1 @c PSPP - a program for statistical analysis.
2 @c Copyright (C) 2017 Free Software Foundation, Inc.
3 @c Permission is granted to copy, distribute and/or modify this document
4 @c under the terms of the GNU Free Documentation License, Version 1.3
5 @c or any later version published by the Free Software Foundation;
6 @c with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
7 @c A copy of the license is included in the section entitled "GNU
8 @c Free Documentation License".
10 @node Data Manipulation
11 @chapter Data transformations
12 @cindex transformations
14 The @pspp{} procedures examined in this chapter manipulate data and
15 prepare the active dataset for later analyses. They do not produce output,
19 * AGGREGATE:: Summarize multiple cases into a single case.
20 * AUTORECODE:: Automatic recoding of variables.
21 * COMPUTE:: Assigning a variable a calculated value.
22 * COUNT:: Counting variables with particular values.
23 * FLIP:: Exchange variables with cases.
24 * IF:: Conditionally assigning a calculated value.
25 * RECODE:: Mapping values from one set to another.
26 * SORT CASES:: Sort the active dataset.
35 OUTFILE=@{*,'@var{file_name}',@var{file_handle}@} [MODE=@{REPLACE, ADDVARIABLES@}]
40 /@var{dest_var}['@var{label}']@dots{}=@var{agr_func}(@var{src_vars}, @var{args}@dots{})@dots{}
43 @cmd{AGGREGATE} summarizes groups of cases into single cases.
44 Cases are divided into groups that have the same values for one or more
45 variables called @dfn{break variables}. Several functions are available
46 for summarizing case contents.
48 The @subcmd{OUTFILE} subcommand is required and must appear first. Specify a
49 system file or portable file by file name or file
50 handle (@pxref{File Handles}), or a dataset by its name
52 The aggregated cases are written to this file. If @samp{*} is
53 specified, then the aggregated cases replace the active dataset's data.
54 Use of @subcmd{OUTFILE} to write a portable file is a @pspp{} extension.
56 If @subcmd{OUTFILE=*} is given, then the subcommand @subcmd{MODE} may also be
58 The mode subcommand has two possible values: @subcmd{ADDVARIABLES} or @subcmd{REPLACE}.
59 In @subcmd{REPLACE} mode, the entire active dataset is replaced by a new dataset
60 which contains just the break variables and the destination varibles.
61 In this mode, the new file will contain as many cases as there are
62 unique combinations of the break variables.
63 In @subcmd{ADDVARIABLES} mode, the destination variables will be appended to
64 the existing active dataset.
65 Cases which have identical combinations of values in their break
66 variables, will receive identical values for the destination variables.
67 The number of cases in the active dataset will remain unchanged.
68 Note that if @subcmd{ADDVARIABLES} is specified, then the data @emph{must} be
69 sorted on the break variables.
71 By default, the active dataset will be sorted based on the break variables
72 before aggregation takes place. If the active dataset is already sorted
73 or otherwise grouped in terms of the break variables, specify
74 @subcmd{PRESORTED} to save time.
75 @subcmd{PRESORTED} is assumed if @subcmd{MODE=ADDVARIABLES} is used.
77 Specify @subcmd{DOCUMENT} to copy the documents from the active dataset into the
78 aggregate file (@pxref{DOCUMENT}). Otherwise, the aggregate file will
79 not contain any documents, even if the aggregate file replaces the
82 Normally, only a single case (for @subcmd{SD} and @subcmd{SD}., two cases) need be
83 non-missing in each group for the aggregate variable to be
84 non-missing. Specifying @subcmd{/MISSING=COLUMNWISE} inverts this behavior, so
85 that the aggregate variable becomes missing if any aggregated value is
88 If @subcmd{PRESORTED}, @subcmd{DOCUMENT}, or @subcmd{MISSING} are specified, they must appear
89 between @subcmd{OUTFILE} and @subcmd{BREAK}.
