AT_BANNER([CTABLES]) dnl TODO: dnl dnl - Parsing (positive and negative) dnl - String variables and values dnl - Date/time variables and values dnl - Multiple-response sets. dnl * MRSETS subcommand. dnl - SPLIT FILE with SEPARATE splits dnl - Definition of columns/rows when labels are rotated from one axis to another. dnl - Preprocessing to distinguish categorical from scale. dnl - )CILEVEL in summary specifications dnl - Summary functions: dnl * Unimplemented ones. dnl * U-prefix for unweighted summaries. dnl * .LCL and .UCL suffixes. dnl * .SE suffixes. dnl * Separate summary functions for totals and subtotals. dnl - Special formats for summary functions: NEGPAREN, NEQUAL, PAREN, PCTPAREN. dnl - Testing details of missing value handling in summaries. dnl - test CLABELS ROWLABELS=LAYER. dnl - CATEGORIES: dnl * Special case for explicit category specifications and multiple dichotomy sets dnl * THRU dnl * OTHERNM dnl * String values dnl * Date values dnl * Data-dependent sorting. dnl - TITLES: )DATE, )TIME, )TABLE. dnl - SIGTEST dnl - COMPARETEST dnl - FORMAT: dnl * MINCOLWIDTH, MAXCOLWIDTH, UNITS. dnl * EMPTY. dnl * MISSING. dnl - VLABELS. dnl - SMISSING. dnl - Test WEIGHT and adjustment weights. dnl - Test PCOMPUTE and PPROPERTIES. dnl - PCOMPUTE: dnl * multi-dimensional dnl * MISSING, OTHERNM dnl * strings dnl - HIDESMALLCOUNTS. dnl - Are string ranges a thing? dnl dnl Bug: dnl CTABLES /TABLE=qnd1 [MEAN, MEDIAN] BY qns3a. dnl produces a bad median: dnl Custom Tables dnl +--------------------------+-----------------------+ dnl | | S3a. GENDER: | dnl | +-----------+-----------+ dnl | | Male | Female | dnl | +----+------+----+------+ dnl | |Mean|Median|Mean|Median| dnl +--------------------------+----+------+----+------+ dnl |D1. AGE: What is your age?| 46| 999| 50| 999| dnl +--------------------------+----+------+----+------+ # AT_SETUP([CTABLES parsing]) # AT_DATA([ctables.sps], # [[DATA LIST LIST NOTABLE /x y z. # CTABLES /TABLE=(x + y) > z. # CTABLES /TABLE=(x[c] + y[c]) > z. # CTABLES /TABLE=(x + y) > z[c]. # CTABLES /TABLE=x BY y BY z. # CTABLES /TABLE=x[c] [ROWPCT.COUNT] > y[c]. # CTABLES /TABLE=x[c] > y[c] [ROWPCT.COUNT]. # ]]) # AT_CHECK([pspp ctables.sps]) # AT_CLEANUP AT_SETUP([CTABLES one categorical variable]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE qn1. CTABLES /TABLE BY qn1. CTABLES /TABLE BY BY qn1. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭────────────────────────────────────────────────────────────────────────┬─────╮ │ │Count│ ├────────────────────────────────────────────────────────────────────────┼─────┤ │ 1. How often do you usually drive a car or other Every day │ 4667│ │motor vehicle? Several days a week │ 1274│ │ Once a week or less │ 361│ │ Only certain times a │ 130│ │ year │ │ │ Never │ 540│ ╰────────────────────────────────────────────────────────────────────────┴─────╯ Custom Tables ╭──────────────────────────────────────────────────────────────────────────────╮ │ 1. How often do you usually drive a car or other motor vehicle? │ ├─────────┬──────────────────┬──────────────────┬────────────────────────┬─────┤ │ │ Several days a │ Once a week or │ Only certain times a │ │ │Every day│ week │ less │ year │Never│ ├─────────┼──────────────────┼──────────────────┼────────────────────────┼─────┤ │ Count │ Count │ Count │ Count │Count│ ├─────────┼──────────────────┼──────────────────┼────────────────────────┼─────┤ │ 4667│ 1274│ 361│ 130│ 540│ ╰─────────┴──────────────────┴──────────────────┴────────────────────────┴─────╯ Custom Tables Every day ╭─────╮ │Count│ ├─────┤ │ 4667│ ╰─────╯ ]) AT_CLEANUP AT_SETUP([CTABLES one scale variable]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE qnd1[COUNT, MEAN, STDDEV, MINIMUM, MAXIMUM]. CTABLES /TABLE BY qnd1. CTABLES /TABLE BY BY qnd1. