feed: copy-edit the special missings post

The LinkedIn opener did not parse - "A SAS numeric missing is not a lone wolf.
It is 28." - and reading the rest of the post and its LinkedIn version together
turned up a further set of style defects:

- the article opener made the missing value the wolf, and padded the count
- "All numeric values means numeric; all strings means character" was clumsy
- procedure and function names were lowercase in places (proc means, cats,
  options MISSING), and "and friends" was too casual for a list of procedures
- "gotcha" and "harmless" undersold the points they introduced
- "One thing worth knowing" opened two separate paragraphs
- "a value ... and as a value with its own place" repeated itself, in both the
  article and the LinkedIn version
- the adapter bullet list mixed trailing periods with none
- the LinkedIn list was split in two by a stray blank line, and "a physical
  constraint" did not say which constraint
- "the most common of them" echoed the "28 of them" in the line above

No claims changed - the range-rule behaviour, the period, the primary key and
the strict dropdown all read as they did.

content/feed/sas-special-missings/index.md

@@ -1,6 +1,6 @@
 ---
 title: '28 Ways to Be Missing in SAS'
-description: A SAS numeric missing is not a lone wolf - there are 28 of them, and Data Controller has handled all of them since v4. How they work, and what the validation rules do with them.
+description: A SAS numeric missing is not a lone wolf - there are 28 of them, and Data Controller has supported all of them since v4. How they work, and what the validation rules do with them.
 date: '2026-09-22 09:00:00'
 author: 'Allan Bowe'
 authorLink: https://www.linkedin.com/in/allanbowe/
@@ -12,19 +12,19 @@ previewImg: './cover.jpeg'
 
 # 28 Ways to Be Missing in SAS
 
-A numeric missing value in SAS is not a lone wolf. The ordinary missing (`.`) is one of **28** distinct missing values available for a numeric variable - the other 27 are written with a single character, the letters `A` to `Z` or an underscore (`._`).
+A SAS numeric missing is not a lone wolf: the ordinary missing (`.`) is one of **28** distinct missing values a numeric variable can hold. The other 27 are written with a single character - the letters `A` to `Z`, or an underscore (`._`).
 
-They exist because "missing" is usually not the whole story. A survey question that was never reached, a reading that was illegible, a value the respondent refused to give - in a well run process those are different facts, and a lone `.` throws the difference away. Special missings record *why* the value is missing.
+They exist because "missing" is usually not the whole story. A survey question that was never reached, a reading that was illegible, a value the respondent refused to give - in a well-run process those are different facts, and a lone `.` throws the difference away. Special missings record *why* the value is missing.
 
 ## They are numbers, not text
 
 - Arithmetic on them yields missing - `.A + 1` is `.`
-- `proc means`, `proc summary` and friends exclude them, exactly as they exclude `.`
+- `PROC MEANS`, `PROC SUMMARY` and the other summarisation procedures exclude them, exactly as they exclude `.`
 - They sort below every non-missing number, in the order `._`, then `.`, then `.A` to `.Z`
-- The `NMISS()` and `CMISS()` functions count them as missing
-- Converting one to text drops the period - `cats(.A)` is the string `A`
+- `NMISS()` and `CMISS()` count them as missing
+- Converting one to text drops the period - `CATS(.A)` is the string `A`
 
-A display gotcha worth knowing: a regular missing prints as `.`, unless `options MISSING=` changes that character - set it to blank and a regular missing renders as an empty cell. The option affects only the regular missing; `._` and `.A`-`.Z` always print as their own letter. So a blank cell in a SAS listing is still unambiguously a regular missing, and a lone letter is still a special one. Data Controller itself is unaffected either way - it sends a regular missing to the browser as `null` and a special missing as its letter.
+One display detail is worth knowing: a regular missing prints as `.`, unless `OPTIONS MISSING=` changes that character - set it to blank and a regular missing renders as an empty cell. The option affects only the regular missing; `._` and `.A`-`.Z` always print as their own letter. So a blank cell in a SAS listing is still unambiguously a regular missing, and a lone letter is still a special one. Data Controller itself is unaffected either way - it sends a regular missing to the browser as `null` and a special missing as its letter.
 
 In a SAS dataset they are written with a leading period (`.A`, `.B` ... `._`). In Data Controller you type the letter or the underscore, with or without that period - `.a` and `a` are the same missing - and the letter is not case sensitive. Two letters, or a letter mixed with a number, are refused rather than guessed.
 
