work on CTABLES
authorBen Pfaff <blp@cs.stanford.edu>
Mon, 27 Dec 2021 00:01:47 +0000 (16:01 -0800)
committerBen Pfaff <blp@cs.stanford.edu>
Wed, 1 Jun 2022 22:22:15 +0000 (15:22 -0700)
28 files changed:
Smake
doc/automake.mk
doc/language.texi
doc/pspp-figures/ctables1.sps [new file with mode: 0644]
doc/pspp-figures/ctables10.sps [new file with mode: 0644]
doc/pspp-figures/ctables11.sps [new file with mode: 0644]
doc/pspp-figures/ctables12.sps [new file with mode: 0644]
doc/pspp-figures/ctables2.sps [new file with mode: 0644]
doc/pspp-figures/ctables3.sps [new file with mode: 0644]
doc/pspp-figures/ctables4.sps [new file with mode: 0644]
doc/pspp-figures/ctables5.sps [new file with mode: 0644]
doc/pspp-figures/ctables6.sps [new file with mode: 0644]
doc/pspp-figures/ctables7.sps [new file with mode: 0644]
doc/pspp-figures/ctables8.sps [new file with mode: 0644]
doc/pspp-figures/ctables9.sps [new file with mode: 0644]
doc/statistics.texi
doc/variables.texi
examples/automake.mk
examples/nhtsa-drinking-2008.sav [new file with mode: 0644]
examples/nhtsa-drinking-2008.sps [new file with mode: 0644]
examples/nhtsa.sav [new file with mode: 0644]
src/language/command.def
src/language/stats/automake.mk
src/language/stats/ctables.c [new file with mode: 0644]
src/libpspp/message.c
src/libpspp/message.h
tests/automake.mk
tests/language/stats/ctables.at [new file with mode: 0644]

diff --git a/Smake b/Smake
index 4bdd8957fe53aecbf4f02ef63c3e719249c87fea..3e63d869a7aaa07048cae896ae4065a0c26f7f3e 100644 (file)
--- a/Smake
+++ b/Smake
@@ -62,6 +62,8 @@ GNULIB_MODULES = \
        gettimeofday \
         getopt-gnu \
        gitlog-to-changelog \
+       havelib \
+       iconv \
        include_next \
        isfinite \
        isinf \
index ae2a5c8cde5b16be5c3050a316b576d17df17917..b90dbaa18df29d0351a3f973143d2592fa094379 100644 (file)
@@ -117,6 +117,18 @@ FIGURE_SYNTAX = \
  doc/pspp-figures/chisquare.sps \
  doc/pspp-figures/compute.sps \
  doc/pspp-figures/count.sps \
+ doc/pspp-figures/ctables1.sps \
+ doc/pspp-figures/ctables2.sps \
+ doc/pspp-figures/ctables3.sps \
+ doc/pspp-figures/ctables4.sps \
+ doc/pspp-figures/ctables5.sps \
+ doc/pspp-figures/ctables6.sps \
+ doc/pspp-figures/ctables7.sps \
+ doc/pspp-figures/ctables8.sps \
+ doc/pspp-figures/ctables9.sps \
+ doc/pspp-figures/ctables10.sps \
+ doc/pspp-figures/ctables11.sps \
+ doc/pspp-figures/ctables12.sps \
  doc/pspp-figures/crosstabs.sps \
  doc/pspp-figures/descriptives.sps \
  doc/pspp-figures/flip.sps \
index 71dd6a5fb73673b02b2d35f08f5bdbfa12024695..1c9a4f0105245a5550f7ad71f577be5db2be0c53 100644 (file)
@@ -507,6 +507,35 @@ they are displayed.  Example: a width of 8, with 2 decimal places.
 Similar to print format, but used by the @cmd{WRITE} command
 (@pxref{WRITE}).
 
+@cindex measurement level
+@item Measurement level
+One of the following:
+
+@table @asis
+@item Nominal
+Each value of a nominal variable represents a distinct category.  The
+possible categories are finite and often have value labels.  The order
+of categories is not significant.  Political parties, US states, and
+yes/no choices are nominal.  Numeric and string variables can be
+nominal.
+
+@item Ordinal
+Ordinal variables also represent distinct categories, but their values
+are arranged according to some natural order.  Likert scales, e.g.@:
+from strongly disagree to strongly agree, are ordinal.  Data grouped
+into ranges, e.g.@: age groups or income groups, are ordinal.  Both
+numeric and string variables can be ordinal.  String values are
+ordered alphabetically, so letter grades from A to F will work as
+expected, but @code{poor}, @code{satisfactory}, @code{excellent} will
+not.
+
+@item Scale
+Scale variables are ones for which differences and ratios are
+meaningful.  These are often values which have a natural unit
+attached, such as age in years, income in dollars, or distance in
+miles.  Only numeric variables are scalar.
+@end table
+
 @cindex custom attributes
 @item Custom attributes
 User-defined associations between names and values.  @xref{VARIABLE
diff --git a/doc/pspp-figures/ctables1.sps b/doc/pspp-figures/ctables1.sps
new file mode 100644 (file)
index 0000000..4876fa2
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE=AgeGroup.
\ No newline at end of file
diff --git a/doc/pspp-figures/ctables10.sps b/doc/pspp-figures/ctables10.sps
new file mode 100644 (file)
index 0000000..8adb5ff
--- /dev/null
@@ -0,0 +1,4 @@
+GET FILE='nhtsa.sav'.
+CTABLES
+    /TABLE=qnd1 [MEAN, MEDIAN] BY qns3a
+    /TABLE=AgeGroup [COLPCT, ROWPCT] BY qns3a.
diff --git a/doc/pspp-figures/ctables11.sps b/doc/pspp-figures/ctables11.sps
new file mode 100644 (file)
index 0000000..d2e064c
--- /dev/null
@@ -0,0 +1,4 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE=AgeGroup [COLPCT 'Gender %' PCT5.0,
+                         ROWPCT 'Age Group %' PCT5.0]
+               BY qns3a.
diff --git a/doc/pspp-figures/ctables12.sps b/doc/pspp-figures/ctables12.sps
new file mode 100644 (file)
index 0000000..0ec07bb
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE=(AgeGroup + qns1)[COLPCT] BY qns3a.
diff --git a/doc/pspp-figures/ctables2.sps b/doc/pspp-figures/ctables2.sps
new file mode 100644 (file)
index 0000000..38b09aa
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE=AgeGroup BY qns3a.
\ No newline at end of file
diff --git a/doc/pspp-figures/ctables3.sps b/doc/pspp-figures/ctables3.sps
new file mode 100644 (file)
index 0000000..4736cce
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE AgeGroup > qns3a BY qn86.
diff --git a/doc/pspp-figures/ctables4.sps b/doc/pspp-figures/ctables4.sps
new file mode 100644 (file)
index 0000000..4ddee23
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE AgeGroup + qn1 BY qns3a.
diff --git a/doc/pspp-figures/ctables5.sps b/doc/pspp-figures/ctables5.sps
new file mode 100644 (file)
index 0000000..ba12f4b
--- /dev/null
@@ -0,0 +1,3 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE qn26 + qn27 > qns3a.
+CTABLES /TABLE (qn26 + qn27) > qns3a.
diff --git a/doc/pspp-figures/ctables6.sps b/doc/pspp-figures/ctables6.sps
new file mode 100644 (file)
index 0000000..9cbaf89
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE qnd1.
diff --git a/doc/pspp-figures/ctables7.sps b/doc/pspp-figures/ctables7.sps
new file mode 100644 (file)
index 0000000..678570a
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE qnd1 > qns3a BY lang.
diff --git a/doc/pspp-figures/ctables8.sps b/doc/pspp-figures/ctables8.sps
new file mode 100644 (file)
index 0000000..799195a
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE qns3a > qnd1 BY lang.
diff --git a/doc/pspp-figures/ctables9.sps b/doc/pspp-figures/ctables9.sps
new file mode 100644 (file)
index 0000000..133d0d7
--- /dev/null
@@ -0,0 +1,2 @@
+GET FILE='nhtsa.sav'.
+CTABLES /TABLE qn20 [C] BY qns3a.
index 01976e27c950fa4ef21087dc40e0fadbd668a3ee..dfc3aad875bc3d32b5b12b81966700a2703c684c 100644 (file)
@@ -20,6 +20,7 @@ far.
 * GRAPH::                       Plot data.
 * CORRELATIONS::                Correlation tables.
 * CROSSTABS::                   Crosstabulation tables.
+* CTABLES::                     Custom tables.
 * FACTOR::                      Factor analysis and Principal Components analysis.
 * GLM::                         Univariate Linear Models.
 * LOGISTIC REGRESSION::         Bivariate Logistic Regression.
@@ -29,7 +30,6 @@ far.
 * ONEWAY::                      One way analysis of variance.
 * QUICK CLUSTER::               K-Means clustering.
 * RANK::                        Compute rank scores.
-* REGRESSION::                  Linear regression.
 * RELIABILITY::                 Reliability analysis.
 * ROC::                         Receiver Operating Characteristic.
 @end menu
@@ -897,6 +897,479 @@ person's occupation.
 @caption {The results of a test of independence between @exvar{sex} and @exvar{occupation}}
 @end float
 
+@node CTABLES
+@section CTABLES
+
+@vindex CTABLES
+@cindex custom tables
+@cindex tables, custom
+
+@code{CTABLES} has the following overall syntax.  At least one
+@code{TABLE} subcommand is required:
+
+@display
+@t{CTABLES}
+  @dots{}@i{global subcommands}@dots{}
+  [@t{/TABLE} @i{axis} [@t{BY} @i{axis} [@t{BY} @i{axis}]]
+   @dots{}@i{per-table subcommands}@dots{}]@dots{}
+@end display
+
+@noindent
+where each @i{axis} may be empty or take one of the following forms:
+
+@display
+@i{variable}
+@i{variable} @t{[}@{@t{C} @math{|} @t{S}@}@t{]}
+@i{axis} + @i{axis}
+@i{axis} > @i{axis}
+(@i{axis})
+@i{axis} @t{(}@i{summary} [@i{string}] [@i{format}]@t{)}
+@end display
+
+The following subcommands precede the first @code{TABLE} subcommand
+and apply to all of the output tables.  All of these subcommands are
+optional:
+
+@display
+@t{/FORMAT}
+    [@t{MINCOLWIDTH=}@{@t{DEFAULT} @math{|} @i{width}@}]
+    [@t{MAXCOLWIDTH=}@{@t{DEFAULT} @math{|} @i{width}@}]
+    [@t{UNITS=}@{@t{POINTS} @math{|} @t{INCHES} @math{|} @t{CM}@}]
+    [@t{EMPTY=}@{@t{ZERO} @math{|} @t{BLANK} @math{|} @i{string}@}]
+    [@t{MISSING=}@i{string}]
+@t{/VLABELS}
+    @t{VARIABLES=}@i{variables}
+    @t{DISPLAY}=@{@t{DEFAULT} @math{|} @t{NAME} @math{|} @t{LABEL} @math{|} @t{BOTH} @math{|} @t{NONE}@}
+@t{/MRSETS COUNTDUPLICATES=}@{@t{YES} @math{|} @t{NO}@}
+@t{/SMISSING} @{@t{VARIABLE} @math{|} @t{LISTWISE}@}
+@t{/PCOMPUTE} @t{&}@i{category}@t{=EXPR(}@i{expression}@t{)}
+@t{/PPROPERTIES} @t{&}@i{category}@dots{}
+    [@t{LABEL=}@i{string}]
+    [@t{FORMAT=}[@i{summary} @i{format}]@dots{}]
+    [@t{HIDESOURCECATS=}@{@t{NO} @math{|} @t{YES}@}
+@t{/WEIGHT VARIABLE=}@i{variable}
+@t{/HIDESMALLCOUNTS COUNT=@i{count}}
+@end display
+
+The following subcommands follow @code{TABLE} and apply only to the
+previous @code{TABLE}.  All of these subcommands are optional:
+
+@display
+@t{/SLABELS}
+    [@t{POSITION=}@{@t{COLUMN} @math{|} @t{ROW} @math{|} @t{LAYER}@}]
+    [@t{VISIBLE=}@{@t{YES} @math{|} @t{NO}@}]
+@t{/CLABELS} @{@t{AUTO} @math{|} @{@t{ROWLABELS}@math{|}@t{COLLABELS}@}@t{=}@{@t{OPPOSITE}@math{|}@t{LAYER}@}@}
+@t{/CRITERIA CILEVEL=}@i{percentage}
+@t{/CATEGORIES} @t{VARIABLES=}@i{variables}
+    @{@t{[}@i{value}@t{,} @i{value}@dots{}@t{]}
+   @math{|} [@t{ORDER=}@{@t{A} @math{|} @t{D}@}]
+     [@t{KEY=}@{@t{VALUE} @math{|} @t{LABEL} @math{|} @i{summary}@t{(}@i{variable}@t{)}@}]
+     [@t{MISSING=}@{@t{EXCLUDE} @math{|} @t{INCLUDE}@}]@}
+    [@t{TOTAL=}@{@t{NO} @math{|} @t{YES}@} [@t{LABEL=}@i{string}] [@t{POSITION=}@{@t{AFTER} @math{|} @t{BEFORE}@}]]
+    [@t{EMPTY=}@{@t{INCLUDE} @math{|} @t{EXCLUDE}@}]
+@t{/TITLES}
+    [@t{TITLE=}@i{string}@dots{}]
+    [@t{CAPTION=}@i{string}@dots{}]
+    [@t{CORNER=}@i{string}@dots{}]
+@t{/SIGTEST TYPE=CHISQUARE}
+    [@t{ALPHA=}@i{siglevel}]
+    [@t{INCLUDEMRSETS=}@{@t{YES} @math{|} @t{NO}@}]
+    [@t{CATEGORIES=}@{@t{ALLVISIBLE} @math{|} @t{SUBTOTALS}@}]
+@t{/COMPARETEST TYPE=}@{@t{PROP} @math{|} @t{MEAN}@}
+    [@t{ALPHA=}@i{value}[@t{,} @i{value}]]
+    [@t{ADJUST=}@{@t{BONFERRONI} @math{|} @t{BH} @math{|} @t{NONE}@}]
+    [@t{INCLUDEMRSETS=}@{@t{YES} @math{|} @t{NO}@}]
+    [@t{MEANSVARIANCE=}@{@t{ALLCATS} @math{|} @t{TESTEDCATS}@}]
+    [@t{CATEGORIES=}@{@t{ALLVISIBLE} @math{|} @t{SUBTOTALS}@}]
+    [@t{MERGE=}@{@t{NO} @math{|} @t{YES}@}]
+    [@t{STYLE=}@{@t{APA} @math{|} @t{SIMPLE}@}]
+    [@t{SHOWSIG=}@{@t{NO} @math{|} @t{YES}@}]
+@end display
+
+The @code{CTABLES} (aka ``custom tables'') command produces
+multi-dimensional tables from categorical and scale data.  It offers
+many options for data summarization and formatting.
+
+This section's examples use data from the 2008 (USA) National Survey
+of Drinking and Driving Attitudes and Behaviors, a public domain data
+set from the (USA) National Highway Traffic Administration and
+available at @url{https://data.transportation.gov}.  @pspp{} includes
+this data set, with a slightly modified dictionary, as
+@file{examples/nhtsa.sav}.
+
+@menu
+* CTABLES Basics::
+* CTABLES Data Summarization::
+@end menu
+
+@node CTABLES Basics
+@subsection Basics
+
+The only required subcommand is @code{TABLE}, which specifies the
+variables to include along each axis:
+@display
+@t{/TABLE} @i{rows} [@t{BY} @i{columns} [@t{BY} @i{layers}]]
+@end display
+@noindent
+In @code{TABLE}, each of @var{rows}, @var{columns}, and @var{layers}
+is either empty or an axis expression that specifies one or more
+variables.  At least one must specify an axis expression.
+
+@menu
+* CTABLES Categorical Variable Basics::
+* CTABLES Scalar Variable Basics::
+* CTABLES Overriding Measurement Level::
+* CTABLES Multiple Response Sets::
+@end menu
+
+@node CTABLES Categorical Variable Basics
+@subsubsection Categorical Variables
+
+An axis expression that names a categorical variable divides the data
+into cells according to the values of that variable.  When all the
+variables named on @code{TABLE} are categorical, by default each cell
+displays the number of cases that it contains, so specifying a single
+variable yields a frequency table:
+
+@example
+CTABLES /TABLE=AgeGroup.
+@end example
+@psppoutput {ctables1}
+
+@noindent
+Specifying a row and a column categorical variable yields a
+crosstabulation:
+
+@example
+CTABLES /TABLE=AgeGroup BY qns3a.
+@end example
+@psppoutput {ctables2}
+
+@noindent
+The @samp{>} ``nesting'' operator nests multiple variables on a single
+axis, e.g.:
+
+@example
+CTABLES /TABLE qn105ba BY AgeGroup > qns3a.
+@end example
+@psppoutput {ctables3}
+
+@noindent
+The @samp{+} ``stacking'' operator allows a single output table to
+include multiple data analyses.  With @samp{+}, @code{CTABLES} divides
+the output table into multiple @dfn{sections}, each of which includes
+an analysis of the full data set.  For example, the following command
+separately tabulates age group and driving frequency by gender:
+
+@example
+CTABLES /TABLE AgeGroup + qn1 BY qns3a.
+@end example
+@psppoutput {ctables4}
+
+@noindent
+When @samp{+} and @samp{>} are used together, @samp{>} binds more
+tightly.  Use parentheses to override operator precedence.  Thus:
+
+@example
+CTABLES /TABLE qn26 + qn27 > qns3a.
+CTABLES /TABLE (qn26 + qn27) > qns3a.
+@end example
+@psppoutput {ctables5}
+
+@node CTABLES Scalar Variable Basics
+@subsubsection Scalar Variables
+
+For a categorical variable, @code{CTABLES} divides the table into a
+cell per category.  For a scalar variables, @code{CTABLES} instead
+calculates a summary measure, by default the mean, of the values that
+fall into a cell.  For example, if the only variable specified is a
+scalar variable, then the output is a single cell that holds the mean
+of all of the data:
+
+@example
+CTABLES /TABLE qnd1.
+@end example
+@psppoutput {ctables6}
+
+A scalar variable may nest with categorical variables.  The following
+example shows the mean age of survey respondents across gender and
+language groups:
+
+@example
+CTABLES /TABLE qns3a > qnd1 BY region.
+@end example
+@psppoutput {ctables7}
+
+The order of nesting of scalar and categorical variables affects table
+labeling, but it does not affect the data displayed in the table.  The
+following example shows how the output changes when the nesting order
+of the scalar and categorical variable are interchanged:
+
+@example
+CTABLES /TABLE qnd1 > qns3a BY region.
+@end example
+@psppoutput {ctables8}
+
+Only a single scalar variable may appear in each section; that is, a
+scalar variable may not nest inside a scalar variable directly or
+indirectly.  Scalar variables may only appear on one axis within
+@code{TABLE}.
+
+@node CTABLES Overriding Measurement Level
+@subsubsection Overriding Measurement Level
+
+By default, @code{CTABLES} uses a variable's measurement level to
+decide whether to treat it as categorical or scalar.  Variables
+assigned the nominal or ordinal measurement level are treated as
+categorical, and scalar variables are treated as scalar.
+
+Use the @code{VARIABLE LEVEL} command to change a variable's
+measurement level (@pxref{VARIABLE LEVEL}).  To treat a variable as
+categorical or scalar only for one use on @code{CTABLES}, add
+@samp{[C]} or @samp{[S]}, respectively, after the variable name.  The
+following example shows how to analyze the scalar variable @code{qn20}
+as categorical:
+
+@example
+CTABLES /TABLE qn20 [C] BY qns3a.
+@end example
+@psppoutput {ctables9}
+
+@node CTABLES Multiple Response Sets
+@subsubheading Multiple Response Sets
+
+The @code{CTABLES} command does not yet support multiple response
+sets.
+
+@node CTABLES Data Summarization
+@subsection Data Summarization
+
+The @code{CTABLES} command allows the user to control how the data are
+summarized with summary specifications, which are enclosed in square
+brackets following a variable name on the @code{TABLE} subcommand.
+When all the variables are categorical, summary specifications can be
+given for the innermost nested variables on any one axis.  When a
+scalar variable is present, only the scalar variable may have summary
+specifications.  The following example includes a summary
+specification for column and row percentages for categorical
+variables, and mean and median for a scalar variable:
+
+@example
+CTABLES
+    /TABLE=qnd1 [MEAN, MEDIAN] BY qns3a
+    /TABLE=AgeGroup [COLPCT, ROWPCT] BY qns3a.
+@end example
+@psppoutput {ctables10}
+
+A summary specification may override the default label and format by
+appending a string or format specification or both (in that order) to
+the summary function name.  For example:
+
+@example
+CTABLES /TABLE=AgeGroup [COLPCT 'Gender %' PCT5.0,
+                         ROWPCT 'Age Group %' PCT5.0]
+               BY qns3a.
+@end example
+@psppoutput {ctables11}
+
+Parentheses provide a shorthand to apply summary specifications to
+multiple variables.  For example, both of these commands:
+
+@example
+CTABLES /TABLE=AgeGroup[COLPCT] + qns1[COLPCT] BY qns3a.
+CTABLES /TABLE=(AgeGroup + qns1)[COLPCT] BY qns3a.
+@end example
+
+@noindent
+produce the same output shown below:
+
+@psppoutput {ctables12}
+
+The following section lists the available summary functions.
+
+@menu
+* CTABLES Summary Functions::
+@end menu
+
+@node CTABLES Summary Functions
+@subsubsection Summary Functions
+
+This section lists the summary functions that can be applied to cells
+in @code{CTABLES}.  Many of these functions have an @var{area} in
+their names.  The supported areas are:
+
+@itemize @bullet
+@item
+Areas that correspond to parts of @dfn{subtables}, whose contents are
+the cells that pair an innermost row variable and an innermost column
+variable:
+
+@table @code
+@item ROW
+A row within a subtable.
+
+@item COL
+A column within a subtable.
+
+@item SUBTABLE
+All the cells in a subtable
+@end table
+
+@item
+Areas that correspond to parts of @dfn{sections}, where stacked
+variables divide each section from another:
+
+@table @code
+@item TABLE
+An entire section.
+
+@item LAYER
+A layer within a section.
+
+@item LAYERROW
+A row in one layer within a section.
+
+@item LAYERCOL
+A column in one layer within a section.
+@end table
+@end itemize
+
+The following summary functions may be applied to any variable
+regardless of whether it is categorical or scalar.  The default label
+for each function is listed in parentheses:
+
+@table @asis
+@item @code{COUNT} (``Count'')
+The sum of weights in a cell.
+
+@item @code{@i{area}PCT} or @code{@i{area}PCT.COUNT} (``@i{Area} %'')
+A percentage within the specified @var{area}.
+
+@item @code{@i{area}PCT.VALIDN} (``@i{Area} Valid N %'')
+A percentage of valid values within the specified @var{area}.
+
+@item @code{@i{area}PCT.TOTALN} (``@i{Area} Total N %'')
+A percentage of total values within the specified @var{area}.
+@end table
+
+The following summary functions apply only to scale variables:
+
+@table @asis
+@item @code{MAXIMUM} (``Maximum'')
+The largest value.
+
+@item @code{MEAN} (``Mean'')
+The mean.
+
+@item @code{MEDIAN} (``Median'')
+The median value.
+
+@item @code{MINIMUM} (``Minimum'')
+The smallest value.
+
+@item @code{MISSING} (``Missing'')
+Sum of weights of user- and system-missing values.
+
+@item @code{MODE} (``Mode'')
+The highest-frequency value.  Ties are broken by taking the smallest mode.
+
+@item @code{@i{area}PCT.SUM} (``@i{Area} Sum %'')
+Percentage of the sum of the values across @var{area}.
+
+@item @code{PTILE} @i{n} (``Percentile @i{n}'')
+The @var{n}th percentile, where @math{0 @leq{} @var{n} @leq{} 100}.
+
+@item @code{RANGE} (``Range'')
+The maximum minus the minimum.
+
+@item @code{SEMEAN} (``Std Error of Mean'')
+The standard error of the mean.
+
+@item @code{STDDEV} (``Std Deviation'')
+The standard deviation.
+
+@item @code{SUM} (``Sum'')
+The sum.
+
+@item @code{TOTALN} (``Total N'')
+The sum of total count weights.
+
+@item @code{VALIDN} (``Valid N'')
+The sum of valid count weights.
+
+@item @code{VARIANCE} (``Variance'')
+The variance.
+@end table
+
+If the @code{WEIGHT} subcommand specified an adjustment weight
+variable, then the following summary functions use its value instead
+of the dictionary weight variable.  Otherwise, they are equivalent to
+the summary function without the @samp{E}-prefix:
+
+@itemize @bullet
+@item
+@code{ECOUNT} (``Adjusted Count'')
+
+@item
+@code{ETOTALN} (``Adjusted Total N'')
+
+@item
+@code{EVALIDN} (``Adjusted Valid N'')
+@end itemize
+
+The following summary functions with a @samp{U}-prefix are equivalent
+to the same ones without the prefix, except that they use unweighted
+counts:
+
+@itemize @bullet
+@item
+@code{UCOUNT} (``Unweighted Count'')
+
+@item
+@code{U@i{area}PCT} or @code{U@i{area}PCT.COUNT} (``Unweighted @i{Area} %'')
+
+@item
+@code{U@i{area}PCT.VALIDN} (``Unweighted @i{Area} Valid N %'')
+
+@item
+@code{U@i{area}PCT.TOTALN} (``Unweighted @i{Area} Total N %'')
+
+@item
+@code{UMEAN} (``Unweighted Mean'')
+
+@item
+@code{UMEDIAN} (``Unweighted Median'')
+
+@item
+@code{UMISSING} (``Unweighted Missing'')
+
+@item
+@code{UMODE} (``Unweight Mode'')
+
+@item
+@code{U@i{area}PCT.SUM} (``Unweighted @i{Area} Sum %'')
+
+@item
+@code{UPTILE} @i{n} (``Unweighted Percentile @i{n}'') 
+
+@item
+@code{USEMEAN} (``Unweighted Std Error of Mean'')
+
+@item
+@code{USTDDEV} (``Unweighted Std Deviation'')
+
+@item
+@code{USUM} (``Unweighted Sum'')
+
+@item
+@code{UTOTALN} (``Unweighted Total N'')
+
+@item
+@code{UVALIDN} (``Unweighted Valid N'')
+
+@item
+@code{UVARIANCE} (``Unweighted Variance'')
+@end itemize
 
 @node FACTOR
 @section FACTOR
index 5cc1a23620a9d530fa142b0db15675f93f14c47c..ab6f83daea2d91c815ebc42e5edd106dafd827d1 100644 (file)
@@ -600,18 +600,12 @@ purposes.   It does not affect the display of variables in the @pspp{} output.
 @section VARIABLE LEVEL
 @vindex VARIABLE LEVEL
 @display
-VARIABLE LEVEL
-        @var{var_list} ( SCALE | NOMINAL | ORDINAL )
-        [ /@var{var_list} ( SCALE | NOMINAL | ORDINAL ) ]
-        .
-        .
-        .
-        [ /@var{var_list} ( SCALE | NOMINAL | ORDINAL ) ]
+@t{VARIABLE LEVEL} @i{variables} @t{(}@{@t{SCALE} @math{|} @t{NOMINAL} @math{|} @t{ORDINAL}@}@t{)}@dots{}
 @end display
 
-@cmd{VARIABLE LEVEL} sets the measurement level of  variables.
-Currently, this has no effect except for certain third party software.
-
+@cmd{VARIABLE LEVEL} sets the measurement level of @var{variables} as
+specified.  @xref{Attributes}, for the definitions of the available
+measurement levels.
