers│ │ │ │ │ │
267 │ who have had too │ │ │ │ │ │
268 │ much to drink to │ │ │ │ │ │
269 │ drive safely will │ │ │ │ │ │
270 │ B. Have an │ │ │ │ │ │
271 │ accident? │ │ │ │ │ │
272 ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
273 │S3a. Male 105b. How likely │ 8%│ 14%│ 12%│ 7%│ 4%│
274 │GENDER: is it that drivers│ │ │ │ │ │
275 │ who have had too │ │ │ │ │ │
276 │ much to drink to │ │ │ │ │ │
277 │ drive safely will │ │ │ │ │ │
278 │ C. Be convicted │ │ │ │ │ │
279 │ for drunk driving?│ │ │ │ │ │
280 │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
281 │ Female 105b. How likely │ 9%│ 15%│ 18%│ 8%│ 5%│
282 │ is it that drivers│ │ │ │ │ │
283 │ who have had too │ │ │ │ │ │
284 │ much to drink to │ │ │ │ │ │
285 │ drive safely will │ │ │ │ │ │
286 │ C. Be convicted │ │ │ │ │ │
287 │ for drunk driving?│ │ │ │ │ │
288 ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
289 │S3a. Male 105b. How likely │ 7%│ 12%│ 14%│ 8%│ 4%│
290 │GENDER: is it that drivers│ │ │ │ │ │
291 │ who have had too │ │ │ │ │ │
292 │ much to drink to │ │ │ │ │ │
293 │ drive safely will │ │ │ │ │ │
294 │ D. Be arrested for│ │ │ │ │ │
295 │ drunk driving? │ │ │ │ │ │
296 │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤
297 │ Female 105b. How likely │ 9%│ 15%│ 19%│ 8%│ 4%│
298 │ is it that drivers│ │ │ │ │ │
299 │ who have had too │ │ │ │ │ │
300 │ much to drink to │ │ │ │ │ │
301 │ drive safely will │ │ │ │ │ │
302 │ D. Be arrested for│ │ │ │ │ │
303 │ drunk driving? │ │ │ │ │ │
304 ╰─────────────────────────────────┴────────┴──────┴─────────┴─────────┴────────╯
308 AT_SETUP([CTABLES nesting and scale variables])
309 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
310 AT_DATA([ctables.sps],
312 CTABLES /TABLE=qnd1 > qn1 BY qns3a.
313 CTABLES /TABLE=qnd1 [MINIMUM, MAXIMUM, MEAN] > qns3a > (qn26 + qn27).
314 CTABLES /TABLE=qnsa1 > qn105ba [COLPCT] BY qns1.
315 CTABLES /TABLE=AgeGroup > qn20 [MEAN F8.1, STDDEV F8.1].
317 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
319 ╭─────────────────────────────────────────────────────────────────┬────────────╮
325 ├─────────────────────────────────────────────────────────────────┼─────┼──────┤
326 │D1. AGE: What 1. How often do you usually drive Every day │ 46│ 46│
327 │is your age? a car or other motor vehicle? Several days a │ 51│ 59│
329 │ Once a week or │ 44│ 54│
331 │ Only certain │ 34│ 41│
334 ╰─────────────────────────────────────────────────────────────────┴─────┴──────╯
337 ╭─────────────────────────────────────────────────────────┬───────┬───────┬────╮
338 │ │Minimum│Maximum│Mean│
339 ├─────────────────────────────────────────────────────────┼───────┼───────┼────┤
340 │D1. AGE: S3a. Male 26. During the last 12 Yes│ 16│ 86│ 42│
341 │What is GENDER: months, has there been a │ │ │ │
342 │your time when you felt you │ │ │ │
343 │age? should cut down on your No │ 16│ 86│ 46│
345 │ ╶───────────────────────────────────────┼───────┼───────┼────┤
346 │ Female 26. During the last 12 Yes│ 16│ 86│ 43│
347 │ months, has there been a │ │ │ │
348 │ time when you felt you │ │ │ │
349 │ should cut down on your No │ 16│ 86│ 48│
351 ├─────────────────────────────────────────────────────────┼───────┼───────┼────┤
352 │D1. AGE: S3a. Male 27. During the last 12 Yes│ 16│ 86│ 38│
353 │What is GENDER: months, has there been a │ │ │ │
354 │your time when people criticized No │ 16│ 86│ 46│
355 │age? your drinking? │ │ │ │
