ensure ANSI sql in examples

doc/syntax/layer/type/area.qmd

@@ -46,10 +46,9 @@ We can reshape the data to 'long format' from our wide format.
 
 ```{ggsql}
 CREATE TABLE long_airquality AS
-SELECT * FROM ggsql:airquality
-UNPIVOT(
-  Value FOR Series IN (Temp, Wind)
-) AS u;
+SELECT Date, 'Temp' AS Series, Temp AS Value FROM ggsql:airquality
+UNION ALL
+SELECT Date, 'Wind' AS Series, Wind AS Value FROM ggsql:airquality;
 ```
 
 Which means we can display multiple series at once, by mapping the identifier to an aesthetic.

doc/syntax/layer/type/errorbar.qmd

@@ -35,13 +35,13 @@ The orientation of errorbar layers is deduced directly from the mapping, because
 #| code-fold: true
 #| code-summary: "Create example data"
 CREATE TABLE penguin_summary AS
-SELECT
-  species,
-  MEAN(bill_dep) - STDDEV(bill_dep) AS low,
-  MEAN(bill_dep) AS mean,
-  MEAN(bill_dep) + STDDEV(bill_dep) AS high
-FROM ggsql:penguins
-GROUP BY species
+WITH stats AS (
+  SELECT species, AVG(bill_dep) AS mean
+  FROM ggsql:penguins
+  GROUP BY species
+)
+SELECT species, mean - 1.5 AS low, mean, mean + 1.5 AS high
+FROM stats
 ```
 
 Classic errorbar with point at centre.

doc/syntax/layer/type/linear.qmd

@@ -52,12 +52,10 @@ VISUALISE FROM ggsql:penguins
 Add multiple reference lines with different colors from a separate dataset. Note we're mapping from data here, so we use `DRAW` instead of `PLACE`.
 
 ```{ggsql}
-WITH lines AS (
-    SELECT * FROM (VALUES
-        (0.4, -1, 'Line A'),
-        (0.2, 8, 'Line B'),
-        (0.8, -19, 'Line C')
-    ) AS t(coef, intercept, label)
+WITH lines(coef, intercept, label) AS (VALUES
+    (0.4, -1, 'Line A'),
+    (0.2, 8, 'Line B'),
+    (0.8, -19, 'Line C')
 )
 VISUALISE FROM ggsql:penguins
   DRAW point MAPPING bill_len AS x, bill_dep AS y

doc/syntax/layer/type/path.qmd

@@ -34,14 +34,15 @@ The path layer has no orientation. The axes are treated symmetrically.
 #| code-fold: true
 #| code-summary: "Create example data"
 CREATE TABLE df AS
-SELECT * FROM (VALUES
+WITH t(x, y, id) AS (VALUES
   (1.0, 1.0, 'A'),
   (2.0, 1.0, 'A'),
   (1.0, 3.0, 'A'),
   (3.0, 1.0, 'B'),
   (2.0, 3.0, 'B'),
-  (3.0, 3.0, 'B'),
-) AS t(x, y, id)
+  (3.0, 3.0, 'B')
+)
+SELECT * FROM t
 ```
 
 Simple example path.

doc/syntax/layer/type/polygon.qmd

@@ -36,14 +36,15 @@ The polygon layer has no orientation. The axes are treated symmetrically.
 #| code-fold: true
 #| code-summary: "Create example data"
 CREATE TABLE df AS
-SELECT * FROM (VALUES
+WITH t(x, y, id) AS (VALUES
   (1.0, 1.0, 'A'),
   (1.0, 3.0, 'A'),
   (2.0, 1.0, 'A'),
   (2.0, 3.0, 'B'),
   (3.0, 1.0, 'B'),
-  (3.0, 3.0, 'B'),
-) AS t(x, y, id)
+  (3.0, 3.0, 'B')
+)
+SELECT * FROM t
 ```
 
 Simple example polygon.

doc/syntax/layer/type/rect.qmd

@@ -2,7 +2,7 @@
 title: "Rectangle"
 ---
 
-> Layers are declared with the [`DRAW` clause](../clause/draw.qmd). Read the documentation for this clause for a thorough description of how to use it.
+> Layers are declared with the [`DRAW` clause](../../clause/draw.qmd). Read the documentation for this clause for a thorough description of how to use it.
 
 Rectangles can be used to draw heatmaps or indicate ranges.
 