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭──────────────────────────┬─────┬────┬─────────────┬───────┬───────╮ │ │Count│Mean│Std Deviation│Minimum│Maximum│ ├──────────────────────────┼─────┼────┼─────────────┼───────┼───────┤ │D1. AGE: What is your age?│ 6930│ 48│ 19│ 16│ 86│ ╰──────────────────────────┴─────┴────┴─────────────┴───────┴───────╯ Custom Tables ╭──────────────────────────╮ │D1. AGE: What is your age?│ ├──────────────────────────┤ │ Mean │ ├──────────────────────────┤ │ 48│ ╰──────────────────────────╯ Custom Tables D1. AGE: What is your age? ╭────╮ │Mean│ ├────┤ │ 48│ ╰────╯ ]) AT_CLEANUP AT_SETUP([CTABLES simple stacking]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE qn105ba + qn105bb + qn105bc + qn105bd BY qns3a [COLPCT PCT8.0]. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭───────────────────────────────────────────────────────────────┬──────────────╮ │ │ S3a. GENDER: │ │ ├──────┬───────┤ │ │ Male │ Female│ │ ├──────┼───────┤ │ │Column│ Column│ │ │ % │ % │ ├───────────────────────────────────────────────────────────────┼──────┼───────┤ │105b. How likely is it that drivers who have had Almost │ 10%│ 11%│ │too much to drink to drive safely will A. Get certain │ │ │ │stopped by the police? Very likely │ 21%│ 22%│ │ Somewhat │ 38%│ 42%│ │ likely │ │ │ │ Somewhat │ 21%│ 18%│ │ unlikely │ │ │ │ Very │ 10%│ 8%│ │ unlikely │ │ │ ├───────────────────────────────────────────────────────────────┼──────┼───────┤ │105b. How likely is it that drivers who have had Almost │ 14%│ 18%│ │too much to drink to drive safely will B. Have an certain │ │ │ │accident? Very likely │ 36%│ 45%│ │ Somewhat │ 39%│ 32%│ │ likely │ │ │ │ Somewhat │ 9%│ 4%│ │ unlikely │ │ │ │ Very │ 3%│ 2%│ │ unlikely │ │ │ ├───────────────────────────────────────────────────────────────┼──────┼───────┤ │105b. How likely is it that drivers who have had Almost │ 18%│ 16%│ │too much to drink to drive safely will C. Be certain │ │ │ │convicted for drunk driving? Very likely │ 32%│ 28%│ │ Somewhat │ 27%│ 32%│ │ likely │ │ │ │ Somewhat │ 15%│ 15%│ │ unlikely │ │ │ │ Very │ 9%│ 9%│ │ unlikely │ │ │ ├───────────────────────────────────────────────────────────────┼──────┼───────┤ │105b. How likely is it that drivers who have had Almost │ 16%│ 16%│ │too much to drink to drive safely will D. Be certain │ │ │ │arrested for drunk driving? Very likely │ 26%│ 27%│ │ Somewhat │ 32%│ 35%│ │ likely │ │ │ │ Somewhat │ 17%│ 15%│ │ unlikely │ │ │ │ Very │ 9%│ 7%│ │ unlikely │ │ │ ╰───────────────────────────────────────────────────────────────┴──────┴───────╯ ]) AT_CLEANUP AT_SETUP([CTABLES show or hide empty categories]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. IF (qn105ba = 2) qn105ba = 1. IF (qns3a = 1) qns3a = 2. CTABLES /TABLE qn105ba BY qns3a [COLPCT PCT8.0]. CTABLES /TABLE qn105ba BY qns3a [COLPCT PCT8.0] /CATEGORIES VAR=qn105ba EMPTY=EXCLUDE. CTABLES /TABLE qn105ba BY qns3a [COLPCT PCT8.0] /CATEGORIES VAR=qns3a EMPTY=EXCLUDE. CTABLES /TABLE qn105ba BY qns3a [COLPCT PCT8.0] /CATEGORIES VAR=ALL EMPTY=EXCLUDE. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭──────────────────────────────────────────────────────────────┬───────────────╮ │ │ S3a. GENDER: │ │ ├───────┬───────┤ │ │ Male │ Female│ │ ├───────┼───────┤ │ │ Column│ Column│ │ │ % │ % │ ├──────────────────────────────────────────────────────────────┼───────┼───────┤ │105b. How likely is it that drivers who have had Almost │ .│ 32%│ │too much to drink to drive safely will A. Get certain │ │ │ │stopped by the police? Very likely│ .│ 0%│ │ Somewhat │ .│ 40%│ │ likely │ │ │ │ Somewhat │ .│ 19%│ │ unlikely │ │ │ │ Very │ .│ 9%│ │ unlikely │ │ │ ╰──────────────────────────────────────────────────────────────┴───────┴───────╯ Custom Tables ╭──────────────────────────────────────────────────────────────┬───────────────╮ │ │ S3a. GENDER: │ │ ├───────┬───────┤ │ │ Male │ Female│ │ ├───────┼───────┤ │ │ Column│ Column│ │ │ % │ % │ ├──────────────────────────────────────────────────────────────┼───────┼───────┤ │105b. How likely is it that drivers who have had Almost │ .