STATS_SPLIT_COLS – split selected columns by category values

What it does

Splits the columns chosen by colFilter into one column per group of colNameForSplit.

Every value stays on the row of its respondent; the rows of the other groups show ".". The block is as tall as the whole sample, so keep the cells below it free.

labels maps the values of colNameForSplit to group names: "1:male,2:female" or "male:1,female:2", ranges "low:1:3,high:3:". A value outside the labels goes to the group "_other". Empty labels — the labels of the column, if it has them.

The sign "." and text in a numeric column do not form a group.

Syntax

=STATS_SPLIT_COLS(columns, colNameForSplit, colFilter, labels)

Parameters

columns — required

Cell range with data, e.g., A1:D100 or A:D.

Usually the first row should contain column names.

You can also add labels as the first row and column names as the second row.

Labels should use formats like "male:1,female:2" or "low:1:3,mid:3:5,high:5:7".

Examples:

  • A1:D100 — use 4 columns
  • A1:C200 — use 3 columns
  • A:F — use 6 columns
  • A1:D100 where row 1 contains labels and row 2 contains column names — use labels from the sheet

If every non-empty cell of the first row holds at least two label rules ("low:1,high:2"), it is the labels row, and the next row holds the column names; an empty cell there is a column without labels.

One rule in a cell ("yes:1") is read as a name, so a header such as "T:1", "Ratio 1:2" or "Note:" stays the names row. Give such a column a second rule, or pass one label in the labels parameter, where one rule is valid.

If the first row contains ordinary text, it is treated as the column names row as before.

A number, a date or a checkbox in the names row is a name: 2025, 2025-01-01, TRUE.

Column names must be unique: two identical headers are an error "Duplicate column name: x".

Every column with values needs a name: an empty header cell over values is an error "The name of column 2 is empty: a column with values needs a name", even when colFilter does not select that column. A column with neither a name nor values (the empty right edge of a range such as A:Z) is dropped without an error.

Column names that start with "#" are reserved/unsupported in filters, because "#" is used for index-based colFilter rules (for example #1, #2-#5).

What counts as a number (the same in every function):

  • A column is numeric when it holds more numbers than text; with as many texts as numbers, or more, it is a text column.
  • Every cell is typed by itself: a number written as text ('10', '007') is the number, a checkbox is 1 (checked) or 0 (unchecked). The texts 'TRUE'/'FALSE' stay text.
  • A cell that does not match the type of its own column (text in a numeric column, a number in a text column) is missing for calculations and is counted in missing.
  • An empty cell is a missing answer; the sign "." means "not applicable" — it is not a missing answer, not a category and not counted in missing.
  • A text column with value labels (a labels row above the names) is analysed by the codes of its labels. A text column without labels is not analysed as numbers: lists of columns skip it with a note, tests on a pair of columns and models show an error.

An empty tail of the range (rows below the data) is dropped — only blank cells make it: a row of "." at the end stays and counts as not applicable, as in the middle. A column with neither a name nor values is dropped; a named empty column stays.

colNameForSplit — optional

Column name with categories for spliting.

Examples:

  • ageGroup
  • gender
  • status
colFilter — optional, default "*"

Comma-separated column selector.

Use names ("age,score"), negative rules ("-id,-note"), a regex ("/^q/"), or index rules ("#N", "#A-#B", "-#N", "-#A-#B").

Case-sensitive; flags are not supported.

A name that does not exist is an error: "Column nope does not exist" (excluding it, "-nope", is ignored). Empty — all columns ("*").

Examples:

  • "age,score" — Names only (include only "age" and "score")
  • "-id,-group" — Exclude some (include all except "id" and "group")
  • "/^q/" — Regex only (all starts with "q")
  • "#1,#3-#5" — Index include rules (first, and range 3..5)
  • "-#1,-#3-#4" — Index exclude rules (drop first and 3..4)
  • "age,#2-#4,-#3" — Mixed name/index rules with deterministic order
  • "age,/^q/,-q5" — Mixed (include age, all starts with "q" except "q5")
  • "/^x1{1,2}$/" — Regex with a comma inside: x1 and x11

Choose which columns from columns to use - a comma-separated string of rules.

