AT_BANNER([CTABLES]) dnl Features not yet tested: dnl - Preprocessing to distinguish categorical from scale. dnl - String variables and values dnl - Testing details of missing value handling in summaries. dnl - test CLABELS ROWLABELS=LAYER. dnl - Test VLABELS. dnl - Test WEIGHT and adjustment weights. dnl - EMPTY=INCLUDE For string ranges. dnl - Summary functions: dnl * Separate summary functions for totals and subtotals. dnl * )CILEVEL in summary label specification dnl Category sorting: dnl * VALUE dnl * LABEL dnl * ascending/descending dnl - CATEGORIES: dnl * String values dnl * Date values dnl * THRU (numeric ranges) dnl * THRU (string ranges) dnl * OTHERNM dnl - FORMAT: dnl * MINCOLWIDTH, MAXCOLWIDTH, UNITS. dnl * EMPTY. dnl * MISSING. dnl - HIDESMALLCOUNTS. dnl - Date/time variables and values dnl - Special formats for summary functions: NEGPAREN, NEQUAL, PAREN, PCTPAREN. dnl - TITLES: )DATE, )TIME, )TABLE. dnl - Test PCOMPUTE: dnl * PCOMPUTE for more than one kind of summary (e.g. [COUNT, ROWPCT]). dnl * MISSING, OTHERNM dnl * strings and string ranges dnl * multi-dimensional (multiple CCT_POSTCOMPUTE in one cell) dnl * dates dnl - PPROPERTIES: dnl * )LABEL[N]. dnl - Summary functions: dnl * U-prefix for unweighted summaries. dnl * areaPCT.SUM and UareaPCT.SUM functions. dnl - SPLIT FILE with SEPARATE splits dnl - Definition of columns/rows when labels are rotated from one axis to another. dnl dnl Not for v1: dnl - Multiple response sets dnl - MRSETS subcommand. dnl - CATEGORIES: Special case for explicit category specifications and multiple dichotomy sets. dnl - SIGTEST dnl - COMPARETEST dnl - Summary functions: dnl * .LCL and .UCL suffixes. dnl * .SE suffixes. dnl - CATEGORIES: dnl * Data-dependent sorting. dnl 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_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /FORMAT MINCOLWIDTH=10 MAXCOLWIDTH=20 UNITS=POINTS EMPTY=ZERO MISSING="x" /FORMAT MINCOLWIDTH=DEFAULT MAXCOLWIDTH=DEFAULT UNITS=INCHES EMPTY=BLANK MISSING="." /FORMAT UNITS=CM EMPTY="(-)" /VLABELS VARIABLES=qn1 DISPLAY=DEFAULT /VLABELS VARIABLES=qn17 DISPLAY=NAME /VLABELS VARIABLES=qns3a DISPLAY=LABEL /VLABELS VARIABLES=qnd1 DISPLAY=BOTH /VLABELS VARIABLES=qn20 DISPLAY=NONE /MRSETS COUNTDUPLICATES=NO /MRSETS COUNTDUPLICATES=YES /SMISSING VARIABLE /SMISSING LISTWISE /WEIGHT VARIABLE=qns3a /HIDESMALLCOUNTS /HIDESMALLCOUNTS COUNT=10 /TABLE qnsa1 /SLABELS POSITION=COLUMN VISIBLE=YES /SLABELS VISIBLE=NO POSITION=ROW /SLABELS POSITION=LAYER /CLABELS AUTO /CLABELS ROWLABELS=OPPOSITE /CRITERIA CILEVEL=50 /CATEGORIES VARIABLES=qn1 qn17 ORDER=A KEY=VALUE MISSING=INCLUDE TOTAL=YES LABEL="xyzzy" POSITION=BEFORE EMPTY=INCLUDE. CTABLES /TABLE qnsa1 /CLABELS ROWLABELS=LAYER. CTABLES /TABLE qnsa1 /CLABELS COLLABELS=OPPOSITE. CTABLES /TABLE qnsa1 /CLABELS COLLABELS=LAYER. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [0], [dnl Custom Tables Count ╭───────────────────┬────┬────╮ │ │ RDD│CELL│ ├───────────────────┼────┼────┤ │Sa1. SAMPLE SOURCE:│5392│1607│ ╰───────────────────┴────┴────╯ Custom Tables RDD ╭───────────────────┬─────╮ │ │Count│ ├───────────────────┼─────┤ │Sa1. SAMPLE SOURCE:│ 5392│ ╰───────────────────┴─────╯ Custom Tables ╭────────────────────────┬─────╮ │ │Count│ ├────────────────────────┼─────┤ │Sa1. SAMPLE SOURCE: RDD │ 5392│ │ CELL│ 1607│ ╰────────────────────────┴─────╯ Custom Tables ╭────────────────────────┬─────╮ │ │Count│ ├────────────────────────┼─────┤ │Sa1. SAMPLE SOURCE: RDD │ 5392│ │ CELL│ 1607│ ╰────────────────────────┴─────╯ ]) AT_CLEANUP AT_SETUP([CTABLES parsing - negative]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES. CTABLES /FORMAT MINCOLWIDTH='foo'. CTABLES /TABLE qn1 [**]. CTABLES /TABLE qn1 [NOTAFUNCTION]. CTABLES /TABLE (qn1. CTABLES /TABLE **. CTABLES /TABLE NOTAVAR. STRING string(A8). CTABLES /TABLE string[S]. CTABLES /TABLE qn1 [PTILE 101]. CTABLES /TABLE qn1 [MEAN F0.1]. CTABLES /TABLE qn1 [MEAN NEGPAREN1.2]. CTABLES /TABLE qn1 [MEAN NEGPAREN3.4]. CTABLES /TABLE qn1 [MEAN TOTALS]. CTABLES /TABLE qn1 [MEAN TOTALS[STDDEV]%]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [SUBTOTAL=x]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [LO **]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [LO THRU x]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [1 THRU **]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 ['x' THRU **]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&**]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&x]. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 KEY=PTILE(qn1, 101). CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 KEY=MEAN(qn1. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 KEY=MEAN. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 MISSING=**. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 TOTAL=**. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 LABEL=**. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 POSITION=**. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 EMPTY=**. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 **. CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [1,2,3] **. CTABLES /PCOMPUTE &k=EXPR(SUBTOTAL[0]). CTABLES /PCOMPUTE &k=EXPR(SUBTOTAL[1**]). CTABLES /PCOMPUTE &k=EXPR([LO **]). CTABLES /PCOMPUTE &k=EXPR([LO THRU **]). CTABLES /PCOMPUTE &k=EXPR([1 THRU **]). CTABLES /PCOMPUTE &k=EXPR([1**]). CTABLES /PCOMPUTE &k=EXPR((1x)). CTABLES /PCOMPUTE **k. CTABLES /PCOMPUTE &1. CTABLES /PCOMPUTE &k**. CTABLES /PCOMPUTE &k=**. CTABLES /PCOMPUTE &k=EXPR**. CTABLES /PCOMPUTE &k=EXPR(1x). CTABLES /PCOMPUTE &k=EXPR(1) /PCOMPUTE &k=EXPR(2). CTABLES /PCOMPUTE &k=EXPR(1) /PPROPERTIES &k FORMAT=NOTAFUNCTION. CTABLES /PCOMPUTE &k=EXPR(1) /PPROPERTIES &k FORMAT=PTILE **. CTABLES /PCOMPUTE &k=EXPR(1) /PPROPERTIES &k LABEL=**. CTABLES /PCOMPUTE &k=EXPR(1) /PPROPERTIES &k HIDESOURCECATS=**. CTABLES /PCOMPUTE &k=EXPR(1) /PPROPERTIES &k **. CTABLES /FORMAT EMPTY=**. CTABLES /FORMAT MISSING=**. CTABLES /FORMAT **. CTABLES /FORMAT MINCOLWIDTH=20 MAXCOLWIDTH=10/. CTABLES /VLABELS **. CTABLES /VLABELS VARIABLES=NOTAVAR. CTABLES /VLABELS VARIABLES=qn1 **. CTABLES /VLABELS VARIABLES=qn1 DISPLAY=**. CTABLES /MRSETS **. CTABLES /MRSETS COUNTDUPLICATES=**. CTABLES /SMISSING **. CTABLES /WEIGHT **. CTABLES /WEIGHT VARIABLE=NOTAVAR. CTABLES /HIDESMALLCOUNTS COUNT=1. CTABLES /QUUX. CTABLES /HIDESMALLCOUNTS COUNT=2. CTABLES /TABLE qn1**. CTABLES /TABLE qn1 /SLABELS POSITION=**. CTABLES /TABLE qn1 /SLABELS VISIBLE=**. CTABLES /TABLE qn1 /SLABELS **. CTABLES /TABLE qn1 /CLABELS ROWLABELS=**. CTABLES /TABLE qn1 /CLABELS COLLABELS=**. CTABLES /TABLE qn1 /CLABELS **. CTABLES /TABLE qn1 /CRITERIA **. CTABLES /TABLE qn1 /CRITERIA CILEVEL=101. CTABLES /TABLE qn1 /TITLES **. CTABLES /TABLE qn1 /SIGTEST TYPE=**. CTABLES /TABLE qn1 /SIGTEST ALPHA=**. CTABLES /TABLE qn1 /SIGTEST INCLUDEMRSETS=**. CTABLES /TABLE qn1 /SIGTEST CATEGORIES=**. CTABLES /TABLE qn1 /SIGTEST **. CTABLES /TABLE qn1 /COMPARETEST TYPE=**. CTABLES /TABLE qn1 /COMPARETEST ALPHA=**. CTABLES /TABLE qn1 /COMPARETEST ALPHA=0,5. CTABLES /TABLE qn1 /COMPARETEST ADJUST=**. CTABLES /TABLE qn1 /COMPARETEST INCLUDEMRSETS=**. CTABLES /TABLE qn1 /COMPARETEST MEANSVARIANCE=**. CTABLES /TABLE qn1 /COMPARETEST CATEGORIES=**. CTABLES /TABLE qn1 /COMPARETEST MERGE=**. CTABLES /TABLE qn1 /COMPARETEST STYLE=**. CTABLES /TABLE qn1 /COMPARETEST SHOWSIG=**. CTABLES /TABLE qn1 /COMPARETEST **. CTABLES /TABLE qn1 / **. CTABLES /TABLE qn1 /CLABELS ROWLABELS=OPPOSITE /CLABELS COLLABELS=OPPOSITE. CTABLES /TABLE qn20 > qnd1. CTABLES /TABLE qn1 [ROWPCT] > qnsa1. NUMERIC datetime (DATETIME17.0). CTABLES /TABLE qn1 /CATEGORIES VARIABLES=datetime ['123']. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [1], [[ctables.sps:2.8: error: CTABLES: Syntax error at end of command: expecting `/'. ctables.sps:3.29-3.33: error: CTABLES: Syntax error at `'foo'': Expected non- negative number for MINCOLWIDTH. ctables.sps:4.21-4.22: error: CTABLES: Syntax error at `**': expecting identifier. ctables.sps:5.21-5.32: error: CTABLES: Syntax error at `NOTAFUNCTION': Expecting summary function name. ctables.sps:6.20: error: CTABLES: Syntax error at end of command: expecting `@:}@'. ctables.sps:7.16-7.17: error: CTABLES: Syntax error at `**': expecting identifier. ctables.sps:8: error: CTABLES: NOTAVAR is not a variable name. ctables.sps:10.16-10.24: error: CTABLES: Cannot use string variable string as a scale variable. 10 | CTABLES /TABLE string[S]. | ^~~~~~~~~ ctables.sps:11.27-11.29: error: CTABLES: Syntax error at `101': Expected number between 0 and 100 for PTILE. ctables.sps:12: error: CTABLES: Output format F0.1 specifies width 0, but F requires a width between 1 and 40. ctables.sps:13.26-13.36: error: CTABLES: Syntax error at `NEGPAREN1.2': Output format NEGPAREN requires width 2 or greater. ctables.sps:14.26-14.36: error: CTABLES: Syntax error at `NEGPAREN3.4': Output format NEGPAREN requires width greater than decimals. ctables.sps:15.21-15.24: error: CTABLES: Summary function MEAN applies only to scale variables. 15 | CTABLES /TABLE qn1 [MEAN TOTALS]. | ^~~~ ctables.sps:15.16-15.18: note: CTABLES: 'QN1' is not a scale variable. 15 | CTABLES /TABLE qn1 [MEAN TOTALS]. | ^~~ ctables.sps:15.32: error: CTABLES: Syntax error at `@:>@': expecting `@<:@'. ctables.sps:16.21-16.24: error: CTABLES: Summary function MEAN applies only to scale variables. 16 | CTABLES /TABLE qn1 [MEAN TOTALS[STDDEV]%]. | ^~~~ ctables.sps:16.16-16.18: note: CTABLES: 'QN1' is not a scale variable. 