│ 32%│ │too much to drink to drive safely will A. Get certain │ │ │ │stopped by the police? Somewhat │ .│ 40%│ │ likely │ │ │ │ Somewhat │ .│ 19%│ │ unlikely │ │ │ │ Very │ .│ 9%│ │ unlikely │ │ │ ╰──────────────────────────────────────────────────────────────┴───────┴───────╯ Custom Tables ╭────────────────────────────────────────────────────────────────────┬─────────╮ │ │ S3a. │ │ │ GENDER: │ │ ├─────────┤ │ │ Female │ │ ├─────────┤ │ │ Column %│ ├────────────────────────────────────────────────────────────────────┼─────────┤ │105b. How likely is it that drivers who have had too Almost │ 32%│ │much to drink to drive safely will A. Get stopped by certain │ │ │the police? Very likely │ 0%│ │ Somewhat │ 40%│ │ likely │ │ │ Somewhat │ 19%│ │ unlikely │ │ │ Very │ 9%│ │ unlikely │ │ ╰────────────────────────────────────────────────────────────────────┴─────────╯ Custom Tables ╭────────────────────────────────────────────────────────────────────┬─────────╮ │ │ S3a. │ │ │ GENDER: │ │ ├─────────┤ │ │ Female │ │ ├─────────┤ │ │ Column %│ ├────────────────────────────────────────────────────────────────────┼─────────┤ │105b. How likely is it that drivers who have had too Almost │ 32%│ │much to drink to drive safely will A. Get stopped by certain │ │ │the police? Somewhat │ 40%│ │ likely │ │ │ Somewhat │ 19%│ │ unlikely │ │ │ Very │ 9%│ │ unlikely │ │ ╰────────────────────────────────────────────────────────────────────┴─────────╯ ]) AT_CLEANUP AT_SETUP([CTABLES simple nesting]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE (qn105ba + qn105bb + qn105bc + qn105bd) > qns3a [COUNT, TABLEPCT PCT8.0] /CATEGORIES VARIABLES=qns3a TOTAL=YES. CTABLES /TABLE qns3a > (qn105ba + qn105bb + qn105bc + qn105bd) [TABLEPCT PCT8.0] /CATEGORIES VARIABLES=qns3a TOTAL=YES /CLABELS ROW=OPPOSITE. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭─────────────────────────────────────────────────────────────────┬─────┬──────╮ │ │ │ Table│ │ │Count│ % │ ├─────────────────────────────────────────────────────────────────┼─────┼──────┤ │105b. How likely is it that drivers Almost S3a. Male │ 297│ 4%│ │who have had too much to drink to certain GENDER: Female│ 403│ 6%│ │drive safely will A. Get stopped by Total │ 700│ 10%│ │the police? ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 660│ 10%│ │ likely GENDER: Female│ 842│ 12%│ │ Total │ 1502│ 22%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 1174│ 17%│ │ likely GENDER: Female│ 1589│ 23%│ │ Total │ 2763│ 40%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 640│ 9%│ │ unlikely GENDER: Female│ 667│ 10%│ │ Total │ 1307│ 19%│ │ ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 311│ 5%│ │ unlikely GENDER: Female│ 298│ 4%│ │ Total │ 609│ 9%│ ├─────────────────────────────────────────────────────────────────┼─────┼──────┤ │105b. How likely is it that drivers Almost S3a. Male │ 429│ 6%│ │who have had too much to drink to certain GENDER: Female│ 671│ 10%│ │drive safely will B. Have an accident? Total │ 1100│ 16%│ │ ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 1104│ 16%│ │ likely GENDER: Female│ 1715│ 25%│ │ Total │ 2819│ 41%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 1203│ 17%│ │ likely GENDER: Female│ 1214│ 18%│ │ Total │ 2417│ 35%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 262│ 4%│ │ unlikely GENDER: Female│ 168│ 2%│ │ Total │ 430│ 6%│ │ ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 81│ 1%│ │ unlikely GENDER: Female│ 59│ 1%│ │ Total │ 140│ 2%│ ├─────────────────────────────────────────────────────────────────┼─────┼──────┤ │105b. How likely is it that drivers Almost S3a. Male │ 539│ 8%│ │who have had too much to drink to certain GENDER: Female│ 610│ 9%│ │drive safely will C. Be convicted for Total │ 1149│ 17%│ │drunk driving? ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 988│ 14%│ │ likely GENDER: Female│ 1049│ 15%│ │ Total │ 2037│ 30%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 822│ 12%│ │ likely GENDER: Female│ 1210│ 18%│ │ Total │ 2032│ 30%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 446│ 7%│ │ unlikely GENDER: Female│ 548│ 8%│ │ Total │ 994│ 15%│ │ ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 268│ 4%│ │ unlikely GENDER: Female│ 354│ 5%│ │ Total │ 622│ 9%│ ├─────────────────────────────────────────────────────────────────┼─────┼──────┤ │105b. How likely is it that drivers Almost S3a. Male │ 498│ 7%│ │who have had too much to drink to certain GENDER: Female│ 603│ 9%│ │drive safely will D. Be arrested for Total │ 1101│ 16%│ │drunk driving? ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 805│ 12%│ │ likely GENDER: Female│ 1029│ 15%│ │ Total │ 1834│ 27%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 975│ 14%│ │ likely GENDER: Female│ 1332│ 19%│ │ Total │ 2307│ 34%│ │ ╶──────────────────────────┼─────┼──────┤ │ Somewhat S3a. Male │ 535│ 8%│ │ unlikely GENDER: Female│ 560│ 8%│ │ Total │ 1095│ 16%│ │ ╶──────────────────────────┼─────┼──────┤ │ Very S3a. Male │ 270│ 4%│ │ unlikely GENDER: Female│ 279│ 4%│ │ Total │ 549│ 8%│ ╰─────────────────────────────────────────────────────────────────┴─────┴──────╯ Custom Tables ╭─────────────────────────────────┬────────┬──────┬─────────┬─────────┬────────╮ │ │ Almost │ Very │ Somewhat│ Somewhat│ Very │ │ │ certain│likely│ likely │ unlikely│unlikely│ │ ├────────┼──────┼─────────┼─────────┼────────┤ │ │ │ Table│ │ │ │ │ │ Table %│ % │ Table % │ Table % │ Table %│ ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │S3a. Male 105b. How likely │ 4%│ 10%│ 17%│ 9%│ 5%│ │GENDER: is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ A. Get stopped by │ │ │ │ │ │ │ the police? │ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Female 105b. How likely │ 6%│ 12%│ 23%│ 10%│ 4%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ A. Get stopped by │ │ │ │ │ │ │ the police? │ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Total 105b. How likely │ 10%│ 22%│ 40%│ 19%│ 9%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ A. Get stopped by │ │ │ │ │ │ │ the police? │ │ │ │ │ │ ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │S3a. Male 105b. How likely │ 6%│ 16%│ 17%│ 4%│ 1%│ │GENDER: is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ B. Have an │ │ │ │ │ │ │ accident? │ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Female 105b. How likely │ 10%│ 25%│ 18%│ 2%│ 1%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ B. Have an │ │ │ │ │ │ │ accident? │ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Total 105b. How likely │ 16%│ 41%│ 35%│ 6%│ 2%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ B. Have an │ │ │ │ │ │ │ accident? │ │ │ │ │ │ ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │S3a. Male 105b. How likely │ 8%│ 14%│ 12%│ 7%│ 4%│ │GENDER: is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ C. Be convicted │ │ │ │ │ │ │ for drunk driving?│ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Female 105b. How likely │ 9%│ 15%│ 18%│ 8%│ 5%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ C. Be convicted │ │ │ │ │ │ │ for drunk driving?│ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Total 105b. How likely │ 17%│ 30%│ 30%│ 15%│ 9%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ C. Be convicted │ │ │ │ │ │ │ for drunk driving?