91 At least one break variable must be specified on @subcmd{BREAK}, a
92 required subcommand. The values of these variables are used to divide
93 the active dataset into groups to be summarized. In addition, at least
94 one @var{dest_var} must be specified.
96 One or more sets of aggregation variables must be specified. Each set
97 comprises a list of aggregation variables, an equals sign (@samp{=}),
98 the name of an aggregation function (see the list below), and a list
99 of source variables in parentheses. Some aggregation functions expect
100 additional arguments following the source variable names.
102 Aggregation variables typically are created with no variable label,
103 value labels, or missing values. Their default print and write
104 formats depend on the aggregation function used, with details given in
105 the table below. A variable label for an aggregation variable may be
106 specified just after the variable's name in the aggregation variable
109 Each set must have exactly as many source variables as aggregation
110 variables. Each aggregation variable receives the results of applying
111 the specified aggregation function to the corresponding source
112 variable. The @subcmd{MEAN}, @subcmd{MEDIAN}, @subcmd{SD}, and @subcmd{SUM}
113 aggregation functions may only be
114 applied to numeric variables. All the rest may be applied to numeric
115 and string variables.
117 The available aggregation functions are as follows:
120 @item @subcmd{FGT(@var{var_name}, @var{value})}
121 Fraction of values greater than the specified constant. The default
124 @item @subcmd{FIN(@var{var_name}, @var{low}, @var{high})}
125 Fraction of values within the specified inclusive range of constants.
126 The default format is F5.3.
128 @item @subcmd{FLT(@var{var_name}, @var{value})}
129 Fraction of values less than the specified constant. The default
132 @item @subcmd{FIRST(@var{var_name})}
133 First non-missing value in break group. The aggregation variable
134 receives the complete dictionary information from the source variable.
135 The sort performed by @cmd{AGGREGATE} (and by @cmd{SORT CASES}) is stable, so that
136 the first case with particular values for the break variables before
137 sorting will also be the first case in that break group after sorting.
139 @item @subcmd{FOUT(@var{var_name}, @var{low}, @var{high})}
140 Fraction of values strictly outside the specified range of constants.
141 The default format is F5.3.
143 @item @subcmd{LAST(@var{var_name})}
144 Last non-missing value in break group. The aggregation variable
145 receives the complete dictionary information from the source variable.
146 The sort performed by @cmd{AGGREGATE} (and by @cmd{SORT CASES}) is stable, so that
147 the last case with particular values for the break variables before
148 sorting will also be the last case in that break group after sorting.
150 @item @subcmd{MAX(@var{var_name})}
151 Maximum value. The aggregation variable receives the complete
152 dictionary information from the source variable.
154 @item @subcmd{MEAN(@var{var_name})}
155 Arithmetic mean. Limited to numeric values. The default format is
158 @item @subcmd{MEDIAN(@var{var_name})}
159 The median value. Limited to numeric values. The default format is F8.2.
161 @item @subcmd{MIN(@var{var_name})}
162 Minimum value. The aggregation variable receives the complete
163 dictionary information from the source variable.
165 @item @subcmd{N(@var{var_name})}
166 Number of non-missing values. The default format is F7.0 if weighting
167 is not enabled, F8.2 if it is (@pxref{WEIGHT}).
170 Number of cases aggregated to form this group. The default format is
171 F7.0 if weighting is not enabled, F8.2 if it is (@pxref{WEIGHT}).
173 @item @subcmd{NMISS(@var{var_name})}
174 Number of missing values. The default format is F7.0 if weighting is
175 not enabled, F8.2 if it is (@pxref{WEIGHT}).
177 @item @subcmd{NU(@var{var_name})}
178 Number of non-missing values. Each case is considered to have a weight
179 of 1, regardless of the current weighting variable (@pxref{WEIGHT}).
180 The default format is F7.0.
183 Number of cases aggregated to form this group. Each case is considered
184 to have a weight of 1, regardless of the current weighting variable.
185 The default format is F7.0.
187 @item @subcmd{NUMISS(@var{var_name})}
188 Number of missing values. Each case is considered to have a weight of
189 1, regardless of the current weighting variable. The default format is F7.0.