@@ -34,11 +34,11 @@ There is one cell where the letter cannot be typed at all. A numeric column that
 
 The Data Controller frontend and the SAS backend exchange data as JSON, and JSON has no way to express a letter as a numeric value - `A` is a string. The conversion is handled in the open source [SASjs Adapter](https://github.com/sasjs/adapter#variable-types):
 
-- The adapter infers each column's SAS type from the values it is given. All numeric values means numeric; all strings means character; and a column holding a single character (`a`-`z`, `_` or `.`) alongside numeric values is numeric, with the lone characters written to SAS as special missings.
+- The adapter infers each column's SAS type from the values it is given. All numeric values mean a numeric column, all strings mean a character column, and a column holding a single character (`a`-`z`, `_` or `.`) alongside numeric values is numeric, with the lone characters written to SAS as special missings.
 - `null` becomes `.` or an empty string, according to the type derived for that column.
 - Two cases cannot be inferred from the values alone: a numeric column containing *only* special missings looks like a single character column, and a character column containing only nulls looks numeric. For those, the adapter accepts an explicit format for the column - and Data Controller sends one automatically, because it already knows each column's SAS format from the metadata returned by the backend.
-- A value that is neither a number nor a single valid character is refused rather than guessed - `aaaa`, or `!` in a numeric column
-- A lone `.` is accepted as another way of typing the regular missing
+- A value that is neither a number nor a single valid character is refused rather than guessed - `aaaa`, or `!` in a numeric column.
+- A lone `.` is accepted as another way of typing the regular missing.
 
 There is nothing to configure. Special missings are available by default, for numeric cells - a date, datetime or time formatted column aside, since those edit through a date picker.
 
@@ -52,9 +52,9 @@ These are Data Controller's own rules, configured per column in the `MPE_VALIDAT
 - `HARDREGEX` - checked against the pattern like any other value; unlike blanks and the plain `.`, special missings are **not** exempt, so a numeric column that carries them needs a pattern which allows for a single letter
 - `SOFTREGEX` - the same check, but a failure is only a warning rather than a block, and it is ignored entirely if the column also has a `HARDREGEX` rule
 - `SOFTSELECT` / `HARDSELECT` - both support them. The dropdown lists a special missing as a bare letter alongside the ordinary values, and a hard rule then accepts it like any other listed value - it still rejects a value that is not in the list
-- `ROUND` - harmless. It only rounds values that are numbers, so a special missing is left exactly as it was typed
+- `ROUND` - no effect. It only rounds values that are numbers, so a special missing is left as it was typed
 
-The range rules compare in the order SAS itself uses, which is what makes them interesting here. SAS puts every missing below every non-missing value, and orders the missing values among themselves: `._` is the lowest, then the regular missing, then `.A` through `.Z`. So a range can be written in special missings and mean exactly what SAS would mean by it:
+The range rules compare in the order SAS itself uses, which is what lets a range be written in special missings. SAS puts every missing below every non-missing value, and orders the missing values among themselves: `._` is the lowest, then the regular missing, then `.A` through `.Z`. A range therefore means exactly what SAS would mean by it:
 
 - `MINVAL .A` with `MAXVAL .C` accepts `.B` and rejects `.D`, and a blank - the regular missing - fails that floor because it sorts below `.A`
 - a number sits above every missing, so it passes a floor of `.A` and fails a ceiling of `.C`
@@ -65,11 +65,11 @@ A formula is the one case where a special missing genuinely does not work:
 
 - `HARDFORMULA` / `SOFTFORMULA` - a formula that reads a special-missing cell does not compute; the grid's spreadsheet engine returns `#VALUE!` for that row, where the plain `.` contributes 0
 
-`CASE` (`UPCASE` / `LOWCASE`) is a character rule and does not come into it: SAS hands the browser a special missing as an uppercase letter, so there is no case to enforce, and a `CASE` rule on a numeric column would reject the column's numbers rather than the missing.
+`CASE` (`UPCASE` / `LOWCASE`) is a character rule, so it does not apply: SAS hands the browser a special missing as an uppercase letter, so there is no case to enforce, and a `CASE` rule on a numeric column would reject the column's numbers rather than the missing.
 