16 | CTABLES /TABLE qn1 [MEAN TOTALS[STDDEV]%]. | ^~~ ctables.sps:16.40: error: CTABLES: Syntax error at `%': expecting `@:>@'. ctables.sps:17.56: error: CTABLES: Syntax error at `x': expecting string. ctables.sps:18.50-18.51: error: CTABLES: Syntax error at `**': expecting THRU. ctables.sps:19.55: error: CTABLES: Syntax error at `x': expecting number. ctables.sps:20.54-20.55: error: CTABLES: Syntax error at `**': expecting number. ctables.sps:21.56-21.57: error: CTABLES: Syntax error at `**': expecting string. ctables.sps:22.48-22.49: error: CTABLES: Syntax error at `**': expecting identifier. ctables.sps:23.47-23.48: error: CTABLES: Unknown postcompute &x. 23 | CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&x]. | ^~ ctables.sps:24.61-24.63: error: CTABLES: Syntax error at `101': Expected number between 0 and 100 for PTILE. ctables.sps:25.58: error: CTABLES: Syntax error at end of command: expecting `@:}@'. ctables.sps:26.54: error: CTABLES: Syntax error at end of command: expecting `@{:@'. ctables.sps:27.54-27.55: error: CTABLES: Syntax error at `**': expecting INCLUDE or EXCLUDE. ctables.sps:28.52-28.53: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:29.52-29.53: error: CTABLES: Syntax error at `**': expecting string. ctables.sps:30.55-30.56: error: CTABLES: Syntax error at `**': expecting BEFORE or AFTER. ctables.sps:31.52-31.53: error: CTABLES: Syntax error at `**': expecting INCLUDE or EXCLUDE. ctables.sps:32.46-32.47: error: CTABLES: Syntax error at `**': expecting ORDER, KEY, MISSING, TOTAL, LABEL, POSITION, or EMPTY. ctables.sps:33.54-33.55: error: CTABLES: Syntax error at `**': expecting TOTAL, LABEL, POSITION, or EMPTY. ctables.sps:34.36: error: CTABLES: Syntax error at `0': Expected positive integer for SUBTOTAL. ctables.sps:35.37-35.38: error: CTABLES: Syntax error at `**': expecting `@:>@'. ctables.sps:36.31-36.32: error: CTABLES: Syntax error at `**': expecting THRU. ctables.sps:37.36-37.37: error: CTABLES: Syntax error at `**': expecting number. ctables.sps:38.35-38.36: error: CTABLES: Syntax error at `**': expecting number. ctables.sps:39.29-39.30: error: CTABLES: Syntax error at `**': expecting `@:>@'. ctables.sps:40.29: error: CTABLES: Syntax error at `x': expecting `@:}@'. ctables.sps:41.19-41.20: error: CTABLES: Syntax error at `**': expecting &. ctables.sps:42.20: error: CTABLES: Syntax error at `1': expecting identifier. ctables.sps:43.21-43.22: error: CTABLES: Syntax error at `**': expecting `='. ctables.sps:44.22-44.23: error: CTABLES: Syntax error at `**': expecting EXPR. ctables.sps:45.26-45.27: error: CTABLES: Syntax error at `**': expecting `('. ctables.sps:46.28: error: CTABLES: Syntax error at `x': expecting `)'. ctables.sps:47.31-47.49: warning: CTABLES: New definition of &k will override the previous definition. 47 | CTABLES /PCOMPUTE &k=EXPR(1) /PCOMPUTE &k=EXPR(2). | ^~~~~~~~~~~~~~~~~~~ ctables.sps:47.10-47.28: note: CTABLES: This is the previous definition. 47 | CTABLES /PCOMPUTE &k=EXPR(1) /PCOMPUTE &k=EXPR(2). | ^~~~~~~~~~~~~~~~~~~ ctables.sps:47.50: error: CTABLES: Syntax error at end of command: expecting `/'. ctables.sps:48.53-48.64: error: CTABLES: Syntax error at `NOTAFUNCTION': Expecting summary function name. ctables.sps:49.59-49.60: error: CTABLES: Syntax error at `**': Expected number between 0 and 100 for PTILE. ctables.sps:50.52-50.53: error: CTABLES: Syntax error at `**': expecting string. ctables.sps:51.61-51.62: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:52.46-52.47: error: CTABLES: Syntax error at `**': expecting LABEL, FORMAT, or HIDESOURCECATS. ctables.sps:53.23-53.24: error: CTABLES: Syntax error at `**': expecting string. ctables.sps:54.25-54.26: error: CTABLES: Syntax error at `**': expecting string. ctables.sps:55.17-55.18: error: CTABLES: Syntax error at `**': expecting MINCOLWIDTH, MAXCOLWIDTH, UNITS, EMPTY, or MISSING. ctables.sps:56: error: CTABLES: MINCOLWIDTH must not be greater than MAXCOLWIDTH. ctables.sps:57.18-57.19: error: CTABLES: Syntax error at `**': expecting VARIABLES. ctables.sps:58: error: CTABLES: NOTAVAR is not a variable name. ctables.sps:59.32-59.33: error: CTABLES: Syntax error at `**': expecting DISPLAY. ctables.sps:60.40-60.41: error: CTABLES: Syntax error at `**': expecting DEFAULT, NAME, LABEL, BOTH, or NONE. ctables.sps:61.17-61.18: error: CTABLES: Syntax error at `**': expecting COUNTDUPLICATES. ctables.sps:62.33-62.34: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:63.19-63.20: error: CTABLES: Syntax error at `**': expecting VARIABLE or LISTWISE. ctables.sps:64.17-64.18: error: CTABLES: Syntax error at `**': expecting VARIABLE. ctables.sps:65: error: CTABLES: NOTAVAR is not a variable name. ctables.sps:66.32: error: CTABLES: Syntax error at `1': Expected integer 2 or greater for HIDESMALLCOUNTS COUNT. ctables.sps:67.10-67.13: error: CTABLES: Syntax error at `QUUX': expecting FORMAT, VLABELS, MRSETS, SMISSING, PCOMPUTE, PPROPERTIES, WEIGHT, HIDESMALLCOUNTS, or TABLE. ctables.sps:68.33: error: CTABLES: Syntax error at end of command: expecting `/'. ctables.sps:69.19-69.20: error: CTABLES: Syntax error at `**': expecting `/'. ctables.sps:70.38-70.39: error: CTABLES: Syntax