│ │ │ │ │ │ ├─────────────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │S3a. Male 105b. How likely │ 7%│ 12%│ 14%│ 8%│ 4%│ │GENDER: is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ D. Be arrested for│ │ │ │ │ │ │ drunk driving? │ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Female 105b. How likely │ 9%│ 15%│ 19%│ 8%│ 4%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ D. Be arrested for│ │ │ │ │ │ │ drunk driving? │ │ │ │ │ │ │ ╶─────────────────────────┼────────┼──────┼─────────┼─────────┼────────┤ │ Total 105b. How likely │ 16%│ 27%│ 34%│ 16%│ 8%│ │ is it that drivers│ │ │ │ │ │ │ who have had too │ │ │ │ │ │ │ much to drink to │ │ │ │ │ │ │ drive safely will │ │ │ │ │ │ │ D. Be arrested for│ │ │ │ │ │ │ drunk driving? │ │ │ │ │ │ ╰─────────────────────────────────┴────────┴──────┴─────────┴─────────┴────────╯ ]) AT_CLEANUP AT_SETUP([CTABLES nesting and scale variables]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE=qnd1 > qn1 BY qns3a. CTABLES /TABLE=qnd1 [MINIMUM, MAXIMUM, MEAN] > qns3a > (qn26 + qn27). CTABLES /TABLE=qnsa1 > qn105ba [COLPCT] BY qns1 /CATEGORIES VAR=qnsa1 EMPTY=EXCLUDE. CTABLES /TABLE=AgeGroup > qn20 [MEAN F8.1, STDDEV F8.1]. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭─────────────────────────────────────────────────────────────────┬────────────╮ │ │S3a. GENDER:│ │ ├─────┬──────┤ │ │ Male│Female│ │ ├─────┼──────┤ │ │ Mean│ Mean │ ├─────────────────────────────────────────────────────────────────┼─────┼──────┤ │D1. AGE: What 1. How often do you usually drive Every day │ 46│ 46│ │is your age? a car or other motor vehicle? Several days a │ 51│ 59│ │ week │ │ │ │ Once a week or │ 44│ 54│ │ less │ │ │ │ Only certain │ 34│ 41│ │ times a year │ │ │ │ Never │ 39│ 55│ ╰─────────────────────────────────────────────────────────────────┴─────┴──────╯ Custom Tables ╭─────────────────────────────────────────────────────────┬───────┬───────┬────╮ │ │Minimum│Maximum│Mean│ ├─────────────────────────────────────────────────────────┼───────┼───────┼────┤ │D1. AGE: S3a. Male 26. During the last 12 Yes│ 16│ 86│ 42│ │What is GENDER: months, has there been a │ │ │ │ │your time when you felt you │ │ │ │ │age? should cut down on your No │ 16│ 86│ 46│ │ drinking? │ │ │ │ │ ╶───────────────────────────────────────┼───────┼───────┼────┤ │ Female 26. During the last 12 Yes│ 16│ 86│ 43│ │ months, has there been a │ │ │ │ │ time when you felt you │ │ │ │ │ should cut down on your No │ 16│ 86│ 48│ │ drinking? │ │ │ │ ├─────────────────────────────────────────────────────────┼───────┼───────┼────┤ │D1. AGE: S3a. Male 27. During the last 12 Yes│ 16│ 86│ 38│ │What is GENDER: months, has there been a │ │ │ │ │your time when people criticized No │ 16│ 86│ 46│ │age? your drinking? │ │ │ │ │ ╶───────────────────────────────────────┼───────┼───────┼────┤ │ Female 27. During the last 12 Yes│ 17│ 69│ 37│ │ months, has there been a │ │ │ │ │ time when people criticized No │ 16│ 86│ 48│ │ your drinking? │ │ │ │ ╰─────────────────────────────────────────────────────────┴───────┴───────┴────╯ Custom Tables ╭─────────────────────────────┬────────────────────────────────────────────────╮ │ │S1. Including yourself, how many members of this│ │ │ household are age 16 or older? │ │ ├──────┬──────┬──────┬──────┬──────┬──────┬──────┤ │ │ │ │ │ │ │ │ 6 or │ │ │ None │ 1 │ 2 │ 3 │ 4 │ 5 │ more │ │ ├──────┼──────┼──────┼──────┼──────┼──────┼──────┤ │ │Column│Column│Column│Column│Column│Column│Column│ │ │ % │ % │ % │ % │ % │ % │ % │ ├─────────────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┤ │Sa1. RDD 105b. Almost │ .│ 9.5%│ 8.2%│ 12.4%│ 9.9%│ 20.0%│ 23.8%│ │SAMPLE How certain │ │ │ │ │ │ │ │ │SOURCE: likely │ │ │ │ │ │ │ │ │ is it Very │ .│ 24.9%│ 18.5%│ 24.0%│ 26.6%│ 25.5%│ 33.3%│ │ that likely │ │ │ │ │ │ │ │ │ drivers │ │ │ │ │ │ │ │ │ who have │ │ │ │ │ │ │ │ │ had too Somewhat│ .│ 38.3%│ 41.9%│ 38.6%│ 37.5%│ 36.4%│ 23.8%│ │ much to likely │ │ │ │ │ │ │ │ │ drink to │ │ │ │ │ │ │ │ │ drive │ │ │ │ │ │ │ │ │ safely Somewhat│ .│ 18.1%│ 21.7%│ 16.8%│ 16.7%│ 10.9%│ 9.5%│ │ will A. unlikely│ │ │ │ │ │ │ │ │ Get │ │ │ │ │ │ │ │ │ stopped Very │ .