356 │ ╶───────────────────────────────────────┼───────┼───────┼────┤
357 │ Female 27. During the last 12 Yes│ 17│ 69│ 37│
358 │ months, has there been a │ │ │ │
359 │ time when people criticized No │ 16│ 86│ 48│
360 │ your drinking? │ │ │ │
361 ╰─────────────────────────────────────────────────────────┴───────┴───────┴────╯
364 ╭──────────────────────────────────┬───────────────────────────────────────────╮
365 │ │S1. Including yourself, how many members of│
366 │ │ this household are age 16 or older? │
367 │ ├──────┬───────┬──────┬──────┬───────┬──────┤
369 │ │ 1 │ 2 │ 3 │ 4 │ 5 │ more │
370 │ ├──────┼───────┼──────┼──────┼───────┼──────┤
371 │ │Column│ Column│Column│Column│ Column│Column│
372 │ │ % │ % │ % │ % │ % │ % │
373 ├──────────────────────────────────┼──────┼───────┼──────┼──────┼───────┼──────┤
374 │Sa1. RDD 105b. How Almost │ 9.5%│ 8.2%│ 12.4%│ 9.9%│ 20.0%│ 23.8%│
375 │SAMPLE likely is it certain │ │ │ │ │ │ │
376 │SOURCE: that drivers Very │ 24.9%│ 18.5%│ 24.0%│ 26.6%│ 25.5%│ 33.3%│
377 │ who have had likely │ │ │ │ │ │ │
378 │ too much to Somewhat│ 38.3%│ 41.9%│ 38.6%│ 37.5%│ 36.4%│ 23.8%│
379 │ drink to likely │ │ │ │ │ │ │
380 │ drive safely Somewhat│ 18.1%│ 21.7%│ 16.8%│ 16.7%│ 10.9%│ 9.5%│
381 │ will A. Get unlikely│ │ │ │ │ │ │
382 │ stopped by Very │ 9.2%│ 9.7%│ 8.2%│ 9.4%│ 7.3%│ 9.5%│
383 │ the police? unlikely│ │ │ │ │ │ │
384 ╰──────────────────────────────────┴──────┴───────┴──────┴──────┴───────┴──────╯
387 ╭──────────────────────────────────────────────────────────────┬────┬──────────╮
390 ├──────────────────────────────────────────────────────────────┼────┼──────────┤
391 │Age 16 to 25 20. On how many of the thirty days in this │ 5.2│ 6.0│
392 │group typical month did you have one or more │ │ │
393 │ alcoholic beverages to drink? │ │ │
394 │ ╶───────────────────────────────────────────────────────┼────┼──────────┤
395 │ 26 to 35 20. On how many of the thirty days in this │ 4.7│ 5.9│
396 │ typical month did you have one or more │ │ │
397 │ alcoholic beverages to drink? │ │ │
398 │ ╶───────────────────────────────────────────────────────┼────┼──────────┤
399 │ 36 to 45 20. On how many of the thirty days in this │ 5.5│ 6.8│
400 │ typical month did you have one or more │ │ │
401 │ alcoholic beverages to drink? │ │ │
402 │ ╶───────────────────────────────────────────────────────┼────┼──────────┤
403 │ 46 to 55 20. On how many of the thirty days in this │ 5.8│ 7.7│
404 │ typical month did you have one or more │ │ │
405 │ alcoholic beverages to drink? │ │ │
406 │ ╶───────────────────────────────────────────────────────┼────┼──────────┤
407 │ 56 to 65 20. On how many of the thirty days in this │ 6.3│ 8.2│
408 │ typical month did you have one or more │ │ │
409 │ alcoholic beverages to drink? │ │ │
410 │ ╶───────────────────────────────────────────────────────┼────┼──────────┤
411 │ 66 or 20. On how many of the thirty days in this │ 7.1│ 9.2│
412 │ older typical month did you have one or more │ │ │
413 │ alcoholic beverages to drink? │ │ │
414 ╰──────────────────────────────────────────────────────────────┴────┴──────────╯
419 AT_SETUP([CTABLES SLABELS])
420 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
421 AT_DATA([ctables.sps],
423 CTABLES /TABLE qn1 [COUNT COLPCT].
424 CTABLES /TABLE qn1 [COUNT COLPCT]
425 /SLABELS POSITION=ROW.
426 CTABLES /TABLE qn1 [COUNT COLPCT]
427 /SLABELS POSITION=ROW VISIBLE=NO.