error at `**': expecting COLUMN, ROW, or LAYER. ctables.sps:71.37-71.38: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:72.29-72.30: error: CTABLES: Syntax error at `**': expecting POSITION or VISIBLE. ctables.sps:73.39-73.40: error: CTABLES: Syntax error at `**': expecting OPPOSITE or LAYER. ctables.sps:74.39-74.40: error: CTABLES: Syntax error at `**': expecting OPPOSITE or LAYER. ctables.sps:75.29-75.30: error: CTABLES: Syntax error at `**': expecting AUTO, ROWLABELS, or COLLABELS. ctables.sps:76.30-76.31: error: CTABLES: Syntax error at `**': expecting CILEVEL. ctables.sps:77.38-77.40: error: CTABLES: Syntax error at `101': Expected number in @<:@0,100@:}@ for CILEVEL. ctables.sps:78.28-78.29: error: CTABLES: Syntax error at `**': expecting CAPTION, CORNER, or TITLE. ctables.sps:79.34-79.35: error: CTABLES: Syntax error at `**': expecting CHISQUARE. ctables.sps:80.35-80.36: error: CTABLES: Syntax error at `**': Expected number in @<:@0,1@:}@ for ALPHA. ctables.sps:81.43-81.44: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:82.40-82.41: error: CTABLES: Syntax error at `**': expecting ALLVISIBLE or SUBTOTALS. ctables.sps:83.29-83.30: error: CTABLES: Syntax error at `**': expecting TYPE, ALPHA, INCLUDEMRSETS, or CATEGORIES. ctables.sps:84.38-84.39: error: CTABLES: Syntax error at `**': expecting PROP or MEAN. ctables.sps:85.39-85.40: error: CTABLES: Syntax error at `**': Expected number in (0,1) for ALPHA. ctables.sps:86.39: error: CTABLES: Syntax error at `0': Expected number in (0,1) for ALPHA. ctables.sps:87.40-87.41: error: CTABLES: Syntax error at `**': expecting BONFERRONI, BH, or NONE. ctables.sps:88.47-88.48: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:89.47-89.48: error: CTABLES: Syntax error at `**': expecting ALLCATS or TESTEDCATS. ctables.sps:90.44-90.45: error: CTABLES: Syntax error at `**': expecting ALLVISIBLE or SUBTOTALS. ctables.sps:91.39-91.40: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:92.39-92.40: error: CTABLES: Syntax error at `**': expecting APA or SIMPLE. ctables.sps:93.41-93.42: error: CTABLES: Syntax error at `**': expecting YES or NO. ctables.sps:94.33-94.34: error: CTABLES: Syntax error at `**': expecting TYPE, ALPHA, ADJUST, INCLUDEMRSETS, MEANSVARIANCE, CATEGORIES, MERGE, STYLE, or SHOWSIG. ctables.sps:95.22-95.23: error: CTABLES: Syntax error at `**': expecting TABLE, SLABELS, CLABELS, CRITERIA, CATEGORIES, TITLES, SIGTEST, or COMPARETEST. ctables.sps:96: error: CTABLES: ROWLABELS and COLLABELS may not both be specified. ctables.sps:97.16-97.26: error: CTABLES: Cannot nest scale variables. 97 | CTABLES /TABLE qn20 > qnd1. | ^~~~~~~~~~~ ctables.sps:97.16-97.19: note: CTABLES: This is an outer scale variable. 97 | CTABLES /TABLE qn20 > qnd1. | ^~~~ ctables.sps:97.23-97.26: note: CTABLES: This is an inner scale variable. 97 | CTABLES /TABLE qn20 > qnd1. | ^~~~ ctables.sps:98.16-98.35: error: CTABLES: Summaries may only be requested for categorical variables at the innermost nesting level. 98 | CTABLES /TABLE qn1 [ROWPCT] > qnsa1. | ^~~~~~~~~~~~~~~~~~~~ ctables.sps:98.16-98.18: note: CTABLES: This outer categorical variable has a summary. 98 | CTABLES /TABLE qn1 [ROWPCT] > qnsa1. | ^~~ ctables.sps:100.52-100.56: error: CTABLES: Failed to parse category specification as format DATETIME: Day (123) must be between 1 and 31.. 100 | CTABLES /TABLE qn1 /CATEGORIES VARIABLES=datetime ['123']. | ^~~~~ ctables.sps:23: error: CTABLES: Summaries may appear only on one axis. ctables.sps:23.16-23.20: note: CTABLES: This variable on the rows axis has a summary. 23 | CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. | ^~~~~ ctables.sps:23.33-23.37: note: CTABLES: This variable on the columns axis has a summary. 23 | CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. | ^~~~~ ctables.sps:23.50-23.54: note: CTABLES: This variable on the layers axis has a summary. 23 | CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. | ^~~~~ ]]) AT_CLEANUP AT_SETUP([CTABLES parsing - more negative]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. CTABLES /PCOMPUTE &pc=EXPR(TOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc, SUBTOTAL, SUBTOTAL]. STRING string(A8). CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 ['string']. CTABLES /TABLE string /CATEGORIES VARIABLES=string [1]. CTABLES /TABLE qn1 /CLABELS ROWLABELS=OPPOSITE /CATEGORIES VARIABLES=qn1 KEY=MEAN(qn1). CTABLES /TABLE qnd1 /CLABELS ROWLABELS=OPPOSITE. CTABLES /TABLE qn1 + string /CLABELS ROWLABELS=OPPOSITE. CTABLES /TABLE qn1 + qnsa1 /CLABELS ROWLABELS=OPPOSITE. CTABLES /TABLE qn105ba + qn105bb /CLABELS ROWLABELS=OPPOSITE /CATEGORIES VARIABLES=qn105ba [1,2,3]. CTABLES /PCOMPUTE &x=EXPR(1**2**3). CTABLES /PCOMPUTE &x=EXPR([**]). CTABLES /PCOMPUTE &x=EXPR(**). CTABLES /TABLE. CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=80], [1], [[ctables.sps:2.76-2.78: error: CTABLES: Computed category &pc references a category not included in the category list. 2 | CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. | ^~~ ctables.sps:2.28-2.35: note: CTABLES: This is the missing category. 