 
 @node VARIABLE ROLE
 @section VARIABLE ROLE
index fd78765c00bc9b86fecfdd025d8f3a572fe190dc..21244bc40814cf5696a7ad43c68258212e6ed400 100644 (file)
@@ -25,6 +25,9 @@ examples_DATA = \
        examples/grid.sps \
        examples/hotel.sav \
        examples/horticulture.sav \
+       examples/nhtsa.sav \
+       examples/nhtsa-drinking-2008.sav \
+       examples/nhtsa-drinking-2008.sps \
        examples/personnel.sav \
        examples/physiology.sav \
        examples/repairs.sav \
diff --git a/examples/nhtsa-drinking-2008.sav b/examples/nhtsa-drinking-2008.sav
new file mode 100644 (file)
index 0000000..bae9e01
Binary files /dev/null and b/examples/nhtsa-drinking-2008.sav differ
diff --git a/examples/nhtsa-drinking-2008.sps b/examples/nhtsa-drinking-2008.sps
new file mode 100644 (file)
index 0000000..2fb8306
--- /dev/null
@@ -0,0 +1,97 @@
+GET 'nhtsa-drinking-2008.sav'.
+VARIABLE LEVEL
+   ALL (NOMINAL)
+   qns1 qn1 qn15 qn49 qn87 qn103 qn1058ba TO qn105bd qn122c qn139a TO qn139n qn139ca TO qn139cn qn140aa TO qn140af qnd8 qnd11 (ORDINAL)
+   id qn18 qn19a qn20 qn23 qn31 qn35 qn36 qn38 qn41 qn44 qn52 qn65 qn66 qn114 qn121 qn126 qnd1 qnd1b qnd9 (SCALE).
+FORMATS
+    state qns1 qn1 (F2.0)
+    qn100 qn102 qn103 qn116 qn123 qn131a qn133 qn139a qn139e qn139g qn139h (F1.0).
+MISSING VALUES
+    qns1 (97, 98, 99)
+    qn1 (6, 7)
+    qn15 (8, 9)
+    qn17 (2, 3)
+    qn18 (98, 99)
+    qn19a (97, 98, 99)
+    qn20 qn23 (98, 99)
+    qn26 qn27 qn28 qn29 (3, 4)
+    qn31 (98, 99)
+    qn33 (3, 4)
+    qn35 (998, 999)
+    qn36 (98, 99)
+    qn37 (2, 3)
+    qn38 (998, 999)
+    qn39h (0)
+    qn39m (0)
+    qn41 (998, 999)
+    qn43a (3, 4)
+    qn44 (98, 99)
+    qn44a (98, 99)
+    qn49 (5, 6)
+    qn52 (998, 999)
+    qn56 (2, 3)
+    qn57 (3, 4)
+    qn61 (3, 4)
+    qn64b (3, 4)
+    qn65 (98, 99)
+    qn65a (3, 4)
+    qn66 (98, 99)
+    qn86 (3, 4)
+    qn87 (6, 7)
+    qn88_1 qn88_2 qn88_3 (2, 3)
+    qn89 qn90 qn90a (3, 4)
+    qn91_1 qn91_2 qn91_3 (2, 3)
+    qn96a (3, 4)
+    qn100 (3, 4)
+    qn101 (2, 3)
+    qn102 qn102b qn102c (3, 4)
+    qn103 (4, 5)
+    qn105ba qn105bb qn105bc qn105bd (6, 7)
+    qn113 (3, 4)
+    qn114 (98, 99)
+    qn116 (7, 8)
+    qn120 (3, 4)
+    qn121 (998, 999)
+    qn122c (6, 7)
+    qn123 (3, 4)
+    qn126 (98, 99)
+    qn131a (3, 4)
+    qn132a (3, 4)
+    qn133 (3, 4)
+    qn139a qn139e qn139g qn139h qn139k qn139l qn139m qn139n (6, 7)
+    qn139_a (3, 4)
+    qn139_b (98, 99)
+    qn139ca qn139ce qn139cf qn139cg qn139ch qn139ck qn139cl qn139cn (6, 7)
+    qn140aa qn140ab qn140ac qn140ad qn140ae qn140af (6, 7)
+    qnd1 (998, 999)
+    qnd1b (8, 9)
+    qnd2_1 qnd2_2 qnd2_3 (2, 3)
+    qnd3 (10, 11)
+    qnd5 (3, 4)
+    qnd5a (9, 10)
+    qnd6_1 qnd6_2 qnd6_3 qnd6_4 qnd6_5 (2, 3)
+    qnd7a (3, 4)
+    qnd8 (8, 9)
+    qnd9 (997, 998, 999)
+    qnd11a (3, 4)
+    qnd11 (6, 7).
+RECODE qnd1 (LO THRU 15=1)
+            (16 THRU 25=2)
+            (26 THRU 35=3)
+            (36 THRU 45=4)
+            (46 THRU 55=5)
+            (56 THRU 65=6)
+            (66 THRU HI=7)
+       INTO agegroup.
+VAR LEVEL agegroup (ORDINAL).
+VARIABLE LABEL agegroup 'Age group'.
+VALUE LABELS
+    /agegroup
+     1 '15 or younger'
+     2 '16 to 25'
+     3 '26 to 35'
+     4 '36 to 45'
+     5 '46 to 55'
+     6 '56 to 65'
+     7 '66 or older'.
+SAVE OUTFILE='nhtsa.sav'.
diff --git a/examples/nhtsa.sav b/examples/nhtsa.sav
new file mode 100644 (file)
index 0000000..9e63f33
Binary files /dev/null and b/examples/nhtsa.sav differ
index 352f7c107893067ce6e3ae8ce873d211969b3e27..6db5e74e2e60b54bfe28603f9fc833c03a2166b3 100644 (file)
@@ -114,6 +114,7 @@ DEF_CMD (S_DATA, 0, "AUTORECODE", cmd_autorecode)
 DEF_CMD (S_DATA, 0, "BEGIN DATA", cmd_begin_data)
 DEF_CMD (S_DATA, 0, "COUNT", cmd_count)
 DEF_CMD (S_DATA, 0, "CROSSTABS", cmd_crosstabs)
+DEF_CMD (S_DATA, 0, "CTABLES", cmd_ctables)
 DEF_CMD (S_DATA, 0, "CORRELATIONS", cmd_correlation)
 DEF_CMD (S_DATA, 0, "DELETE VARIABLES", cmd_delete_variables)
 DEF_CMD (S_DATA, 0, "DESCRIPTIVES", cmd_descriptives)
@@ -194,7 +195,6 @@ UNIMPL_CMD ("CSLOGISTIC", "Complex samples logistic regression")
 UNIMPL_CMD ("CSPLAN", "Complex samples design")
 UNIMPL_CMD ("CSSELECT", "Select complex samples")
 UNIMPL_CMD ("CSTABULATE", "Tabulate complex samples")
-UNIMPL_CMD ("CTABLES", "Display complex samples")
 UNIMPL_CMD ("CURVEFIT", "Fit curve to line plot")
 UNIMPL_CMD ("DATE", "Create time series data")
 UNIMPL_CMD ("DETECTANOMALY", "Find unusual cases")
index 460e95e7077d1cf1c773e3b298b2071ed449713f..99d00510817f89e48d5c080e9e1282ac2be1c523 100644 (file)
@@ -31,6 +31,7 @@ language_stats_sources = \
        src/language/stats/cochran.h \
        src/language/stats/correlations.c \
        src/language/stats/crosstabs.c \
+       src/language/stats/ctables.c \
        src/language/stats/descriptives.c \
        src/language/stats/examine.c \
        src/language/stats/factor.c \
diff --git a/src/language/stats/ctables.c b/src/language/stats/ctables.c
new file mode 100644 (file)
index 0000000..51493b0
--- /dev/null
@@ -0,0 +1,5302 @@
+/* PSPP - a program for statistical analysis.
+   Copyright (C) 2021 Free Software Foundation, Inc.
+
+   This program is free software: you can redistribute it and/or modify
+   it under the terms of the GNU General Public License as published by
+   the Free Software Foundation, either version 3 of the License, or
+   (at your option) any later version.
+
+   This program is distributed in the hope that it will be useful,
+   but WITHOUT ANY WARRANTY; without even the implied warranty of
+   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+   GNU General Public License for more details.
+
+   You should have received a copy of the GNU General Public License
+   along with this program.  If not, see <http://www.gnu.org/licenses/>. */
+
+#include <config.h>
+
+#include <math.h>
+#include <errno.h>
+
+#include "data/casereader.h"
+#include "data/casewriter.h"
+#include "data/dataset.h"
+#include "data/dictionary.h"
+#include "data/mrset.h"
+#include "data/subcase.h"
+#include "data/value-labels.h"
+#include "language/command.h"
+#include "language/lexer/format-parser.h"
+#include "language/lexer/lexer.h"
+#include "language/lexer/variable-parser.h"
+#include "libpspp/array.h"
+#include "libpspp/assertion.h"
+#include "libpspp/hash-functions.h"
+#include "libpspp/hmap.h"
+#include "libpspp/i18n.h"
+#include "libpspp/message.h"
+#include "libpspp/string-array.h"
+#include "math/mode.h"
+#include "math/moments.h"
+#include "math/percentiles.h"
+#include "math/sort.h"
+#include "output/pivot-table.h"
+
+#include "gl/minmax.h"
+#include "gl/xalloc.h"
+
+#include "gettext.h"
+#define _(msgid) gettext (msgid)
+#define N_(msgid) (msgid)
+
+enum ctables_vlabel
+  {
+    CTVL_NONE = SETTINGS_VALUE_SHOW_DEFAULT,
+    CTVL_NAME = SETTINGS_VALUE_SHOW_VALUE,
+    CTVL_LABEL = SETTINGS_VALUE_SHOW_LABEL,
+    CTVL_BOTH = SETTINGS_VALUE_SHOW_BOTH,
+  };
+
+/* XXX:
+   - unweighted summaries (U*)
+   - lower confidence limits (*.LCL)
+   - upper confidence limits (*.UCL)
+   - standard error (*.SE)
+ */
+#define SUMMARIES                                                       \
+    /* All variables. */                                                \
+    S(CTSF_COUNT, "COUNT", N_("Count"), CTF_COUNT, CTFA_ALL)            \
+    S(CTSF_ECOUNT, "ECOUNT", N_("Adjusted Count"), CTF_COUNT, CTFA_ALL) \
+    S(CTSF_ROWPCT_COUNT, "ROWPCT.COUNT", N_("Row %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_COLPCT_COUNT, "COLPCT.COUNT", N_("Column %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_TABLEPCT_COUNT, "TABLEPCT.COUNT", N_("Table %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_SUBTABLEPCT_COUNT, "SUBTABLEPCT.COUNT", N_("Subtable %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERPCT_COUNT, "LAYERPCT.COUNT", N_("Layer %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERROWPCT_COUNT, "LAYERROWPCT.COUNT", N_("Layer Row %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERCOLPCT_COUNT, "LAYERCOLPCT.COUNT", N_("Layer Column %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_ROWPCT_VALIDN, "ROWPCT.VALIDN", N_("Row Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_COLPCT_VALIDN, "COLPCT.VALIDN", N_("Column Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_TABLEPCT_VALIDN, "TABLEPCT.VALIDN", N_("Table Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_SUBTABLEPCT_VALIDN, "SUBTABLEPCT.VALIDN", N_("Subtable Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERPCT_VALIDN, "LAYERPCT.VALIDN", N_("Layer Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERROWPCT_VALIDN, "LAYERROWPCT.VALIDN", N_("Layer Row Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERCOLPCT_VALIDN, "LAYERCOLPCT.VALIDN", N_("Layer Column Valid N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_ROWPCT_TOTALN, "ROWPCT.TOTALN", N_("Row Total N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_COLPCT_TOTALN, "COLPCT.TOTALN", N_("Column Total N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_TABLEPCT_TOTALN, "TABLEPCT.TOTALN", N_("Table Total N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_SUBTABLEPCT_TOTALN, "SUBTABLEPCT.TOTALN", N_("Subtable Total N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERPCT_TOTALN, "LAYERPCT.TOTALN", N_("Layer Total N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERROWPCT_TOTALN, "LAYERROWPCT.TOTALN", N_("Layer Row Total N %"), CTF_PERCENT, CTFA_ALL) \
+    S(CTSF_LAYERCOLPCT_TOTALN, "LAYERCOLPCT.TOTALN", N_("Layer Column Total N %"), CTF_PERCENT, CTFA_ALL) \
+                                                                        \
+    /* Scale variables, totals, and subtotals. */                       \
+    S(CTSF_MAXIMUM, "MAXIMUM", N_("Maximum"), CTF_GENERAL, CTFA_SCALE)  \
+    S(CTSF_MEAN, "MEAN", N_("Mean"), CTF_GENERAL, CTFA_SCALE)           \
+    S(CTSF_MEDIAN, "MEDIAN", N_("Median"), CTF_GENERAL, CTFA_SCALE)     \
+    S(CTSF_MINIMUM, "MINIMUM", N_("Minimum"), CTF_GENERAL, CTFA_SCALE)  \
+    S(CTSF_MISSING, "MISSING", N_("Missing"), CTF_GENERAL, CTFA_SCALE)  \
+    S(CTSF_MODE, "MODE", N_("Mode"), CTF_GENERAL, CTFA_SCALE)           \
+    S(CTSF_PTILE, "PTILE", N_("Percentile"), CTF_GENERAL, CTFA_SCALE)   \
+    S(CTSF_RANGE, "RANGE", N_("Range"), CTF_GENERAL, CTFA_SCALE)        \
+    S(CTSF_SEMEAN, "SEMEAN", N_("Std Error of Mean"), CTF_GENERAL, CTFA_SCALE) \
+    S(CTSF_STDDEV, "STDDEV", N_("Std Deviation"), CTF_GENERAL, CTFA_SCALE) \
+    S(CTSF_SUM, "SUM", N_("Sum"), CTF_GENERAL, CTFA_SCALE)              \
+    S(CSTF_TOTALN, "TOTALN", N_("Total N"), CTF_COUNT, CTFA_SCALE)      \
+    S(CTSF_ETOTALN, "ETOTALN", N_("Adjusted Total N"), CTF_COUNT, CTFA_SCALE) \
+    S(CTSF_VALIDN, "VALIDN", N_("Valid N"), CTF_COUNT, CTFA_SCALE)      \
+    S(CTSF_EVALIDN, "EVALIDN", N_("Adjusted Valid N"), CTF_COUNT, CTFA_SCALE) \
+    S(CTSF_VARIANCE, "VARIANCE", N_("Variance"), CTF_GENERAL, CTFA_SCALE) \
+    S(CTSF_ROWPCT_SUM, "ROWPCT.SUM", N_("Row Sum %"), CTF_PERCENT, CTFA_SCALE) \
+    S(CTSF_COLPCT_SUM, "COLPCT.SUM", N_("Column Sum %"), CTF_PERCENT, CTFA_SCALE) \
+    S(CTSF_TABLEPCT_SUM, "TABLEPCT.SUM", N_("Table Sum %"), CTF_PERCENT, CTFA_SCALE) \
+    S(CTSF_SUBTABLEPCT_SUM, "SUBTABLEPCT.SUM", N_("Subtable Sum %"), CTF_PERCENT, CTFA_SCALE) \
+    S(CTSF_LAYERPCT_SUM, "LAYERPCT.SUM", N_("Layer Sum %"), CTF_PERCENT, CTFA_SCALE) \
+    S(CTSF_LAYERROWPCT_SUM, "LAYERROWPCT.SUM", N_("Layer Row Sum %"), CTF_PERCENT, CTFA_SCALE) \
+    S(CTSF_LAYERCOLPCT_SUM, "LAYERCOLPCT.SUM", N_("Layer Column Sum %"), CTF_PERCENT, CTFA_SCALE) \
+                                                                        \
+    /* Multiple response sets. */                                       \
+  S(CTSF_RESPONSES, "RESPONSES", N_("Responses"), CTF_COUNT, CTFA_MRSETS) \
+    S(CTSF_ROWPCT_RESPONSES, "ROWPCT.RESPONSES", N_("Row Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_COLPCT_RESPONSES, "COLPCT.RESPONSES", N_("Column Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_TABLEPCT_RESPONSES, "TABLEPCT.RESPONSES", N_("Table Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_SUBTABLEPCT_RESPONSES, "SUBTABLEPCT.RESPONSES", N_("Subtable Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERPCT_RESPONSES, "LAYERPCT.RESPONSES", N_("Layer Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERROWPCT_RESPONSES, "LAYERROWPCT.RESPONSES", N_("Layer Row Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERCOLPCT_RESPONSES, "LAYERCOLPCT.RESPONSES", N_("Layer Column Responses %"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_ROWPCT_RESPONSES_COUNT, "ROWPCT.RESPONSES.COUNT", N_("Row Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_COLPCT_RESPONSES_COUNT, "COLPCT.RESPONSES.COUNT", N_("Column Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_TABLEPCT_RESPONSES_COUNT, "TABLEPCT.RESPONSES.COUNT", N_("Table Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_SUBTABLEPCT_RESPONSES_COUNT, "SUBTABLEPCT.RESPONSES.COUNT", N_("Subtable Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERPCT_RESPONSES_COUNT, "LAYERPCT.RESPONSES.COUNT", N_("Layer Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERROWPCT_RESPONSES_COUNT, "LAYERROWPCT.RESPONSES.COUNT", N_("Layer Row Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERCOLPCT_RESPONSES_COUNT, "LAYERCOLPCT.RESPONSES.COUNT", N_("Layer Column Responses % (Base: Count)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_ROWPCT_COUNT_RESPONSES, "ROWPCT.COUNT.RESPONSES", N_("Row Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_COLPCT_COUNT_RESPONSES, "COLPCT.COUNT.RESPONSES", N_("Column Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_TABLEPCT_COUNT_RESPONSES, "TABLEPCT.COUNT.RESPONSES", N_("Table Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_SUBTABLEPCT_COUNT_RESPONSES, "SUBTABLEPCT.COUNT.RESPONSES", N_("Subtable Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERPCT_COUNT_RESPONSES, "LAYERPCT.COUNT.RESPONSES", N_("Layer Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERROWPCT_COUNT_RESPONSES, "LAYERROWPCT.COUNT.RESPONSES", N_("Layer Row Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS) \
+    S(CTSF_LAYERCOLPCT_COUNT_RESPONSES, "LAYERCOLPCT.RESPONSES.COUNT", N_("Layer Column Count % (Base: Responses)"), CTF_PERCENT, CTFA_MRSETS)
+
+enum ctables_summary_function
+  {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) ENUM,
+    SUMMARIES
+#undef S
+  };
+
+enum {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) +1
+  N_CTSF_FUNCTIONS = SUMMARIES
+#undef S
+};
+
+enum ctables_domain_type
+  {
+    /* Within a section, where stacked variables divide one section from
+       another. */
+    CTDT_TABLE,                  /* All layers of a whole section. */
+    CTDT_LAYER,                  /* One layer within a section. */
+    CTDT_LAYERROW,               /* Row in one layer within a section. */
+    CTDT_LAYERCOL,               /* Column in one layer within a section. */
+
+    /* Within a subtable, where a subtable pairs an innermost row variable with
+       an innermost column variable within a single layer.  */
+    CTDT_SUBTABLE,               /* Whole subtable. */
+    CTDT_ROW,                    /* Row within a subtable. */
+    CTDT_COL,                    /* Column within a subtable. */
+#define N_CTDTS 7
+  };
+
+struct ctables_domain
+  {
+    struct hmap_node node;
+
+    const struct ctables_cell *example;
+
+    double d_valid;             /* Dictionary weight. */
+    double d_missing;
+    double e_valid;             /* Effective weight */
+    double e_missing;
+  };
+
+enum ctables_summary_variant
+  {
+    CSV_CELL,
+    CSV_TOTAL
+#define N_CSVS 2
+  };
+
+struct ctables_cell
+  {
+    /* In struct ctables_section's 'cells' hmap.  Indexed by all the values in
+       all the axes (except the scalar variable, if any). */
+    struct hmap_node node;
+
+    /* The domains that contain this cell. */
+    bool contributes_to_domains;
+    struct ctables_domain *domains[N_CTDTS];
+
+    bool hide;
+    bool postcompute;
+    enum ctables_summary_variant sv;
+
+    struct ctables_cell_axis
+      {
+        struct ctables_cell_value
+          {
+            const struct ctables_category *category;
+            union value value;
+          }
+        *cvs;
+        int leaf;
+      }
+    axes[PIVOT_N_AXES];
+
+    union ctables_summary *summaries;
+  };
+
+struct ctables
+  {
+    const struct dictionary *dict;
+    struct pivot_table_look *look;
+
+    /* If this is NULL, zeros are displayed using the normal print format.
+       Otherwise, this string is displayed. */
+    char *zero;
+
+    /* If this is NULL, missing values are displayed using the normal print
+       format.  Otherwise, this string is displayed. */
+    char *missing;
+
+    /* Indexed by variable dictionary index. */
+    enum ctables_vlabel *vlabels;
+
+    struct hmap postcomputes;   /* Contains "struct ctables_postcompute"s. */
+
+    bool mrsets_count_duplicates; /* MRSETS. */
+    bool smissing_listwise;       /* SMISSING. */
+    struct variable *e_weight;    /* WEIGHT. */
+    int hide_threshold;           /* HIDESMALLCOUNTS. */
+
+    struct ctables_table **tables;
+    size_t n_tables;
+  };
+
+static struct ctables_postcompute *ctables_find_postcompute (struct ctables *,
+                                                             const char *name);
+
+struct ctables_postcompute
+  {
+    struct hmap_node hmap_node; /* In struct ctables's 'pcompute' hmap. */
+    char *name;                 /* Name, without leading &. */
+
+    struct msg_location *location; /* Location of definition. */
+    struct ctables_pcexpr *expr;
+    char *label;
+    struct ctables_summary_spec_set *specs;
+    bool hide_source_cats;
+  };
+
+struct ctables_pcexpr
+  {
+    /* Precedence table:
+
+       ()
+       **
+       -
+       * /
+       - +
+    */
+    enum ctables_postcompute_op
+      {
+        /* Terminals. */
+        CTPO_CONSTANT,          /* 5 */
+        CTPO_CAT_NUMBER,        /* [5] */
+        CTPO_CAT_STRING,        /* ["STRING"] */
+        CTPO_CAT_RANGE,         /* [LO THRU 5] */
+        CTPO_CAT_MISSING,       /* MISSING */
+        CTPO_CAT_OTHERNM,       /* OTHERNM */
+        CTPO_CAT_SUBTOTAL,      /* SUBTOTAL */
+        CTPO_CAT_TOTAL,         /* TOTAL */
+
+        /* Nonterminals. */
+        CTPO_ADD,
+        CTPO_SUB,
+        CTPO_MUL,
+        CTPO_DIV,
+        CTPO_POW,
+        CTPO_NEG,
+      }
+    op;
+
+    union
+      {
+        /* CTPO_CAT_NUMBER. */
+        double number;
+
+        /* CTPO_CAT_STRING. */
+        char *string;
+
+        /* CTPO_CAT_RANGE. */
+        double range[2];
+
+        /* CTPO_CAT_SUBTOTAL. */
+        size_t subtotal_index;
+
+        /* Two elements: CTPO_ADD, CTPO_SUB, CTPO_MUL, CTPO_DIV, CTPO_POW.
+           One element: CTPO_NEG. */
+        struct ctables_pcexpr *subs[2];
+      };
+
+    /* Source location. */
+    struct msg_location *location;
+  };
+
+static void ctables_pcexpr_destroy (struct ctables_pcexpr *);
+static struct ctables_pcexpr *ctables_pcexpr_allocate_binary (
+  enum ctables_postcompute_op, struct ctables_pcexpr *sub0,
+  struct ctables_pcexpr *sub1);
+
+struct ctables_summary_spec_set
+  {
+    struct ctables_summary_spec *specs;
+    size_t n;
+    size_t allocated;
+
+    struct variable *var;
+  };
+
+static void ctables_summary_spec_set_clone (struct ctables_summary_spec_set *,
+                                            const struct ctables_summary_spec_set *);
+static void ctables_summary_spec_set_uninit (struct ctables_summary_spec_set *);
+
+/* A nested sequence of variables, e.g. a > b > c. */
+struct ctables_nest
+  {
+    struct variable **vars;
+    size_t n;
+    size_t scale_idx;
+    size_t *domains[N_CTDTS];
+    size_t n_domains[N_CTDTS];
+
+    struct ctables_summary_spec_set specs[N_CSVS];
+  };
+
+/* A stack of nestings, e.g. nest1 + nest2 + ... + nestN. */
+struct ctables_stack
+  {
+    struct ctables_nest *nests;
+    size_t n;
+  };
+
+struct ctables_value
+  {
+    struct hmap_node node;
+    union value value;
+    int leaf;
+  };
+
+struct ctables_occurrence
+  {
+    struct hmap_node node;
+    union value value;
+  };
+
+struct ctables_section
+  {
+    struct ctables_table *table;
+    struct ctables_nest *nests[PIVOT_N_AXES];
+    struct hmap *occurrences[PIVOT_N_AXES];
+    struct hmap cells;            /* Contains "struct ctable_cell"s. */
+    struct hmap domains[N_CTDTS]; /* Contains "struct ctable_domain"s. */
+  };
+
+struct ctables_table
+  {
+    struct ctables *ctables;
+    struct ctables_axis *axes[PIVOT_N_AXES];
+    struct ctables_stack stacks[PIVOT_N_AXES];
+    struct ctables_section *sections;
+    size_t n_sections;
+    enum pivot_axis_type summary_axis;
+    struct ctables_summary_spec_set summary_specs;
+
+    const struct variable *clabels_example;
+    struct hmap clabels_values_map;
+    struct ctables_value **clabels_values;
+    size_t n_clabels_values;
+
+    enum pivot_axis_type slabels_axis;
+    bool slabels_visible;
+
+    /* The innermost category labels for axis 'a' appear on axis label_axis[a].
+
+       Most commonly, label_axis[a] == a, and in particular we always have
+       label_axis{PIVOT_AXIS_LAYER] == PIVOT_AXIS_LAYER.
+
+       If ROWLABELS or COLLABELS is specified, then one of
+       label_axis[PIVOT_AXIS_ROW] or label_axis[PIVOT_AXIS_COLUMN] can be the
+       opposite axis or PIVOT_AXIS_LAYER.  Only one of them will differ.