429 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
431 ╭────────────────────────────────────────────────────────────────┬─────┬───────╮
434 ├────────────────────────────────────────────────────────────────┼─────┼───────┤
435 │ 1. How often do you usually drive a car or Every day │ 4667│ 66.9%│
436 │other motor vehicle? Several days a week│ 1274│ 18.3%│
437 │ Once a week or less│ 361│ 5.2%│
438 │ Only certain times │ 130│ 1.9%│
441 ╰────────────────────────────────────────────────────────────────┴─────┴───────╯
444 ╭────────────────────────────────────────────────────────────────────────┬─────╮
445 │ 1. How often do you usually drive a car or Every day Count │ 4667│
446 │other motor vehicle? Column │66.9%│
448 │ ╶───────────────────────────┼─────┤
449 │ Several days a week Count │ 1274│
452 │ ╶───────────────────────────┼─────┤
453 │ Once a week or less Count │ 361│
456 │ ╶───────────────────────────┼─────┤
457 │ Only certain times Count │ 130│
458 │ a year Column │ 1.9%│
460 │ ╶───────────────────────────┼─────┤
464 ╰────────────────────────────────────────────────────────────────────────┴─────╯
467 ╭────────────────────────────────────────────────────────────────────────┬─────╮
468 │ 1. How often do you usually drive a car or other Every day │ 4667│
469 │motor vehicle? │66.9%│
470 │ Several days a week │ 1274│
472 │ Once a week or less │ 361│
474 │ Only certain times a │ 130│
478 ╰────────────────────────────────────────────────────────────────────────┴─────╯
482 AT_SETUP([CTABLES simple totals])
483 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
484 AT_DATA([ctables.sps],
487 /CATEGORIES VARIABLES=qn17 TOTAL=YES LABEL='Number responding'.
488 CTABLES /TABLE=region > qn18 [MEAN, COUNT]
489 /CATEGORIES VARIABLES=region TOTAL=YES LABEL='All regions'.
491 AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl
493 ╭────────────────────────────────────────────────────────────────────────┬─────╮
495 ├────────────────────────────────────────────────────────────────────────┼─────┤
496 │17. When you drink alcoholic beverages, which ONE of OR, something else│ 2│
497 │the following beverages do you drink MOST OFTEN? Beer │ 1073│
500 │ Wine coolers │ 137│
501 │ Hard liquor or │ 888│
503 │ Flavored malt │ 83│
505 │ Number responding │ 4221│
506 ╰────────────────────────────────────────────────────────────────────────┴─────╯
509 ╭───────────────────────────────────────────────────────────────────┬────┬─────╮
511 ├───────────────────────────────────────────────────────────────────┼────┼─────┤
512 │Region NE 18. When you drink ANSWERFROM(QN17R1), about how │4.36│ 949│
513 │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │
515 │ ╶────────────────────────────────────────────────────────────┼────┼─────┤
516 │ MW 18. When you drink ANSWERFROM(QN17R1), about how │4.67│ 1027│
517 │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │
519 │ ╶────────────────────────────────────────────────────────────┼────┼─────┤
520 │ S 18. When you drink ANSWERFROM(QN17R1), about how │4.71│ 1287│
521 │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │
523 │ ╶────────────────────────────────────────────────────────────┼────┼─────┤
524 │ W 18. When you drink ANSWERFROM(QN17R1), about how │4.69│ 955│
525 │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │
527 │ ╶────────────────────────────────────────────────────────────┼────┼─────┤
528 │ All 18. When you drink ANSWERFROM(QN17R1), about how │4.62│ 4218│
529 │ regions many ANSWERFROM(QN17R2) do you usually drink per │ │ │
531 ╰───────────────────────────────────────────────────────────────────┴────┴─────╯
535 AT_SETUP([CTABLES subtotals])
536 AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .])
537 AT_DATA([ctables.sps],
539 CTABLES /TABLE=qn105ba BY qns1
540 /CATEGORIES VARIABLES=qns1 [1, 2, SUBTOTAL, 3, 4, 5, SUBTOTAL].
541 CTABLES /TABLE=qn105ba [COLPCT] BY qns1
542 /CATEGORIES VARIABLES=qn105ba [1, 2, 3, SUBTOTAL, 4, 5, SUBTOTAL].
543 CTABLES /TABLE=qn105ba BY qns1
544 /CATEGORIES VARIABLES=qn105ba [1, 2, 3, SUBTOTAL, 4, 5, SUBTOTAL]
545 /CATEGORIES VARIABLES=qns1 [1, 2, SUBTOTAL, 3, 4, 5, SUBTOTAL].