2 | CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. | ^~~~~~~~ ctables.sps:2.76-2.79: note: CTABLES: To fix the problem, add subtotals to the list of categories here. 2 | CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. | ^~~~ ctables.sps:3.73-3.75: error: CTABLES: Computed category &pc references a category not included in the category list. 3 | CTABLES /PCOMPUTE &pc=EXPR(TOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. | ^~~ ctables.sps:3.28-3.32: note: CTABLES: This is the missing category. 3 | CTABLES /PCOMPUTE &pc=EXPR(TOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc]. | ^~~~~ ctables.sps:3: note: CTABLES: To fix the problem, add TOTAL=YES to the variable's CATEGORIES specification. ctables.sps:4.76-4.99: error: CTABLES: These categories include 2 instances of SUBTOTAL or HSUBTOTAL, so references from computed categories must refer to subtotals by position, e.g. SUBTOTAL[1]. 4 | CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc, SUBTOTAL, SUBTOTAL]. | ^~~~~~~~~~~~~~~~~~~~~~~~ ctables.sps:4.28-4.35: note: CTABLES: This is the reference that lacks a position. 4 | CTABLES /PCOMPUTE &pc=EXPR(SUBTOTAL) /TABLE qn1 /CATEGORIES VARIABLES=qn1 [&pc, SUBTOTAL, SUBTOTAL]. | ^~~~~~~~ ctables.sps:7.47-7.54: error: CTABLES: This category specification may be applied only to string variables, but this subcommand tries to apply it to numeric variable QN1. 7 | CTABLES /TABLE qn1 /CATEGORIES VARIABLES=qn1 ['string']. | ^~~~~~~~ ctables.sps:8.53: error: CTABLES: This category specification may be applied only to numeric variables, but this subcommand tries to apply it to string variable string. 8 | CTABLES /TABLE string /CATEGORIES VARIABLES=string [1]. | ^ ctables.sps:10: error: CTABLES: ROWLABELS=OPPOSITE is not allowed with sorting based on a summary function. ctables.sps:12: error: CTABLES: ROWLABELS=OPPOSITE requires the variables to be moved to be categorical, but qnd1 is a scale variable. ctables.sps:13: error: CTABLES: ROWLABELS=OPPOSITE requires the variables to be moved to have the same width, but QN1 has width 0 and string has width 8. ctables.sps:14: error: CTABLES: ROWLABELS=OPPOSITE requires the variables to be moved to have the same value labels, but QN1 and QNSA1 have different value labels. ctables.sps:15: error: CTABLES: ROWLABELS=OPPOSITE requires the variables to be moved to have the same category specifications, but QN105BA and QN105BB have different category specifications. ctables.sps:17.27-17.33: warning: CTABLES: The exponentiation operator (`**') is left-associative: `a**b**c' equals `(a**b)**c', not `a**(b**c)'. To disable this warning, insert parentheses. 17 | CTABLES /PCOMPUTE &x=EXPR(1**2**3). | ^~~~~~~ ctables.sps:17.35: error: CTABLES: Syntax error at end of command: expecting `/'. ctables.sps:18.28-18.29: error: CTABLES: Syntax error at `**'. ctables.sps:19.27-19.28: error: CTABLES: Syntax error at `**'. ctables.sps:21.15: error: CTABLES: Syntax error at end of command: At least one variable must be specified. ctables.sps:23: error: CTABLES: Summaries may appear only on one axis. ctables.sps:23.16-23.20: note: CTABLES: This variable on the rows axis has a summary. 23 | CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. | ^~~~~ ctables.sps:23.33-23.37: note: CTABLES: This variable on the columns axis has a summary. 23 | CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. | ^~~~~ ctables.sps:23.50-23.54: note: CTABLES: This variable on the layers axis has a summary. 23 | CTABLES /TABLE qn113 [COUNT] BY qn114 [COUNT] BY qn116 [COUNT]. | ^~~~~ ]]) 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, VALIDN, TOTALN, 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 ╭──────────────────────┬─────┬───────┬───────┬────┬────────────┬───────┬───────╮ │ │ │ │ │ │ Std │ │ │ │ │Count│Valid N│Total N│Mean│ Deviation │Minimum│Maximum│ ├──────────────────────┼─────┼───────┼───────┼────┼────────────┼───────┼───────┤ │D1. AGE: What is your │ 6999│ 6930│ 6999│ 48│ 19│ 16│ 86│ │age? │ │ │ │ │ │ │ │ ╰──────────────────────┴─────┴───────┴───────┴────┴────────────┴───────┴───────╯ 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'. DESCRIPTIVES qn18/STATISTICS=MEAN. CTABLES /TABLE=region > qn18 [MEAN, COUNT, VALIDN, TOTALN] /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│ ╰────────────────────────────────────────────────────────────────────────┴─────╯ Descriptive Statistics ╭────────────────────────────────────────────────────────────────────┬────┬────╮ │ │ N │Mean│ ├────────────────────────────────────────────────────────────────────┼────┼────┤ │18. When you drink ANSWERFROM(QN17R1), about how many │4218│4.62│ │ANSWERFROM(QN17R2) do you usually drink per