+    */
+    enum pivot_axis_type label_axis[PIVOT_N_AXES];
+    enum pivot_axis_type clabels_from_axis;
+
+    /* Indexed by variable dictionary index. */
+    struct ctables_categories **categories;
+    size_t n_categories;
+
+    double cilevel;
+
+    char *caption;
+    char *corner;
+    char *title;
+
+    struct ctables_chisq *chisq;
+    struct ctables_pairwise *pairwise;
+  };
+
+struct ctables_var
+  {
+    bool is_mrset;
+    union
+      {
+        struct variable *var;
+        const struct mrset *mrset;
+      };
+  };
+
+static const struct fmt_spec *
+ctables_var_get_print_format (const struct ctables_var *var)
+{
+  return (var->is_mrset
+          ? var_get_print_format (var->mrset->vars[0])
+          : var_get_print_format (var->var));
+}
+
+static const char *
+ctables_var_name (const struct ctables_var *var)
+{
+  return var->is_mrset ? var->mrset->name : var_get_name (var->var);
+}
+
+struct ctables_categories
+  {
+    size_t n_refs;
+    struct ctables_category *cats;
+    size_t n_cats;
+    bool show_empty;
+  };
+
+struct ctables_category
+  {
+    enum ctables_category_type
+      {
+        /* Explicit category lists. */
+        CCT_NUMBER,
+        CCT_STRING,
+        CCT_RANGE,
+        CCT_MISSING,
+        CCT_OTHERNM,
+        CCT_POSTCOMPUTE,
+
+        /* Totals and subtotals. */
+        CCT_SUBTOTAL,
+        CCT_TOTAL,
+
+        /* Implicit category lists. */
+        CCT_VALUE,
+        CCT_LABEL,
+        CCT_FUNCTION,
+      }
+    type;
+
+    struct ctables_category *subtotal;
+
+    bool hide;
+
+    union
+      {
+        double number;          /* CCT_NUMBER. */
+        char *string;           /* CCT_STRING. */
+        double range[2];        /* CCT_RANGE. */
+
+        struct
+          {
+            char *total_label;      /* CCT_SUBTOTAL, CCT_TOTAL. */
+            bool hide_subcategories; /* CCT_SUBTOTAL. */
+          };
+
+        const struct ctables_postcompute *pc; /* CCT_POSTCOMPUTE. */
+
+        /* CCT_VALUE, CCT_LABEL, CCT_FUNCTION. */
+        struct
+          {
+            bool include_missing;
+            bool sort_ascending;
+
+            /* CCT_FUNCTION. */
+            enum ctables_summary_function sort_function;
+            struct variable *sort_var;
+            double percentile;
+          };
+      };
+
+    /* Source location.  This is null for CCT_TOTAL, CCT_VALUE, CCT_LABEL,
+       CCT_FUNCTION. */
+    struct msg_location *location;
+  };
+
+static void
+ctables_category_uninit (struct ctables_category *cat)
+{
+  if (!cat)
+    return;
+
+  switch (cat->type)
+    {
+    case CCT_NUMBER:
+    case CCT_RANGE:
+    case CCT_MISSING:
+    case CCT_OTHERNM:
+    case CCT_POSTCOMPUTE:
+      break;
+
+    case CCT_STRING:
+      free (cat->string);
+      break;
+
+    case CCT_SUBTOTAL:
+    case CCT_TOTAL:
+      free (cat->total_label);
+      break;
+
+    case CCT_VALUE:
+    case CCT_LABEL:
+    case CCT_FUNCTION:
+      break;
+    }
+}
+
+static bool
+ctables_category_equal (const struct ctables_category *a,
+                        const struct ctables_category *b)
+{
+  if (a->type != b->type)
+    return false;
+
+  switch (a->type)
+    {
+    case CCT_NUMBER:
+      return a->number == b->number;
+
+    case CCT_STRING:
+      return strcmp (a->string, b->string);
+
+    case CCT_RANGE:
+      return a->range[0] == b->range[0] && a->range[1] == b->range[1];
+
+    case CCT_MISSING:
+    case CCT_OTHERNM:
+      return true;
+
+    case CCT_POSTCOMPUTE:
+      return a->pc == b->pc;
+
+    case CCT_SUBTOTAL:
+    case CCT_TOTAL:
+      return !strcmp (a->total_label, b->total_label);
+
+    case CCT_VALUE:
+    case CCT_LABEL:
+    case CCT_FUNCTION:
+      return (a->include_missing == b->include_missing
+              && a->sort_ascending == b->sort_ascending
+              && a->sort_function == b->sort_function
+              && a->sort_var == b->sort_var
+              && a->percentile == b->percentile);
+    }
+
+  NOT_REACHED ();
+}
+
+static void
+ctables_categories_unref (struct ctables_categories *c)
+{
+  if (!c)
+    return;
+
+  assert (c->n_refs > 0);
+  if (--c->n_refs)
+    return;
+
+  for (size_t i = 0; i < c->n_cats; i++)
+    ctables_category_uninit (&c->cats[i]);
+  free (c->cats);
+  free (c);
+}
+
+static bool
+ctables_categories_equal (const struct ctables_categories *a,
+                          const struct ctables_categories *b)
+{
+  if (a->n_cats != b->n_cats || a->show_empty != b->show_empty)
+    return false;
+
+  for (size_t i = 0; i < a->n_cats; i++)
+    if (!ctables_category_equal (&a->cats[i], &b->cats[i]))
+      return false;
+
+  return true;
+}
+
+/* Chi-square test (SIGTEST). */
+struct ctables_chisq
+  {
+    double alpha;
+    bool include_mrsets;
+    bool all_visible;
+  };
+
+/* Pairwise comparison test (COMPARETEST). */
+struct ctables_pairwise
+  {
+    enum { PROP, MEAN } type;
+    double alpha[2];
+    bool include_mrsets;
+    bool meansvariance_allcats;
+    bool all_visible;
+    enum { BONFERRONI = 1, BH } adjust;
+    bool merge;
+    bool apa_style;
+    bool show_sig;
+  };
+
+struct ctables_axis
+  {
+    enum ctables_axis_op
+      {
+        /* Terminals. */
+        CTAO_VAR,
+
+        /* Nonterminals. */
+        CTAO_STACK,             /* + */
+        CTAO_NEST,              /* > */
+      }
+    op;
+
+    union
+      {
+        /* Terminals. */
+        struct
+          {
+            struct ctables_var var;
+            bool scale;
+            struct ctables_summary_spec_set specs[N_CSVS];
+          };
+
+        /* Nonterminals. */
+        struct ctables_axis *subs[2];
+      };
+
+    struct msg_location *loc;
+  };
+
+static void ctables_axis_destroy (struct ctables_axis *);
+
+enum ctables_format
+  {
+    CTF_COUNT,
+    CTF_PERCENT,
+    CTF_GENERAL
+  };
+
+enum ctables_function_availability
+  {
+    CTFA_ALL,                /* Any variables. */
+    CTFA_SCALE,              /* Only scale variables, totals, and subtotals. */
+    CTFA_MRSETS,             /* Only multiple-response sets */
+  };
+
+struct ctables_summary_spec
+  {
+    enum ctables_summary_function function;
+    double percentile;          /* CTSF_PTILE only. */
+    char *label;
+    struct fmt_spec format;     /* XXX extra CTABLES formats */
+    size_t axis_idx;
+  };
+
+static void
+ctables_summary_spec_clone (struct ctables_summary_spec *dst,
+                            const struct ctables_summary_spec *src)
+{
+  *dst = *src;
+  dst->label = xstrdup (src->label);
+}
+
+static void
+ctables_summary_spec_uninit (struct ctables_summary_spec *s)
+{
+  if (s)
+    free (s->label);
+}
+
+static void
+ctables_summary_spec_set_clone (struct ctables_summary_spec_set *dst,
+                                const struct ctables_summary_spec_set *src)
+{
+  struct ctables_summary_spec *specs = xnmalloc (src->n, sizeof *specs);
+  for (size_t i = 0; i < src->n; i++)
+    ctables_summary_spec_clone (&specs[i], &src->specs[i]);
+
+  *dst = (struct ctables_summary_spec_set) {
+    .specs = specs,
+    .n = src->n,
+    .allocated = src->n,
+    .var = src->var
+  };
+}
+
+static void
+ctables_summary_spec_set_uninit (struct ctables_summary_spec_set *set)
+{
+  for (size_t i = 0; i < set->n; i++)
+    ctables_summary_spec_uninit (&set->specs[i]);
+  free (set->specs);
+}
+
+static bool
+parse_col_width (struct lexer *lexer, const char *name, double *width)
+{
+  lex_match (lexer, T_EQUALS);
+  if (lex_match_id (lexer, "DEFAULT"))
+    *width = SYSMIS;
+  else if (lex_force_num_range_closed (lexer, name, 0, DBL_MAX))
+    {
+      *width = lex_number (lexer);
+      lex_get (lexer);
+    }
+  else
+    return false;
+
+  return true;
+}
+
+static bool
+parse_bool (struct lexer *lexer, bool *b)
+{
+  if (lex_match_id (lexer, "NO"))
+    *b = false;
+  else if (lex_match_id (lexer, "YES"))
+    *b = true;
+  else
+    {
+      lex_error_expecting (lexer, "YES", "NO");
+      return false;
+    }
+  return true;
+}
+
+static enum ctables_function_availability
+ctables_function_availability (enum ctables_summary_function f)
+{
+  static enum ctables_function_availability availability[] = {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) [ENUM] = AVAILABILITY,
+    SUMMARIES
+#undef S
+  };
+
+  return availability[f];
+}
+
+static bool
+parse_ctables_summary_function (struct lexer *lexer,
+                                enum ctables_summary_function *f)
+{
+  struct pair
+    {
+      enum ctables_summary_function function;
+      struct substring name;
+    };
+  static struct pair names[] = {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) \
+    { ENUM, SS_LITERAL_INITIALIZER (NAME) },
+    SUMMARIES
+
+    /* The .COUNT suffix may be omitted. */
+    S(CTSF_ROWPCT_COUNT, "ROWPCT", _, _, _)
+    S(CTSF_COLPCT_COUNT, "COLPCT", _, _, _)
+    S(CTSF_TABLEPCT_COUNT, "TABLEPCT", _, _, _)
+    S(CTSF_SUBTABLEPCT_COUNT, "SUBTABLEPCT", _, _, _)
+    S(CTSF_LAYERPCT_COUNT, "LAYERPCT", _, _, _)
+    S(CTSF_LAYERROWPCT_COUNT, "LAYERROWPCT", _, _, _)
+    S(CTSF_LAYERCOLPCT_COUNT, "LAYERCOLPCT", _, _, _)
+#undef S
+  };
+
+  if (!lex_force_id (lexer))
+    return false;
+
+  for (size_t i = 0; i < sizeof names / sizeof *names; i++)
+    if (ss_equals_case (names[i].name, lex_tokss (lexer)))
+      {
+        *f = names[i].function;
+        lex_get (lexer);
+        return true;
+      }
+
+  lex_error (lexer, _("Expecting summary function name."));
+  return false;
+}
+
+static void
+ctables_axis_destroy (struct ctables_axis *axis)
+{
+  if (!axis)
+    return;
+
+  switch (axis->op)
+    {
+    case CTAO_VAR:
+      for (size_t i = 0; i < N_CSVS; i++)
+        ctables_summary_spec_set_uninit (&axis->specs[i]);
+      break;
+
+    case CTAO_STACK:
+    case CTAO_NEST:
+      ctables_axis_destroy (axis->subs[0]);
+      ctables_axis_destroy (axis->subs[1]);
+      break;
+    }
+  msg_location_destroy (axis->loc);
+  free (axis);
+}
+
+static struct ctables_axis *
+ctables_axis_new_nonterminal (enum ctables_axis_op op,
+                              struct ctables_axis *sub0,
+                              struct ctables_axis *sub1,
+                              struct lexer *lexer, int start_ofs)
+{
+  struct ctables_axis *axis = xmalloc (sizeof *axis);
+  *axis = (struct ctables_axis) {
+    .op = op,
+    .subs = { sub0, sub1 },
+    .loc = lex_ofs_location (lexer, start_ofs, lex_ofs (lexer) - 1),
+  };
+  return axis;
+}
+
+struct ctables_axis_parse_ctx
+  {
+    struct lexer *lexer;
+    struct dictionary *dict;
+    struct ctables *ct;
+    struct ctables_table *t;
+  };
+
+static struct fmt_spec
+ctables_summary_default_format (enum ctables_summary_function function,
+                                const struct ctables_var *var)
+{
+  static const enum ctables_format default_formats[] = {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) [ENUM] = FORMAT,
+    SUMMARIES
+#undef S
+  };
+  switch (default_formats[function])
+    {
+    case CTF_COUNT:
+      return (struct fmt_spec) { .type = FMT_F, .w = 40 };
+
+    case CTF_PERCENT:
+      return (struct fmt_spec) { .type = FMT_PCT, .w = 40, .d = 1 };
+
+    case CTF_GENERAL:
+      return *ctables_var_get_print_format (var);
+
+    default:
+      NOT_REACHED ();
+    }
+}
+
+static char *
+ctables_summary_default_label (enum ctables_summary_function function,
+                               double percentile)
+{
+  static const char *default_labels[] = {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) [ENUM] = LABEL,
+    SUMMARIES
+#undef S
+  };
+
+  return (function == CTSF_PTILE
+          ? xasprintf (_("Percentile %.2f"), percentile)
+          : xstrdup (gettext (default_labels[function])));
+}
+
+static const char *
+ctables_summary_function_name (enum ctables_summary_function function)
+{
+  static const char *names[] = {
+#define S(ENUM, NAME, LABEL, FORMAT, AVAILABILITY) [ENUM] = NAME,
+    SUMMARIES
+#undef S
+  };
+  return names[function];
+}
+
+static bool
+add_summary_spec (struct ctables_axis *axis,
+                  enum ctables_summary_function function, double percentile,
+                  const char *label, const struct fmt_spec *format,
+                  const struct msg_location *loc, enum ctables_summary_variant sv)
+{
+  if (axis->op == CTAO_VAR)
+    {
+      const char *function_name = ctables_summary_function_name (function);
+      const char *var_name = ctables_var_name (&axis->var);
+      switch (ctables_function_availability (function))
+        {
+        case CTFA_MRSETS:
+          if (!axis->var.is_mrset)
+            {
+              msg_at (SE, loc, _("Summary function %s applies only to multiple "
+                                 "response sets."), function_name);
+              msg_at (SN, axis->loc, _("'%s' is not a multiple response set."),
+                      var_name);
+              return false;
+            }
+          break;
+
+        case CTFA_SCALE:
+          if (!axis->scale)
+            {
+              msg_at (SE, loc,
+                      _("Summary function %s applies only to scale variables."),
+                      function_name);
+              msg_at (SN, axis->loc, _("'%s' is not a scale variable."),
+                      var_name);
+              return false;
+            }
+          break;
+
+        case CTFA_ALL:
+          break;
+        }
+
+      struct ctables_summary_spec_set *set = &axis->specs[sv];
+      if (set->n >= set->allocated)
+        set->specs = x2nrealloc (set->specs, &set->allocated,
+                                 sizeof *set->specs);
+
+      struct ctables_summary_spec *dst = &set->specs[set->n++];
+      *dst = (struct ctables_summary_spec) {
+        .function = function,
+        .percentile = percentile,
+        .label = xstrdup (label),
+        .format = (format ? *format
+                   : ctables_summary_default_format (function, &axis->var)),
+      };
+      return true;
+    }
+  else
+    {
+      for (size_t i = 0; i < 2; i++)
+        if (!add_summary_spec (axis->subs[i], function, percentile, label,
+                               format, loc, sv))
+          return false;
+      return true;
+    }
+}
+
+static struct ctables_axis *ctables_axis_parse_stack (
+  struct ctables_axis_parse_ctx *);
+
+static bool
+ctables_var_parse (struct lexer *lexer, struct dictionary *dict,
+                   struct ctables_var *var)
+{
+  if (ss_starts_with (lex_tokss (lexer), ss_cstr ("$")))
+    {
+      *var = (struct ctables_var) {
+        .is_mrset = true,
+        .mrset = dict_lookup_mrset (dict, lex_tokcstr (lexer))
+      };
+      if (!var->mrset)
+        {
+          lex_error (lexer, _("'%s' does not name a multiple-response set "
+                              "in the active file dictionary."),
+                     lex_tokcstr (lexer));
+          return false;
+        }
+      lex_get (lexer);
+      return true;
+    }
+  else
+    {
+      *var = (struct ctables_var) {
+        .is_mrset = false,
+        .var = parse_variable (lexer, dict),
+      };
+      return var->var != NULL;
+    }
+}
+
+static struct ctables_axis *
+ctables_axis_parse_primary (struct ctables_axis_parse_ctx *ctx)
+{
+  if (lex_match (ctx->lexer, T_LPAREN))
+    {
+      struct ctables_axis *sub = ctables_axis_parse_stack (ctx);
+      if (!sub || !lex_force_match (ctx->lexer, T_RPAREN))
+        {
+          ctables_axis_destroy (sub);
+          return NULL;
+        }
+      return sub;
+    }
+
+  if (!lex_force_id (ctx->lexer))
+    return NULL;
+
+  int start_ofs = lex_ofs (ctx->lexer);
+  struct ctables_var var;
+  if (!ctables_var_parse (ctx->lexer, ctx->dict, &var))
+    return NULL;
+
+  struct ctables_axis *axis = xmalloc (sizeof *axis);
+  *axis = (struct ctables_axis) { .op = CTAO_VAR, .var = var };
+
+  /* XXX should figure out default measures by reading data */
+  axis->scale = (var.is_mrset ? false
+                 : lex_match_phrase (ctx->lexer, "[S]") ? true
+                 : lex_match_phrase (ctx->lexer, "[C]") ? false
+                 : var_get_measure (var.var) == MEASURE_SCALE);
+  axis->loc = lex_ofs_location (ctx->lexer, start_ofs,
+                                lex_ofs (ctx->lexer) - 1);
+  return axis;
+}
+
+static bool
+has_digit (const char *s)
+{
+  return s[strcspn (s, "0123456789")] != '\0';
+}
+
+static struct ctables_axis *
+ctables_axis_parse_postfix (struct ctables_axis_parse_ctx *ctx)
+{
+  struct ctables_axis *sub = ctables_axis_parse_primary (ctx);
+  if (!sub || !lex_match (ctx->lexer, T_LBRACK))
+    return sub;
+
+  enum ctables_summary_variant sv = CSV_CELL;
+  for (;;)
+    {
+      int start_ofs = lex_ofs (ctx->lexer);
+
+      /* Parse function. */
+      enum ctables_summary_function function;
+      if (!parse_ctables_summary_function (ctx->lexer, &function))
+        goto error;
+
+      /* Parse percentile. */
+      double percentile = 0;
+      if (function == CTSF_PTILE)
+        {
+          if (!lex_force_num_range_closed (ctx->lexer, "PTILE", 0, 100))
+            goto error;
+          percentile = lex_number (ctx->lexer);
+          lex_get (ctx->lexer);
+        }
+
+      /* Parse label. */
+      char *label;
+      if (lex_is_string (ctx->lexer))
+        {
+          label = ss_xstrdup (lex_tokss (ctx->lexer));
+          lex_get (ctx->lexer);
+        }
+      else
+        label = ctables_summary_default_label (function, percentile);
+
+      /* Parse format. */
+      struct fmt_spec format;
+      const struct fmt_spec *formatp;
+      if (lex_token (ctx->lexer) == T_ID
+          && has_digit (lex_tokcstr (ctx->lexer)))
+        {
+          if (!parse_format_specifier (ctx->lexer, &format)
+              || !fmt_check_output (&format)
+              || !fmt_check_type_compat (&format, VAL_NUMERIC))
+            {
+              free (label);
+              goto error;
+            }
+          formatp = &format;
+        }
+      else
+        formatp = NULL;
+
+      struct msg_location *loc = lex_ofs_location (ctx->lexer, start_ofs,
+                                                   lex_ofs (ctx->lexer) - 1);
+      add_summary_spec (sub, function, percentile, label, formatp, loc, sv);
+      free (label);
+      msg_location_destroy (loc);
+
+      lex_match (ctx->lexer, T_COMMA);
+      if (sv == CSV_CELL && lex_match_id (ctx->lexer, "TOTALS"))
+        {
+          if (!lex_force_match (ctx->lexer, T_LBRACK))
+            goto error;
+          sv = CSV_TOTAL;
+        }
+      else if (lex_match (ctx->lexer, T_RBRACK))
+        {
+          if (sv == CSV_TOTAL && !lex_force_match (ctx->lexer, T_RBRACK))
+            goto error;
+          return sub;
+        }
+    }
+
+error:
+  ctables_axis_destroy (sub);
+  return NULL;
+}
+
+static const struct ctables_axis *
+find_scale (const struct ctables_axis *axis)
+{
+  if (!axis)
+    return NULL;
+  else if (axis->op == CTAO_VAR)
+    {
+      if (axis->scale)
+        {
+          assert (!axis->var.is_mrset);
+          return axis;
+        }
+      else
+        return NULL;
+    }
+  else
+    {
+      for (size_t i = 0; i < 2; i++)
+        {
+          const struct ctables_axis *scale = find_scale (axis->subs[i]);
+          if (scale)
+            return scale;
+        }
+      return NULL;
+    }
+}
+
+static const struct ctables_axis *
+find_categorical_summary_spec (const struct ctables_axis *axis)
+{
+  if (!axis)
+    return NULL;
+  else if (axis->op == CTAO_VAR)
+    return !axis->scale && axis->specs[CSV_CELL].n ? axis : NULL;
+  else
+    {
+      for (size_t i = 0; i < 2; i++)
+        {
+          const struct ctables_axis *sum
+            = find_categorical_summary_spec (axis->subs[i]);
+          if (sum)
+            return sum;
+        }
+      return NULL;
+    }
+}
+
+static struct ctables_axis *
+ctables_axis_parse_nest (struct ctables_axis_parse_ctx *ctx)
+{
+  int start_ofs = lex_ofs (ctx->lexer);
+  struct ctables_axis *lhs = ctables_axis_parse_postfix (ctx);
+  if (!lhs)
+    return NULL;
+
+  while (lex_match (ctx->lexer, T_GT))
+    {
+      struct ctables_axis *rhs = ctables_axis_parse_postfix (ctx);
+      if (!rhs)
+        return NULL;
+
+      struct ctables_axis *nest = ctables_axis_new_nonterminal (
+        CTAO_NEST, lhs, rhs, ctx->lexer, start_ofs);
+
+      const struct ctables_axis *outer_scale = find_scale (lhs);
+      const struct ctables_axis *inner_scale = find_scale (rhs);
+      if (outer_scale && inner_scale)
+        {
+          msg_at (SE, nest->loc, _("Cannot nest scale variables."));
+          msg_at (SN, outer_scale->loc, _("This is an outer scale variable."));
+          msg_at (SN, inner_scale->loc, _("This is an inner scale variable."));
+          ctables_axis_destroy (nest);
+          return NULL;
+        }
+
+      const struct ctables_axis *outer_sum = find_categorical_summary_spec (lhs);
+      if (outer_sum)
+        {
+          msg_at (SE, nest->loc,
+                  _("Summaries may only be requested for categorical variables "
+                    "at the innermost nesting level."));
+          msg_at (SN, outer_sum->loc,
+                  _("This outer categorical variable has a summary."));
+          ctables_axis_destroy (nest);
+          return NULL;
+        }
+
+      lhs = nest;
+    }
+
+  return lhs;
+}
+
+static struct ctables_axis *
+ctables_axis_parse_stack (struct ctables_axis_parse_ctx *ctx)
+{
+  int start_ofs = lex_ofs (ctx->lexer);
+  struct ctables_axis *lhs = ctables_axis_parse_nest (ctx);
+  if (!lhs)
+    return NULL;
+
+  while (lex_match (ctx->lexer, T_PLUS))
+    {
+      struct ctables_axis *rhs = ctables_axis_parse_nest (ctx);
+      if (!rhs)
+        return NULL;
+
+      lhs = ctables_axis_new_nonterminal (CTAO_STACK, lhs, rhs,
+                                          ctx->lexer, start_ofs);
+    }
+
+  return lhs;
+}
+
+static bool
+ctables_axis_parse (struct lexer *lexer, struct dictionary *dict,
+                    struct ctables *ct, struct ctables_table *t,
+                    enum pivot_axis_type a)
+{
+  if (lex_token (lexer) == T_BY
+      || lex_token (lexer) == T_SLASH
+      || lex_token (lexer) == T_ENDCMD)
+    return true;
+
+  struct ctables_axis_parse_ctx ctx = {
+    .lexer = lexer,
+    .dict = dict,
+    .ct = ct,
+    .t = t
+  };
+  t->axes[a] = ctables_axis_parse_stack (&ctx);
+  return t->axes[a] != NULL;
+}
+
+static void
+ctables_chisq_destroy (struct ctables_chisq *chisq)
+{
+  free (chisq);
+}
+
+static void
+ctables_pairwise_destroy (struct ctables_pairwise *pairwise)
+{
+  free (pairwise);
+}
+
+static void
+ctables_table_destroy (struct ctables_table *t)
+{
+  if (!t)
+    return;
+
+  for (size_t i = 0; i < t->n_categories; i++)
+    ctables_categories_unref (t->categories[i]);
+  free (t->categories);
+
+  ctables_axis_destroy (t->axes[PIVOT_AXIS_COLUMN]);
+  ctables_axis_destroy (t->axes[PIVOT_AXIS_ROW]);
+  ctables_axis_destroy (t->axes[PIVOT_AXIS_LAYER]);
+  free (t->caption);
+  free (t->corner);
+  free (t->title);
+  ctables_chisq_destroy (t->chisq);
+  ctables_pairwise_destroy (t->pairwise);
+  free (t);
+}
+
+static void
+ctables_destroy (struct ctables *ct)
+{
+  if (!ct)
+    return;
+
+  pivot_table_look_unref (ct->look);
+  free (ct->zero);
+  free (ct->missing);
+  free (ct->vlabels);
+  for (size_t i = 0; i < ct->n_tables; i++)
+    ctables_table_destroy (ct->tables[i]);
+  free (ct->tables);
+  free (ct);
+}
+
+static struct ctables_category
+cct_range (double low, double high)
+{
+  return (struct ctables_category) {
+    .type = CCT_RANGE,
+    .range = { low, high }
+  };
+}
+
+static bool
+ctables_table_parse_subtotal (struct lexer *lexer, bool hide_subcategories,
+                              struct ctables_category *cat)
+{
+  char *total_label;
+  if (lex_match (lexer, T_EQUALS))
+    {
+      if (!lex_force_string (lexer))
+        return false;
+
+      total_label = ss_xstrdup (lex_tokss (lexer));
+      lex_get (lexer);
+    }
+  else
+    total_label = xstrdup (_("Subtotal"));
+
+  *cat = (struct ctables_category) {
+    .type = CCT_SUBTOTAL,
+    .hide_subcategories = hide_subcategories,
+    .total_label = total_label
+  };
+  return true;
+}
+
+static bool
+ctables_table_parse_explicit_category (struct lexer *lexer, struct ctables *ct,
+                                       struct ctables_category *cat)
+{
+  if (lex_match_id (lexer, "OTHERNM"))
+    *cat = (struct ctables_category) { .type = CCT_OTHERNM };
+  else if (lex_match_id (lexer, "MISSING"))
+    *cat = (struct ctables_category) { .type = CCT_MISSING };
+  else if (lex_match_id (lexer, "SUBTOTAL"))
+    return ctables_table_parse_subtotal (lexer, false, cat);
+  else if (lex_match_id (lexer, "HSUBTOTAL"))
+    return ctables_table_parse_subtotal (lexer, true, cat);
+  else if (lex_match_id (lexer, "LO"))
+    {
+      if (!lex_force_match_id (lexer, "THRU") || lex_force_num (lexer))
+        return false;
+      *cat = cct_range (-DBL_MAX, lex_number (lexer));
+      lex_get (lexer);
+    }
+  else if (lex_is_number (lexer))
+    {
+      double number = lex_number (lexer);
+      lex_get (lexer);
+      if (lex_match_id (lexer, "THRU"))
+        {
+          if (lex_match_id (lexer, "HI"))
+            *cat = cct_range (number, DBL_MAX);
+          else
+            {
+              if (!lex_force_num (lexer))
+                return false;
+              *cat = cct_range (number, lex_number (lexer));
+              lex_get (lexer);
+            }
+        }
+      else
+        *cat = (struct ctables_category) {
+          .type = CCT_NUMBER,
+          .number = number
+        };
+    }
+  else if (lex_is_string (lexer))
+    {
+      *cat = (struct ctables_category) {
+        .type = CCT_STRING,
+        .string = ss_xstrdup (lex_tokss (lexer)),
+      };
+      lex_get (lexer);
+    }
+  else if (lex_match (lexer, T_AND))
+    {
+      if (!lex_force_id (lexer))
+        return false;
+      struct ctables_postcompute *pc = ctables_find_postcompute (
+        ct, lex_tokcstr (lexer));
+      if (!pc)
+        {
+          struct msg_location *loc = lex_get_location (lexer, -1, 0);
+          msg_at (SE, loc, _("Unknown postcompute &%s."),