@@ -85,8 +85,7 @@ SELECT
   MIN(Temp) AS min,
   MAX(Temp) AS max
 FROM ggsql:airquality
-GROUP BY
-  WEEKOFYEAR(Date)
+GROUP BY Week
 
 VISUALISE start AS xmin, end AS xmax, min AS ymin, max AS ymax
   DRAW rect
@@ -103,4 +102,4 @@ VISUALISE FROM ggsql:airquality
     ymax => 100,
     colour => 'dodgerblue'
   DRAW line MAPPING Date AS x, Temp AS y
-```
+```

doc/syntax/layer/type/ribbon.qmd

@@ -44,13 +44,13 @@ Ribbon plots are great for showing the range of some aggregation.
 
 ```{ggsql}
 // Weekly aggregation of temperature
-SELECT 
-  WEEKOFYEAR(Date) AS Week, 
-  MAX(Temp) AS MaxTemp, 
-  MEAN(Temp) AS MeanTemp,
-  MIN(Temp) AS MinTemp 
+SELECT
+  Week,
+  MAX(Temp) AS MaxTemp,
+  AVG(Temp) AS MeanTemp,
+  MIN(Temp) AS MinTemp
 FROM ggsql:airquality
-GROUP BY WEEKOFYEAR(Date)
+GROUP BY Week
 
 VISUALISE Week AS x
   DRAW ribbon 

doc/syntax/layer/type/rule.qmd

@@ -54,12 +54,10 @@ VISUALISE FROM ggsql:penguins
 Add multiple threshold lines with different colors. Note that because we're mapping data from data, we use the `DRAW` clause instead of the `PLACE` clause.
 
 ```{ggsql}
-WITH thresholds AS (
-    SELECT * FROM (VALUES
-        (70, 'Target'),
-        (80, 'Warning'),
-        (90, 'Critical')
-    ) AS t(value, label)
+WITH thresholds(value, label) AS (VALUES
+    (70, 'Target'),
+    (80, 'Warning'),
+    (90, 'Critical')
 )
 SELECT Date AS date, temp AS temperature
 FROM ggsql:airquality

doc/syntax/layer/type/segment.qmd

@@ -38,17 +38,15 @@ The segment layer has no orientations. The axes are treated symmetrically.
 Segments are useful when you have known start and end points of the data. For example in a graph
 
 ```{ggsql}
-WITH edges AS (
-  SELECT * FROM (VALUES
-      (0, 0, 1, 1, 'A'),
-      (1, 1, 2, 1, 'A'),
-      (2, 1, 3, 0, 'A'),
-      (0, 3, 1, 2, 'B'),
-      (1, 2, 2, 2, 'B'),
-      (2, 2, 3, 3, 'B'),
-      (1, 1, 1, 2, 'C'),
-      (2, 2, 2, 1, 'C')
-  ) AS t(x, y, xend, yend, type)
+WITH edges(x, y, xend, yend, type) AS (VALUES
+    (0, 0, 1, 1, 'A'),
+    (1, 1, 2, 1, 'A'),
+    (2, 1, 3, 0, 'A'),
+    (0, 3, 1, 2, 'B'),
+    (1, 2, 2, 2, 'B'),
+    (2, 2, 3, 3, 'B'),
+    (1, 1, 1, 2, 'C'),
+    (2, 2, 2, 1, 'C')
 )
 VISUALISE x, y, xend, yend FROM edges
   DRAW segment MAPPING type AS stroke
@@ -81,7 +79,7 @@ SELECT
     ELSE 'warmer'
   END AS trend
 FROM ggsql:airquality
-GROUP BY WEEKOFYEAR(Date)
+GROUP BY Week
 
 VISUALISE date AS x, trend AS colour
   DRAW segment 

doc/syntax/layer/type/smooth.qmd

@@ -2,7 +2,7 @@
 title: "Smooth"
 ---
 
-> Layers are declared with the [`DRAW` clause](../clause/draw.qmd). Read the documentation for this clause for a thorough description of how to use it.
+> Layers are declared with the [`DRAW` clause](../../clause/draw.qmd). Read the documentation for this clause for a thorough description of how to use it.
 
 Smooth layers are used to display a trendline among a series of observations.
 
@@ -119,17 +119,17 @@ The default `method => 'nw'` might be too coarse for timeseries.
 <!-- Ideally, we would just use the date here directly but we currently require numeric data -->
 
 ```{ggsql}
-SELECT *, EPOCH(Date) AS numdate FROM ggsql:airquality
-VISUALISE numdate AS x, Temp AS y
+SELECT * FROM ggsql:airquality
+VISUALISE Epoch AS x, Temp AS y
   DRAW point
   DRAW smooth
 ```
 
 You can make the fit more granular by reducing the bandwidth, for example using `adjust`.
 