191 @item @subcmd{PGT(@var{var_name}, @var{value})}
192 Percentage between 0 and 100 of values greater than the specified
193 constant. The default format is F5.1.
195 @item @subcmd{PIN(@var{var_name}, @var{low}, @var{high})}
196 Percentage of values within the specified inclusive range of
197 constants. The default format is F5.1.
199 @item @subcmd{PLT(@var{var_name}, @var{value})}
200 Percentage of values less than the specified constant. The default
203 @item @subcmd{POUT(@var{var_name}, @var{low}, @var{high})}
204 Percentage of values strictly outside the specified range of
205 constants. The default format is F5.1.
207 @item @subcmd{SD(@var{var_name})}
208 Standard deviation of the mean. Limited to numeric values. The
209 default format is F8.2.
211 @item @subcmd{SUM(@var{var_name})}
212 Sum. Limited to numeric values. The default format is F8.2.
215 Aggregation functions compare string values in terms of internal
217 On most modern computers, this is @acronym{ASCII} or a superset thereof.
219 The aggregation functions listed above exclude all user-missing values
220 from calculations. To include user-missing values, insert a period
221 (@samp{.}) at the end of the function name. (e.g.@: @samp{SUM.}).
222 (Be aware that specifying such a function as the last token on a line
223 will cause the period to be interpreted as the end of the command.)
225 @cmd{AGGREGATE} both ignores and cancels the current @cmd{SPLIT FILE}
226 settings (@pxref{SPLIT FILE}).
233 AUTORECODE VARIABLES=@var{src_vars} INTO @var{dest_vars}
237 [ /BLANK = @{VALID, MISSING@} ]
240 The @cmd{AUTORECODE} procedure considers the @var{n} values that a variable
241 takes on and maps them onto values 1@dots{}@var{n} on a new numeric
244 Subcommand @subcmd{VARIABLES} is the only required subcommand and must come
245 first. Specify @subcmd{VARIABLES}, an equals sign (@samp{=}), a list of source
246 variables, @subcmd{INTO}, and a list of target variables. There must the same
247 number of source and target variables. The target variables must not
250 @cmd{AUTORECODE} ordinarily assigns each increasing non-missing value
251 of a source variable (for a string, this is based on character code
252 comparisons) to consecutive values of its target variable. For
253 example, the smallest non-missing value of the source variable is
254 recoded to value 1, the next smallest to 2, and so on. If the source
255 variable has user-missing values, they are recoded to
256 consecutive values just above the non-missing values. For example, if
257 a source variables has seven distinct non-missing values, then the
258 smallest missing value would be recoded to 8, the next smallest to 9,
261 Use @subcmd{DESCENDING} to reverse the sort order for non-missing
262 values, so that the largest non-missing value is recoded to 1, the
263 second-largest to 2, and so on. Even with @subcmd{DESCENDING},
264 user-missing values are still recoded in ascending order just above
265 the non-missing values.
267 The system-missing value is always recoded into the system-missing
268 variable in target variables.
270 If a source value has a value label, then that value label is retained
271 for the new value in the target variable. Otherwise, the source value
272 itself becomes each new value's label.
274 @subcmd{PRINT} is currently ignored.
276 The @subcmd{GROUP} subcommand is relevant only if more than one variable is to be
277 recoded. It causes a single mapping between source and target values to
278 be used, instead of one map per variable. With @subcmd{GROUP},
279 user-missing values are taken from the first source variable that has
280 any user-missing values.
282 If @subcmd{/BLANK=MISSING} is given, then string variables which contain only
283 whitespace are recoded as SYSMIS. If @subcmd{/BLANK=VALID} is given then they
284 will be allocated a value like any other. @subcmd{/BLANK} is not relevant
285 to numeric values. @subcmd{/BLANK=VALID} is the default.
287 @cmd{AUTORECODE} is a procedure. It causes the data to be read.