-One thing worth knowing about the regex rules: although the pattern is written in SAS PRX syntax, the check itself runs in the browser - SAS only parses the pattern (`PRXPARSE`) when the rule is saved - so the two engines can disagree on exotic patterns, and SAS pads a numeric-to-character conversion, so a pattern re-used in SAS needs `strip()` for an anchored match.
+Worth knowing about the regex rules: although the pattern is written in SAS PRX syntax, the check itself runs in the browser - SAS only parses the pattern (`PRXPARSE`) when the rule is saved - so the two engines can disagree on exotic patterns, and SAS pads a numeric-to-character conversion, so a pattern re-used in SAS needs `strip()` for an anchored match.
 
-In short, a special missing counts as a value for the pattern and dropdown rules, and as a value with its own place in the order for the range rules: it sits below every number, so a numeric minimum rejects it and a numeric maximum accepts it, while a range written in special missings is decided among the missing values themselves.
+In short, a special missing counts as a value for the pattern and dropdown rules, and takes its own place in the order for the range rules: it sits below every number, so a numeric minimum rejects it and a numeric maximum accepts it, while a range written in special missings is decided among the missing values themselves.
 
 ## See it in action
 
@@ -84,9 +84,9 @@ LinkedIn version of this post - publish it with the "Special Missings in Data
 Controller" video attached. Kept in sync with the copy above: same points, same
 claims, same order.
 
-A SAS numeric missing is not a lone wolf. It is 28.
+A SAS numeric missing is not a lone wolf. There are 28 of them.
 
-The ordinary missing (.) is just the most common of them. The other 27 are single characters - the letters A to Z, or an underscore (._) - and they let you record WHY a value is missing: the question was never reached, the reading was illegible, the respondent refused.
+The ordinary missing (.) is the best known of the 28. The other 27 are single characters - the letters A to Z, or an underscore (._) - and they let you record WHY a value is missing: the question was never reached, the reading was illegible, the respondent refused.
 
 They are real numeric values, not text:
 
@@ -94,7 +94,7 @@ They are real numeric values, not text:
 - PROC MEANS excludes them, like any other missing
 - they sort below every number: ._ then . then .A to .Z
 - NMISS() and CMISS() count them as missing
-- a regular missing prints as . unless options MISSING changes it - and that option never touches a special missing
+- a regular missing prints as . unless OPTIONS MISSING= changes it - and that option never touches a special missing
 
 The hard part is every tool that is not SAS. JSON has no way to say "this number is a letter" - A is just a string. So a value that is perfectly legal in a SAS dataset quietly breaks in the browser, in Excel, in an API.
 
@@ -102,22 +102,21 @@ We solved that in the open source SASjs Adapter, and it has been in Data Control
 
 - the adapter infers the column type from the values, so a column of numbers that also holds a lone letter is written to SAS as numeric, with the letter as a special missing
 - where the type cannot be inferred - a numeric column holding ONLY special missings - Data Controller passes the column format explicitly
-- you type the letter or the underscore, with or without the period: a, .a, _, ._, and case does not matter
+- you type the letter or the underscore, with or without the period (a, .a, _, ._), and case does not matter
 - one exception: a date, datetime or time formatted numeric column edits through a date picker, which takes only a date
 
 How they behave in Data Controller's validation rules:
 
-- NOTNULL rejects one: a special missing is a missing value, so it fails the rule and a physical constraint. A primary key column is NOT NULL whether or not a rule is configured
+- NOTNULL rejects one: a special missing is a missing value, so it fails the rule, and a physical NOT NULL constraint on the target table rejects it too. A primary key column is NOT NULL whether or not a rule is configured
 - HARDREGEX checks it against the pattern, unlike blanks and plain .
 - SOFTREGEX warns instead of blocking (and is ignored if the column also has a HARDREGEX)
 - SOFTSELECT and HARDSELECT both support them - the dropdown lists the missing as a bare letter, and a hard rule accepts it like any other listed value
 - ROUND leaves it alone, because it only rounds numbers
-
 - a HARDFORMULA/SOFTFORMULA that reads a special-missing cell returns #VALUE! rather than a number
 
 The range rules compare in SAS's own order, so a range can be written in special missings: MINVAL .A with MAXVAL .C accepts .B and rejects .D. A missing sorts below every number, so it fails a numeric MINVAL and passes a numeric MAXVAL; a number sits above every missing.
 
-In short: a value for the pattern and dropdown rules, and a value with its own place in the order for the range rules - below every number, so a numeric minimum rejects it and a numeric maximum accepts it.
+In short: a value for the pattern and dropdown rules, and its own place in the order for the range rules - below every number, so a numeric minimum rejects it and a numeric maximum accepts it.
 
 The video shows the whole cycle - entering them, the rejections, submit, approve, and the DIFF, including a range written in special missings.