⚙️ Four rule types (you can mix them):

  1. By name - exact header text (case-sensitive)
    • "age,score,total"
  2. Negative rules - exclude by name (prefix with -)
    • "-id,-notes" (include all except id and notes)
  3. Regex - a regular expression between slashes /.../
    • "/^q/" (all headers starting with q), "/(score|age)/", "/^x1{1,2}$/" (commas inside /.../ do not split the filter)
    • ❗— case-sensitive
    • ❗— flags are not supported.
  4. Index rules - position-based rules with #
    • "#1" (first selected column), "#2-#5" (range), "-#1", "-#2-#4"

"*" alone selects every column; it cannot be combined with other rules ("*,-id" is an error) — write "-id" instead.

Rules are applied in the written order, and the selected columns keep that order ("/^q/,-q5,age" puts age last).

Index rules count the columns of the range: "#1" is its first column.

A name that does not exist is an error: "Column nope does not exist" — also in colName, yName, steps, rowCol, colCol and colNameForSplit. Excluding a name that does not exist ("-nope") is ignored.

A filter that selects no column — a regex without a match ("/^Q/" where the columns are q1, q2), index rules past the end, exclusions that remove every column — is an error that names the filter and the columns of the range: colFilter "/^Q/" selects no columns (columns: q1, q2, t). Empty and "*" select every column.

In STATS_ANALYZE, a regex with brackets or | needs the new syntax: PEARSON('/(score|age)/').

A colFilter saved in Settings applies to every formula without its own filter: on a range without those columns the formula shows the error above.

# prefix is reserved for index syntax and is not treated as a column-name filter token.

colFilter applies to all expressions in query. It does not create separate groups per expression.

labels — optional

Groups for the values of a column: "label:value,label:value" for exact values, "label:min:max" for ranges.

A range is [min, max): min included, max not; an empty bound is open on its side ("high:3:" — 3 and above, "low::0" — every value below 0).

Spaces around the colon are not part of the label: "Never : 1" names Never, here and in a labels row above the names.

On a text column the value is the text of the cell ("male:m,female:f").

Examples:

  • "male:m,female:f" — text answers m and f named male and female
  • "low:1:3,high:3:" — ranges: 1 ≤ x < 3 is low, 3 and above is high
  • "good:1:3,normal:3:6,bad:6:11" — three ranges
  • "low::0,high:0:" — open bounds: negative values are low, 0 and above is high

Labels given here win over the labels of the column (a labels row above the names). Empty — the labels of the column, if it has them.

Groups are listed in the order of the labels. A value outside the labels goes to the group "_other", listed last.

STATS_FREQUENCIES shows the first part as the group name: write "label:value".

STATS_SPLIT_COLS takes both orders, "1:male" and "male:1", and names the columns {column}-{label}.

Without labels, groups follow SPSS: numbers ascending, text alphabetically. A text scale with a natural order (education levels, Likert words) needs labels to keep that order.

Examples

  • — the sample data (50 rows) all examples use
  • — x and x1 by gender: x-male, x1-male, x-female, x1-female (group by group) =STATS_SPLIT_COLS(Data!A1:T51, "gender", "x,x1","1:male,2:female")
  • — every column except gender =STATS_SPLIT_COLS(Data!A1:T51, "gender", "-gender","1:male,2:female")
  • — no labels: columns q1-group1, q1-group2, … =STATS_SPLIT_COLS(Data!A1:T51, "group", "/q/")

What the result contains

A 2D array: the first row holds the new column names, then one row per row of the source.

Column names: {column}-{label} with labels ("x-male"); without labels {column}-{value} for a text split column ("x-m") and {column}-{split column}{value} for a numeric one ("x-gender1").

Errors

A column name that does not exist: one cell "Column nope does not exist".

About STATS_SPLIT_COLS

STATS_SPLIT_COLS splits the selected columns into one column per group of another column — for example, the scores of men and women side by side. Use it when the scores are in one column and the group in another, and the next step needs one column per group. With labels "male:1,female:2" the new columns are named x-male and x-female; without labels, a numeric group column gives names like x-gender1, and a text one names like x-m.

Every value stays on the row of its respondent, and the rows of the other groups show "." (not applicable). The block is therefore as tall as the whole sample: keep the cells below it free. It recalculates by itself when new responses arrive from Google Forms.

Labels name exact values ("male:1" or "1:male" — both orders work) or ranges ("low:1:3,high:3:", min included, max not). A value outside the labels goes to the group "_other". Without labels, the labels row of the group column is used if it has one; otherwise groups follow SPSS: numbers ascending, text alphabetically.