294 COMPUTE @var{variable} = @var{expression}.
298 COMPUTE vector(@var{index}) = @var{expression}.
301 @cmd{COMPUTE} assigns the value of an expression to a target
302 variable. For each case, the expression is evaluated and its value
303 assigned to the target variable. Numeric and string
304 variables may be assigned. When a string expression's width differs
305 from the target variable's width, the string result of the expression
306 is truncated or padded with spaces on the right as necessary. The
307 expression and variable types must match.
309 For numeric variables only, the target variable need not already
310 exist. Numeric variables created by @cmd{COMPUTE} are assigned an
311 @code{F8.2} output format. String variables must be declared before
312 they can be used as targets for @cmd{COMPUTE}.
314 The target variable may be specified as an element of a vector
315 (@pxref{VECTOR}). In this case, an expression @var{index} must be
316 specified in parentheses following the vector name. The expression @var{index}
317 must evaluate to a numeric value that, after rounding down
318 to the nearest integer, is a valid index for the named vector.
320 Using @cmd{COMPUTE} to assign to a variable specified on @cmd{LEAVE}
321 (@pxref{LEAVE}) resets the variable's left state. Therefore,
322 @code{LEAVE} should be specified following @cmd{COMPUTE}, not before.
324 @cmd{COMPUTE} is a transformation. It does not cause the active dataset to be
327 When @cmd{COMPUTE} is specified following @cmd{TEMPORARY}
328 (@pxref{TEMPORARY}), the @cmd{LAG} function may not be used
336 COUNT @var{var_name} = @var{var}@dots{} (@var{value}@dots{})
337 [/@var{var_name} = @var{var}@dots{} (@var{value}@dots{})]@dots{}
339 Each @var{value} takes one of the following forms:
342 @var{num1} THRU @var{num2}
345 where @var{num1} is a numeric expression or the words @subcmd{LO} or @subcmd{LOWEST}
346 and @var{num2} is a numeric expression or @subcmd{HI} or @subcmd{HIGHEST}.
349 @cmd{COUNT} creates or replaces a numeric @dfn{target} variable that
350 counts the occurrence of a @dfn{criterion} value or set of values over
351 one or more @dfn{test} variables for each case.
353 The target variable values are always nonnegative integers. They are
354 never missing. The target variable is assigned an F8.2 output format.
355 @xref{Input and Output Formats}. Any variables, including
356 string variables, may be test variables.
358 User-missing values of test variables are treated just like any other
359 values. They are @strong{not} treated as system-missing values.
360 User-missing values that are criterion values or inside ranges of
361 criterion values are counted as any other values. However (for numeric
362 variables), keyword @subcmd{MISSING} may be used to refer to all system-
363 and user-missing values.
365 @cmd{COUNT} target variables are assigned values in the order
366 specified. In the command @subcmd{COUNT @var{A}=@var{A} @var{B}(1) /@var{B}=@var{A} @var{B}(2).}, the
367 following actions occur:
371 The number of occurrences of 1 between @var{A} and @var{B} is counted.
374 @var{A} is assigned this value.
377 The number of occurrences of 1 between @var{B} and the @strong{new}
378 value of @var{A} is counted.
381 @var{B} is assigned this value.
384 Despite this ordering, all @cmd{COUNT} criterion variables must exist
385 before the procedure is executed---they may not be created as target
386 variables earlier in the command! Break such a command into two
389 The examples below may help to clarify.
393 Assuming @code{Q0}, @code{Q2}, @dots{}, @code{Q9} are numeric variables,
394 the following commands:
398 Count the number of times the value 1 occurs through these variables
399 for each case and assigns the count to variable @code{QCOUNT}.
402 Print out the total number of times the value 1 occurs throughout
403 @emph{all} cases using @cmd{DESCRIPTIVES}. @xref{DESCRIPTIVES}, for
408 COUNT QCOUNT=Q0 TO Q9(1).
409 DESCRIPTIVES QCOUNT /STATISTICS=SUM.
413 Given these same variables, the following commands:
417 Count the number of valid values of these variables for each case and
418 assigns the count to variable @code{QVALID}.
