diff --git a/docs/src/data/stan-example.json b/docs/src/data/stan-example.json
new file mode 100644
index 000000000..992b777f8
--- /dev/null
+++ b/docs/src/data/stan-example.json
@@ -0,0 +1,4 @@
+{
+ "shape": ["triangle", "square", "circle", "square", "triangle", "square", "triangle", "circle", "circle", "square"],
+ "rate": [9.8870, 0.0130, 2.9010, 7.4670, 8.5910, 9.5310, 5.8240, 4.2370, 8.3350, 8.2430]
+}
diff --git a/docs/src/shapes-of-data.md b/docs/src/shapes-of-data.md
index 491311211..9667bbd9c 100644
--- a/docs/src/shapes-of-data.md
+++ b/docs/src/shapes-of-data.md
@@ -474,3 +474,94 @@ output -- as any full transpose must.
Thanks to @Fravadona on [issue 321](https://github.com/johnkerl/miller/issues/321)
for the original version of this recipe.
+
+## Columns as JSON arrays
+
+Some downstream tools -- for example the [Stan](https://mc-stan.org/) modeling
+language -- want their input as a JSON object whose values are arrays, one
+array per column, rather than the more usual array-of-records shape:
+
+
+{
+ "shape": ["triangle", "square", "circle"],
+ "rate": [9.8870, 0.0130, 2.9010]
+}
+
+
+rather than
+
+
+[
+ {"shape": "triangle", "rate": 9.8870},
+ {"shape": "square", "rate": 0.0130},
+ {"shape": "circle", "rate": 2.9010}
+]
+
+
+There's no dedicated Miller file format for this -- it's just a particular
+shape of JSON, and the same [out-of-stream
+variable](reference-dsl-variables.md#out-of-stream-variables) technique from
+the transposing example above gets you there, keying by field name first and
+row number second (rather than the other way around). The
+[`arrayify`](reference-dsl-builtin-functions.md#arrayify) function turns the
+per-column maps (keyed `"1"`, `"2"`, ...) into real JSON arrays, and
+[`emit1`](reference-dsl-output-statements.md#emit1-and-emitemitpemitf) emits the
+whole thing as a single record rather than splitting it one-record-per-key
+the way plain `emit` would:
+
+
+mlr --icsv --ojson cut -f shape,rate then put -q '
+ for (k, v in $*) {
+ @output_record[k][NR] = v;
+ }
+ end {
+ emit1 arrayify(@output_record);
+ }
+' example.csv
+
+
+[
+{
+ "shape": ["triangle", "square", "circle", "square", "triangle", "square", "triangle", "circle", "circle", "square"],
+ "rate": [9.8870, 0.0130, 2.9010, 7.4670, 8.5910, 9.5310, 5.8240, 4.2370, 8.3350, 8.2430]
+}
+]
+
+
+To go the other way -- expanding column-arrays back into one record per row
+-- find the longest array in the record, then re-key by row index first and
+field name second:
+
+
+mlr --ijson --ocsv put -q '
+ n = 0;
+ for (k, v in $*) {
+ n = max(n, length(v));
+ }
+ keys = get_keys($*);
+ for (int i = 1; i <= n; i += 1) {
+ map row = {};
+ for (k in keys) {
+ row[k] = $[k][i];
+ }
+ emit row;
+ }
+' data/stan-example.json
+
+
+shape,rate
+triangle,9.8870
+square,0.0130
+circle,2.9010
+square,7.4670
+triangle,8.5910
+square,9.5310
+triangle,5.8240
+circle,4.2370
+circle,8.3350
+square,8.2430
+
+
+Save either of these as a `.mlr` file and pull it in with `put -q -f
+mkstan.mlr` or `put -q -f unstan.mlr` to reuse them without retyping. See also
+[issue 392](https://github.com/johnkerl/miller/issues/392).
diff --git a/docs/src/shapes-of-data.md.in b/docs/src/shapes-of-data.md.in
index 0b81d4c10..227ba32ac 100644
--- a/docs/src/shapes-of-data.md.in
+++ b/docs/src/shapes-of-data.md.in
@@ -260,3 +260,73 @@ output -- as any full transpose must.
Thanks to @Fravadona on [issue 321](https://github.com/johnkerl/miller/issues/321)
for the original version of this recipe.
+
+## Columns as JSON arrays
+
+Some downstream tools -- for example the [Stan](https://mc-stan.org/) modeling
+language -- want their input as a JSON object whose values are arrays, one
+array per column, rather than the more usual array-of-records shape:
+
+GENMD-CARDIFY
+{
+ "shape": ["triangle", "square", "circle"],
+ "rate": [9.8870, 0.0130, 2.9010]
+}
+GENMD-EOF
+
+rather than
+
+GENMD-CARDIFY
+[
+ {"shape": "triangle", "rate": 9.8870},
+ {"shape": "square", "rate": 0.0130},
+ {"shape": "circle", "rate": 2.9010}
+]
+GENMD-EOF
+
+There's no dedicated Miller file format for this -- it's just a particular
+shape of JSON, and the same [out-of-stream
+variable](reference-dsl-variables.md#out-of-stream-variables) technique from
+the transposing example above gets you there, keying by field name first and
+row number second (rather than the other way around). The
+[`arrayify`](reference-dsl-builtin-functions.md#arrayify) function turns the
+per-column maps (keyed `"1"`, `"2"`, ...) into real JSON arrays, and
+[`emit1`](reference-dsl-output-statements.md#emit1-and-emitemitpemitf) emits the
+whole thing as a single record rather than splitting it one-record-per-key
+the way plain `emit` would:
+
+GENMD-RUN-COMMAND
+mlr --icsv --ojson cut -f shape,rate then put -q '
+ for (k, v in $*) {
+ @output_record[k][NR] = v;
+ }
+ end {
+ emit1 arrayify(@output_record);
+ }
+' example.csv
+GENMD-EOF
+
+To go the other way -- expanding column-arrays back into one record per row
+-- find the longest array in the record, then re-key by row index first and
+field name second:
+
+GENMD-RUN-COMMAND
+mlr --ijson --ocsv put -q '
+ n = 0;
+ for (k, v in $*) {
+ n = max(n, length(v));
+ }
+ keys = get_keys($*);
+ for (int i = 1; i <= n; i += 1) {
+ map row = {};
+ for (k in keys) {
+ row[k] = $[k][i];
+ }
+ emit row;
+ }
+' data/stan-example.json
+GENMD-EOF
+
+Save either of these as a `.mlr` file and pull it in with `put -q -f
+mkstan.mlr` or `put -q -f unstan.mlr` to reuse them without retyping. See also
+[issue 392](https://github.com/johnkerl/miller/issues/392).