+                  lex_tokcstr (lexer));
+          msg_location_destroy (loc);
+          return false;
+        }
+      lex_get (lexer);
+
+      *cat = (struct ctables_category) { .type = CCT_POSTCOMPUTE, .pc = pc };
+    }
+  else
+    {
+      lex_error (lexer, NULL);
+      return false;
+    }
+
+  return true;
+}
+
+static struct ctables_category *
+ctables_find_category_for_postcompute (const struct ctables_categories *cats,
+                                       const struct ctables_pcexpr *e)
+{
+  struct ctables_category *best = NULL;
+  size_t n_subtotals = 0;
+  for (size_t i = 0; i < cats->n_cats; i++)
+    {
+      struct ctables_category *cat = &cats->cats[i];
+      switch (e->op)
+        {
+        case CTPO_CAT_NUMBER:
+          if (cat->type == CCT_NUMBER && cat->number == e->number)
+            best = cat;
+          break;
+
+        case CTPO_CAT_STRING:
+          if (cat->type == CCT_STRING && !strcmp (cat->string, e->string))
+            best = cat;
+          break;
+
+        case CTPO_CAT_RANGE:
+          if (cat->type == CCT_RANGE
+              && cat->range[0] == e->range[0]
+              && cat->range[1] == e->range[1])
+            best = cat;
+          break;
+
+        case CTPO_CAT_MISSING:
+          if (cat->type == CCT_MISSING)
+            best = cat;
+          break;
+
+        case CTPO_CAT_OTHERNM:
+          if (cat->type == CCT_OTHERNM)
+            best = cat;
+          break;
+
+        case CTPO_CAT_SUBTOTAL:
+          if (cat->type == CCT_SUBTOTAL)
+            {
+              n_subtotals++;
+              if (e->subtotal_index == n_subtotals)
+                return cat;
+              else if (e->subtotal_index == 0)
+                best = cat;
+            }
+          break;
+
+        case CTPO_CAT_TOTAL:
+          if (cat->type == CCT_TOTAL)
+            return cat;
+          break;
+
+        case CTPO_CONSTANT:
+        case CTPO_ADD:
+        case CTPO_SUB:
+        case CTPO_MUL:
+        case CTPO_DIV:
+        case CTPO_POW:
+        case CTPO_NEG:
+          NOT_REACHED ();
+        }
+    }
+  if (e->op == CTPO_CAT_SUBTOTAL && e->subtotal_index == 0 && n_subtotals > 1)
+    return NULL;
+  return best;
+}
+
+static bool
+ctables_recursive_check_postcompute (const struct ctables_pcexpr *e,
+                                     struct ctables_category *pc_cat,
+                                     const struct ctables_categories *cats,
+                                     const struct msg_location *cats_location)
+{
+  switch (e->op)
+    {
+    case CTPO_CAT_NUMBER:
+    case CTPO_CAT_STRING:
+    case CTPO_CAT_RANGE:
+    case CTPO_CAT_MISSING:
+    case CTPO_CAT_OTHERNM:
+    case CTPO_CAT_SUBTOTAL:
+    case CTPO_CAT_TOTAL:
+      {
+        struct ctables_category *cat = ctables_find_category_for_postcompute (
+          cats, e);
+        if (!cat)
+          {
+            if (e->op == CTPO_CAT_SUBTOTAL && e->subtotal_index == 0)
+              {
+                size_t n_subtotals = 0;
+                for (size_t i = 0; i < cats->n_cats; i++)
+                  n_subtotals += cats->cats[i].type == CCT_SUBTOTAL;
+                if (n_subtotals > 1)
+                  {
+                    msg_at (SE, cats_location,
+                            ngettext ("These categories include %zu instance "
+                                      "of SUBTOTAL or HSUBTOTAL, so references "
+                                      "from computed categories must refer to "
+                                      "subtotals by position.",
+                                      "These categories include %zu instances "
+                                      "of SUBTOTAL or HSUBTOTAL, so references "
+                                      "from computed categories must refer to "
+                                      "subtotals by position.",
+                                      n_subtotals),
+                            n_subtotals);
+                    msg_at (SN, e->location,
+                            _("This is the reference that lacks a position."));
+                    return NULL;
+                  }
+              }
+
+            msg_at (SE, pc_cat->location,
+                    _("Computed category &%s references a category not included "
+                      "in the category list."),
+                    pc_cat->pc->name);
+            msg_at (SN, e->location, _("This is the missing category."));
+            msg_at (SN, cats_location,
+                    _("To fix the problem, add the missing category to the "
+                      "list of categories here."));
+            return false;
+          }
+        if (pc_cat->pc->hide_source_cats)
+          cat->hide = true;
+        return true;
+      }
+
+    case CTPO_CONSTANT:
+      return true;
+
+    case CTPO_ADD:
+    case CTPO_SUB:
+    case CTPO_MUL:
+    case CTPO_DIV:
+    case CTPO_POW:
+    case CTPO_NEG:
+      for (size_t i = 0; i < 2; i++)
+        if (e->subs[i] && !ctables_recursive_check_postcompute (
+              e->subs[i], pc_cat, cats, cats_location))
+          return false;
+      return true;
+
+    default:
+      NOT_REACHED ();
+    }
+}
+
+static bool
+ctables_table_parse_categories (struct lexer *lexer, struct dictionary *dict,
+                                struct ctables *ct, struct ctables_table *t)
+{
+  if (!lex_match_id (lexer, "VARIABLES"))
+    return false;
+  lex_match (lexer, T_EQUALS);
+
+  struct variable **vars;
+  size_t n_vars;
+  if (!parse_variables (lexer, dict, &vars, &n_vars, PV_NO_SCRATCH))
+    return false;
+
+  struct ctables_categories *c = xmalloc (sizeof *c);
+  *c = (struct ctables_categories) { .n_refs = n_vars, .show_empty = true };
+  for (size_t i = 0; i < n_vars; i++)
+    {
+      struct ctables_categories **cp
+        = &t->categories[var_get_dict_index (vars[i])];
+      ctables_categories_unref (*cp);
+      *cp = c;
+    }
+  free (vars);
+
+  size_t allocated_cats = 0;
+  if (lex_match (lexer, T_LBRACK))
+    {
+      int cats_start_ofs = lex_ofs (lexer);
+      do
+        {
+          if (c->n_cats >= allocated_cats)
+            c->cats = x2nrealloc (c->cats, &allocated_cats, sizeof *c->cats);
+
+          int start_ofs = lex_ofs (lexer);
+          struct ctables_category *cat = &c->cats[c->n_cats];
+          if (!ctables_table_parse_explicit_category (lexer, ct, cat))
+            return false;
+          cat->location = lex_ofs_location (lexer, start_ofs, lex_ofs (lexer) - 1);
+          c->n_cats++;
+
+          lex_match (lexer, T_COMMA);
+        }
+      while (!lex_match (lexer, T_RBRACK));
+
+      struct msg_location *cats_location
+        = lex_ofs_location (lexer, cats_start_ofs, lex_ofs (lexer) - 1);
+      for (size_t i = 0; i < c->n_cats; i++)
+        {
+          struct ctables_category *cat = &c->cats[i];
+          if (cat->type == CCT_POSTCOMPUTE
+              && !ctables_recursive_check_postcompute (cat->pc->expr, cat,
+                                                       c, cats_location))
+            return false;
+        }
+    }
+
+  struct ctables_category cat = {
+    .type = CCT_VALUE,
+    .include_missing = false,
+    .sort_ascending = true,
+  };
+  bool show_totals = false;
+  char *total_label = NULL;
+  bool totals_before = false;
+  while (lex_token (lexer) != T_SLASH && lex_token (lexer) != T_ENDCMD)
+    {
+      if (!c->n_cats && lex_match_id (lexer, "ORDER"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (lex_match_id (lexer, "A"))
+            cat.sort_ascending = true;
+          else if (lex_match_id (lexer, "D"))
+            cat.sort_ascending = false;
+          else
+            {
+              lex_error_expecting (lexer, "A", "D");
+              return false;
+            }
+        }
+      else if (!c->n_cats && lex_match_id (lexer, "KEY"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (lex_match_id (lexer, "VALUE"))
+            cat.type = CCT_VALUE;
+          else if (lex_match_id (lexer, "LABEL"))
+            cat.type = CCT_LABEL;
+          else
+            {
+              cat.type = CCT_FUNCTION;
+              if (!parse_ctables_summary_function (lexer, &cat.sort_function))
+                return false;
+
+              if (lex_match (lexer, T_LPAREN))
+                {
+                  cat.sort_var = parse_variable (lexer, dict);
+                  if (!cat.sort_var)
+                    return false;
+
+                  if (cat.sort_function == CTSF_PTILE)
+                    {
+                      lex_match (lexer, T_COMMA);
+                      if (!lex_force_num_range_closed (lexer, "PTILE", 0, 100))
+                        return false;
+                      cat.percentile = lex_number (lexer);
+                      lex_get (lexer);
+                    }
+
+                  if (!lex_force_match (lexer, T_RPAREN))
+                    return false;
+                }
+              else if (ctables_function_availability (cat.sort_function)
+                       == CTFA_SCALE)
+                {
+                  bool UNUSED b = lex_force_match (lexer, T_LPAREN);
+                  return false;
+                }
+            }
+        }
+      else if (!c->n_cats && lex_match_id (lexer, "MISSING"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (lex_match_id (lexer, "INCLUDE"))
+            cat.include_missing = true;
+          else if (lex_match_id (lexer, "EXCLUDE"))
+            cat.include_missing = false;
+          else
+            {
+              lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
+              return false;
+            }
+        }
+      else if (lex_match_id (lexer, "TOTAL"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (!parse_bool (lexer, &show_totals))
+            return false;
+        }
+      else if (lex_match_id (lexer, "LABEL"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (!lex_force_string (lexer))
+            return false;
+          free (total_label);
+          total_label = ss_xstrdup (lex_tokss (lexer));
+          lex_get (lexer);
+        }
+      else if (lex_match_id (lexer, "POSITION"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (lex_match_id (lexer, "BEFORE"))
+            totals_before = true;
+          else if (lex_match_id (lexer, "AFTER"))
+            totals_before = false;
+          else
+            {
+              lex_error_expecting (lexer, "BEFORE", "AFTER");
+              return false;
+            }
+        }
+      else if (lex_match_id (lexer, "EMPTY"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (lex_match_id (lexer, "INCLUDE"))
+            c->show_empty = true;
+          else if (lex_match_id (lexer, "EXCLUDE"))
+            c->show_empty = false;
+          else
+            {
+              lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
+              return false;
+            }
+        }
+      else
+        {
+          if (!c->n_cats)
+            lex_error_expecting (lexer, "ORDER", "KEY", "MISSING",
+                                 "TOTAL", "LABEL", "POSITION", "EMPTY");
+          else
+            lex_error_expecting (lexer, "TOTAL", "LABEL", "POSITION", "EMPTY");
+          return false;
+        }
+    }
+
+  if (!c->n_cats)
+    {
+      if (c->n_cats >= allocated_cats)
+        c->cats = x2nrealloc (c->cats, &allocated_cats, sizeof *c->cats);
+      c->cats[c->n_cats++] = cat;
+    }
+
+  if (show_totals)
+    {
+      if (c->n_cats >= allocated_cats)
+        c->cats = x2nrealloc (c->cats, &allocated_cats, sizeof *c->cats);
+
+      struct ctables_category *totals;
+      if (totals_before)
+        {
+          insert_element (c->cats, c->n_cats, sizeof *c->cats, 0);
+          totals = &c->cats[0];
+        }
+      else
+        totals = &c->cats[c->n_cats];
+      c->n_cats++;
+
+      *totals = (struct ctables_category) {
+        .type = CCT_TOTAL,
+        .total_label = total_label ? total_label : xstrdup (_("Total")),
+      };
+    }
+
+  struct ctables_category *subtotal = NULL;
+  for (size_t i = totals_before ? 0 : c->n_cats;
+       totals_before ? i < c->n_cats : i-- > 0;
+       totals_before ? i++ : 0)
+    {
+      struct ctables_category *cat = &c->cats[i];
+      switch (cat->type)
+        {
+        case CCT_NUMBER:
+        case CCT_STRING:
+        case CCT_RANGE:
+        case CCT_MISSING:
+        case CCT_OTHERNM:
+          cat->subtotal = subtotal;
+          break;
+
+        case CCT_POSTCOMPUTE:
+          break;
+
+        case CCT_SUBTOTAL:
+          subtotal = cat;
+          break;
+
+        case CCT_TOTAL:
+        case CCT_VALUE:
+        case CCT_LABEL:
+        case CCT_FUNCTION:
+          break;
+        }
+    }
+
+  return true;
+}
+
+static void
+ctables_nest_uninit (struct ctables_nest *nest)
+{
+  if (nest)
+    free (nest->vars);
+}
+
+static void
+ctables_stack_uninit (struct ctables_stack *stack)
+{
+  if (stack)
+    {
+      for (size_t i = 0; i < stack->n; i++)
+        ctables_nest_uninit (&stack->nests[i]);
+      free (stack->nests);
+    }
+}
+
+static struct ctables_stack
+nest_fts (struct ctables_stack s0, struct ctables_stack s1)
+{
+  if (!s0.n)
+    return s1;
+  else if (!s1.n)
+    return s0;
+
+  struct ctables_stack stack = { .nests = xnmalloc (s0.n, s1.n * sizeof *stack.nests) };
+  for (size_t i = 0; i < s0.n; i++)
+    for (size_t j = 0; j < s1.n; j++)
+      {
+        const struct ctables_nest *a = &s0.nests[i];
+        const struct ctables_nest *b = &s1.nests[j];
+
+        size_t allocate = a->n + b->n;
+        struct variable **vars = xnmalloc (allocate, sizeof *vars);
+        enum pivot_axis_type *axes = xnmalloc (allocate, sizeof *axes);
+        size_t n = 0;
+        for (size_t k = 0; k < a->n; k++)
+          vars[n++] = a->vars[k];
+        for (size_t k = 0; k < b->n; k++)
+          vars[n++] = b->vars[k];
+        assert (n == allocate);
+
+        const struct ctables_nest *summary_src;
+        if (!a->specs[CSV_CELL].var)
+          summary_src = b;
+        else if (!b->specs[CSV_CELL].var)
+          summary_src = a;
+        else
+          NOT_REACHED ();
+
+        struct ctables_nest *new = &stack.nests[stack.n++];
+        *new = (struct ctables_nest) {
+          .vars = vars,
+          .scale_idx = (a->scale_idx != SIZE_MAX ? a->scale_idx
+                        : b->scale_idx != SIZE_MAX ? a->n + b->scale_idx
+                        : SIZE_MAX),
+          .n = n,
+        };
+        for (enum ctables_summary_variant sv = 0; sv < N_CSVS; sv++)
+          ctables_summary_spec_set_clone (&new->specs[sv], &summary_src->specs[sv]);
+      }
+  ctables_stack_uninit (&s0);
+  ctables_stack_uninit (&s1);
+  return stack;
+}
+
+static struct ctables_stack
+stack_fts (struct ctables_stack s0, struct ctables_stack s1)
+{
+  struct ctables_stack stack = { .nests = xnmalloc (s0.n + s1.n, sizeof *stack.nests) };
+  for (size_t i = 0; i < s0.n; i++)
+    stack.nests[stack.n++] = s0.nests[i];
+  for (size_t i = 0; i < s1.n; i++)
+    stack.nests[stack.n++] = s1.nests[i];
+  assert (stack.n == s0.n + s1.n);
+  free (s0.nests);
+  free (s1.nests);
+  return stack;
+}
+
+static struct ctables_stack
+enumerate_fts (enum pivot_axis_type axis_type, const struct ctables_axis *a)
+{
+  if (!a)
+    return (struct ctables_stack) { .n = 0 };
+
+  switch (a->op)
+    {
+    case CTAO_VAR:
+      assert (!a->var.is_mrset);
+
+      struct variable **vars = xmalloc (sizeof *vars);
+      *vars = a->var.var;
+
+      struct ctables_nest *nest = xmalloc (sizeof *nest);
+      *nest = (struct ctables_nest) {
+        .vars = vars,
+        .n = 1,
+        .scale_idx = a->scale ? 0 : SIZE_MAX,
+      };
+      if (a->specs[CSV_CELL].n || a->scale)
+        for (enum ctables_summary_variant sv = 0; sv < N_CSVS; sv++)
+          {
+            ctables_summary_spec_set_clone (&nest->specs[sv], &a->specs[sv]);
+            nest->specs[sv].var = a->var.var;
+          }
+      return (struct ctables_stack) { .nests = nest, .n = 1 };
+
+    case CTAO_STACK:
+      return stack_fts (enumerate_fts (axis_type, a->subs[0]),
+                        enumerate_fts (axis_type, a->subs[1]));
+
+    case CTAO_NEST:
+      return nest_fts (enumerate_fts (axis_type, a->subs[0]),
+                       enumerate_fts (axis_type, a->subs[1]));
+    }
+
+  NOT_REACHED ();
+}
+
+union ctables_summary
+  {
+    /* COUNT, VALIDN, TOTALN. */
+    struct
+      {
+        double valid;
+        double missing;
+      };
+
+    /* MINIMUM, MAXIMUM, RANGE. */
+    struct
+      {
+        double min;
+        double max;
+      };
+
+    /* MEAN, SEMEAN, STDDEV, SUM, VARIANCE, *.SUM. */
+    struct moments1 *moments;
+
+    /* MEDIAN, MODE, PTILE. */
+    struct
+      {
+        struct casewriter *writer;
+        double ovalid;
+        double ovalue;
+      };
+
+    /* XXX multiple response */
+  };
+
+static void
+ctables_summary_init (union ctables_summary *s,
+                      const struct ctables_summary_spec *ss)
+{
+  switch (ss->function)
+    {
+    case CTSF_COUNT:
+    case CTSF_ECOUNT:
+    case CTSF_ROWPCT_COUNT:
+    case CTSF_COLPCT_COUNT:
+    case CTSF_TABLEPCT_COUNT:
+    case CTSF_SUBTABLEPCT_COUNT:
+    case CTSF_LAYERPCT_COUNT:
+    case CTSF_LAYERROWPCT_COUNT:
+    case CTSF_LAYERCOLPCT_COUNT:
+    case CTSF_ROWPCT_VALIDN:
+    case CTSF_COLPCT_VALIDN:
+    case CTSF_TABLEPCT_VALIDN:
+    case CTSF_SUBTABLEPCT_VALIDN:
+    case CTSF_LAYERPCT_VALIDN:
+    case CTSF_LAYERROWPCT_VALIDN:
+    case CTSF_LAYERCOLPCT_VALIDN:
+    case CTSF_ROWPCT_TOTALN:
+    case CTSF_COLPCT_TOTALN:
+    case CTSF_TABLEPCT_TOTALN:
+    case CTSF_SUBTABLEPCT_TOTALN:
+    case CTSF_LAYERPCT_TOTALN:
+    case CTSF_LAYERROWPCT_TOTALN:
+    case CTSF_LAYERCOLPCT_TOTALN:
+    case CTSF_MISSING:
+    case CSTF_TOTALN:
+    case CTSF_ETOTALN:
+    case CTSF_VALIDN:
+    case CTSF_EVALIDN:
+      s->missing = s->valid = 0;
+      break;
+
+    case CTSF_MAXIMUM:
+    case CTSF_MINIMUM:
+    case CTSF_RANGE:
+      s->min = s->max = SYSMIS;
+      break;
+
+    case CTSF_MEAN:
+    case CTSF_SEMEAN:
+    case CTSF_STDDEV:
+    case CTSF_SUM:
+    case CTSF_VARIANCE:
+    case CTSF_ROWPCT_SUM:
+    case CTSF_COLPCT_SUM:
+    case CTSF_TABLEPCT_SUM:
+    case CTSF_SUBTABLEPCT_SUM:
+    case CTSF_LAYERPCT_SUM:
+    case CTSF_LAYERROWPCT_SUM:
+    case CTSF_LAYERCOLPCT_SUM:
+      s->moments = moments1_create (MOMENT_VARIANCE);
+      break;
+
+    case CTSF_MEDIAN:
+    case CTSF_MODE:
+    case CTSF_PTILE:
+      {
+        struct caseproto *proto = caseproto_create ();
+        proto = caseproto_add_width (proto, 0);
+        proto = caseproto_add_width (proto, 0);
+
+        struct subcase ordering;
+        subcase_init (&ordering, 0, 0, SC_ASCEND);
+        s->writer = sort_create_writer (&ordering, proto);
+        subcase_uninit (&ordering);
+        caseproto_unref (proto);
+
+        s->ovalid = 0;
+        s->ovalue = SYSMIS;
+      }
+      break;
+
+    case CTSF_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES:
+    case CTSF_COLPCT_RESPONSES:
+    case CTSF_TABLEPCT_RESPONSES:
+    case CTSF_SUBTABLEPCT_RESPONSES:
+    case CTSF_LAYERPCT_RESPONSES:
+    case CTSF_LAYERROWPCT_RESPONSES:
+    case CTSF_LAYERCOLPCT_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES_COUNT:
+    case CTSF_COLPCT_RESPONSES_COUNT:
+    case CTSF_TABLEPCT_RESPONSES_COUNT:
+    case CTSF_SUBTABLEPCT_RESPONSES_COUNT:
+    case CTSF_LAYERPCT_RESPONSES_COUNT:
+    case CTSF_LAYERROWPCT_RESPONSES_COUNT:
+    case CTSF_LAYERCOLPCT_RESPONSES_COUNT:
+    case CTSF_ROWPCT_COUNT_RESPONSES:
+    case CTSF_COLPCT_COUNT_RESPONSES:
+    case CTSF_TABLEPCT_COUNT_RESPONSES:
+    case CTSF_SUBTABLEPCT_COUNT_RESPONSES:
+    case CTSF_LAYERPCT_COUNT_RESPONSES:
+    case CTSF_LAYERROWPCT_COUNT_RESPONSES:
+    case CTSF_LAYERCOLPCT_COUNT_RESPONSES:
+      NOT_REACHED ();
+    }
+}
+
+static void UNUSED
+ctables_summary_uninit (union ctables_summary *s,
+                        const struct ctables_summary_spec *ss)
+{
+  switch (ss->function)
+    {
+    case CTSF_COUNT:
+    case CTSF_ECOUNT:
+    case CTSF_ROWPCT_COUNT:
+    case CTSF_COLPCT_COUNT:
+    case CTSF_TABLEPCT_COUNT:
+    case CTSF_SUBTABLEPCT_COUNT:
+    case CTSF_LAYERPCT_COUNT:
+    case CTSF_LAYERROWPCT_COUNT:
+    case CTSF_LAYERCOLPCT_COUNT:
+    case CTSF_ROWPCT_VALIDN:
+    case CTSF_COLPCT_VALIDN:
+    case CTSF_TABLEPCT_VALIDN:
+    case CTSF_SUBTABLEPCT_VALIDN:
+    case CTSF_LAYERPCT_VALIDN:
+    case CTSF_LAYERROWPCT_VALIDN:
+    case CTSF_LAYERCOLPCT_VALIDN:
+    case CTSF_ROWPCT_TOTALN:
+    case CTSF_COLPCT_TOTALN:
+    case CTSF_TABLEPCT_TOTALN:
+    case CTSF_SUBTABLEPCT_TOTALN:
+    case CTSF_LAYERPCT_TOTALN:
+    case CTSF_LAYERROWPCT_TOTALN:
+    case CTSF_LAYERCOLPCT_TOTALN:
+    case CTSF_MISSING:
+    case CSTF_TOTALN:
+    case CTSF_ETOTALN:
+    case CTSF_VALIDN:
+    case CTSF_EVALIDN:
+      break;
+
+    case CTSF_MAXIMUM:
+    case CTSF_MINIMUM:
+    case CTSF_RANGE:
+      break;
+
+    case CTSF_MEAN:
+    case CTSF_SEMEAN:
+    case CTSF_STDDEV:
+    case CTSF_SUM:
+    case CTSF_VARIANCE:
+    case CTSF_ROWPCT_SUM:
+    case CTSF_COLPCT_SUM:
+    case CTSF_TABLEPCT_SUM:
+    case CTSF_SUBTABLEPCT_SUM:
+    case CTSF_LAYERPCT_SUM:
+    case CTSF_LAYERROWPCT_SUM:
+    case CTSF_LAYERCOLPCT_SUM:
+      moments1_destroy (s->moments);
+      break;
+
+    case CTSF_MEDIAN:
+    case CTSF_MODE:
+    case CTSF_PTILE:
+      casewriter_destroy (s->writer);
+      break;
+
+    case CTSF_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES:
+    case CTSF_COLPCT_RESPONSES:
+    case CTSF_TABLEPCT_RESPONSES:
+    case CTSF_SUBTABLEPCT_RESPONSES:
+    case CTSF_LAYERPCT_RESPONSES:
+    case CTSF_LAYERROWPCT_RESPONSES:
+    case CTSF_LAYERCOLPCT_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES_COUNT:
+    case CTSF_COLPCT_RESPONSES_COUNT:
+    case CTSF_TABLEPCT_RESPONSES_COUNT:
+    case CTSF_SUBTABLEPCT_RESPONSES_COUNT:
+    case CTSF_LAYERPCT_RESPONSES_COUNT:
+    case CTSF_LAYERROWPCT_RESPONSES_COUNT:
+    case CTSF_LAYERCOLPCT_RESPONSES_COUNT:
+    case CTSF_ROWPCT_COUNT_RESPONSES:
+    case CTSF_COLPCT_COUNT_RESPONSES:
+    case CTSF_TABLEPCT_COUNT_RESPONSES:
+    case CTSF_SUBTABLEPCT_COUNT_RESPONSES:
+    case CTSF_LAYERPCT_COUNT_RESPONSES:
+    case CTSF_LAYERROWPCT_COUNT_RESPONSES:
+    case CTSF_LAYERCOLPCT_COUNT_RESPONSES:
+      NOT_REACHED ();
+    }
+}
+
+static void
+ctables_summary_add (union ctables_summary *s,
+                     const struct ctables_summary_spec *ss,
+                     const struct variable *var, const union value *value,
+                     double d_weight, double e_weight)
+{
+  switch (ss->function)
+    {
+    case CTSF_COUNT:
+    case CSTF_TOTALN:
+    case CTSF_VALIDN:
+      if (var_is_value_missing (var, value))
+        s->missing += d_weight;
+      else
+        s->valid += d_weight;
+      break;
+
+    case CTSF_ECOUNT:
+    case CTSF_ROWPCT_COUNT:
+    case CTSF_COLPCT_COUNT:
+    case CTSF_TABLEPCT_COUNT:
+    case CTSF_SUBTABLEPCT_COUNT:
+    case CTSF_LAYERPCT_COUNT:
+    case CTSF_LAYERROWPCT_COUNT:
+    case CTSF_LAYERCOLPCT_COUNT:
+    case CTSF_ROWPCT_VALIDN:
+    case CTSF_COLPCT_VALIDN:
+    case CTSF_TABLEPCT_VALIDN:
+    case CTSF_SUBTABLEPCT_VALIDN:
+    case CTSF_LAYERPCT_VALIDN:
+    case CTSF_LAYERROWPCT_VALIDN:
+    case CTSF_LAYERCOLPCT_VALIDN:
+    case CTSF_ROWPCT_TOTALN:
+    case CTSF_COLPCT_TOTALN:
+    case CTSF_TABLEPCT_TOTALN:
+    case CTSF_SUBTABLEPCT_TOTALN:
+    case CTSF_LAYERPCT_TOTALN:
+    case CTSF_LAYERROWPCT_TOTALN:
+    case CTSF_LAYERCOLPCT_TOTALN:
+    case CTSF_MISSING:
+    case CTSF_ETOTALN:
+    case CTSF_EVALIDN:
+      if (var_is_value_missing (var, value))
+        s->missing += e_weight;
+      else
+        s->valid += e_weight;
+      break;
+
+    case CTSF_MAXIMUM:
+    case CTSF_MINIMUM:
+    case CTSF_RANGE:
+      if (!var_is_value_missing (var, value))
+        {
+          assert (!var_is_alpha (var)); /* XXX? */
+          if (s->min == SYSMIS || value->f < s->min)
+            s->min = value->f;
+          if (s->max == SYSMIS || value->f > s->max)
+            s->max = value->f;
+        }
+      break;
+
+    case CTSF_MEAN:
+    case CTSF_SEMEAN:
+    case CTSF_STDDEV:
+    case CTSF_SUM:
+    case CTSF_VARIANCE:
+    case CTSF_ROWPCT_SUM:
+    case CTSF_COLPCT_SUM:
+    case CTSF_TABLEPCT_SUM:
+    case CTSF_SUBTABLEPCT_SUM:
+    case CTSF_LAYERPCT_SUM:
+    case CTSF_LAYERROWPCT_SUM:
+    case CTSF_LAYERCOLPCT_SUM:
+      if (!var_is_value_missing (var, value))
+        moments1_add (s->moments, value->f, e_weight);
+      break;
+
+    case CTSF_MEDIAN:
+    case CTSF_MODE:
+    case CTSF_PTILE:
+      if (var_is_value_missing (var, value))
+        {
+          s->ovalid += e_weight;
+
+          struct ccase *c = case_create (casewriter_get_proto (s->writer));
+          *case_num_rw_idx (c, 0) = value->f;
+          *case_num_rw_idx (c, 1) = e_weight;
+          casewriter_write (s->writer, c);
+        }
+      break;
+
+    case CTSF_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES:
+    case CTSF_COLPCT_RESPONSES:
+    case CTSF_TABLEPCT_RESPONSES:
+    case CTSF_SUBTABLEPCT_RESPONSES:
+    case CTSF_LAYERPCT_RESPONSES:
+    case CTSF_LAYERROWPCT_RESPONSES:
+    case CTSF_LAYERCOLPCT_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES_COUNT:
+    case CTSF_COLPCT_RESPONSES_COUNT:
+    case CTSF_TABLEPCT_RESPONSES_COUNT:
+    case CTSF_SUBTABLEPCT_RESPONSES_COUNT:
+    case CTSF_LAYERPCT_RESPONSES_COUNT:
+    case CTSF_LAYERROWPCT_RESPONSES_COUNT:
+    case CTSF_LAYERCOLPCT_RESPONSES_COUNT:
+    case CTSF_ROWPCT_COUNT_RESPONSES:
+    case CTSF_COLPCT_COUNT_RESPONSES:
+    case CTSF_TABLEPCT_COUNT_RESPONSES:
+    case CTSF_SUBTABLEPCT_COUNT_RESPONSES:
+    case CTSF_LAYERPCT_COUNT_RESPONSES:
+    case CTSF_LAYERROWPCT_COUNT_RESPONSES:
+    case CTSF_LAYERCOLPCT_COUNT_RESPONSES:
+      NOT_REACHED ();
+    }
+}
+
+static enum ctables_domain_type
+ctables_function_domain (enum ctables_summary_function function)
+{
+  switch (function)
+    {
+    case CTSF_COUNT:
+    case CTSF_ECOUNT:
+    case CTSF_MISSING:
+    case CSTF_TOTALN:
+    case CTSF_ETOTALN:
+    case CTSF_VALIDN:
+    case CTSF_EVALIDN:
+    case CTSF_MAXIMUM:
+    case CTSF_MINIMUM:
+    case CTSF_RANGE:
+    case CTSF_MEAN:
+    case CTSF_SEMEAN:
+    case CTSF_STDDEV:
+    case CTSF_SUM:
+    case CTSF_VARIANCE:
+    case CTSF_MEDIAN:
+    case CTSF_PTILE:
+    case CTSF_MODE:
+    case CTSF_RESPONSES:
+      NOT_REACHED ();
+
+    case CTSF_COLPCT_COUNT:
+    case CTSF_COLPCT_COUNT_RESPONSES:
+    case CTSF_COLPCT_RESPONSES:
+    case CTSF_COLPCT_RESPONSES_COUNT:
+    case CTSF_COLPCT_SUM:
+    case CTSF_COLPCT_TOTALN:
+    case CTSF_COLPCT_VALIDN:
+      return CTDT_COL;
+
+    case CTSF_LAYERCOLPCT_COUNT:
+    case CTSF_LAYERCOLPCT_COUNT_RESPONSES:
+    case CTSF_LAYERCOLPCT_RESPONSES:
+    case CTSF_LAYERCOLPCT_RESPONSES_COUNT:
+    case CTSF_LAYERCOLPCT_SUM:
+    case CTSF_LAYERCOLPCT_TOTALN:
+    case CTSF_LAYERCOLPCT_VALIDN:
+      return CTDT_LAYERCOL;
+
+    case CTSF_LAYERPCT_COUNT:
+    case CTSF_LAYERPCT_COUNT_RESPONSES:
+    case CTSF_LAYERPCT_RESPONSES:
+    case CTSF_LAYERPCT_RESPONSES_COUNT:
+    case CTSF_LAYERPCT_SUM:
+    case CTSF_LAYERPCT_TOTALN:
+    case CTSF_LAYERPCT_VALIDN:
+      return CTDT_LAYER;
+
+    case CTSF_LAYERROWPCT_COUNT:
+    case CTSF_LAYERROWPCT_COUNT_RESPONSES:
+    case CTSF_LAYERROWPCT_RESPONSES:
+    case CTSF_LAYERROWPCT_RESPONSES_COUNT:
+    case CTSF_LAYERROWPCT_SUM:
+    case CTSF_LAYERROWPCT_TOTALN:
+    case CTSF_LAYERROWPCT_VALIDN:
+      return CTDT_LAYERROW;
+
+    case CTSF_ROWPCT_COUNT:
+    case CTSF_ROWPCT_COUNT_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES_COUNT:
+    case CTSF_ROWPCT_SUM:
+    case CTSF_ROWPCT_TOTALN:
+    case CTSF_ROWPCT_VALIDN:
+      return CTDT_ROW;
+
+    case CTSF_SUBTABLEPCT_COUNT:
+    case CTSF_SUBTABLEPCT_COUNT_RESPONSES:
+    case CTSF_SUBTABLEPCT_RESPONSES:
+    case CTSF_SUBTABLEPCT_RESPONSES_COUNT:
+    case CTSF_SUBTABLEPCT_SUM:
+    case CTSF_SUBTABLEPCT_TOTALN:
+    case CTSF_SUBTABLEPCT_VALIDN:
+      return CTDT_SUBTABLE;
+
+    case CTSF_TABLEPCT_COUNT:
+    case CTSF_TABLEPCT_COUNT_RESPONSES:
+    case CTSF_TABLEPCT_RESPONSES:
+    case CTSF_TABLEPCT_RESPONSES_COUNT:
+    case CTSF_TABLEPCT_SUM:
+    case CTSF_TABLEPCT_TOTALN:
+    case CTSF_TABLEPCT_VALIDN:
+      return CTDT_TABLE;
+    }
+
+  NOT_REACHED ();
+}
+
+static double
+ctables_summary_value (const struct ctables_cell *cell,
+                       union ctables_summary *s,
+                       const struct ctables_summary_spec *ss)
+{
+  switch (ss->function)
+    {
+    case CTSF_COUNT:
+    case CTSF_ECOUNT:
+      return s->valid;
+
+    case CTSF_ROWPCT_COUNT:
+    case CTSF_COLPCT_COUNT:
+    case CTSF_TABLEPCT_COUNT:
+    case CTSF_SUBTABLEPCT_COUNT:
+    case CTSF_LAYERPCT_COUNT:
+    case CTSF_LAYERROWPCT_COUNT:
+    case CTSF_LAYERCOLPCT_COUNT:
+      {
+        enum ctables_domain_type d = ctables_function_domain (ss->function);
+        return (cell->domains[d]->e_valid
+                ? s->valid / cell->domains[d]->e_valid * 100
+                : SYSMIS);
+      }
+
+    case CTSF_ROWPCT_VALIDN:
+    case CTSF_COLPCT_VALIDN:
+    case CTSF_TABLEPCT_VALIDN:
+    case CTSF_SUBTABLEPCT_VALIDN:
+    case CTSF_LAYERPCT_VALIDN:
+    case CTSF_LAYERROWPCT_VALIDN:
+    case CTSF_LAYERCOLPCT_VALIDN:
+    case CTSF_ROWPCT_TOTALN:
+    case CTSF_COLPCT_TOTALN:
+    case CTSF_TABLEPCT_TOTALN:
+    case CTSF_SUBTABLEPCT_TOTALN:
+    case CTSF_LAYERPCT_TOTALN:
+    case CTSF_LAYERROWPCT_TOTALN:
+    case CTSF_LAYERCOLPCT_TOTALN:
+      NOT_REACHED ();
+
+    case CTSF_MISSING:
+      return s->missing;
+
+    case CSTF_TOTALN:
+    case CTSF_ETOTALN:
+      return s->valid + s->missing;
+
+    case CTSF_VALIDN:
+    case CTSF_EVALIDN:
+      return s->valid;
+
+    case CTSF_MAXIMUM:
+      return s->max;
+
+    case CTSF_MINIMUM:
+      return s->min;
+
+    case CTSF_RANGE:
+      return s->max != SYSMIS && s->min != SYSMIS ? s->max - s->min : SYSMIS;
+
+    case CTSF_MEAN:
+      {
+        double mean;
+        moments1_calculate (s->moments, NULL, &mean, NULL, NULL, NULL);
+        return mean;
+      }
+
+    case CTSF_SEMEAN:
+      {
+        double weight, variance;
+        moments1_calculate (s->moments, &weight, NULL, &variance, NULL, NULL);
+        return calc_semean (variance, weight);
+      }
+
+    case CTSF_STDDEV:
+      {
+        double variance;
+        moments1_calculate (s->moments, NULL, NULL, &variance, NULL, NULL);
+        return variance != SYSMIS ? sqrt (variance) : SYSMIS;
+      }
+
+    case CTSF_SUM:
+      {
+        double weight, mean;
+        moments1_calculate (s->moments, &weight, &mean, NULL, NULL, NULL);
+        return weight != SYSMIS && mean != SYSMIS ? weight * mean : SYSMIS;
+      }
+
+    case CTSF_VARIANCE:
+      {
+        double variance;
+        moments1_calculate (s->moments, NULL, NULL, &variance, NULL, NULL);
+        return variance;
+      }
+
+    case CTSF_ROWPCT_SUM:
+    case CTSF_COLPCT_SUM:
+    case CTSF_TABLEPCT_SUM:
+    case CTSF_SUBTABLEPCT_SUM:
+    case CTSF_LAYERPCT_SUM:
+    case CTSF_LAYERROWPCT_SUM:
+    case CTSF_LAYERCOLPCT_SUM:
+      NOT_REACHED ();
+
+    case CTSF_MEDIAN:
+    case CTSF_PTILE:
+      if (s->writer)
+        {
+          struct casereader *reader = casewriter_make_reader (s->writer);
+          s->writer = NULL;
+
+          struct percentile *ptile = percentile_create (
+            ss->function == CTSF_PTILE ? ss->percentile : 0.5, s->ovalid);
+          struct order_stats *os = &ptile->parent;
+          order_stats_accumulate_idx (&os, 1, reader, 1, 0);
+          s->ovalue = percentile_calculate (ptile, PC_HAVERAGE);
+          statistic_destroy (&ptile->parent.parent);
+        }
+      return s->ovalue;
+
+    case CTSF_MODE:
+      if (s->writer)
+        {
+          struct casereader *reader = casewriter_make_reader (s->writer);
+          s->writer = NULL;
+
+          struct mode *mode = mode_create ();
+          struct order_stats *os = &mode->parent;
+          order_stats_accumulate_idx (&os, 1, reader, 1, 0);
+          s->ovalue = mode->mode;
+          statistic_destroy (&mode->parent.parent);
+        }
+      return s->ovalue;
+
+    case CTSF_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES:
+    case CTSF_COLPCT_RESPONSES:
+    case CTSF_TABLEPCT_RESPONSES:
+    case CTSF_SUBTABLEPCT_RESPONSES:
+    case CTSF_LAYERPCT_RESPONSES:
+    case CTSF_LAYERROWPCT_RESPONSES:
+    case CTSF_LAYERCOLPCT_RESPONSES:
+    case CTSF_ROWPCT_RESPONSES_COUNT:
+    case CTSF_COLPCT_RESPONSES_COUNT:
+    case CTSF_TABLEPCT_RESPONSES_COUNT:
+    case CTSF_SUBTABLEPCT_RESPONSES_COUNT:
+    case CTSF_LAYERPCT_RESPONSES_COUNT:
+    case CTSF_LAYERROWPCT_RESPONSES_COUNT:
+    case CTSF_LAYERCOLPCT_RESPONSES_COUNT:
+    case CTSF_ROWPCT_COUNT_RESPONSES:
+    case CTSF_COLPCT_COUNT_RESPONSES:
+    case CTSF_TABLEPCT_COUNT_RESPONSES:
+    case CTSF_SUBTABLEPCT_COUNT_RESPONSES:
+    case CTSF_LAYERPCT_COUNT_RESPONSES:
+    case CTSF_LAYERROWPCT_COUNT_RESPONSES:
+    case CTSF_LAYERCOLPCT_COUNT_RESPONSES:
+      NOT_REACHED ();
+    }
+
+  NOT_REACHED ();
+}
+
+struct ctables_cell_sort_aux
+  {
+    const struct ctables_nest *nest;
+    enum pivot_axis_type a;
+  };
+
+static int
+ctables_cell_compare_3way (const void *a_, const void *b_, const void *aux_)
+{
+  const struct ctables_cell_sort_aux *aux = aux_;
+  struct ctables_cell *const *ap = a_;
+  struct ctables_cell *const *bp = b_;
+  const struct ctables_cell *a = *ap;
+  const struct ctables_cell *b = *bp;
+
+  const struct ctables_nest *nest = aux->nest;
+  for (size_t i = 0; i < nest->n; i++)
+    if (i != nest->scale_idx)
+      {
+        const struct variable *var = nest->vars[i];
+        const struct ctables_cell_value *a_cv = &a->axes[aux->a].cvs[i];
+        const struct ctables_cell_value *b_cv = &b->axes[aux->a].cvs[i];
+        if (a_cv->category != b_cv->category)
+          return a_cv->category > b_cv->category ? 1 : -1;
+
+        const union value *a_val = &a_cv->value;
+        const union value *b_val = &b_cv->value;
+        switch (a_cv->category->type)
+          {
+          case CCT_NUMBER:
+          case CCT_STRING:
+          case CCT_SUBTOTAL:
+          case CCT_TOTAL:
+          case CCT_POSTCOMPUTE:
+            /* Must be equal. */
+            continue;
+
+          case CCT_RANGE:
+          case CCT_MISSING:
+          case CCT_OTHERNM:
+            {
+              int cmp = value_compare_3way (a_val, b_val, var_get_width (var));
+              if (cmp)
+                return cmp;
+            }
+            break;
+
+          case CCT_VALUE:
+            {
+              int cmp = value_compare_3way (a_val, b_val, var_get_width (var));
+              if (cmp)
+                return a_cv->category->sort_ascending ? cmp : -cmp;
+            }
+            break;
+
+          case CCT_LABEL:
+            {
+              const char *a_label = var_lookup_value_label (var, a_val);
+              const char *b_label = var_lookup_value_label (var, b_val);
+              int cmp = (a_label
+                         ? (b_label ? strcmp (a_label, b_label) : 1)
+                         : (b_label ? -1 : value_compare_3way (
+                              a_val, b_val, var_get_width (var))));
+              if (cmp)
+                return a_cv->category->sort_ascending ? cmp : -cmp;
+            }
+            break;
+
+          case CCT_FUNCTION:
+            NOT_REACHED ();
+          }
+      }
+  return 0;
+}
+
+/* Algorithm:
+
+   For each row:
+       For each ctables_table:
+           For each combination of row vars:
+               For each combination of column vars:
+                   For each combination of layer vars:
+                       Add entry
+   Make a table of row values:
+       Sort entries by row values
+       Assign a 0-based index to each actual value
+       Construct a dimension
+   Make a table of column values
+   Make a table of layer values
+   For each entry:
+       Fill the table entry using the indexes from before.
+ */
+
+static struct ctables_domain *
+ctables_domain_insert (struct ctables_section *s, struct ctables_cell *cell,
+                       enum ctables_domain_type domain)
+{
+  size_t hash = 0;
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = 0; i < nest->n_domains[domain]; i++)
+        {
+          size_t v_idx = nest->domains[domain][i];
+          hash = value_hash (&cell->axes[a].cvs[v_idx].value,
+                             var_get_width (nest->vars[v_idx]), hash);
+        }
+    }
+
+  struct ctables_domain *d;
+  HMAP_FOR_EACH_WITH_HASH (d, struct ctables_domain, node, hash, &s->domains[domain])
+    {
+      const struct ctables_cell *df = d->example;
+      for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+        {
+          const struct ctables_nest *nest = s->nests[a];
+          for (size_t i = 0; i < nest->n_domains[domain]; i++)
+            {
+              size_t v_idx = nest->domains[domain][i];
+              if (!value_equal (&df->axes[a].cvs[v_idx].value,
+                                &cell->axes[a].cvs[v_idx].value,
+                                var_get_width (nest->vars[v_idx])))
+                goto not_equal;
+            }
+        }
+      return d;
+
+    not_equal: ;
+    }
+
+  d = xmalloc (sizeof *d);
+  *d = (struct ctables_domain) { .example = cell };
+  hmap_insert (&s->domains[domain], &d->node, hash);
+  return d;
+}
+
+static const struct ctables_category *
+ctables_categories_match (const struct ctables_categories *c,
+                          const union value *v, const struct variable *var)
+{
+  const struct ctables_category *othernm = NULL;
+  for (size_t i = c->n_cats; i-- > 0; )
+    {
+      const struct ctables_category *cat = &c->cats[i];
+      switch (cat->type)
+        {
+        case CCT_NUMBER:
+          if (cat->number == v->f)
+            return cat;
+          break;
+
+        case CCT_STRING:
+          NOT_REACHED ();
+
+        case CCT_RANGE:
+          if ((cat->range[0] == -DBL_MAX || v->f >= cat->range[0])
+              && (cat->range[1] == DBL_MAX || v->f <= cat->range[1]))
+            return cat;
+          break;
+
+        case CCT_MISSING:
+          if (var_is_value_missing (var, v))
+            return cat;
+          break;
+
+        case CCT_POSTCOMPUTE:
+          break;
+
+        case CCT_OTHERNM:
+          if (!othernm)
+            othernm = cat;
+          break;
+
+        case CCT_SUBTOTAL:
+        case CCT_TOTAL:
+          break;
+
+        case CCT_VALUE:
+        case CCT_LABEL:
+        case CCT_FUNCTION:
+          return (cat->include_missing || !var_is_value_missing (var, v) ? cat
+                  : NULL);
+        }
+    }
+
+  return var_is_value_missing (var, v) ? NULL : othernm;
+}
+
+static const struct ctables_category *
+ctables_categories_total (const struct ctables_categories *c)
+{
+  const struct ctables_category *first = &c->cats[0];
+  const struct ctables_category *last = &c->cats[c->n_cats - 1];
+  return (first->type == CCT_TOTAL ? first
+          : last->type == CCT_TOTAL ? last
+          : NULL);
+}
+
+static struct ctables_cell *
+ctables_cell_insert__ (struct ctables_section *s, const struct ccase *c,
+                       const struct ctables_category *cats[PIVOT_N_AXES][10])
+{
+  size_t hash = 0;
+  enum ctables_summary_variant sv = CSV_CELL;
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = 0; i < nest->n; i++)
+        if (i != nest->scale_idx)
+          {
+            hash = hash_pointer (cats[a][i], hash);
+            if (cats[a][i]->type != CCT_TOTAL
+                && cats[a][i]->type != CCT_SUBTOTAL
+                && cats[a][i]->type != CCT_POSTCOMPUTE)
+              hash = value_hash (case_data (c, nest->vars[i]),
+                                 var_get_width (nest->vars[i]), hash);
+            else
+              sv = CSV_TOTAL;
+          }
+    }
+
+  struct ctables_cell *cell;
+  HMAP_FOR_EACH_WITH_HASH (cell, struct ctables_cell, node, hash, &s->cells)
+    {
+      for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+        {
+          const struct ctables_nest *nest = s->nests[a];
+          for (size_t i = 0; i < nest->n; i++)
+            if (i != nest->scale_idx
+                && (cats[a][i] != cell->axes[a].cvs[i].category
+                    || (cats[a][i]->type != CCT_TOTAL
+                        && cats[a][i]->type != CCT_SUBTOTAL
+                        && cats[a][i]->type != CCT_POSTCOMPUTE
+                        && !value_equal (case_data (c, nest->vars[i]),
+                                         &cell->axes[a].cvs[i].value,
+                                         var_get_width (nest->vars[i])))))
+                goto not_equal;
+        }
+
+      return cell;
+
+    not_equal: ;
+    }
+
+  cell = xmalloc (sizeof *cell);
+  cell->hide = false;
+  cell->sv = sv;
+  cell->contributes_to_domains = true;
+  cell->postcompute = false;
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      cell->axes[a].cvs = (nest->n
+                        ? xnmalloc (nest->n, sizeof *cell->axes[a].cvs)
+                        : NULL);
+      for (size_t i = 0; i < nest->n; i++)
+        {
+          const struct ctables_category *cat = cats[a][i];
+          if (i != nest->scale_idx)
+            {
+              const struct ctables_category *subtotal = cat->subtotal;
+              if (cat->hide || (subtotal && subtotal->hide_subcategories))
+                cell->hide = true;
+
+              if (cat->type == CCT_TOTAL
+                  || cat->type == CCT_SUBTOTAL
+                  || cat->type == CCT_POSTCOMPUTE)
+                cell->contributes_to_domains = false;
+              if (cat->type == CCT_POSTCOMPUTE)
+                cell->postcompute = true;
+            }
+
+          cell->axes[a].cvs[i].category = cat;
+          value_clone (&cell->axes[a].cvs[i].value, case_data (c, nest->vars[i]),
+                       var_get_width (nest->vars[i]));
+        }
+    }
+
+  const struct ctables_nest *ss = s->nests[s->table->summary_axis];
+  const struct ctables_summary_spec_set *specs = &ss->specs[cell->sv];
+  cell->summaries = xmalloc (specs->n * sizeof *cell->summaries);
+  for (size_t i = 0; i < specs->n; i++)
+    ctables_summary_init (&cell->summaries[i], &specs->specs[i]);
+  for (enum ctables_domain_type dt = 0; dt < N_CTDTS; dt++)
+    cell->domains[dt] = ctables_domain_insert (s, cell, dt);
+  hmap_insert (&s->cells, &cell->node, hash);
+  return cell;
+}
+
+static void
+ctables_cell_add__ (struct ctables_section *s, const struct ccase *c,
+                    const struct ctables_category *cats[PIVOT_N_AXES][10],
+                    double d_weight, double e_weight)
+{
+  struct ctables_cell *cell = ctables_cell_insert__ (s, c, cats);
+  const struct ctables_nest *ss = s->nests[s->table->summary_axis];
+
+  const struct ctables_summary_spec_set *specs = &ss->specs[cell->sv];
+  for (size_t i = 0; i < specs->n; i++)
+    ctables_summary_add (&cell->summaries[i], &specs->specs[i], specs->var,
+                         case_data (c, specs->var), d_weight, e_weight);
+  if (cell->contributes_to_domains)
+    {
+      for (enum ctables_domain_type dt = 0; dt < N_CTDTS; dt++)
+        {
+          cell->domains[dt]->d_valid += d_weight;
+          cell->domains[dt]->e_valid += e_weight;
+        }
+    }
+}
+
+static void
+recurse_totals (struct ctables_section *s, const struct ccase *c,
+                const struct ctables_category *cats[PIVOT_N_AXES][10],
+                double d_weight, double e_weight,
+                enum pivot_axis_type start_axis, size_t start_nest)
+{
+  for (enum pivot_axis_type a = start_axis; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = start_nest; i < nest->n; i++)
+        {
+          if (i == nest->scale_idx)
+            continue;
+
+          const struct variable *var = nest->vars[i];
+
+          const struct ctables_category *total = ctables_categories_total (
+            s->table->categories[var_get_dict_index (var)]);
+          if (total)
+            {
+              const struct ctables_category *save = cats[a][i];
+              cats[a][i] = total;
+              ctables_cell_add__ (s, c, cats, d_weight, e_weight);
+              recurse_totals (s, c, cats, d_weight, e_weight, a, i + 1);
+              cats[a][i] = save;
+            }
+        }
+      start_nest = 0;
+    }
+}
+
+static void
+recurse_subtotals (struct ctables_section *s, const struct ccase *c,
+                   const struct ctables_category *cats[PIVOT_N_AXES][10],
+                   double d_weight, double e_weight,
+                   enum pivot_axis_type start_axis, size_t start_nest)
+{
+  for (enum pivot_axis_type a = start_axis; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = start_nest; i < nest->n; i++)
+        {
+          if (i == nest->scale_idx)
+            continue;
+
+          const struct ctables_category *save = cats[a][i];
+          if (save->subtotal)
+            {
+              cats[a][i] = save->subtotal;
+              ctables_cell_add__ (s, c, cats, d_weight, e_weight);
+              recurse_subtotals (s, c, cats, d_weight, e_weight, a, i + 1);
+              cats[a][i] = save;
+            }
+        }
+      start_nest = 0;
+    }
+}
+
+static void
+ctables_add_occurrence (const struct variable *var,
+                        const union value *value,
+                        struct hmap *occurrences)
+{
+  int width = var_get_width (var);
+  unsigned int hash = value_hash (value, width, 0);
+
+  struct ctables_occurrence *o;
+  HMAP_FOR_EACH_WITH_HASH (o, struct ctables_occurrence, node, hash,
+                           occurrences)
+    if (value_equal (value, &o->value, width))
+      return;
+
+  o = xmalloc (sizeof *o);
+  value_clone (&o->value, value, width);
+  hmap_insert (occurrences, &o->node, hash);
+}
+
+static void
+ctables_cell_insert (struct ctables_section *s,
+                     const struct ccase *c,
+                     double d_weight, double e_weight)
+{
+  const struct ctables_category *cats[PIVOT_N_AXES][10]; /* XXX */
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = 0; i < nest->n; i++)
+        {
+          if (i == nest->scale_idx)
+            continue;
+
+          const struct variable *var = nest->vars[i];
+          const union value *value = case_data (c, var);
+
+          if (var_is_numeric (var) && value->f == SYSMIS)
+            return;
+
+          cats[a][i] = ctables_categories_match (
+            s->table->categories[var_get_dict_index (var)], value, var);
+          if (!cats[a][i])
+            return;
+        }
+    }
+
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = 0; i < nest->n; i++)
+        if (i != nest->scale_idx)
+          {
+            const struct variable *var = nest->vars[i];
+            const union value *value = case_data (c, var);
+            ctables_add_occurrence (var, value, &s->occurrences[a][i]);
+          }
+    }
+
+  ctables_cell_add__ (s, c, cats, d_weight, e_weight);
+
+  recurse_totals (s, c, cats, d_weight, e_weight, 0, 0);
+  recurse_subtotals (s, c, cats, d_weight, e_weight, 0, 0);
+}
+
+struct merge_item
+  {
+    const struct ctables_summary_spec_set *set;
+    size_t ofs;
+  };
+
+static int
+merge_item_compare_3way (const struct merge_item *a, const struct merge_item *b)
+{
+  const struct ctables_summary_spec *as = &a->set->specs[a->ofs];
+  const struct ctables_summary_spec *bs = &b->set->specs[b->ofs];
+  if (as->function != bs->function)
+    return as->function > bs->function ? 1 : -1;
+  else if (as->percentile != bs->percentile)
+    return as->percentile < bs->percentile ? 1 : -1;
+  return strcmp (as->label, bs->label);
+}
+
+static struct pivot_value *
+ctables_category_create_label (const struct ctables_category *cat,
+                               const struct variable *var,
+                               const union value *value)
+{
+  return (cat->type == CCT_TOTAL || cat->type == CCT_SUBTOTAL
+          ? pivot_value_new_user_text (cat->total_label, SIZE_MAX)
+          : cat->type == CCT_POSTCOMPUTE && cat->pc->label
+          ? pivot_value_new_user_text (cat->pc->label, SIZE_MAX)
+          : pivot_value_new_var_value (var, value));
+}
+
+static struct ctables_value *
+ctables_value_find__ (struct ctables_table *t, const union value *value,
+                      int width, unsigned int hash)
+{
+  struct ctables_value *clv;
+  HMAP_FOR_EACH_WITH_HASH (clv, struct ctables_value, node,
+                           hash, &t->clabels_values_map)
+    if (value_equal (value, &clv->value, width))
+      return clv;
+  return NULL;
+}
+
+static struct ctables_value *
+ctables_value_find (struct ctables_table *t,
+                    const union value *value, int width)
+{
+  return ctables_value_find__ (t, value, width,
+                               value_hash (value, width, 0));
+}
+
+static void
+ctables_table_add_section (struct ctables_table *t, enum pivot_axis_type a,
+                           size_t ix[PIVOT_N_AXES])
+{
+  if (a < PIVOT_N_AXES)
+    {
+      size_t limit = MAX (t->stacks[a].n, 1);
+      for (ix[a] = 0; ix[a] < limit; ix[a]++)
+        ctables_table_add_section (t, a + 1, ix);
+    }
+  else
+    {
+      struct ctables_section *s = &t->sections[t->n_sections++];
+      *s = (struct ctables_section) {
+        .table = t,
+        .cells = HMAP_INITIALIZER (s->cells),
+      };
+      for (a = 0; a < PIVOT_N_AXES; a++)
+        if (t->stacks[a].n)
+          {
+            struct ctables_nest *nest = &t->stacks[a].nests[ix[a]];
+            s->nests[a] = nest;
+            s->occurrences[a] = xnmalloc (nest->n, sizeof *s->occurrences[a]);
+            for (size_t i = 0; i < nest->n; i++)
+              hmap_init (&s->occurrences[a][i]);
+        }
+      for (size_t i = 0; i < N_CTDTS; i++)
+        hmap_init (&s->domains[i]);
+    }
+}
+
+static double
+ctpo_add (double a, double b)
+{
+  return a + b;
+}
+
+static double
+ctpo_sub (double a, double b)
+{
+  return a - b;
+}
+
+static double
+ctpo_mul (double a, double b)
+{
+  return a * b;
+}
+
+static double
+ctpo_div (double a, double b)
+{
+  return b ? a / b : SYSMIS;
+}
+
+static double
+ctpo_pow (double a, double b)
+{
+  int save_errno = errno;
+  errno = 0;
+  double result = pow (a, b);
+  if (errno)
+    result = SYSMIS;
+  errno = save_errno;
+  return result;
+}
+
+static double
+ctpo_neg (double a, double b UNUSED)
+{
+  return -a;
+}
+
+struct ctables_pcexpr_evaluate_ctx
+  {
+    const struct ctables_cell *cell;
+    const struct ctables_section *section;
+    const struct ctables_categories *cats;
+    enum pivot_axis_type pc_a;
+    size_t pc_a_idx;
+  };
+
+static double ctables_pcexpr_evaluate (
+  const struct ctables_pcexpr_evaluate_ctx *, const struct ctables_pcexpr *);
+
+static double
+ctables_pcexpr_evaluate_nonterminal (
+  const struct ctables_pcexpr_evaluate_ctx *ctx,
+  const struct ctables_pcexpr *e, size_t n_args,
+  double evaluate (double, double))
+{
+  double args[2] = { 0, 0 };
+  for (size_t i = 0; i < n_args; i++)
+    {
+      args[i] = ctables_pcexpr_evaluate (ctx, e->subs[i]);
+      if (!isfinite (args[i]) || args[i] == SYSMIS)
+        return SYSMIS;
+    }
+  return evaluate (args[0], args[1]);
+}
+
+static double
+ctables_pcexpr_evaluate_category (const struct ctables_pcexpr_evaluate_ctx *ctx,
+                                  const struct ctables_cell_value *pc_cv)
+{
+  const struct ctables_section *s = ctx->section;
+
+  size_t hash = 0;
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      const struct ctables_nest *nest = s->nests[a];
+      for (size_t i = 0; i < nest->n; i++)
+        if (i != nest->scale_idx)
+          {
+            const struct ctables_cell_value *cv
+              = (a == ctx->pc_a && i == ctx->pc_a_idx ? pc_cv
+                 : &ctx->cell->axes[a].cvs[i]);
+            hash = hash_pointer (cv->category, hash);
+            if (cv->category->type != CCT_TOTAL
+                && cv->category->type != CCT_SUBTOTAL
+                && cv->category->type != CCT_POSTCOMPUTE)
+              hash = value_hash (&cv->value,