│ 9.2%│ 9.7%│ 8.2%│ 9.4%│ 7.3%│ 9.5%│ │ by the unlikely│ │ │ │ │ │ │ │ │ police? │ │ │ │ │ │ │ │ ╰─────────────────────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────╯ Custom Tables ╭──────────────────────────────────────────────────────────────┬────┬──────────╮ │ │ │ Std │ │ │Mean│ Deviation│ ├──────────────────────────────────────────────────────────────┼────┼──────────┤ │Age 16 to 25 20. On how many of the thirty days in this │ 5.2│ 6.0│ │group typical month did you have one or more │ │ │ │ alcoholic beverages to drink? │ │ │ │ ╶───────────────────────────────────────────────────────┼────┼──────────┤ │ 26 to 35 20. On how many of the thirty days in this │ 4.7│ 5.9│ │ typical month did you have one or more │ │ │ │ alcoholic beverages to drink? │ │ │ │ ╶───────────────────────────────────────────────────────┼────┼──────────┤ │ 36 to 45 20. On how many of the thirty days in this │ 5.5│ 6.8│ │ typical month did you have one or more │ │ │ │ alcoholic beverages to drink? │ │ │ │ ╶───────────────────────────────────────────────────────┼────┼──────────┤ │ 46 to 55 20. On how many of the thirty days in this │ 5.8│ 7.7│ │ typical month did you have one or more │ │ │ │ alcoholic beverages to drink? │ │ │ │ ╶───────────────────────────────────────────────────────┼────┼──────────┤ │ 56 to 65 20. On how many of the thirty days in this │ 6.3│ 8.2│ │ typical month did you have one or more │ │ │ │ alcoholic beverages to drink? │ │ │ │ ╶───────────────────────────────────────────────────────┼────┼──────────┤ │ 66 or 20. On how many of the thirty days in this │ 7.1│ 9.2│ │ older typical month did you have one or more │ │ │ │ alcoholic beverages to drink? │ │ │ ╰──────────────────────────────────────────────────────────────┴────┴──────────╯ ]) AT_CLEANUP AT_SETUP([CTABLES SLABELS]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE qn1 [COUNT COLPCT]. CTABLES /TABLE qn1 [COUNT COLPCT] /SLABELS POSITION=ROW. CTABLES /TABLE qn1 [COUNT COLPCT] /SLABELS POSITION=ROW VISIBLE=NO. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭────────────────────────────────────────────────────────────────┬─────┬───────╮ │ │ │ Column│ │ │Count│ % │ ├────────────────────────────────────────────────────────────────┼─────┼───────┤ │ 1. How often do you usually drive a car or Every day │ 4667│ 66.9%│ │other motor vehicle? Several days a week│ 1274│ 18.3%│ │ Once a week or less│ 361│ 5.2%│ │ Only certain times │ 130│ 1.9%│ │ a year │ │ │ │ Never │ 540│ 7.7%│ ╰────────────────────────────────────────────────────────────────┴─────┴───────╯ Custom Tables ╭────────────────────────────────────────────────────────────────────────┬─────╮ │ 1. How often do you usually drive a car or Every day Count │ 4667│ │other motor vehicle? Column │66.9%│ │ % │ │ │ ╶───────────────────────────┼─────┤ │ Several days a week Count │ 1274│ │ Column │18.3%│ │ % │ │ │ ╶───────────────────────────┼─────┤ │ Once a week or less Count │ 361│ │ Column │ 5.2%│ │ % │ │ │ ╶───────────────────────────┼─────┤ │ Only certain times Count │ 130│ │ a year Column │ 1.9%│ │ % │ │ │ ╶───────────────────────────┼─────┤ │ Never Count │ 540│ │ Column │ 7.7%│ │ % │ │ ╰────────────────────────────────────────────────────────────────────────┴─────╯ Custom Tables ╭────────────────────────────────────────────────────────────────────────┬─────╮ │ 1. How often do you usually drive a car or other Every day │ 4667│ │motor vehicle? │66.9%│ │ Several days a week │ 1274│ │ │18.3%│ │ Once a week or less │ 361│ │ │ 5.2%│ │ Only certain times a │ 130│ │ year │ 1.9%│ │ Never │ 540│ │ │ 7.7%│ ╰────────────────────────────────────────────────────────────────────────┴─────╯ ]) AT_CLEANUP AT_SETUP([CTABLES simple totals]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE=qn17 /CATEGORIES VARIABLES=qn17 TOTAL=YES LABEL='Number responding'. CTABLES /TABLE=region > qn18 [MEAN, COUNT] /CATEGORIES VARIABLES=region TOTAL=YES LABEL='All regions'. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables ╭────────────────────────────────────────────────────────────────────────┬─────╮ │ │Count│ ├────────────────────────────────────────────────────────────────────────┼─────┤ │17. When you drink alcoholic beverages, which ONE of OR, something else│ 2│ │the following beverages do you drink MOST OFTEN? Beer │ 1073│ │ Light beer │ 620│ │ Wine │ 1418│ │ Wine coolers │ 137│ │ Hard liquor or │ 888│ │ mixed drinks │ │ │ Flavored malt │ 83│ │ drinks │ │ │ Number responding │ 4221│ ╰────────────────────────────────────────────────────────────────────────┴─────╯ Custom Tables ╭───────────────────────────────────────────────────────────────────┬────┬─────╮ │ │Mean│Count│ ├───────────────────────────────────────────────────────────────────┼────┼─────┤ │Region NE 18. When you drink ANSWERFROM(QN17R1), about how │4.36│ 949│ │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │ │ sitting? │ │ │ │ ╶────────────────────────────────────────────────────────────┼────┼─────┤ │ MW 18. When you drink ANSWERFROM(QN17R1), about how │4.67│ 1027│ │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │ │ sitting? │ │ │ │ ╶────────────────────────────────────────────────────────────┼────┼─────┤ │ S 18. When you drink ANSWERFROM(QN17R1), about how │4.71│ 1287│ │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │ │ sitting? │ │ │ │ ╶────────────────────────────────────────────────────────────┼────┼─────┤ │ W 18. When you drink ANSWERFROM(QN17R1), about how │4.69│ 955│ │ many ANSWERFROM(QN17R2) do you usually drink per │ │ │ │ sitting? │ │ │ │ ╶────────────────────────────────────────────────────────────┼────┼─────┤ │ All 18. When you drink ANSWERFROM(QN17R1), about how │4.62│ 4218│ │ regions many ANSWERFROM(QN17R2) do you usually drink per │ │ │ │ sitting? │ │ │ ╰───────────────────────────────────────────────────────────────────┴────┴─────╯ ]) AT_CLEANUP AT_SETUP([CTABLES subtotals]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE=qn105ba BY qns1 /CATEGORIES VARIABLES=qns1 [1, 2, SUBTOTAL, 3, 4, 5, SUBTOTAL]. CTABLES /TABLE=qn105ba [COLPCT] BY qns1 /CATEGORIES VARIABLES=qn105ba [1, 2, 3, SUBTOTAL, 4, 5, SUBTOTAL]. CTABLES /TABLE=qn105ba BY qns1 /CATEGORIES VARIABLES=qn105ba [1, 2, 3, SUBTOTAL, 4, 5, SUBTOTAL] /CATEGORIES VARIABLES=qns1 [1, 2, SUBTOTAL, 3, 4, 5, SUBTOTAL]. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=120], [0], [dnl Custom Tables ╭─────────────────────────────────────────────────────────┬────────────────────────────────────────────────────────────╮ │ │ S1. Including yourself, how many members of this household │ │ │ are age 16 or older? │ │ ├───────┬───────┬─────────┬───────┬────────┬──────┬──────────┤ │ │ 1 │ 2 │ Subtotal│ 3 │ 4 │ 5 │ Subtotal │ │ ├───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤ │ │ Count │ Count │ Count │ Count │ Count │ Count│ Count │ ├─────────────────────────────────────────────────────────┼───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤ │105b. How likely is it that drivers who have Almost │ 147│ 246│ 393│ 62│ 19│ 11│ 92│ │had too much to drink to drive safely will A. certain │ │ │ │ │ │ │ │ │Get stopped by the police? Very likely│ 384│ 552│ 936│ 120│ 51│ 14│ 185│ │ Somewhat │ 590│ 1249│ 1839│ 193│ 72│ 20│ 285│ │ likely │ │ │ │ │ │ │ │ │ Somewhat │ 278│ 647│ 925│ 84│ 32│ 6│ 122│ │ unlikely │ │ │ │ │ │ │ │ │ Very │ 141│ 290│ 431│ 41│ 18│ 4│ 63│ │ unlikely │ │ │ │ │ │ │ │ ╰─────────────────────────────────────────────────────────┴───────┴───────┴─────────┴───────┴────────┴──────┴──────────╯ Custom Tables ╭────────────────────────────────────────────────────────┬─────────────────────────────────────────────────────────────╮ │ │ S1. Including yourself, how many members of this household │ │ │ are age 16 or older? │ │ ├────────┬────────┬────────┬────────┬───────┬────────┬────────┤ │ │ │ │ │ │ │ │ 6 or │ │ │ None │ 1 │ 2 │ 3 │ 4 │ 5 │ more │ │ ├────────┼────────┼────────┼────────┼───────┼────────┼────────┤ │ │ │ │ │ │ Column│ │ │ │ │Column %│Column %│Column %│Column %│ % │Column %│Column %│ ├────────────────────────────────────────────────────────┼────────┼────────┼────────┼────────┼───────┼────────┼────────┤ │105b. How likely is it that drivers who have Almost │ .