421 Multiplies each value of @code{QVALID} by 10 to obtain a percentage of
422 valid values, using @cmd{COMPUTE}. @xref{COMPUTE}, for details.
425 Print out the percentage of valid values across all cases, using
426 @cmd{DESCRIPTIVES}. @xref{DESCRIPTIVES}, for details.
430 COUNT QVALID=Q0 TO Q9 (LO THRU HI).
431 COMPUTE QVALID=QVALID*10.
432 DESCRIPTIVES QVALID /STATISTICS=MEAN.
441 FLIP /VARIABLES=@var{var_list} /NEWNAMES=@var{var_name}.
444 @cmd{FLIP} transposes rows and columns in the active dataset. It
445 causes cases to be swapped with variables, and vice versa.
447 All variables in the transposed active dataset are numeric. String
448 variables take on the system-missing value in the transposed file.
450 @subcmd{N} subcommands are required. If specified, the @subcmd{VARIABLES} subcommand
451 selects variables to be transformed into cases, and variables not
452 specified are discarded. If the @subcmd{VARIABLES} subcommand is omitted, all
453 variables are selected for transposition.
455 The variables specified by @subcmd{NEWNAMES}, which must be a
457 used to give names to the variables created by @cmd{FLIP}. Only the
458 first 8 characters of the variable are used. If
459 @subcmd{NEWNAMES} is not
460 specified then the default is a variable named CASE_LBL, if it exists.
461 If it does not then the variables created by @cmd{FLIP} are named VAR000
462 through VAR999, then VAR1000, VAR1001, and so on.
464 When a @subcmd{NEWNAMES} variable is available, the names must be canonicalized
465 before becoming variable names. Invalid characters are replaced by
466 letter @samp{V} in the first position, or by @samp{_} in subsequent
467 positions. If the name thus generated is not unique, then numeric
468 extensions are added, starting with 1, until a unique name is found or
469 there are no remaining possibilities. If the latter occurs then the
470 @cmd{FLIP} operation aborts.
472 The resultant dictionary contains a CASE_LBL variable, a string
473 variable of width 8, which stores the names of the variables in the
474 dictionary before the transposition. Variables names longer than 8
475 characters are truncated. If the active dataset is subsequently
476 transposed using @cmd{FLIP}, this variable can be used to recreate the
477 original variable names.
479 @cmd{FLIP} honors @cmd{N OF CASES} (@pxref{N OF CASES}). It ignores
480 @cmd{TEMPORARY} (@pxref{TEMPORARY}), so that ``temporary''
481 transformations become permanent.
488 IF @var{condition} @var{variable}=@var{expression}.
492 IF @var{condition} vector(@var{index})=@var{expression}.
495 The @cmd{IF} transformation conditionally assigns the value of a target
496 expression to a target variable, based on the truth of a test
499 Specify a boolean-valued expression (@pxref{Expressions}) to be tested
500 following the @cmd{IF} keyword. This expression is evaluated for each case.
501 If the value is true, then the value of the expression is computed and
502 assigned to the specified variable. If the value is false or missing,
503 nothing is done. Numeric and string variables may be
504 assigned. When a string expression's width differs from the target
505 variable's width, the string result of the expression is truncated or
506 padded with spaces on the right as necessary. The expression and
507 variable types must match.
509 The target variable may be specified as an element of a vector
510 (@pxref{VECTOR}). In this case, a vector index expression must be
511 specified in parentheses following the vector name. The index
512 expression must evaluate to a numeric value that, after rounding down
513 to the nearest integer, is a valid index for the named vector.
515 Using @cmd{IF} to assign to a variable specified on @cmd{LEAVE}
516 (@pxref{LEAVE}) resets the variable's left state. Therefore,
517 @code{LEAVE} should be specified following @cmd{IF}, not before.
519 When @cmd{IF} is specified following @cmd{TEMPORARY}
520 (@pxref{TEMPORARY}), the @cmd{LAG} function may not be used
527 The @cmd{RECODE} command is used to transform existing values into other,
528 user specified values.