+                                 var_get_width (nest->vars[i]), hash);
+          }
+    }
+
+  struct ctables_cell *tc;
+  HMAP_FOR_EACH_WITH_HASH (tc, struct ctables_cell, node, hash, &s->cells)
+    {
+      for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+        {
+          const struct ctables_nest *nest = s->nests[a];
+          for (size_t i = 0; i < nest->n; i++)
+            if (i != nest->scale_idx)
+              {
+                const struct ctables_cell_value *p_cv
+                  = (a == ctx->pc_a && i == ctx->pc_a_idx ? pc_cv
+                     : &ctx->cell->axes[a].cvs[i]);
+                const struct ctables_cell_value *t_cv = &tc->axes[a].cvs[i];
+                if (p_cv->category != t_cv->category
+                    || (p_cv->category->type != CCT_TOTAL
+                        && p_cv->category->type != CCT_SUBTOTAL
+                        && p_cv->category->type != CCT_POSTCOMPUTE
+                        && !value_equal (&p_cv->value,
+                                         &t_cv->value,
+                                         var_get_width (nest->vars[i]))))
+                  goto not_equal;
+              }
+        }
+
+      goto found;
+
+    not_equal: ;
+    }
+  return 0;
+
+found: ;
+  const struct ctables_table *t = s->table;
+  const struct ctables_nest *specs_nest = s->nests[t->summary_axis];
+  const struct ctables_summary_spec_set *specs = &specs_nest->specs[tc->sv];
+  size_t j = 0 /* XXX */;
+  return ctables_summary_value (tc, &tc->summaries[j], &specs->specs[j]);
+}
+
+static double
+ctables_pcexpr_evaluate (const struct ctables_pcexpr_evaluate_ctx *ctx,
+                         const struct ctables_pcexpr *e)
+{
+  switch (e->op)
+    {
+    case CTPO_CONSTANT:
+      return e->number;
+
+    case CTPO_CAT_RANGE:
+      {
+        struct ctables_cell_value cv = {
+          .category = ctables_find_category_for_postcompute (ctx->cats, e)
+        };
+        assert (cv.category != NULL);
+
+        struct hmap *occurrences = &ctx->section->occurrences[ctx->pc_a][ctx->pc_a_idx];
+        const struct ctables_occurrence *o;
+
+        double sum = 0.0;
+        const struct variable *var = ctx->section->nests[ctx->pc_a]->vars[ctx->pc_a_idx];
+        HMAP_FOR_EACH (o, struct ctables_occurrence, node, occurrences)
+          if (ctables_categories_match (ctx->cats, &o->value, var) == cv.category)
+            {
+              cv.value = o->value;
+              sum += ctables_pcexpr_evaluate_category (ctx, &cv);
+            }
+        return sum;
+      }
+
+    case CTPO_CAT_NUMBER:
+    case CTPO_CAT_STRING:
+    case CTPO_CAT_MISSING:
+    case CTPO_CAT_OTHERNM:
+    case CTPO_CAT_SUBTOTAL:
+    case CTPO_CAT_TOTAL:
+      {
+        struct ctables_cell_value cv = {
+          .category = ctables_find_category_for_postcompute (ctx->cats, e),
+          .value = { .f = e->number },
+        };
+        assert (cv.category != NULL);
+        return ctables_pcexpr_evaluate_category (ctx, &cv);
+      }
+
+    case CTPO_ADD:
+      return ctables_pcexpr_evaluate_nonterminal (ctx, e, 2, ctpo_add);
+
+    case CTPO_SUB:
+      return ctables_pcexpr_evaluate_nonterminal (ctx, e, 2, ctpo_sub);
+
+    case CTPO_MUL:
+      return ctables_pcexpr_evaluate_nonterminal (ctx, e, 2, ctpo_mul);
+
+    case CTPO_DIV:
+      return ctables_pcexpr_evaluate_nonterminal (ctx, e, 2, ctpo_div);
+
+    case CTPO_POW:
+      return ctables_pcexpr_evaluate_nonterminal (ctx, e, 2, ctpo_pow);
+
+    case CTPO_NEG:
+      return ctables_pcexpr_evaluate_nonterminal (ctx, e, 1, ctpo_neg);
+    }
+
+  NOT_REACHED ();
+}
+
+static double
+ctables_cell_calculate_postcompute (const struct ctables_section *s,
+                                    const struct ctables_cell *cell)
+{
+  enum pivot_axis_type pc_a;
+  size_t pc_a_idx;
+  const struct ctables_postcompute *pc;
+  for (pc_a = 0; ; pc_a++)
+    {
+      assert (pc_a < PIVOT_N_AXES);
+      for (pc_a_idx = 0; pc_a_idx < s->nests[pc_a]->n; pc_a_idx++)
+        {
+          const struct ctables_cell_value *cv = &cell->axes[pc_a].cvs[pc_a_idx];
+          if (cv->category->type == CCT_POSTCOMPUTE)
+            {
+              pc = cv->category->pc;
+              goto found;
+            }
+        }
+    }
+found: ;
+
+  const struct variable *var = s->nests[pc_a]->vars[pc_a_idx];
+  const struct ctables_categories *cats = s->table->categories[
+    var_get_dict_index (var)];
+  struct ctables_pcexpr_evaluate_ctx ctx = {
+    .cell = cell,
+    .section = s,
+    .cats = cats,
+    .pc_a = pc_a,
+    .pc_a_idx = pc_a_idx,
+  };
+  return ctables_pcexpr_evaluate (&ctx, pc->expr);
+}
+
+static void
+ctables_table_output (struct ctables *ct, struct ctables_table *t)
+{
+  struct pivot_table *pt = pivot_table_create__ (
+    (t->title
+     ? pivot_value_new_user_text (t->title, SIZE_MAX)
+     : pivot_value_new_text (N_("Custom Tables"))),
+    "Custom Tables");
+  if (t->caption)
+    pivot_table_set_caption (
+      pt, pivot_value_new_user_text (t->caption, SIZE_MAX));
+  if (t->corner)
+    pivot_table_set_caption (
+      pt, pivot_value_new_user_text (t->corner, SIZE_MAX));
+
+  bool summary_dimension = (t->summary_axis != t->slabels_axis
+                            || (!t->slabels_visible
+                                && t->summary_specs.n > 1));
+  if (summary_dimension)
+    {
+      struct pivot_dimension *d = pivot_dimension_create (
+        pt, t->slabels_axis, N_("Statistics"));
+      const struct ctables_summary_spec_set *specs = &t->summary_specs;
+      if (!t->slabels_visible)
+        d->hide_all_labels = true;
+      for (size_t i = 0; i < specs->n; i++)
+        pivot_category_create_leaf (
+          d->root, pivot_value_new_text (specs->specs[i].label));
+    }
+
+  bool categories_dimension = t->clabels_example != NULL;
+  if (categories_dimension)
+    {
+      struct pivot_dimension *d = pivot_dimension_create (
+        pt, t->label_axis[t->clabels_from_axis],
+        t->clabels_from_axis == PIVOT_AXIS_ROW
+        ? N_("Row Categories")
+        : N_("Column Categories"));
+      const struct variable *var = t->clabels_example;
+      const struct ctables_categories *c = t->categories[var_get_dict_index (var)];
+      for (size_t i = 0; i < t->n_clabels_values; i++)
+        {
+          const struct ctables_value *value = t->clabels_values[i];
+          const struct ctables_category *cat = ctables_categories_match (c, &value->value, var);
+          assert (cat != NULL);
+          pivot_category_create_leaf (d->root, ctables_category_create_label (
+                                        cat, t->clabels_example, &value->value));
+        }
+    }
+
+  pivot_table_set_look (pt, ct->look);
+  struct pivot_dimension *d[PIVOT_N_AXES];
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    {
+      static const char *names[] = {
+        [PIVOT_AXIS_ROW] = N_("Rows"),
+        [PIVOT_AXIS_COLUMN] = N_("Columns"),
+        [PIVOT_AXIS_LAYER] = N_("Layers"),
+      };
+      d[a] = (t->axes[a] || a == t->summary_axis
+              ? pivot_dimension_create (pt, a, names[a])
+              : NULL);
+      if (!d[a])
+        continue;
+
+      assert (t->axes[a]);
+
+      for (size_t i = 0; i < t->stacks[a].n; i++)
+        {
+          struct ctables_nest *nest = &t->stacks[a].nests[i];
+          struct ctables_section **sections = xnmalloc (t->n_sections,
+                                                        sizeof *sections);
+          size_t n_sections = 0;
+
+          size_t n_total_cells = 0;
+          size_t max_depth = 0;
+          for (size_t j = 0; j < t->n_sections; j++)
+            if (t->sections[j].nests[a] == nest)
+              {
+                struct ctables_section *s = &t->sections[j];
+                sections[n_sections++] = s;
+                n_total_cells += s->cells.count;
+
+                size_t depth = s->nests[a]->n;
+                max_depth = MAX (depth, max_depth);
+              }
+
+          struct ctables_cell **sorted = xnmalloc (n_total_cells,
+                                                   sizeof *sorted);
+          size_t n_sorted = 0;
+
+          for (size_t j = 0; j < n_sections; j++)
+            {
+              struct ctables_section *s = sections[j];
+
+              struct ctables_cell *cell;
+              HMAP_FOR_EACH (cell, struct ctables_cell, node, &s->cells)
+                if (!cell->hide)
+                  sorted[n_sorted++] = cell;
+              assert (n_sorted <= n_total_cells);
+            }
+
+          struct ctables_cell_sort_aux aux = { .nest = nest, .a = a };
+          sort (sorted, n_sorted, sizeof *sorted, ctables_cell_compare_3way, &aux);
+
+          struct ctables_level
+            {
+              enum ctables_level_type
+                {
+                  CTL_VAR,          /* Variable label for nest->vars[var_idx]. */
+                  CTL_CATEGORY,     /* Category for nest->vars[var_idx]. */
+                  CTL_SUMMARY,      /* Summary functions. */
+                }
+                type;
+
+              size_t var_idx;
+            };
+          struct ctables_level *levels = xnmalloc (1 + 2 * max_depth, sizeof *levels);
+          size_t n_levels = 0;
+          for (size_t k = 0; k < nest->n; k++)
+            {
+              enum ctables_vlabel vlabel = ct->vlabels[var_get_dict_index (nest->vars[k])];
+              if (vlabel != CTVL_NONE)
+                {
+                  levels[n_levels++] = (struct ctables_level) {
+                    .type = CTL_VAR,
+                    .var_idx = k,
+                  };
+                }
+
+              if (nest->scale_idx != k
+                  && (k != nest->n - 1 || t->label_axis[a] == a))
+                {
+                  levels[n_levels++] = (struct ctables_level) {
+                    .type = CTL_CATEGORY,
+                    .var_idx = k,
+                  };
+                }
+            }
+
+          if (!summary_dimension && a == t->slabels_axis)
+            {
+              levels[n_levels++] = (struct ctables_level) {
+                .type = CTL_SUMMARY,
+                .var_idx = SIZE_MAX,
+              };
+            }
+
+          /* Pivot categories:
+
+             - variable label for nest->vars[0], if vlabel != CTVL_NONE
+             - category for nest->vars[0], if nest->scale_idx != 0
+             - variable label for nest->vars[1], if vlabel != CTVL_NONE
+             - category for nest->vars[1], if nest->scale_idx != 1
+             ...
+             - variable label for nest->vars[n - 1], if vlabel != CTVL_NONE
+             - category for nest->vars[n - 1], if t->label_axis[a] == a && nest->scale_idx != n - 1.
+             - summary function, if 'a == t->slabels_axis && a ==
+             t->summary_axis'.
+
+             Additional dimensions:
+
+             - If 'a == t->slabels_axis && a != t->summary_axis', add a summary
+             dimension.
+             - If 't->label_axis[b] == a' for some 'b != a', add a category
+             dimension to 'a'.
+          */
+
+
+          struct pivot_category **groups = xnmalloc (1 + 2 * max_depth, sizeof *groups);
+          int prev_leaf = 0;
+          for (size_t j = 0; j < n_sorted; j++)
+            {
+              struct ctables_cell *cell = sorted[j];
+              struct ctables_cell *prev = j > 0 ? sorted[j - 1] : NULL;
+
+              size_t n_common = 0;
+              if (j > 0)
+                {
+                  for (; n_common < n_levels; n_common++)
+                    {
+                      const struct ctables_level *level = &levels[n_common];
+                      if (level->type == CTL_CATEGORY)
+                        {
+                          size_t var_idx = level->var_idx;
+                          const struct ctables_category *c = cell->axes[a].cvs[var_idx].category;
+                          if (prev->axes[a].cvs[var_idx].category != c)
+                            break;
+                          else if (c->type != CCT_SUBTOTAL
+                                   && c->type != CCT_TOTAL
+                                   && c->type != CCT_POSTCOMPUTE
+                                   && !value_equal (&prev->axes[a].cvs[var_idx].value,
+                                                    &cell->axes[a].cvs[var_idx].value,
+                                                    var_get_type (nest->vars[var_idx])))
+                            break;
+                        }
+                    }
+                }
+
+              for (size_t k = n_common; k < n_levels; k++)
+                {
+                  const struct ctables_level *level = &levels[k];
+                  struct pivot_category *parent = k ? groups[k - 1] : d[a]->root;
+                  if (level->type == CTL_SUMMARY)
+                    {
+                      assert (k == n_levels - 1);
+
+                      const struct ctables_summary_spec_set *specs = &t->summary_specs;
+                      for (size_t m = 0; m < specs->n; m++)
+                        {
+                          int leaf = pivot_category_create_leaf (
+                            parent, pivot_value_new_text (specs->specs[m].label));
+                          if (!m)
+                            prev_leaf = leaf;
+                        }
+                    }
+                  else
+                    {
+                      const struct variable *var = nest->vars[level->var_idx];
+                      struct pivot_value *label;
+                      if (level->type == CTL_VAR)
+                        label = pivot_value_new_variable (var);
+                      else if (level->type == CTL_CATEGORY)
+                        {
+                          const struct ctables_cell_value *cv = &cell->axes[a].cvs[level->var_idx];
+                          label = ctables_category_create_label (cv->category,
+                                                                 var, &cv->value);
+                        }
+                      else
+                        NOT_REACHED ();
+
+                      if (k == n_levels - 1)
+                        prev_leaf = pivot_category_create_leaf (parent, label);
+                      else
+                        groups[k] = pivot_category_create_group__ (parent, label);
+                    }
+                }
+
+              cell->axes[a].leaf = prev_leaf;
+            }
+          free (sorted);
+          free (groups);
+        }
+    }
+
+  for (size_t i = 0; i < t->n_sections; i++)
+    {
+      struct ctables_section *s = &t->sections[i];
+
+      struct ctables_cell *cell;
+      HMAP_FOR_EACH (cell, struct ctables_cell, node, &s->cells)
+        {
+          if (cell->hide)
+            continue;
+
+          const struct ctables_nest *specs_nest = s->nests[t->summary_axis];
+          const struct ctables_summary_spec_set *specs = &specs_nest->specs[cell->sv];
+          for (size_t j = 0; j < specs->n; j++)
+            {
+              size_t dindexes[5];
+              size_t n_dindexes = 0;
+
+              if (summary_dimension)
+                dindexes[n_dindexes++] = specs->specs[j].axis_idx;
+
+              if (categories_dimension)
+                {
+                  const struct ctables_nest *clabels_nest = s->nests[t->clabels_from_axis];
+                  const struct variable *var = clabels_nest->vars[clabels_nest->n - 1];
+                  const union value *value = &cell->axes[t->clabels_from_axis].cvs[clabels_nest->n - 1].value;
+                  const struct ctables_value *ctv = ctables_value_find (t, value, var_get_width (var));
+                  assert (ctv != NULL);
+                  dindexes[n_dindexes++] = ctv->leaf;
+                }
+
+              for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+                if (d[a])
+                  {
+                    int leaf = cell->axes[a].leaf;
+                    if (a == t->summary_axis && !summary_dimension)
+                      leaf += j;
+                    dindexes[n_dindexes++] = leaf;
+                  }
+
+              double d = (cell->postcompute
+                          ? ctables_cell_calculate_postcompute (s, cell)
+                          : ctables_summary_value (cell, &cell->summaries[j], &specs->specs[j]));
+              struct pivot_value *value = pivot_value_new_number (d);
+              value->numeric.format = specs->specs[j].format;
+              pivot_table_put (pt, dindexes, n_dindexes, value);
+            }
+        }
+    }
+
+  pivot_table_submit (pt);
+}
+
+static bool
+ctables_check_label_position (struct ctables_table *t, enum pivot_axis_type a)
+{
+  enum pivot_axis_type label_pos = t->label_axis[a];
+  if (label_pos == a)
+    return true;
+
+  t->clabels_from_axis = a;
+
+  const char *subcommand_name = a == PIVOT_AXIS_ROW ? "ROWLABELS" : "COLLABELS";
+  const char *pos_name = label_pos == PIVOT_AXIS_LAYER ? "LAYER" : "OPPOSITE";
+
+  const struct ctables_stack *stack = &t->stacks[a];
+  if (!stack->n)
+    return true;
+
+  const struct ctables_nest *n0 = &stack->nests[0];
+  assert (n0->n > 0);
+  const struct variable *v0 = n0->vars[n0->n - 1];
+  struct ctables_categories *c0 = t->categories[var_get_dict_index (v0)];
+  t->clabels_example = v0;
+
+  for (size_t i = 0; i < c0->n_cats; i++)
+    if (c0->cats[i].type == CCT_FUNCTION)
+      {
+        msg (SE, _("%s=%s is not allowed with sorting based "
+                   "on a summary function."),
+             subcommand_name, pos_name);
+        return false;
+      }
+  if (n0->n - 1 == n0->scale_idx)
+    {
+      msg (SE, _("%s=%s requires the variables to be moved to be categorical, "
+                 "but %s is a scale variable."),
+           subcommand_name, pos_name, var_get_name (v0));
+      return false;
+    }
+
+  for (size_t i = 1; i < stack->n; i++)
+    {
+      const struct ctables_nest *ni = &stack->nests[i];
+      assert (ni->n > 0);
+      const struct variable *vi = ni->vars[ni->n - 1];
+      struct ctables_categories *ci = t->categories[var_get_dict_index (vi)];
+
+      if (ni->n - 1 == ni->scale_idx)
+        {
+          msg (SE, _("%s=%s requires the variables to be moved to be "
+                     "categorical, but %s is a scale variable."),
+               subcommand_name, pos_name, var_get_name (vi));
+          return false;
+        }
+      if (var_get_width (v0) != var_get_width (vi))
+        {
+          msg (SE, _("%s=%s requires the variables to be "
+                     "moved to have the same width, but %s has "
+                     "width %d and %s has width %d."),
+               subcommand_name, pos_name,
+               var_get_name (v0), var_get_width (v0),
+               var_get_name (vi), var_get_width (vi));
+          return false;
+        }
+      if (!val_labs_equal (var_get_value_labels (v0),
+                           var_get_value_labels (vi)))
+        {
+          msg (SE, _("%s=%s requires the variables to be "
+                     "moved to have the same value labels, but %s "
+                     "and %s have different value labels."),
+               subcommand_name, pos_name,
+               var_get_name (v0), var_get_name (vi));
+          return false;
+        }
+      if (!ctables_categories_equal (c0, ci))
+        {
+          msg (SE, _("%s=%s requires the variables to be "
+                     "moved to have the same category "
+                     "specifications, but %s and %s have different "
+                     "category specifications."),
+               subcommand_name, pos_name,
+               var_get_name (v0), var_get_name (vi));
+          return false;
+        }
+    }
+
+  return true;
+}
+
+static bool
+ctables_prepare_table (struct ctables_table *t)
+{
+  for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+    if (t->axes[a])
+      {
+        t->stacks[a] = enumerate_fts (a, t->axes[a]);
+
+        for (size_t j = 0; j < t->stacks[a].n; j++)
+          {
+            struct ctables_nest *nest = &t->stacks[a].nests[j];
+            for (enum ctables_domain_type dt = 0; dt < N_CTDTS; dt++)
+              {
+                nest->domains[dt] = xmalloc (nest->n * sizeof *nest->domains[dt]);
+                nest->n_domains[dt] = 0;
+
+                for (size_t k = 0; k < nest->n; k++)
+                  {
+                    if (k == nest->scale_idx)
+                      continue;
+
+                    switch (dt)
+                      {
+                      case CTDT_TABLE:
+                        continue;
+
+                      case CTDT_LAYER:
+                        if (a != PIVOT_AXIS_LAYER)
+                          continue;
+                        break;
+
+                      case CTDT_SUBTABLE:
+                      case CTDT_ROW:
+                      case CTDT_COL:
+                        if (dt == CTDT_SUBTABLE ? a != PIVOT_AXIS_LAYER
+                            : dt == CTDT_ROW ? a == PIVOT_AXIS_COLUMN
+                            : a == PIVOT_AXIS_ROW)
+                          {
+                            if (k == nest->n - 1
+                                || (nest->scale_idx == nest->n - 1
+                                    && k == nest->n - 2))
+                              continue;
+                          }
+                        break;
+
+                      case CTDT_LAYERROW:
+                        if (a == PIVOT_AXIS_COLUMN)
+                          continue;
+                        break;
+
+                      case CTDT_LAYERCOL:
+                        if (a == PIVOT_AXIS_ROW)
+                          continue;
+                        break;
+                      }
+
+                    nest->domains[dt][nest->n_domains[dt]++] = k;
+                  }
+              }
+          }
+      }
+    else
+      {
+        struct ctables_nest *nest = xmalloc (sizeof *nest);
+        *nest = (struct ctables_nest) { .n = 0 };
+        t->stacks[a] = (struct ctables_stack) { .nests = nest, .n = 1 };
+      }
+
+  struct ctables_stack *stack = &t->stacks[t->summary_axis];
+  for (size_t i = 0; i < stack->n; i++)
+    {
+      struct ctables_nest *nest = &stack->nests[i];
+      if (!nest->specs[CSV_CELL].n)
+        {
+          struct ctables_summary_spec_set *specs = &nest->specs[CSV_CELL];
+          specs->specs = xmalloc (sizeof *specs->specs);
+          specs->n = 1;
+
+          enum ctables_summary_function function
+            = specs->var ? CTSF_MEAN : CTSF_COUNT;
+          struct ctables_var var = { .is_mrset = false, .var = specs->var };
+
+          *specs->specs = (struct ctables_summary_spec) {
+            .function = function,
+            .format = ctables_summary_default_format (function, &var),
+            .label = ctables_summary_default_label (function, 0),
+          };
+          if (!specs->var)
+            specs->var = nest->vars[0];
+
+          ctables_summary_spec_set_clone (&nest->specs[CSV_TOTAL],
+                                          &nest->specs[CSV_CELL]);
+        }
+      else if (!nest->specs[CSV_TOTAL].n)
+        ctables_summary_spec_set_clone (&nest->specs[CSV_TOTAL],
+                                        &nest->specs[CSV_CELL]);
+    }
+
+  struct ctables_summary_spec_set *merged = &t->summary_specs;
+  struct merge_item *items = xnmalloc (2 * stack->n, sizeof *items);
+  size_t n_left = 0;
+  for (size_t j = 0; j < stack->n; j++)
+    {
+      const struct ctables_nest *nest = &stack->nests[j];
+      if (nest->n)
+        for (enum ctables_summary_variant sv = 0; sv < N_CSVS; sv++)
+          items[n_left++] = (struct merge_item) { .set = &nest->specs[sv] };
+    }
+
+  while (n_left > 0)
+    {
+      struct merge_item min = items[0];
+      for (size_t j = 1; j < n_left; j++)
+        if (merge_item_compare_3way (&items[j], &min) < 0)
+          min = items[j];
+
+      if (merged->n >= merged->allocated)
+        merged->specs = x2nrealloc (merged->specs, &merged->allocated,
+                                    sizeof *merged->specs);
+      merged->specs[merged->n++] = min.set->specs[min.ofs];
+
+      for (size_t j = 0; j < n_left; )
+        {
+          if (merge_item_compare_3way (&items[j], &min) == 0)
+            {
+              struct merge_item *item = &items[j];
+              item->set->specs[item->ofs].axis_idx = merged->n - 1;
+              if (++item->ofs >= item->set->n)
+                {
+                  items[j] = items[--n_left];
+                  continue;
+                }
+            }
+          j++;
+        }
+    }
+
+#if 0
+  for (size_t j = 0; j < merged->n; j++)
+    printf ("%s\n", ctables_summary_function_name (merged->specs[j].function));
+
+  for (size_t j = 0; j < stack->n; j++)
+    {
+      const struct ctables_nest *nest = &stack->nests[j];
+      for (enum ctables_summary_variant sv = 0; sv < N_CSVS; sv++)
+        {
+          const struct ctables_summary_spec_set *specs = &nest->specs[sv];
+          for (size_t k = 0; k < specs->n; k++)
+            printf ("(%s, %zu) ", ctables_summary_function_name (specs->specs[k].function),
+                    specs->specs[k].axis_idx);
+          printf ("\n");
+        }
+    }
+#endif
+
+  return (ctables_check_label_position (t, PIVOT_AXIS_ROW)
+          && ctables_check_label_position (t, PIVOT_AXIS_COLUMN));
+}
+
+static void
+ctables_insert_clabels_values (struct ctables_table *t, const struct ccase *c,
+                               enum pivot_axis_type a)
+{
+  struct ctables_stack *stack = &t->stacks[a];
+  for (size_t i = 0; i < stack->n; i++)
+    {
+      const struct ctables_nest *nest = &stack->nests[i];
+      const struct variable *var = nest->vars[nest->n - 1];
+      int width = var_get_width (var);
+      const union value *value = case_data (c, var);
+
+      if (var_is_numeric (var) && value->f == SYSMIS)
+        continue;
+
+      if (!ctables_categories_match (t->categories [var_get_dict_index (var)],
+                                     value, var))
+        continue;
+
+      unsigned int hash = value_hash (value, width, 0);
+