│ 9.5%│ 8.2%│ 12.4%│ 9.9%│ 20.0%│ 23.8%│ │had too much to drink to drive safely will certain │ │ │ │ │ │ │ │ │A. Get stopped by the police? Very likely│ .│ 24.9%│ 18.5%│ 24.0%│ 26.6%│ 25.5%│ 33.3%│ │ Somewhat │ .│ 38.3%│ 41.9%│ 38.6%│ 37.5%│ 36.4%│ 23.8%│ │ likely │ │ │ │ │ │ │ │ │ Subtotal │ │ 72.8%│ 68.6%│ 75.0%│ 74.0%│ 81.8%│ 81.0%│ │ Somewhat │ .│ 18.1%│ 21.7%│ 16.8%│ 16.7%│ 10.9%│ 9.5%│ │ unlikely │ │ │ │ │ │ │ │ │ Very │ .│ 9.2%│ 9.7%│ 8.2%│ 9.4%│ 7.3%│ 9.5%│ │ unlikely │ │ │ │ │ │ │ │ │ Subtotal │ │ 27.2%│ 31.4%│ 25.0%│ 26.0%│ 18.2%│ 19.0%│ ╰────────────────────────────────────────────────────────┴────────┴────────┴────────┴────────┴───────┴────────┴────────╯ Custom Tables ╭─────────────────────────────────────────────────────────┬────────────────────────────────────────────────────────────╮ │ │ S1. Including yourself, how many members of this household │ │ │ are age 16 or older? │ │ ├───────┬───────┬─────────┬───────┬────────┬──────┬──────────┤ │ │ 1 │ 2 │ Subtotal│ 3 │ 4 │ 5 │ Subtotal │ │ ├───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤ │ │ Count │ Count │ Count │ Count │ Count │ Count│ Count │ ├─────────────────────────────────────────────────────────┼───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤ │105b. How likely is it that drivers who have Almost │ 147│ 246│ 393│ 62│ 19│ 11│ 92│ │had too much to drink to drive safely will A. certain │ │ │ │ │ │ │ │ │Get stopped by the police? Very likely│ 384│ 552│ 936│ 120│ 51│ 14│ 185│ │ Somewhat │ 590│ 1249│ 1839│ 193│ 72│ 20│ 285│ │ likely │ │ │ │ │ │ │ │ │ Subtotal │ 1121│ 2047│ 3168│ 375│ 142│ 45│ 562│ │ Somewhat │ 278│ 647│ 925│ 84│ 32│ 6│ 122│ │ unlikely │ │ │ │ │ │ │ │ │ Very │ 141│ 290│ 431│ 41│ 18│ 4│ 63│ │ unlikely │ │ │ │ │ │ │ │ │ Subtotal │ 419│ 937│ 1356│ 125│ 50│ 10│ 185│ ╰─────────────────────────────────────────────────────────┴───────┴───────┴─────────┴───────┴────────┴──────┴──────────╯ ]) AT_CLEANUP AT_SETUP([CTABLES PCOMPUTE]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /PCOMPUTE &x=EXPR([3] + [4]) /PCOMPUTE &y=EXPR([4] + [5]) /PPROPERTIES &x LABEL='3+4' HIDESOURCECATS=YES /PPROPERTIES &y LABEL='4+5' /TABLE=qn105ba BY qns1 /CATEGORIES VARIABLES=qns1 [1, 2, SUBTOTAL, 3, 4, 5, &x, &y, SUBTOTAL] ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=120], [0], [dnl Custom Tables ╭─────────────────────────────────────────────────────────┬────────────────────────────────────────────────────────────╮ │ │ S1. Including yourself, how many members of this household │ │ │ are age 16 or older? │ │ ├───────┬───────┬─────────┬───────┬────────┬──────┬──────────┤ │ │ 1 │ 2 │ Subtotal│ 5 │ 3+4 │ 4+5 │ Subtotal │ │ ├───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤ │ │ Count │ Count │ Count │ Count │ Count │ Count│ Count │ ├─────────────────────────────────────────────────────────┼───────┼───────┼─────────┼───────┼────────┼──────┼──────────┤ │105b. How likely is it that drivers who have Almost │ 147│ 246│ 393│ 11│ 81│ 30│ 92│ │had too much to drink to drive safely will A. certain │ │ │ │ │ │ │ │ │Get stopped by the police? Very likely│ 384│ 552│ 936│ 14│ 171│ 65│ 185│ │ Somewhat │ 590│ 1249│ 1839│ 20│ 265│ 92│ 285│ │ likely │ │ │ │ │ │ │ │ │ Somewhat │ 278│ 647│ 925│ 6│ 116│ 38│ 122│ │ unlikely │ │ │ │ │ │ │ │ │ Very │ 141│ 290│ 431│ 4│ 59│ 22│ 63│ │ unlikely │ │ │ │ │ │ │ │ ╰─────────────────────────────────────────────────────────┴───────┴───────┴─────────┴───────┴────────┴──────┴──────────╯ ]) AT_CLEANUP