547 AT_CHECK([pspp ctables.sps -O box=unicode -O width=120], [0], [dnl
549 ╭─────────────────────────────────────────────────────────┬────────────────────────────────────────────────────────────╮
550 │ │ S1. Including yourself, how many members of this household │
551 │ │ are age 16 or older? │
552 │ ├───────┬───────┬─────────┬───────┬────────┬──────┬──────────┤
553 │ │ 1 │ 2 │ Subtotal│ 3 │ 4 │ 5 │ Subtotal │
554 │ ├───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤
555 │ │ Count │ Count │ Count │ Count │ Count │ Count│ Count │
556 ├─────────────────────────────────────────────────────────┼───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤
557 │105b. How likely is it that drivers who have Almost │ 147│ 246│ 393│ 62│ 19│ 11│ 92│
558 │had too much to drink to drive safely will A. certain │ │ │ │ │ │ │ │
559 │Get stopped by the police? Very likely│ 384│ 552│ 936│ 120│ 51│ 14│ 185│
560 │ Somewhat │ 590│ 1249│ 1839│ 193│ 72│ 20│ 285│
561 │ likely │ │ │ │ │ │ │ │
562 │ Somewhat │ 278│ 647│ 925│ 84│ 32│ 6│ 122│
563 │ unlikely │ │ │ │ │ │ │ │
564 │ Very │ 141│ 290│ 431│ 41│ 18│ 4│ 63│
565 │ unlikely │ │ │ │ │ │ │ │
566 ╰─────────────────────────────────────────────────────────┴───────┴───────┴─────────┴───────┴────────┴──────┴──────────╯
569 ╭────────────────────────────────────────────────────────────┬─────────────────────────────────────────────────────────╮
570 │ │ S1. Including yourself, how many members of this │
571 │ │ household are age 16 or older? │
572 │ ├─────────┬────────┬─────────┬────────┬─────────┬─────────┤
573 │ │ 1 │ 2 │ 3 │ 4 │ 5 │6 or more│
574 │ ├─────────┼────────┼─────────┼────────┼─────────┼─────────┤
575 │ │ Column %│Column %│ Column %│Column %│ Column %│ Column %│
576 ├────────────────────────────────────────────────────────────┼─────────┼────────┼─────────┼────────┼─────────┼─────────┤
577 │105b. How likely is it that drivers who have had Almost │ 4.8%│ 4.1%│ 6.2%│ 4.9%│ 10.0%│ 11.9%│
578 │too much to drink to drive safely will A. Get certain │ │ │ │ │ │ │
579 │stopped by the police? Very likely│ 12.5%│ 9.2%│ 12.0%│ 13.3%│ 12.7%│ 16.7%│
580 │ Somewhat │ 19.2%│ 20.9%│ 19.3%│ 18.8%│ 18.2%│ 11.9%│
581 │ likely │ │ │ │ │ │ │
582 │ Subtotal │ 36.4%│ 34.3%│ 37.5%│ 37.0%│ 40.9%│ 40.5%│
583 │ Somewhat │ 9.0%│ 10.8%│ 8.4%│ 8.3%│ 5.5%│ 4.8%│
584 │ unlikely │ │ │ │ │ │ │
585 │ Very │ 4.6%│ 4.9%│ 4.1%│ 4.7%│ 3.6%│ 4.8%│
586 │ unlikely │ │ │ │ │ │ │
587 │ Subtotal │ 13.6%│ 15.7%│ 12.5%│ 13.0%│ 9.1%│ 9.5%│
588 ╰────────────────────────────────────────────────────────────┴─────────┴────────┴─────────┴────────┴─────────┴─────────╯
591 ╭─────────────────────────────────────────────────────────┬────────────────────────────────────────────────────────────╮
592 │ │ S1. Including yourself, how many members of this household │
593 │ │ are age 16 or older? │
594 │ ├───────┬───────┬─────────┬───────┬────────┬──────┬──────────┤
595 │ │ 1 │ 2 │ Subtotal│ 3 │ 4 │ 5 │ Subtotal │
596 │ ├───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤
597 │ │ Count │ Count │ Count │ Count │ Count │ Count│ Count │
598 ├─────────────────────────────────────────────────────────┼───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤
599 │105b. How likely is it that drivers who have Almost │ 147│ 246│ 393│ 62│ 19│ 11│ 92│
600 │had too much to drink to drive safely will A. certain │ │ │ │ │ │ │ │
601 │Get stopped by the police? Very likely│ 384│ 552│ 936│ 120│ 51│ 14│ 185│
602 │ Somewhat │ 590│ 1249│ 1839│ 193│ 72│ 20│ 285│
603 │ likely │ │ │ │ │ │ │ │
604 │ Subtotal │ 1121│ 2047│ 3168│ 375│ 142│ 45│ 562│
605 │ Somewhat │ 278│ 647│ 925│ 84│ 32│ 6│ 122│
606 │ unlikely │ │ │ │ │ │ │ │
607 │ Very │ 141│ 290│ 431│ 41│ 18│ 4│ 63│
608 │ unlikely │ │ │ │ │ │ │ │
609 │ Subtotal │ 419│ 937│ 1356│ 125│ 50│ 10│ 185│
610 ╰─────────────────────────────────────────────────────────┴───────┴───────┴─────────┴───────┴────────┴──────┴──────────╯