532 RECODE @var{src_vars}
533 (@var{src_value} @var{src_value} @dots{} = @var{dest_value})
534 (@var{src_value} @var{src_value} @dots{} = @var{dest_value})
535 (@var{src_value} @var{src_value} @dots{} = @var{dest_value}) @dots{}
536 [INTO @var{dest_vars}].
539 Following the @cmd{RECODE} keyword itself comes @var{src_vars} which is a list
540 of variables whose values are to be transformed.
541 These variables may be string variables or they may be numeric.
542 However the list must be homogeneous; you may not mix string variables and
543 numeric variables in the same recoding.
545 After the list of source variables, there should be one or more @dfn{mappings}.
546 Each mapping is enclosed in parentheses, and contains the source values and
547 a destination value separated by a single @samp{=}.
548 The source values are used to specify the values in the dataset which
549 need to change, and the destination value specifies the new value
550 to which they should be changed.
551 Each @var{src_value} may take one of the following forms:
554 If the source variables are numeric then @var{src_value} may be a literal
557 If the source variables are string variables then @var{src_value} may be a
558 literal string (like all strings, enclosed in single or double quotes).
559 @item @var{num1} THRU @var{num2}
560 This form is valid only when the source variables are numeric.
561 It specifies all values in the range between @var{num1} and @var{num2},
562 including both endpoints of the range. By convention, @var{num1}
563 should be less than @var{num2}.
564 Open-ended ranges may be specified using @samp{LO} or @samp{LOWEST}
566 or @samp{HI} or @samp{HIGHEST} for @var{num2}.
568 The literal keyword @samp{MISSING} matches both system missing and user
570 It is valid for both numeric and string variables.
572 The literal keyword @samp{SYSMIS} matches system missing
574 It is valid for both numeric variables only.
576 The @samp{ELSE} keyword may be used to match any values which are
577 not matched by any other @var{src_value} appearing in the command.
578 If this keyword appears, it should be used in the last mapping of the
582 After the source variables comes an @samp{=} and then the @var{dest_value}.
583 The @var{dest_value} may take any of the following forms:
586 A literal numeric value to which the source values should be changed.
587 This implies the destination variable must be numeric.
589 A literal string value (enclosed in quotation marks) to which the source
590 values should be changed.
591 This implies the destination variable must be a string variable.
593 The keyword @samp{SYSMIS} changes the value to the system missing value.
594 This implies the destination variable must be numeric.
596 The special keyword @samp{COPY} means that the source value should not be
598 copied directly to the destination value.
599 This is meaningful only if @samp{INTO @var{dest_vars}} is specified.
602 Mappings are considered from left to right.
603 Therefore, if a value is matched by a @var{src_value} from more than
604 one mapping, the first (leftmost) mapping which matches will be considered.
605 Any subsequent matches will be ignored.
607 The clause @samp{INTO @var{dest_vars}} is optional.
608 The behaviour of the command is slightly different depending on whether it
611 If @samp{INTO @var{dest_vars}} does not appear, then values will be recoded
613 This means that the recoded values are written back to the
614 source variables from whence the original values came.
615 In this case, the @var{dest_value} for every mapping must imply a value which
616 has the same type as the @var{src_value}.
617 For example, if the source value is a string value, it is not permissible for
618 @var{dest_value} to be @samp{SYSMIS} or another forms which implies a numeric
620 It is also not permissible for @var{dest_value} to be longer than the width
621 of the source variable.
623 The following example two numeric variables @var{x} and @var{y} are recoded
625 Zero is recoded to 99, the values 1 to 10 inclusive are unchanged,
626 values 1000 and higher are recoded to the system-missing value and all other
627 values are changed to 999:
629 recode @var{x} @var{y}
632 (1000 THRU HIGHEST = SYSMIS)
636 If @samp{INTO @var{dest_vars}} is given, then recoded values are written
637 into the variables specified in @var{dest_vars}, which must therefore
638 contain a list of valid variable names.