sitting? │ │ │ │Valid N (listwise) │6999│ │ │Missing N (listwise) │2781│ │ ╰────────────────────────────────────────────────────────────────────┴────┴────╯ Custom Tables ╭──────────────────────────────────────────────────────┬────┬─────┬──────┬─────╮ │ │ │ │ Valid│Total│ │ │Mean│Count│ N │ N │ ├──────────────────────────────────────────────────────┼────┼─────┼──────┼─────┤ │Region NE 18. When you drink ANSWERFROM(QN17R1),│4.36│ 1409│ 949│ 1409│ │ about how many ANSWERFROM(QN17R2) do │ │ │ │ │ │ you usually drink per sitting? │ │ │ │ │ │ ╶───────────────────────────────────────────────┼────┼─────┼──────┼─────┤ │ MW 18. When you drink ANSWERFROM(QN17R1),│4.67│ 1654│ 1027│ 1654│ │ about how many ANSWERFROM(QN17R2) do │ │ │ │ │ │ you usually drink per sitting? │ │ │ │ │ │ ╶───────────────────────────────────────────────┼────┼─────┼──────┼─────┤ │ S 18. When you drink ANSWERFROM(QN17R1),│4.71│ 2390│ 1287│ 2390│ │ about how many ANSWERFROM(QN17R2) do │ │ │ │ │ │ you usually drink per sitting? │ │ │ │ │ │ ╶───────────────────────────────────────────────┼────┼─────┼──────┼─────┤ │ W 18. When you drink ANSWERFROM(QN17R1),│4.69│ 1546│ 955│ 1546│ │ about how many ANSWERFROM(QN17R2) do │ │ │ │ │ │ you usually drink per sitting? │ │ │ │ │ │ ╶───────────────────────────────────────────────┼────┼─────┼──────┼─────┤ │ All 18. When you drink ANSWERFROM(QN17R1),│4.62│ 6999│ 4218│ 6999│ │ regions about how 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 FORMAT=COUNT F8.2 /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│ 81.00│ 30│ 92│ │had too much to drink to drive safely will certain │ │ │ │ │ │ │ │ │A. Get stopped by the police? Very likely│ 384│ 552│ 936│ 14│ 171.00│ 65│ 185│ │ Somewhat │ 590│ 1249│ 1839│ 20│ 265.00│ 92│ 285│ │ likely │ │ │ │ │ │ │ │ │ Somewhat │ 278│ 647│ 925│ 6│ 116.00│ 38│ 122│ │ unlikely │ │ │ │ │ │ │ │ │ Very │ 141│ 290│ 431│ 4│ 59.00│ 22│ 63│ │ unlikely │ │ │ │ │ │ │ │ ╰────────────────────────────────────────────────────────┴───────┴───────┴──────────┴───────┴────────┴──────┴──────────╯ ]) AT_CLEANUP AT_SETUP([CTABLES CLABELS]) AT_CHECK([ln $top_srcdir/examples/nhtsa.sav . || cp $top_srcdir/examples/nhtsa.sav .]) AT_DATA([ctables.sps], [[GET 'nhtsa.sav'. CTABLES /TABLE AgeGroup BY qns3a /CLABELS ROWLABELS=OPPOSITE. CTABLES /TABLE AgeGroup BY qns3a /CLABELS COLLABELS=OPPOSITE. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=120], [0], [dnl Custom Tables ╭───────┬──────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ │ S3a. GENDER: │ │ ├──────────────────────────────────────────────────────┬───────────────────────────────────────────────────────┤ │ │ Male │ Female │ │ ├─────────┬───────┬──────┬──────┬──────┬───────┬───────┼──────────┬──────┬───────┬──────┬──────┬──────┬────────┤ │ │ 15 or │ 16 to │ 26 to│ 36 to│ 46 to│ 56 to │ 66 or │ 15 or │ 16 to│ 26 to │ 36 to│ 46 to│ 56 to│ 66 or │ │ │ younger │ 25 │ 35 │ 45 │ 55 │ 65 │ older │ younger │ 25 │ 35 │ 45 │ 55 │ 65 │ older │ │ ├─────────┼───────┼──────┼──────┼──────┼───────┼───────┼──────────┼──────┼───────┼──────┼──────┼──────┼────────┤ │ │ Count │ Count │ Count│ Count│ Count│ Count │ Count │ Count │ Count│ Count │ Count│ Count│ Count│ Count │ ├───────┼─────────┼───────┼──────┼──────┼──────┼───────┼───────┼──────────┼──────┼───────┼──────┼──────┼──────┼────────┤ │Age │ 0│ 594│ 476│ 489│ 526│ 516│ 531│ 0│ 505│ 491│ 548│ 649│ 731│ 943│ │group │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ ╰───────┴─────────┴───────┴──────┴──────┴──────┴───────┴───────┴──────────┴──────┴───────┴──────┴──────┴──────┴────────╯ Custom Tables ╭──────────────────────────────┬────────────╮ │ │S3a. GENDER:│ │ ├────────────┤ │ │ Count │ ├──────────────────────────────┼────────────┤ │Age group 15 or younger Male │ 0│ │ Female│ 0│ │ ╶────────────────────┼────────────┤ │ 16 to 25 Male │ 594│ │ Female│ 505│ │ ╶────────────────────┼────────────┤ │ 26 to 35 Male │ 476│ │ Female│ 491│ │ ╶────────────────────┼────────────┤ │ 36 to 45 Male │ 489│ │ Female│ 548│ │ ╶────────────────────┼────────────┤ │ 46 to 55 Male │ 526│ │ Female│ 649│ │ ╶────────────────────┼────────────┤ │ 56 to 65 Male │ 516│ │ Female│ 731│ │ ╶────────────────────┼────────────┤ │ 66 or older Male │ 531│ │ Female│ 943│ ╰──────────────────────────────┴────────────╯ ]) AT_CLEANUP AT_SETUP([CTABLES missing values]) AT_DATA([ctables.sps], [[DATA LIST LIST NOTABLE/x y. BEGIN DATA. 1 1 1 2 1 3 1 4 1 5 1 . 2 1 2 2 2 3 2 4 2 5 2 . 3 1 3 2 3 3 3 4 3 5 3 . 4 1 4 2 4 3 4 4 4 5 4 . 5 1 5 2 5 3 5 4 5 5 5 . . 1 . 2 . 3 . 4 . 