+      struct ctables_value *clv = ctables_value_find__ (t, value, width, hash);
+      if (!clv)
+        {
+          clv = xmalloc (sizeof *clv);
+          value_clone (&clv->value, value, width);
+          hmap_insert (&t->clabels_values_map, &clv->node, hash);
+        }
+    }
+}
+
+static int
+compare_clabels_values_3way (const void *a_, const void *b_, const void *width_)
+{
+  const struct ctables_value *const *ap = a_;
+  const struct ctables_value *const *bp = b_;
+  const struct ctables_value *a = *ap;
+  const struct ctables_value *b = *bp;
+  const int *width = width_;
+  return value_compare_3way (&a->value, &b->value, *width);
+}
+
+static void
+ctables_sort_clabels_values (struct ctables_table *t)
+{
+  int width = var_get_width (t->clabels_example);
+
+  size_t n = hmap_count (&t->clabels_values_map);
+  t->clabels_values = xnmalloc (n, sizeof *t->clabels_values);
+
+  struct ctables_value *clv;
+  size_t i = 0;
+  HMAP_FOR_EACH (clv, struct ctables_value, node, &t->clabels_values_map)
+    t->clabels_values[i++] = clv;
+  t->n_clabels_values = n;
+  assert (i == n);
+
+  sort (t->clabels_values, n, sizeof *t->clabels_values,
+        compare_clabels_values_3way, &width);
+
+  for (size_t i = 0; i < n; i++)
+    t->clabels_values[i]->leaf = i;
+}
+
+static void
+ctables_add_category_occurrences (const struct variable *var,
+                                  struct hmap *occurrences,
+                                  const struct ctables_categories *cats)
+{
+  const struct val_labs *val_labs = var_get_value_labels (var);
+
+  for (size_t i = 0; i < cats->n_cats; i++)
+    {
+      const struct ctables_category *c = &cats->cats[i];
+      switch (c->type)
+        {
+        case CCT_NUMBER:
+          ctables_add_occurrence (var, &(const union value) { .f = c->number },
+                                  occurrences);
+          break;
+
+        case CCT_STRING:
+          abort ();             /* XXX */
+
+        case CCT_RANGE:
+          assert (var_is_numeric (var));
+          for (const struct val_lab *vl = val_labs_first (val_labs); vl;
+               vl = val_labs_next (val_labs, vl))
+            if (vl->value.f >= c->range[0] && vl->value.f <= c->range[1])
+              ctables_add_occurrence (var, &vl->value, occurrences);
+          break;
+
+        case CCT_MISSING:
+          for (const struct val_lab *vl = val_labs_first (val_labs); vl;
+               vl = val_labs_next (val_labs, vl))
+            if (var_is_value_missing (var, &vl->value))
+              ctables_add_occurrence (var, &vl->value, occurrences);
+          break;
+
+        case CCT_OTHERNM:
+          for (const struct val_lab *vl = val_labs_first (val_labs); vl;
+               vl = val_labs_next (val_labs, vl))
+            ctables_add_occurrence (var, &vl->value, occurrences);
+          break;
+
+        case CCT_POSTCOMPUTE:
+          break;
+
+        case CCT_SUBTOTAL:
+        case CCT_TOTAL:
+          break;
+
+        case CCT_VALUE:
+        case CCT_LABEL:
+        case CCT_FUNCTION:
+          for (const struct val_lab *vl = val_labs_first (val_labs); vl;
+               vl = val_labs_next (val_labs, vl))
+            if (c->include_missing || !var_is_value_missing (var, &vl->value))
+              ctables_add_occurrence (var, &vl->value, occurrences);
+          break;
+        }
+    }
+}
+
+static void
+ctables_section_recurse_add_empty_categories (
+  struct ctables_section *s,
+  const struct ctables_category *cats[PIVOT_N_AXES][10], struct ccase *c,
+  enum pivot_axis_type a, size_t a_idx)
+{
+  if (a >= PIVOT_N_AXES)
+    ctables_cell_insert__ (s, c, cats);
+  else if (!s->nests[a] || a_idx >= s->nests[a]->n)
+    ctables_section_recurse_add_empty_categories (s, cats, c, a + 1, 0);
+  else
+    {
+      const struct variable *var = s->nests[a]->vars[a_idx];
+      const struct ctables_categories *categories = s->table->categories[
+        var_get_dict_index (var)];
+      int width = var_get_width (var);
+      const struct hmap *occurrences = &s->occurrences[a][a_idx];
+      const struct ctables_occurrence *o;
+      HMAP_FOR_EACH (o, struct ctables_occurrence, node, occurrences)
+        {
+          union value *value = case_data_rw (c, var);
+          value_destroy (value, width);
+          value_clone (value, &o->value, width);
+          cats[a][a_idx] = ctables_categories_match (categories, value, var);
+          assert (cats[a][a_idx] != NULL);
+          ctables_section_recurse_add_empty_categories (s, cats, c, a, a_idx + 1);
+        }
+
+      for (size_t i = 0; i < categories->n_cats; i++)
+        {
+          const struct ctables_category *cat = &categories->cats[i];
+          if (cat->type == CCT_POSTCOMPUTE)
+            {
+              cats[a][a_idx] = cat;
+              ctables_section_recurse_add_empty_categories (s, cats, c, a, a_idx + 1);
+            }
+        }
+    }
+}
+
+static void
+ctables_section_add_empty_categories (struct ctables_section *s)
+{
+  bool show_empty = false;
+  for (size_t a = 0; a < PIVOT_N_AXES; a++)
+    if (s->nests[a])
+      for (size_t k = 0; k < s->nests[a]->n; k++)
+        if (k != s->nests[a]->scale_idx)
+          {
+            const struct variable *var = s->nests[a]->vars[k];
+            const struct ctables_categories *cats = s->table->categories[
+              var_get_dict_index (var)];
+            if (cats->show_empty)
+              {
+                show_empty = true;
+                ctables_add_category_occurrences (var, &s->occurrences[a][k], cats);
+              }
+          }
+  if (!show_empty)
+    return;
+
+  const struct ctables_category *cats[PIVOT_N_AXES][10]; /* XXX */
+  struct ccase *c = case_create (dict_get_proto (s->table->ctables->dict));
+  ctables_section_recurse_add_empty_categories (s, cats, c, 0, 0);
+  case_unref (c);
+}
+
+static bool
+ctables_execute (struct dataset *ds, struct ctables *ct)
+{
+  for (size_t i = 0; i < ct->n_tables; i++)
+    {
+      struct ctables_table *t = ct->tables[i];
+      t->sections = xnmalloc (MAX (1, t->stacks[PIVOT_AXIS_ROW].n) *
+                              MAX (1, t->stacks[PIVOT_AXIS_COLUMN].n) *
+                              MAX (1, t->stacks[PIVOT_AXIS_LAYER].n),
+                              sizeof *t->sections);
+      size_t ix[PIVOT_N_AXES];
+      ctables_table_add_section (t, 0, ix);
+    }
+
+  struct casereader *input = proc_open (ds);
+  bool warn_on_invalid = true;
+  for (struct ccase *c = casereader_read (input); c;
+       case_unref (c), c = casereader_read (input))
+    {
+      double d_weight = dict_get_case_weight (dataset_dict (ds), c,
+                                              &warn_on_invalid);
+      double e_weight = (ct->e_weight
+                         ? var_force_valid_weight (ct->e_weight,
+                                                   case_num (c, ct->e_weight),
+                                                   &warn_on_invalid)
+                         : d_weight);
+
+      for (size_t i = 0; i < ct->n_tables; i++)
+        {
+          struct ctables_table *t = ct->tables[i];
+
+          for (size_t j = 0; j < t->n_sections; j++)
+            ctables_cell_insert (&t->sections[j], c, d_weight, e_weight);
+
+          for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+            if (t->label_axis[a] != a)
+              ctables_insert_clabels_values (t, c, a);
+        }
+    }
+  casereader_destroy (input);
+
+  for (size_t i = 0; i < ct->n_tables; i++)
+    {
+      struct ctables_table *t = ct->tables[i];
+
+      if (t->clabels_example)
+        ctables_sort_clabels_values (t);
+
+      for (size_t j = 0; j < t->n_sections; j++)
+        ctables_section_add_empty_categories (&t->sections[j]);
+
+      ctables_table_output (ct, ct->tables[i]);
+    }
+  return proc_commit (ds);
+}
+\f
+/* Postcomputes. */
+
+typedef struct ctables_pcexpr *parse_recursively_func (struct lexer *);
+
+static void
+ctables_pcexpr_destroy (struct ctables_pcexpr *e)
+{
+  if (e)
+    {
+      switch (e->op)
+        {
+        case CTPO_CAT_STRING:
+          free (e->string);
+          break;
+
+        case CTPO_ADD:
+        case CTPO_SUB:
+        case CTPO_MUL:
+        case CTPO_DIV:
+        case CTPO_POW:
+        case CTPO_NEG:
+          for (size_t i = 0; i < 2; i++)
+            ctables_pcexpr_destroy (e->subs[i]);
+          break;
+
+        case CTPO_CONSTANT:
+        case CTPO_CAT_NUMBER:
+        case CTPO_CAT_RANGE:
+        case CTPO_CAT_MISSING:
+        case CTPO_CAT_OTHERNM:
+        case CTPO_CAT_SUBTOTAL:
+        case CTPO_CAT_TOTAL:
+          break;
+        }
+
+      msg_location_destroy (e->location);
+      free (e);
+    }
+}
+
+static struct ctables_pcexpr *
+ctables_pcexpr_allocate_binary (enum ctables_postcompute_op op,
+                                struct ctables_pcexpr *sub0,
+                                struct ctables_pcexpr *sub1)
+{
+  struct ctables_pcexpr *e = xmalloc (sizeof *e);
+  *e = (struct ctables_pcexpr) {
+    .op = op,
+    .subs = { sub0, sub1 },
+    .location = msg_location_merged (sub0->location, sub1->location),
+  };
+  return e;
+}
+
+/* How to parse an operator. */
+struct operator
+  {
+    enum token_type token;
+    enum ctables_postcompute_op op;
+  };
+
+static const struct operator *
+match_operator (struct lexer *lexer, const struct operator ops[], size_t n_ops)
+{
+  for (const struct operator *op = ops; op < ops + n_ops; op++)
+    if (lex_token (lexer) == op->token)
+      {
+        if (op->token != T_NEG_NUM)
+          lex_get (lexer);
+
+        return op;
+      }
+
+  return NULL;
+}
+
+static struct ctables_pcexpr *
+parse_binary_operators__ (struct lexer *lexer,
+                          const struct operator ops[], size_t n_ops,
+                          parse_recursively_func *parse_next_level,
+                          const char *chain_warning,
+                          struct ctables_pcexpr *lhs)
+{
+  for (int op_count = 0; ; op_count++)
+    {
+      const struct operator *op = match_operator (lexer, ops, n_ops);
+      if (!op)
+        {
+          if (op_count > 1 && chain_warning)
+            msg_at (SW, lhs->location, "%s", chain_warning);
+
+          return lhs;
+        }
+
+      struct ctables_pcexpr *rhs = parse_next_level (lexer);
+      if (!rhs)
+        {
+          ctables_pcexpr_destroy (lhs);
+          return NULL;
+        }
+
+      lhs = ctables_pcexpr_allocate_binary (op->op, lhs, rhs);
+    }
+}
+
+static struct ctables_pcexpr *
+parse_binary_operators (struct lexer *lexer,
+                        const struct operator ops[], size_t n_ops,
+                        parse_recursively_func *parse_next_level,
+                        const char *chain_warning)
+{
+  struct ctables_pcexpr *lhs = parse_next_level (lexer);
+  if (!lhs)
+    return NULL;
+
+  return parse_binary_operators__ (lexer, ops, n_ops, parse_next_level,
+                                   chain_warning, lhs);
+}
+
+static struct ctables_pcexpr *parse_add (struct lexer *);
+
+static struct ctables_pcexpr
+ctpo_cat_range (double low, double high)
+{
+  return (struct ctables_pcexpr) {
+    .op = CTPO_CAT_RANGE,
+    .range = { low, high },
+  };
+}
+
+static struct ctables_pcexpr *
+parse_primary (struct lexer *lexer)
+{
+  int start_ofs = lex_ofs (lexer);
+  struct ctables_pcexpr e;
+  if (lex_is_number (lexer))
+    {
+      e = (struct ctables_pcexpr) { .op = CTPO_CONSTANT,
+                                    .number = lex_number (lexer) };
+      lex_get (lexer);
+    }
+  else if (lex_match_id (lexer, "MISSING"))
+    e = (struct ctables_pcexpr) { .op = CTPO_CAT_MISSING };
+  else if (lex_match_id (lexer, "OTHERNM"))
+    e = (struct ctables_pcexpr) { .op = CTPO_CAT_OTHERNM };
+  else if (lex_match_id (lexer, "TOTAL"))
+    e = (struct ctables_pcexpr) { .op = CTPO_CAT_TOTAL };
+  else if (lex_match_id (lexer, "SUBTOTAL"))
+    {
+      size_t subtotal_index = 0;
+      if (lex_match (lexer, T_LBRACK))
+        {
+          if (!lex_force_int_range (lexer, "SUBTOTAL", 1, LONG_MAX))
+            return NULL;
+          subtotal_index = lex_integer (lexer);
+          lex_get (lexer);
+          if (!lex_force_match (lexer, T_RBRACK))
+            return NULL;
+        }
+      e = (struct ctables_pcexpr) { .op = CTPO_CAT_SUBTOTAL,
+                                    .subtotal_index = subtotal_index };
+    }
+  else if (lex_match (lexer, T_LBRACK))
+    {
+      if (lex_match_id (lexer, "LO"))
+        {
+          if (!lex_force_match_id (lexer, "THRU") || lex_force_num (lexer))
+            return false;
+          e = ctpo_cat_range (-DBL_MAX, lex_number (lexer));
+          lex_get (lexer);
+        }
+      else if (lex_is_number (lexer))
+        {
+          double number = lex_number (lexer);
+          lex_get (lexer);
+          if (lex_match_id (lexer, "THRU"))
+            {
+              if (lex_match_id (lexer, "HI"))
+                e = ctpo_cat_range (number, DBL_MAX);
+              else
+                {
+                  if (!lex_force_num (lexer))
+                    return false;
+                  e = ctpo_cat_range (number, lex_number (lexer));
+                  lex_get (lexer);
+                }
+            }
+          else
+            e = (struct ctables_pcexpr) { .op = CTPO_CAT_NUMBER,
+                                          .number = number };
+        }
+      else if (lex_is_string (lexer))
+        {
+          e = (struct ctables_pcexpr) {
+            .op = CTPO_CAT_STRING,
+            .string = ss_xstrdup (lex_tokss (lexer)),
+          };
+          lex_get (lexer);
+        }
+      else
+        {
+          lex_error (lexer, NULL);
+          return NULL;
+        }
+
+      if (!lex_force_match (lexer, T_RBRACK))
+        {
+          if (e.op == CTPO_CAT_STRING)
+            free (e.string);
+          return NULL;
+        }
+    }
+  else if (lex_match (lexer, T_LPAREN))
+    {
+      struct ctables_pcexpr *ep = parse_add (lexer);
+      if (!ep)
+        return NULL;
+      if (!lex_force_match (lexer, T_RPAREN))
+        {
+          ctables_pcexpr_destroy (ep);
+          return NULL;
+        }
+      return ep;
+    }
+  else
+    {
+      lex_error (lexer, NULL);
+      return NULL;
+    }
+
+  e.location = lex_ofs_location (lexer, start_ofs, lex_ofs (lexer) - 1);
+  return xmemdup (&e, sizeof e);
+}
+
+static struct ctables_pcexpr *
+ctables_pcexpr_allocate_neg (struct ctables_pcexpr *sub,
+                             struct lexer *lexer, int start_ofs)
+{
+  struct ctables_pcexpr *e = xmalloc (sizeof *e);
+  *e = (struct ctables_pcexpr) {
+    .op = CTPO_NEG,
+    .subs = { sub },
+    .location = lex_ofs_location (lexer, start_ofs, lex_ofs (lexer) - 1),
+  };
+  return e;
+}
+
+static struct ctables_pcexpr *
+parse_exp (struct lexer *lexer)
+{
+  static const struct operator op = { T_EXP, CTPO_POW };
+
+  const char *chain_warning =
+    _("The exponentiation operator (`**') is left-associative: "
+      "`a**b**c' equals `(a**b)**c', not `a**(b**c)'.  "
+      "To disable this warning, insert parentheses.");
+
+  if (lex_token (lexer) != T_NEG_NUM || lex_next_token (lexer, 1) != T_EXP)
+    return parse_binary_operators (lexer, &op, 1,
+                                   parse_primary, chain_warning);
+
+  /* Special case for situations like "-5**6", which must be parsed as
+     -(5**6). */
+
+  int start_ofs = lex_ofs (lexer);
+  struct ctables_pcexpr *lhs = xmalloc (sizeof *lhs);
+  *lhs = (struct ctables_pcexpr) {
+    .op = CTPO_CONSTANT,
+    .number = -lex_tokval (lexer),
+    .location = lex_ofs_location (lexer, start_ofs, lex_ofs (lexer)),
+  };
+  lex_get (lexer);
+
+  struct ctables_pcexpr *node = parse_binary_operators__ (
+    lexer, &op, 1, parse_primary, chain_warning, lhs);
+  if (!node)
+    return NULL;
+
+  return ctables_pcexpr_allocate_neg (node, lexer, start_ofs);
+}
+
+/* Parses the unary minus level. */
+static struct ctables_pcexpr *
+parse_neg (struct lexer *lexer)
+{
+  int start_ofs = lex_ofs (lexer);
+  if (!lex_match (lexer, T_DASH))
+    return parse_exp (lexer);
+
+  struct ctables_pcexpr *inner = parse_neg (lexer);
+  if (!inner)
+    return NULL;
+
+  return ctables_pcexpr_allocate_neg (inner, lexer, start_ofs);
+}
+
+/* Parses the multiplication and division level. */
+static struct ctables_pcexpr *
+parse_mul (struct lexer *lexer)
+{
+  static const struct operator ops[] =
+    {
+      { T_ASTERISK, CTPO_MUL },
+      { T_SLASH, CTPO_DIV },
+    };
+
+  return parse_binary_operators (lexer, ops, sizeof ops / sizeof *ops,
+                                 parse_neg, NULL);
+}
+
+/* Parses the addition and subtraction level. */
+static struct ctables_pcexpr *
+parse_add (struct lexer *lexer)
+{
+  static const struct operator ops[] =
+    {
+      { T_PLUS, CTPO_ADD },
+      { T_DASH, CTPO_SUB },
+      { T_NEG_NUM, CTPO_ADD },
+    };
+
+  return parse_binary_operators (lexer, ops, sizeof ops / sizeof *ops,
+                                 parse_mul, NULL);
+}
+
+static struct ctables_postcompute *
+ctables_find_postcompute (struct ctables *ct, const char *name)
+{
+  struct ctables_postcompute *pc;
+  HMAP_FOR_EACH_WITH_HASH (pc, struct ctables_postcompute, hmap_node,
+                           utf8_hash_case_string (name, 0), &ct->postcomputes)
+    if (!utf8_strcasecmp (pc->name, name))
+      return pc;
+  return NULL;
+}
+
+static bool
+ctables_parse_pcompute (struct lexer *lexer, struct ctables *ct)
+{
+  int pcompute_start = lex_ofs (lexer) - 1;
+
+  if (!lex_force_match (lexer, T_AND) || !lex_force_id (lexer))
+    return false;
+
+  char *name = ss_xstrdup (lex_tokss (lexer));
+
+  lex_get (lexer);
+  if (!lex_force_match (lexer, T_EQUALS)
+      || !lex_force_match_id (lexer, "EXPR")
+      || !lex_force_match (lexer, T_LPAREN))
+    {
+      free (name);
+      return false;
+    }
+
+  int expr_start = lex_ofs (lexer);
+  struct ctables_pcexpr *expr = parse_add (lexer);
+  int expr_end = lex_ofs (lexer) - 1;
+  if (!expr || !lex_force_match (lexer, T_RPAREN))
+    {
+      free (name);
+      return false;
+    }
+  int pcompute_end = lex_ofs (lexer) - 1;
+
+  struct msg_location *location = lex_ofs_location (lexer, pcompute_start,
+                                                    pcompute_end);
+
+  struct ctables_postcompute *pc = ctables_find_postcompute (ct, name);
+  if (pc)
+    {
+      msg_at (SW, location, _("New definition of &%s will override the "
+                              "previous definition."),
+              pc->name);
+      msg_at (SN, pc->location, _("This is the previous definition."));
+
+      ctables_pcexpr_destroy (pc->expr);
+      msg_location_destroy (pc->location);
+      free (name);
+    }
+  else
+    {
+      pc = xmalloc (sizeof *pc);
+      *pc = (struct ctables_postcompute) { .name = name };
+      hmap_insert (&ct->postcomputes, &pc->hmap_node,
+                   utf8_hash_case_string (pc->name, 0));
+    }
+  pc->expr = expr;
+  pc->location = location;
+  if (!pc->label)
+    pc->label = lex_ofs_representation (lexer, expr_start, expr_end);
+  return true;
+}
+
+static bool
+ctables_parse_pproperties_format (struct lexer *lexer,
+                                  struct ctables_summary_spec_set *sss)
+{
+  *sss = (struct ctables_summary_spec_set) { .n = 0 };
+
+  while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH
+         && !(lex_token (lexer) == T_ID
+              && (lex_id_match (ss_cstr ("LABEL"), lex_tokss (lexer))
+                  || lex_id_match (ss_cstr ("HIDESOURCECATS"),
+                                   lex_tokss (lexer)))))
+    {
+      /* Parse function. */
+      enum ctables_summary_function function;
+      if (!parse_ctables_summary_function (lexer, &function))
+        goto error;
+
+      /* Parse percentile. */
+      double percentile = 0;
+      if (function == CTSF_PTILE)
+        {
+          if (!lex_force_num_range_closed (lexer, "PTILE", 0, 100))
+            goto error;
+          percentile = lex_number (lexer);
+          lex_get (lexer);
+        }
+
+      /* Parse format. */
+      struct fmt_spec format;
+      if (!parse_format_specifier (lexer, &format)
+          || !fmt_check_output (&format)
+          || !fmt_check_type_compat (&format, VAL_NUMERIC))
+        goto error;
+
+      if (sss->n >= sss->allocated)
+        sss->specs = x2nrealloc (sss->specs, &sss->allocated,
+                                 sizeof *sss->specs);
+      sss->specs[sss->n++] = (struct ctables_summary_spec) {
+        .function = function,
+        .percentile = percentile,
+        .format = format,
+      };
+    }
+  return true;
+
+error:
+  ctables_summary_spec_set_uninit (sss);
+  return false;
+}
+
+static bool
+ctables_parse_pproperties (struct lexer *lexer, struct ctables *ct)
+{
+  struct ctables_postcompute **pcs = NULL;
+  size_t n_pcs = 0;
+  size_t allocated_pcs = 0;
+
+  while (lex_match (lexer, T_AND))
+    {
+      if (!lex_force_id (lexer))
+        goto error;
+      struct ctables_postcompute *pc
+        = ctables_find_postcompute (ct, lex_tokcstr (lexer));
+      if (!pc)
+        {
+          msg (SE, _("Unknown computed category &%s."), lex_tokcstr (lexer));
+          goto error;
+        }
+      lex_get (lexer);
+
+      if (n_pcs >= allocated_pcs)
+        pcs = x2nrealloc (pcs, &allocated_pcs, sizeof *pcs);
+      pcs[n_pcs++] = pc;
+    }
+
+  while (lex_token (lexer) != T_SLASH && lex_token (lexer) != T_ENDCMD)
+    {
+      if (lex_match_id (lexer, "LABEL"))
+        {
+          lex_match (lexer, T_EQUALS);
+          if (!lex_force_string (lexer))
+            goto error;
+
+          for (size_t i = 0; i < n_pcs; i++)
+            {
+              free (pcs[i]->label);
+              pcs[i]->label = ss_xstrdup (lex_tokss (lexer));
+            }
+
+          lex_get (lexer);
+        }
+      else if (lex_match_id (lexer, "FORMAT"))
+        {
+          lex_match (lexer, T_EQUALS);
+
+          struct ctables_summary_spec_set sss;
+          if (!ctables_parse_pproperties_format (lexer, &sss))
+            goto error;
+
+          for (size_t i = 0; i < n_pcs; i++)
+            {
+              if (pcs[i]->specs)
+                ctables_summary_spec_set_uninit (pcs[i]->specs);
+              else
+                pcs[i]->specs = xmalloc (sizeof *pcs[i]->specs);
+              ctables_summary_spec_set_clone (pcs[i]->specs, &sss);
+            }
+          ctables_summary_spec_set_uninit (&sss);
+        }
+      else if (lex_match_id (lexer, "HIDESOURCECATS"))
+        {
+          lex_match (lexer, T_EQUALS);
+          bool hide_source_cats;
+          if (!parse_bool (lexer, &hide_source_cats))
+            goto error;
+          for (size_t i = 0; i < n_pcs; i++)
+            pcs[i]->hide_source_cats = hide_source_cats;
+        }
+      else
+        {
+          lex_error_expecting (lexer, "LABEL", "FORMAT", "HIDESOURCECATS");
+          goto error;
+        }
+    }
+  free (pcs);
+  return true;
+
+error:
+  free (pcs);
+  return false;
+}
+
+int
+cmd_ctables (struct lexer *lexer, struct dataset *ds)
+{
+  size_t n_vars = dict_get_n_vars (dataset_dict (ds));
+  enum ctables_vlabel *vlabels = xnmalloc (n_vars, sizeof *vlabels);
+  enum settings_value_show tvars = settings_get_show_variables ();
+  for (size_t i = 0; i < n_vars; i++)
+    vlabels[i] = (enum ctables_vlabel) tvars;
+
+  struct ctables *ct = xmalloc (sizeof *ct);
+  *ct = (struct ctables) {
+    .dict = dataset_dict (ds),
+    .look = pivot_table_look_unshare (pivot_table_look_ref (
+                                        pivot_table_look_get_default ())),
+    .vlabels = vlabels,
+    .postcomputes = HMAP_INITIALIZER (ct->postcomputes),
+    .hide_threshold = 5,
+  };
+  ct->look->omit_empty = false;
+
+  if (!lex_force_match (lexer, T_SLASH))
+    goto error;
+
+  while (!lex_match_id (lexer, "TABLE"))
+    {
+      if (lex_match_id (lexer, "FORMAT"))
+        {
+          double widths[2] = { SYSMIS, SYSMIS };
+          double units_per_inch = 72.0;
+
+          while (lex_token (lexer) != T_SLASH)
+            {
+              if (lex_match_id (lexer, "MINCOLWIDTH"))
+                {
+                  if (!parse_col_width (lexer, "MINCOLWIDTH", &widths[0]))
+                    goto error;
+                }
+              else if (lex_match_id (lexer, "MAXCOLWIDTH"))
+                {
+                  if (!parse_col_width (lexer, "MAXCOLWIDTH", &widths[1]))
+                    goto error;
+                }
+              else if (lex_match_id (lexer, "UNITS"))
+                {
+                  lex_match (lexer, T_EQUALS);
+                  if (lex_match_id (lexer, "POINTS"))
+                    units_per_inch = 72.0;
+                  else if (lex_match_id (lexer, "INCHES"))
+                    units_per_inch = 1.0;
+                  else if (lex_match_id (lexer, "CM"))
+                    units_per_inch = 2.54;
+                  else
+                    {
+                      lex_error_expecting (lexer, "POINTS", "INCHES", "CM");
+                      goto error;
+                    }
+                }
+              else if (lex_match_id (lexer, "EMPTY"))
+                {
+                  free (ct->zero);
+                  ct->zero = NULL;
+
+                  lex_match (lexer, T_EQUALS);
+                  if (lex_match_id (lexer, "ZERO"))
+                    {
+                      /* Nothing to do. */
+                    }
+                  else if (lex_match_id (lexer, "BLANK"))
+                    ct->zero = xstrdup ("");
+                  else if (lex_force_string (lexer))
+                    {
+                      ct->zero = ss_xstrdup (lex_tokss (lexer));
+                      lex_get (lexer);
+                    }
+                  else
+                    goto error;
+                }
+              else if (lex_match_id (lexer, "MISSING"))
+                {
+                  lex_match (lexer, T_EQUALS);
+                  if (!lex_force_string (lexer))
+                    goto error;
+
+                  free (ct->missing);
+                  ct->missing = (strcmp (lex_tokcstr (lexer), ".")