639 The number of variables in @var{dest_vars} must be the same as the number
640 of variables in @var{src_vars}
641 and the respective order of the variables in @var{dest_vars} corresponds to
642 the order of @var{src_vars}.
643 That is to say, recoded values whose
644 original value came from the @var{n}th variable in @var{src_vars} will be
645 placed into the @var{n}th variable in @var{dest_vars}.
646 The source variables will be unchanged.
647 If any mapping implies a string as its destination value, then the respective
648 destination variable must already exist, or
649 have been declared using @cmd{STRING} or another transformation.
650 Numeric variables however will be automatically created if they don't already
652 The following example deals with two source variables, @var{a} and @var{b}
653 which contain string values. Hence there are two destination variables
654 @var{v1} and @var{v2}.
655 Any cases where @var{a} or @var{b} contain the values @samp{apple},
656 @samp{pear} or @samp{pomegranate} will result in @var{v1} or @var{v2} being
657 filled with the string @samp{fruit} whilst cases with
658 @samp{tomato}, @samp{lettuce} or @samp{carrot} will result in @samp{vegetable}.
659 Any other values will produce the result @samp{unknown}:
661 string @var{v1} (a20).
662 string @var{v2} (a20).
664 recode @var{a} @var{b}
665 ("apple" "pear" "pomegranate" = "fruit")
666 ("tomato" "lettuce" "carrot" = "vegetable")
668 into @var{v1} @var{v2}.
671 There is one very special mapping, not mentioned above.
672 If the source variable is a string variable
673 then a mapping may be specified as @samp{(CONVERT)}.
674 This mapping, if it appears must be the last mapping given and
675 the @samp{INTO @var{dest_vars}} clause must also be given and
676 must not refer to a string variable.
677 @samp{CONVERT} causes a number specified as a string to
678 be converted to a numeric value.
679 For example it will convert the string @samp{"3"} into the numeric
680 value 3 (note that it will not convert @samp{three} into 3).
681 If the string cannot be parsed as a number, then the system-missing value
683 In the following example, cases where the value of @var{x} (a string variable)
684 is the empty string, are recoded to 999 and all others are converted to the
685 numeric equivalent of the input value. The results are placed into the
686 numeric variable @var{y}:
694 It is possible to specify multiple recodings on a single command.
695 Introduce additional recodings with a slash (@samp{/}) to
696 separate them from the previous recodings:
699 @var{a} (2 = 22) (else = 99)
700 /@var{b} (1 = 3) into @var{z}
703 @noindent Here we have two recodings. The first affects the source variable
704 @var{a} and recodes in-place the value 2 into 22 and all other values to 99.
705 The second recoding copies the values of @var{b} into the variable @var{z},
706 changing any instances of 1 into 3.
713 SORT CASES BY @var{var_list}[(@{D|A@}] [ @var{var_list}[(@{D|A@}] ] ...
716 @cmd{SORT CASES} sorts the active dataset by the values of one or more
719 Specify @subcmd{BY} and a list of variables to sort by. By default, variables
720 are sorted in ascending order. To override sort order, specify @subcmd{(D)} or
721 @subcmd{(DOWN)} after a list of variables to get descending order, or @subcmd{(A)} or @subcmd{(UP)}
722 for ascending order. These apply to all the listed variables
723 up until the preceding @subcmd{(A)}, @subcmd{(D)}, @subcmd{(UP)} or @subcmd{(DOWN)}.
725 The sort algorithms used by @cmd{SORT CASES} are stable. That is,
726 records that have equal values of the sort variables will have the
727 same relative order before and after sorting. As a special case,
728 re-sorting an already sorted file will not affect the ordering of
731 @cmd{SORT CASES} is a procedure. It causes the data to be read.
733 @cmd{SORT CASES} attempts to sort the entire active dataset in main memory.
734 If workspace is exhausted, it falls back to a merge sort algorithm that
735 involves creates numerous temporary files.
737 @cmd{SORT CASES} may not be specified following @cmd{TEMPORARY}.