5 . . END DATA. MISSING VALUES x (1, 2) y (2, 3). VARIABLE LEVEL ALL (NOMINAL). CTABLES /TABLE x[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, TOTALS[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, VALIDN, TOTALN]] /CATEGORIES VARIABLES=ALL TOTAL=YES. CTABLES /TABLE x[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, TOTALS[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, VALIDN, TOTALN]] /CATEGORIES VARIABLES=ALL TOTAL=YES MISSING=INCLUDE. CTABLES /TABLE x BY y[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, ROWPCT, ROWPCT.VALIDN, ROWPCT.TOTALN, TOTALS[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, ROWPCT, ROWPCT.VALIDN, ROWPCT.TOTALN, VALIDN, TOTALN]] /CATEGORIES VARIABLES=ALL TOTAL=YES /SLABELS POSITION=ROW. CTABLES /TABLE x BY y[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, ROWPCT, ROWPCT.VALIDN, ROWPCT.TOTALN, TOTALS[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, ROWPCT, ROWPCT.VALIDN, ROWPCT.TOTALN, VALIDN, TOTALN]] /CATEGORIES VARIABLES=ALL TOTAL=YES MISSING=INCLUDE /SLABELS POSITION=ROW. CTABLES /TABLE x BY y[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, ROWPCT, ROWPCT.VALIDN, ROWPCT.TOTALN, TOTALS[COUNT, COLPCT, COLPCT.VALIDN, COLPCT.TOTALN, ROWPCT, ROWPCT.VALIDN, ROWPCT.TOTALN, VALIDN, TOTALN]] /CATEGORIES VARIABLES=x [1, 2, 3, 4] TOTAL=YES /CATEGORIES VARIABLES=y [1, 3, 4, 5] TOTAL=YES /SLABELS POSITION=ROW. ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=120], [0], [dnl Custom Tables ╭───────┬─────┬────────┬────────────────┬────────────────┬───────┬───────╮ │ │Count│Column %│Column Valid N %│Column Total N %│Valid N│Total N│ ├───────┼─────┼────────┼────────────────┼────────────────┼───────┼───────┤ │x 3.00 │ 6│ 33.3%│ 33.3%│ 16.7%│ │ │ │ 4.00 │ 6│ 33.3%│ 33.3%│ 16.7%│ │ │ │ 5.00 │ 6│ 33.3%│ 33.3%│ 16.7%│ │ │ │ Total│ 18│ 100.0%│ 100.0%│ 100.0%│ 18│ 36│ ╰───────┴─────┴────────┴────────────────┴────────────────┴───────┴───────╯ dnl Note that Column Total N % doesn't add up to 100 because missing dnl values are included in the total but not shown as a category and this dnl is expected behavior. Custom Tables ╭───────┬─────┬────────┬────────────────┬────────────────┬───────┬───────╮ │ │Count│Column %│Column Valid N %│Column Total N %│Valid N│Total N│ ├───────┼─────┼────────┼────────────────┼────────────────┼───────┼───────┤ │x 1.00 │ 6│ 20.0%│ .0%│ 16.7%│ │ │ │ 2.00 │ 6│ 20.0%│ .0%│ 16.7%│ │ │ │ 3.00 │ 6│ 20.0%│ 33.3%│ 16.7%│ │ │ │ 4.00 │ 6│ 20.0%│ 33.3%│ 16.7%│ │ │ │ 5.00 │ 6│ 20.0%│ 33.3%│ 16.7%│ │ │ │ Total│ 30│ 100.0%│ 100.0%│ 100.0%│ 18│ 36│ ╰───────┴─────┴────────┴────────────────┴────────────────┴───────┴───────╯ dnl Note that Column Total N % doesn't add up to 100 because system-missing dnl values are included in the total but not shown as a category and this dnl is expected behavior. Custom Tables ╭────────────────────────┬───────────────────────────╮ │ │ y │ │ ├──────┬──────┬──────┬──────┤ │ │ 1.00 │ 4.00 │ 5.00 │ Total│ ├────────────────────────┼──────┼──────┼──────┼──────┤ │x 3.00 Count │ 1│ 1│ 1│ 3│ │ Column % │ 33.3%│ 33.3%│ 33.3%│ .│ │ Column Valid N %│ 33.3%│ 33.3%│ 33.3%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 33.3%│ 33.3%│ 33.3%│100.0%│ │ Row Valid N % │ 33.3%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ 3│ │ Total N │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┤ │ 4.00 Count │ 1│ 1│ 1│ 3│ │ Column % │ 33.3%│ 33.3%│ 33.3%│ .│ │ Column Valid N %│ 33.3%│ 33.3%│ 33.3%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 33.3%│ 33.3%│ 33.3%│100.0%│ │ Row Valid N % │ 33.3%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ 3│ │ Total N │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┤ │ 5.00 Count │ 1│ 1│ 1│ 3│ │ Column % │ 33.3%│ 33.3%│ 33.3%│ .│ │ Column Valid N %│ 33.3%│ 33.3%│ 33.3%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 33.3%│ 33.3%│ 33.3%│100.0%│ │ Row Valid N % │ 33.3%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ 3│ │ Total N │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┤ │ Total Count │ 3│ 3│ 3│ 9│ │ Column % │100.0%│100.0%│100.0%│ .│ │ Column Valid N %│100.0%│100.0%│100.0%│ .│ │ Column Total N %│100.0%│100.0%│100.0%│ .│ │ Row % │ .│ .│ .│ .│ │ Row Valid N % │ .│ .│ .│ .│ │ Row Total N % │ .│ .│ .│ .│ │ Valid N │ 3│ 3│ 3│ 9│ │ Total N │ 6│ 6│ 6│ 36│ ╰────────────────────────┴──────┴──────┴──────┴──────╯ Custom Tables ╭────────────────────────┬─────────────────────────────────────────╮ │ │ y │ │ ├──────┬──────┬──────┬──────┬──────┬──────┤ │ │ 1.00 │ 2.00 │ 3.00 │ 4.00 │ 5.00 │ Total│ ├────────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┤ │x 1.00 Count │ 1│ 1│ 1│ 1│ 1│ 5│ │ Column % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Column Valid N %│ .0%│ .│ .│ .0%│ .0%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│100.0%│ │ Row Valid N % │ .│ .│ .│ .│ .│ .│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ │ 0│ │ Total N │ │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┤ │ 2.00 Count │ 1│ 1│ 1│ 1│ 1│ 5│ │ Column % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Column Valid N %│ .0%│ .│ .│ .0%│ .0%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│100.0%│ │ Row Valid N % │ .│ .│ .│ .│ .│ .