+                                 ? ss_xstrdup (lex_tokss (lexer))
+                                 : NULL);
+                  lex_get (lexer);
+                }
+              else
+                {
+                  lex_error_expecting (lexer, "MINCOLWIDTH", "MAXCOLWIDTH",
+                                       "UNITS", "EMPTY", "MISSING");
+                  goto error;
+                }
+            }
+
+          if (widths[0] != SYSMIS && widths[1] != SYSMIS
+              && widths[0] > widths[1])
+            {
+              msg (SE, _("MINCOLWIDTH must not be greater than MAXCOLWIDTH."));
+              goto error;
+            }
+
+          for (size_t i = 0; i < 2; i++)
+            if (widths[i] != SYSMIS)
+              {
+                int *wr = ct->look->width_ranges[TABLE_HORZ];
+                wr[i] = widths[i] / units_per_inch * 96.0;
+                if (wr[0] > wr[1])
+                  wr[!i] = wr[i];
+              }
+        }
+      else if (lex_match_id (lexer, "VLABELS"))
+        {
+          if (!lex_force_match_id (lexer, "VARIABLES"))
+            goto error;
+          lex_match (lexer, T_EQUALS);
+
+          struct variable **vars;
+          size_t n_vars;
+          if (!parse_variables (lexer, dataset_dict (ds), &vars, &n_vars,
+                                PV_NO_SCRATCH))
+            goto error;
+
+          if (!lex_force_match_id (lexer, "DISPLAY"))
+            {
+              free (vars);
+              goto error;
+            }
+          lex_match (lexer, T_EQUALS);
+
+          enum ctables_vlabel vlabel;
+          if (lex_match_id (lexer, "DEFAULT"))
+            vlabel = (enum ctables_vlabel) settings_get_show_variables ();
+          else if (lex_match_id (lexer, "NAME"))
+            vlabel = CTVL_NAME;
+          else if (lex_match_id (lexer, "LABEL"))
+            vlabel = CTVL_LABEL;
+          else if (lex_match_id (lexer, "BOTH"))
+            vlabel = CTVL_BOTH;
+          else if (lex_match_id (lexer, "NONE"))
+            vlabel = CTVL_NONE;
+          else
+            {
+              lex_error_expecting (lexer, "DEFAULT", "NAME", "LABEL",
+                                   "BOTH", "NONE");
+              free (vars);
+              goto error;
+            }
+
+          for (size_t i = 0; i < n_vars; i++)
+            ct->vlabels[var_get_dict_index (vars[i])] = vlabel;
+          free (vars);
+        }
+      else if (lex_match_id (lexer, "MRSETS"))
+        {
+          if (!lex_force_match_id (lexer, "COUNTDUPLICATES"))
+            goto error;
+          lex_match (lexer, T_EQUALS);
+          if (!parse_bool (lexer, &ct->mrsets_count_duplicates))
+            goto error;
+        }
+      else if (lex_match_id (lexer, "SMISSING"))
+        {
+          if (lex_match_id (lexer, "VARIABLE"))
+            ct->smissing_listwise = false;
+          else if (lex_match_id (lexer, "LISTWISE"))
+            ct->smissing_listwise = true;
+          else
+            {
+              lex_error_expecting (lexer, "VARIABLE", "LISTWISE");
+              goto error;
+            }
+        }
+      else if (lex_match_id (lexer, "PCOMPUTE"))
+        {
+          if (!ctables_parse_pcompute (lexer, ct))
+            goto error;
+        }
+      else if (lex_match_id (lexer, "PPROPERTIES"))
+        {
+          if (!ctables_parse_pproperties (lexer, ct))
+            goto error;
+        }
+      else if (lex_match_id (lexer, "WEIGHT"))
+        {
+          if (!lex_force_match_id (lexer, "VARIABLE"))
+            goto error;
+          lex_match (lexer, T_EQUALS);
+          ct->e_weight = parse_variable (lexer, dataset_dict (ds));
+          if (!ct->e_weight)
+            goto error;
+        }
+      else if (lex_match_id (lexer, "HIDESMALLCOUNTS"))
+        {
+          if (!lex_force_match_id (lexer, "COUNT"))
+            goto error;
+          lex_match (lexer, T_EQUALS);
+          if (!lex_force_int_range (lexer, "HIDESMALLCOUNTS COUNT", 2, INT_MAX))
+            goto error;
+          ct->hide_threshold = lex_integer (lexer);
+          lex_get (lexer);
+        }
+      else
+        {
+          lex_error_expecting (lexer, "FORMAT", "VLABELS", "MRSETS",
+                               "SMISSING", "PCOMPUTE", "PPROPERTIES",
+                               "WEIGHT", "HIDESMALLCOUNTS", "TABLE");
+          goto error;
+        }
+
+      if (!lex_force_match (lexer, T_SLASH))
+        goto error;
+    }
+
+  size_t allocated_tables = 0;
+  do
+    {
+      if (ct->n_tables >= allocated_tables)
+        ct->tables = x2nrealloc (ct->tables, &allocated_tables,
+                                 sizeof *ct->tables);
+
+      struct ctables_category *cat = xmalloc (sizeof *cat);
+      *cat = (struct ctables_category) {
+        .type = CCT_VALUE,
+        .include_missing = false,
+        .sort_ascending = true,
+      };
+
+      struct ctables_categories *c = xmalloc (sizeof *c);
+      size_t n_vars = dict_get_n_vars (dataset_dict (ds));
+      *c = (struct ctables_categories) {
+        .n_refs = n_vars,
+        .cats = cat,
+        .n_cats = 1,
+        .show_empty = true,
+      };
+
+      struct ctables_categories **categories = xnmalloc (n_vars,
+                                                         sizeof *categories);
+      for (size_t i = 0; i < n_vars; i++)
+        categories[i] = c;
+
+      struct ctables_table *t = xmalloc (sizeof *t);
+      *t = (struct ctables_table) {
+        .ctables = ct,
+        .slabels_axis = PIVOT_AXIS_COLUMN,
+        .slabels_visible = true,
+        .clabels_values_map = HMAP_INITIALIZER (t->clabels_values_map),
+        .label_axis = {
+          [PIVOT_AXIS_ROW] = PIVOT_AXIS_ROW,
+          [PIVOT_AXIS_COLUMN] = PIVOT_AXIS_COLUMN,
+          [PIVOT_AXIS_LAYER] = PIVOT_AXIS_LAYER,
+        },
+        .clabels_from_axis = PIVOT_AXIS_LAYER, 
+        .categories = categories,
+        .n_categories = n_vars,
+        .cilevel = 95,
+      };
+      ct->tables[ct->n_tables++] = t;
+
+      lex_match (lexer, T_EQUALS);
+      if (!ctables_axis_parse (lexer, dataset_dict (ds), ct, t, PIVOT_AXIS_ROW))
+        goto error;
+      if (lex_match (lexer, T_BY))
+        {
+          if (!ctables_axis_parse (lexer, dataset_dict (ds),
+                                   ct, t, PIVOT_AXIS_COLUMN))
+            goto error;
+
+          if (lex_match (lexer, T_BY))
+            {
+              if (!ctables_axis_parse (lexer, dataset_dict (ds),
+                                       ct, t, PIVOT_AXIS_LAYER))
+                goto error;
+            }
+        }
+
+      if (!t->axes[PIVOT_AXIS_ROW] && !t->axes[PIVOT_AXIS_COLUMN]
+          && !t->axes[PIVOT_AXIS_LAYER])
+        {
+          lex_error (lexer, _("At least one variable must be specified."));
+          goto error;
+        }
+
+      const struct ctables_axis *scales[PIVOT_N_AXES];
+      size_t n_scales = 0;
+      for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+        {
+          scales[a] = find_scale (t->axes[a]);
+          if (scales[a])
+            n_scales++;
+        }
+      if (n_scales > 1)
+        {
+          msg (SE, _("Scale variables may appear only on one axis."));
+          if (scales[PIVOT_AXIS_ROW])
+            msg_at (SN, scales[PIVOT_AXIS_ROW]->loc,
+                    _("This scale variable appears on the rows axis."));
+          if (scales[PIVOT_AXIS_COLUMN])
+            msg_at (SN, scales[PIVOT_AXIS_COLUMN]->loc,
+                    _("This scale variable appears on the columns axis."));
+          if (scales[PIVOT_AXIS_LAYER])
+            msg_at (SN, scales[PIVOT_AXIS_LAYER]->loc,
+                    _("This scale variable appears on the layer axis."));
+          goto error;
+        }
+
+      const struct ctables_axis *summaries[PIVOT_N_AXES];
+      size_t n_summaries = 0;
+      for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+        {
+          summaries[a] = (scales[a]
+                          ? scales[a]
+                          : find_categorical_summary_spec (t->axes[a]));
+          if (summaries[a])
+            n_summaries++;
+        }
+      if (n_summaries > 1)
+        {
+          msg (SE, _("Summaries may appear only on one axis."));
+          if (summaries[PIVOT_AXIS_ROW])
+            msg_at (SN, summaries[PIVOT_AXIS_ROW]->loc,
+                    _("This variable on the rows axis has a summary."));
+          if (summaries[PIVOT_AXIS_COLUMN])
+            msg_at (SN, summaries[PIVOT_AXIS_COLUMN]->loc,
+                    _("This variable on the columns axis has a summary."));
+          if (summaries[PIVOT_AXIS_LAYER])
+            msg_at (SN, summaries[PIVOT_AXIS_LAYER]->loc,
+                    _("This variable on the layers axis has a summary."));
+          goto error;
+        }
+      for (enum pivot_axis_type a = 0; a < PIVOT_N_AXES; a++)
+        if (n_summaries ? summaries[a] : t->axes[a])
+          {
+            t->summary_axis = a;
+            break;
+          }
+
+      if (lex_token (lexer) == T_ENDCMD)
+        {
+          if (!ctables_prepare_table (t))
+            goto error;
+          break;
+        }
+      if (!lex_force_match (lexer, T_SLASH))
+        break;
+
+      while (!lex_match_id (lexer, "TABLE") && lex_token (lexer) != T_ENDCMD)
+        {
+          if (lex_match_id (lexer, "SLABELS"))
+            {
+              while (lex_token (lexer) != T_SLASH && lex_token (lexer) != T_ENDCMD)
+                {
+                  if (lex_match_id (lexer, "POSITION"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "COLUMN"))
+                        t->slabels_axis = PIVOT_AXIS_COLUMN;
+                      else if (lex_match_id (lexer, "ROW"))
+                        t->slabels_axis = PIVOT_AXIS_ROW;
+                      else if (lex_match_id (lexer, "LAYER"))
+                        t->slabels_axis = PIVOT_AXIS_LAYER;
+                      else
+                        {
+                          lex_error_expecting (lexer, "COLUMN", "ROW", "LAYER");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "VISIBLE"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (!parse_bool (lexer, &t->slabels_visible))
+                        goto error;
+                    }
+                  else
+                    {
+                      lex_error_expecting (lexer, "POSITION", "VISIBLE");
+                      goto error;
+                    }
+                }
+            }
+          else if (lex_match_id (lexer, "CLABELS"))
+            {
+              while (lex_token (lexer) != T_SLASH && lex_token (lexer) != T_ENDCMD)
+                {
+                  if (lex_match_id (lexer, "AUTO"))
+                    {
+                      t->label_axis[PIVOT_AXIS_ROW] = PIVOT_AXIS_ROW;
+                      t->label_axis[PIVOT_AXIS_COLUMN] = PIVOT_AXIS_COLUMN;
+                    }
+                  else if (lex_match_id (lexer, "ROWLABELS"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "OPPOSITE"))
+                        t->label_axis[PIVOT_AXIS_ROW] = PIVOT_AXIS_COLUMN;
+                      else if (lex_match_id (lexer, "LAYER"))
+                        t->label_axis[PIVOT_AXIS_ROW] = PIVOT_AXIS_LAYER;
+                      else
+                        {
+                          lex_error_expecting (lexer, "OPPOSITE", "LAYER");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "COLLABELS"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "OPPOSITE"))
+                        t->label_axis[PIVOT_AXIS_COLUMN] = PIVOT_AXIS_ROW;
+                      else if (lex_match_id (lexer, "LAYER"))
+                        t->label_axis[PIVOT_AXIS_COLUMN] = PIVOT_AXIS_LAYER;
+                      else
+                        {
+                          lex_error_expecting (lexer, "OPPOSITE", "LAYER");
+                          goto error;
+                        }
+                    }
+                  else
+                    {
+                      lex_error_expecting (lexer, "AUTO", "ROWLABELS",
+                                           "COLLABELS");
+                      goto error;
+                    }
+                }
+            }
+          else if (lex_match_id (lexer, "CRITERIA"))
+            {
+              if (!lex_force_match_id (lexer, "CILEVEL"))
+                goto error;
+              lex_match (lexer, T_EQUALS);
+
+              if (!lex_force_num_range_halfopen (lexer, "CILEVEL", 0, 100))
+                goto error;
+              t->cilevel = lex_number (lexer);
+              lex_get (lexer);
+            }
+          else if (lex_match_id (lexer, "CATEGORIES"))
+            {
+              if (!ctables_table_parse_categories (lexer, dataset_dict (ds),
+                                                   ct, t))
+                goto error;
+            }
+          else if (lex_match_id (lexer, "TITLES"))
+            {
+              do
+                {
+                  char **textp;
+                  if (lex_match_id (lexer, "CAPTION"))
+                    textp = &t->caption;
+                  else if (lex_match_id (lexer, "CORNER"))
+                    textp = &t->corner;
+                  else if (lex_match_id (lexer, "TITLE"))
+                    textp = &t->title;
+                  else
+                    {
+                      lex_error_expecting (lexer, "CAPTION", "CORNER", "TITLE");
+                      goto error;
+                    }
+                  lex_match (lexer, T_EQUALS);
+
+                  struct string s = DS_EMPTY_INITIALIZER;
+                  while (lex_is_string (lexer))
+                    {
+                      if (!ds_is_empty (&s))
+                        ds_put_byte (&s, ' ');
+                      ds_put_substring (&s, lex_tokss (lexer));
+                      lex_get (lexer);
+                    }
+                  free (*textp);
+                  *textp = ds_steal_cstr (&s);
+                }
+              while (lex_token (lexer) != T_SLASH
+                     && lex_token (lexer) != T_ENDCMD);
+            }
+          else if (lex_match_id (lexer, "SIGTEST"))
+            {
+              if (!t->chisq)
+                {
+                  t->chisq = xmalloc (sizeof *t->chisq);
+                  *t->chisq = (struct ctables_chisq) {
+                    .alpha = .05,
+                    .include_mrsets = true,
+                    .all_visible = true,
+                  };
+                }
+
+              do
+                {
+                  if (lex_match_id (lexer, "TYPE"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (!lex_force_match_id (lexer, "CHISQUARE"))
+                        goto error;
+                    }
+                  else if (lex_match_id (lexer, "ALPHA"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (!lex_force_num_range_halfopen (lexer, "ALPHA", 0, 1))
+                        goto error;
+                      t->chisq->alpha = lex_number (lexer);
+                      lex_get (lexer);
+                    }
+                  else if (lex_match_id (lexer, "INCLUDEMRSETS"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (parse_bool (lexer, &t->chisq->include_mrsets))
+                        goto error;
+                    }
+                  else if (lex_match_id (lexer, "CATEGORIES"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "ALLVISIBLE"))
+                        t->chisq->all_visible = true;
+                      else if (lex_match_id (lexer, "SUBTOTALS"))
+                        t->chisq->all_visible = false;
+                      else
+                        {
+                          lex_error_expecting (lexer,
+                                               "ALLVISIBLE", "SUBTOTALS");
+                          goto error;
+                        }
+                    }
+                  else
+                    {
+                      lex_error_expecting (lexer, "TYPE", "ALPHA",
+                                           "INCLUDEMRSETS", "CATEGORIES");
+                      goto error;
+                    }
+                }
+              while (lex_token (lexer) != T_SLASH
+                     && lex_token (lexer) != T_ENDCMD);
+            }
+          else if (lex_match_id (lexer, "COMPARETEST"))
+            {
+              if (!t->pairwise)
+                {
+                  t->pairwise = xmalloc (sizeof *t->pairwise);
+                  *t->pairwise = (struct ctables_pairwise) {
+                    .type = PROP,
+                    .alpha = { .05, .05 },
+                    .adjust = BONFERRONI,
+                    .include_mrsets = true,
+                    .meansvariance_allcats = true,
+                    .all_visible = true,
+                    .merge = false,
+                    .apa_style = true,
+                    .show_sig = false,
+                  };
+                }
+
+              do
+                {
+                  if (lex_match_id (lexer, "TYPE"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "PROP"))
+                        t->pairwise->type = PROP;
+                      else if (lex_match_id (lexer, "MEAN"))
+                        t->pairwise->type = MEAN;
+                      else
+                        {
+                          lex_error_expecting (lexer, "PROP", "MEAN");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "ALPHA"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+
+                      if (!lex_force_num_range_open (lexer, "ALPHA", 0, 1))
+                        goto error;
+                      double a0 = lex_number (lexer);
+                      lex_get (lexer);
+
+                      lex_match (lexer, T_COMMA);
+                      if (lex_is_number (lexer))
+                        {
+                          if (!lex_force_num_range_open (lexer, "ALPHA", 0, 1))
+                            goto error;
+                          double a1 = lex_number (lexer);
+                          lex_get (lexer);
+
+                          t->pairwise->alpha[0] = MIN (a0, a1);
+                          t->pairwise->alpha[1] = MAX (a0, a1);
+                        }
+                      else
+                        t->pairwise->alpha[0] = t->pairwise->alpha[1] = a0;
+                    }
+                  else if (lex_match_id (lexer, "ADJUST"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "BONFERRONI"))
+                        t->pairwise->adjust = BONFERRONI;
+                      else if (lex_match_id (lexer, "BH"))
+                        t->pairwise->adjust = BH;
+                      else if (lex_match_id (lexer, "NONE"))
+                        t->pairwise->adjust = 0;
+                      else
+                        {
+                          lex_error_expecting (lexer, "BONFERRONI", "BH",
+                                               "NONE");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "INCLUDEMRSETS"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (!parse_bool (lexer, &t->pairwise->include_mrsets))
+                        goto error;
+                    }
+                  else if (lex_match_id (lexer, "MEANSVARIANCE"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "ALLCATS"))
+                        t->pairwise->meansvariance_allcats = true;
+                      else if (lex_match_id (lexer, "TESTEDCATS"))
+                        t->pairwise->meansvariance_allcats = false;
+                      else
+                        {
+                          lex_error_expecting (lexer, "ALLCATS", "TESTEDCATS");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "CATEGORIES"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "ALLVISIBLE"))
+                        t->pairwise->all_visible = true;
+                      else if (lex_match_id (lexer, "SUBTOTALS"))
+                        t->pairwise->all_visible = false;
+                      else
+                        {
+                          lex_error_expecting (lexer, "ALLVISIBLE",
+                                               "SUBTOTALS");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "MERGE"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (!parse_bool (lexer, &t->pairwise->merge))
+                        goto error;
+                    }
+                  else if (lex_match_id (lexer, "STYLE"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (lex_match_id (lexer, "APA"))
+                        t->pairwise->apa_style = true;
+                      else if (lex_match_id (lexer, "SIMPLE"))
+                        t->pairwise->apa_style = false;
+                      else
+                        {
+                          lex_error_expecting (lexer, "APA", "SIMPLE");
+                          goto error;
+                        }
+                    }
+                  else if (lex_match_id (lexer, "SHOWSIG"))
+                    {
+                      lex_match (lexer, T_EQUALS);
+                      if (!parse_bool (lexer, &t->pairwise->show_sig))
+                        goto error;
+                    }
+                  else
+                    {
+                      lex_error_expecting (lexer, "TYPE", "ALPHA", "ADJUST",
+                                           "INCLUDEMRSETS", "MEANSVARIANCE",
+                                           "CATEGORIES", "MERGE", "STYLE",
+                                           "SHOWSIG");
+                      goto error;
+                    }
+                }
+              while (lex_token (lexer) != T_SLASH
+                     && lex_token (lexer) != T_ENDCMD);
+            }
+          else
+            {
+              lex_error_expecting (lexer, "TABLE", "SLABELS", "CLABELS",
+                                   "CRITERIA", "CATEGORIES", "TITLES",
+                                   "SIGTEST", "COMPARETEST");
+              goto error;
+            }
+
+          if (!lex_match (lexer, T_SLASH))
+            break;
+        }
+
+      if (t->label_axis[PIVOT_AXIS_ROW] != PIVOT_AXIS_ROW
+          && t->label_axis[PIVOT_AXIS_COLUMN] != PIVOT_AXIS_COLUMN)
+        {
+          msg (SE, _("ROWLABELS and COLLABELS may not both be specified."));
+          goto error;
+        }
+
+      if (!ctables_prepare_table (t))
+        goto error;
+    }
+  while (lex_token (lexer) != T_ENDCMD);
+
+  bool ok = ctables_execute (ds, ct);
+  ctables_destroy (ct);
+  return ok ? CMD_SUCCESS : CMD_FAILURE;
+
+error:
+  ctables_destroy (ct);
+  return CMD_FAILURE;
+}
+
index 83c7320168eef5a8ca4cf68baaa6c129bd98dd0d..38726d9f5b4827661940d8500e9294a85b785d79 100644 (file)
@@ -174,6 +174,16 @@ msg_location_merge (struct msg_location **dstp, const struct msg_location *src)
     dst->end = src->end;
 }
 
+struct msg_location *
+msg_location_merged (const struct msg_location *a,
+                     const struct msg_location *b)
+{
+  struct msg_location *new = msg_location_dup (a);
+  if (b)
+    msg_location_merge (&new, b);
+  return new;
+}
+
 struct msg_location *
 msg_location_dup (const struct msg_location *src)
 {
index 813febe82a07a3906315937999a8886cc05d6fd0..11e5b9d98eeda0694180836d8149c71ee2d24055 100644 (file)
@@ -118,6 +118,8 @@ struct msg_location *msg_location_dup (const struct msg_location *);
 void msg_location_remove_columns (struct msg_location *);
 
 void msg_location_merge (struct msg_location **, const struct msg_location *);
+struct msg_location *msg_location_merged (const struct msg_location *,
+                                          const struct msg_location *);
 
 bool msg_location_is_empty (const struct msg_location *);
 void msg_location_format (const struct msg_location *, struct string *);
index f9bea8fa51cca393a6141ccccd1e043d15d73bd3..24f3e5bc650393b44ab30cfafbc2d6b3654a5999 100644 (file)
@@ -398,6 +398,7 @@ TESTSUITE_AT = \
        tests/language/stats/autorecode.at \
        tests/language/stats/correlations.at \
        tests/language/stats/crosstabs.at \
+       tests/language/stats/ctables.at \
        tests/language/stats/descriptives.at \
        tests/language/stats/examine.at \
        tests/language/stats/graph.at \
diff --git a/tests/language/stats/ctables.at b/tests/language/stats/ctables.at
new file mode 100644 (file)
index 0000000..e19007e
--- /dev/null
@@ -0,0 +1,862 @@
+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