│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ │ 0│ │ Total N │ │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┤ │ 3.00 Count │ 1│ 1│ 1│ 1│ 1│ 5│ │ Column % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Column Valid N %│ 33.3%│ .│ .│ 33.3%│ 33.3%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│100.0%│ │ Row Valid N % │ 33.3%│ .0%│ .0%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ │ 3│ │ Total N │ │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┤ │ 4.00 Count │ 1│ 1│ 1│ 1│ 1│ 5│ │ Column % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Column Valid N %│ 33.3%│ .│ .│ 33.3%│ 33.3%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│100.0%│ │ Row Valid N % │ 33.3%│ .0%│ .0%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ │ 3│ │ Total N │ │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┤ │ 5.00 Count │ 1│ 1│ 1│ 1│ 1│ 5│ │ Column % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Column Valid N %│ 33.3%│ .│ .│ 33.3%│ 33.3%│ .│ │ Column Total N %│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│ .│ │ Row % │ 20.0%│ 20.0%│ 20.0%│ 20.0%│ 20.0%│100.0%│ │ Row Valid N % │ 33.3%│ .0%│ .0%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ │ 3│ │ Total N │ │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┼──────┤ │ Total Count │ 5│ 5│ 5│ 5│ 5│ 25│ │ Column % │100.0%│100.0%│100.0%│100.0%│100.0%│ .│ │ Column Valid N %│100.0%│ .│ .│100.0%│100.0%│ .│ │ Column Total N %│100.0%│100.0%│100.0%│100.0%│100.0%│ .│ │ Row % │ .│ .│ .│ .│ .│ .│ │ Row Valid N % │ .│ .│ .│ .│ .│ .│ │ Row Total N % │ .│ .│ .│ .│ .│ .│ │ Valid N │ 3│ 0│ 0│ 3│ 3│ 9│ │ Total N │ 6│ 6│ 6│ 6│ 6│ 36│ ╰────────────────────────┴──────┴──────┴──────┴──────┴──────┴──────╯ Custom Tables ╭────────────────────────┬──────────────────────────────────╮ │ │ y │ │ ├──────┬──────┬──────┬──────┬──────┤ │ │ 1.00 │ 3.00 │ 4.00 │ 5.00 │ Total│ ├────────────────────────┼──────┼──────┼──────┼──────┼──────┤ │x 1.00 Count │ 1│ 1│ 1│ 1│ 4│ │ Column % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│ .│ │ Column Valid N %│ .0%│ .│ .0%│ .0%│ .│ │ Column Total N %│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Row % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│100.0%│ │ Row Valid N % │ .│ .│ .│ .│ .│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ 0│ │ Total N │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┤ │ 2.00 Count │ 1│ 1│ 1│ 1│ 4│ │ Column % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│ .│ │ Column Valid N %│ .0%│ .│ .0%│ .0%│ .│ │ Column Total N %│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Row % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│100.0%│ │ Row Valid N % │ .│ .│ .│ .│ .│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ 0│ │ Total N │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┤ │ 3.00 Count │ 1│ 1│ 1│ 1│ 4│ │ Column % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│ .│ │ Column Valid N %│ 50.0%│ .│ 50.0%│ 50.0%│ .│ │ Column Total N %│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Row % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│100.0%│ │ Row Valid N % │ 33.3%│ .0%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ 3│ │ Total N │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┤ │ 4.00 Count │ 1│ 1│ 1│ 1│ 4│ │ Column % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│ .│ │ Column Valid N %│ 50.0%│ .│ 50.0%│ 50.0%│ .│ │ Column Total N %│ 20.0%│ 20.0%│ 20.0%│ 20.0%│ .│ │ Row % │ 25.0%│ 25.0%│ 25.0%│ 25.0%│100.0%│ │ Row Valid N % │ 33.3%│ .0%│ 33.3%│ 33.3%│100.0%│ │ Row Total N % │ 16.7%│ 16.7%│ 16.7%│ 16.7%│100.0%│ │ Valid N │ │ │ │ │ 3│ │ Total N │ │ │ │ │ 6│ │ ╶──────────────────────┼──────┼──────┼──────┼──────┼──────┤ │ Total Count │ 4│ 4│ 4│ 4│ 16│ │ Column % │100.0%│100.0%│100.0%│100.0%│ .│ │ Column Valid N %│100.0%│ .│100.0%│100.0%│ .│ │ Column Total N %│100.0%│100.0%│100.0%│100.0%│ .│ │ Row % │ .│ .│ .│ .│ .│ │ Row Valid N % │ .│ .│ .│ .│ .│ │ Row Total N % │ .│ .│ .│ .│ .│ │ Valid N │ 2│ 0│ 2│ 2│ 6│ │ Total N │ 5│ 5│ 5│ 5│ 30│ ╰────────────────────────┴──────┴──────┴──────┴──────┴──────╯ ]) AT_CLEANUP AT_SETUP([CTABLES SMISSING=LISTWISE]) AT_KEYWORDS([SMISSING LISTWISE]) AT_DATA([ctables.sps], [[DATA LIST LIST NOTABLE/x y z. BEGIN DATA. 1 . 40 1 10 50 1 20 60 1 . . 1 30 . END DATA. VARIABLE LEVEL x (NOMINAL). CTABLES /TABLE (y + z) > x. CTABLES /SMISSING LISTWISE /TABLE (y + z) > x. * The following doesn't come out as listwise because the tables are separate, not linked by an > operator. CTABLES /SMISSING LISTWISE /TABLE (y > x) + (z > x). ]]) AT_CHECK([pspp ctables.sps -O box=unicode -O width=120], [0], [dnl Custom Tables ╭────────┬─────╮ │ │ Mean│ ├────────┼─────┤ │y x 1.00│20.00│ ├────────┼─────┤ │z x 1.00│50.00│ ╰────────┴─────╯ Custom Tables ╭────────┬─────╮ │ │ Mean│ ├────────┼─────┤ │y x 1.00│15.00│ ├────────┼─────┤ │z x 1.00│55.00│ ╰────────┴─────╯ Custom Tables ╭────────┬─────╮ │ │ Mean│ ├────────┼─────┤ │y x 1.00│20.00│ ├────────┼─────┤ │z x 1.00│50.00│ ╰────────┴─────╯ ]) AT_CLEANUP