 ```{ggsql}
-SELECT *, EPOCH(Date) AS numdate FROM ggsql:airquality
-VISUALISE numdate AS x, Temp AS y
+SELECT * FROM ggsql:airquality
+VISUALISE Epoch AS x, Temp AS y
   DRAW point
   DRAW smooth SETTING adjust => 0.2
 ```
@@ -150,4 +150,4 @@ VISUALISE bill_len AS x, bill_dep AS y, species AS stroke FROM ggsql:penguins
    DRAW point SETTING opacity => 0
    DRAW smooth SETTING method => 'ols'
    DRAW smooth MAPPING 'All' AS stroke SETTING method => 'ols'
-```
+```

doc/syntax/scale/type/identity.qmd

@@ -21,11 +21,12 @@ SCALE IDENTITY size
 #### Use color values directly
 
 ```{ggsql}
-SELECT * FROM (VALUES
-      ('A', 45, 'forestgreen'),
-      ('B', 72, '#3401e3'),
-      ('C', 38, 'hsl(150deg 30% 60%)')
-  ) AS t(category, value, style)
+WITH t(category, value, style) AS (VALUES
+    ('A', 45, 'forestgreen'),
+    ('B', 72, '#3401e3'),
+    ('C', 38, 'hsl(150deg 30% 60%)')
+)
+SELECT * FROM t
 VISUALISE category AS x, value AS y, style AS fill
 DRAW bar
 SCALE IDENTITY fill

ggsql-jupyter/src/display.rs

@@ -9,18 +9,32 @@ use serde_json::{json, Value};
 
 /// Format execution result as Jupyter display_data content
 ///
-/// Returns a JSON value matching the Jupyter display_data message format:
+/// Returns `Some(Value)` for results that should be displayed, or `None` for
+/// empty results (e.g., DDL statements like CREATE TABLE that have no columns).
+///
+/// Note: A SELECT that returns 0 rows but has columns will still display
+/// an empty table with headers. Only truly empty DataFrames (0 columns)
+/// from DDL statements return `None`.
+///
+/// The returned JSON matches the Jupyter display_data message format:
 /// ```json
 /// {
 ///   "data": { "mime/type": content, ... },
 ///   "metadata": { ... },
 ///   "transient": { ... }
 /// }
 /// ```
-pub fn format_display_data(result: ExecutionResult) -> Value {
+pub fn format_display_data(result: ExecutionResult) -> Option<Value> {
     match result {
-        ExecutionResult::Visualization { spec } => format_vegalite(spec),
-        ExecutionResult::DataFrame(df) => format_dataframe(df),
+        ExecutionResult::Visualization { spec } => Some(format_vegalite(spec)),
+        ExecutionResult::DataFrame(df) => {
+            // DDL statements return DataFrames with 0 columns - don't display anything
+            if df.width() == 0 {
+                None
+            } else {
+                Some(format_dataframe(df))
+            }
+        }
     }
 }
 
@@ -199,12 +213,42 @@ mod tests {
     fn test_vegalite_format() {
         let spec = r#"{"mark": "point"}"#.to_string();
         let result = ExecutionResult::Visualization { spec };
-        let display = format_display_data(result);
+        let display = format_display_data(result).expect("Visualization should return Some");
 
         assert!(display["data"]["text/html"].is_string());
         assert!(display["data"]["text/plain"].is_string());
     }
 
+    #[test]
+    fn test_empty_dataframe_returns_none() {
+        use polars::prelude::*;
+
+        // DDL statements return DataFrames with 0 columns
+        let df = DataFrame::new(Vec::<Column>::new()).unwrap();
+        let result = ExecutionResult::DataFrame(df);
+        let display = format_display_data(result);
+
+        assert!(
+            display.is_none(),
+            "Empty DataFrame (0 columns) should return None"
+        );
+    }
+
+    #[test]
+    fn test_empty_rows_dataframe_returns_some() {
+        use polars::prelude::*;
+
+        // SELECT with 0 rows but columns should still display
+        let df = DataFrame::new(vec![Column::new("x".into(), Vec::<i32>::new())]).unwrap();
+        let result = ExecutionResult::DataFrame(df);
+        let display = format_display_data(result);
+
+        assert!(
+            display.is_some(),
+            "DataFrame with columns but 0 rows should return Some"
+        );
+    }
+
     #[test]
     fn test_html_escape() {
         assert_eq!(

ggsql-jupyter/src/kernel.rs

@@ -312,23 +312,24 @@ impl KernelServer {
             Ok(exec_result) => {
                 // Send execute_result (not display_data)
                 // Per Jupyter spec: execute_result includes execution_count
+                // Only send if there's something to display (DDL returns None)
                 if !silent {
-                    let display_data = format_display_data(exec_result);
+                    if let Some(display_data) = format_display_data(exec_result) {
+                        // Build message content, including output_location if present
+                        let mut content = json!({
+                            "execution_count": self.execution_count,
+                            "data": display_data["data"],
+                            "metadata": display_data["metadata"]
+                        });
+
+                        // Add output_location for Positron routing (e.g., to Plots pane)
+                        if let Some(location) = display_data.get("output_location") {
+                            content["output_location"] = location.clone();
+                            tracing::info!("Setting output_location: {}", location);
+                        }
 
-                    // Build message content, including output_location if present
-                    let mut content = json!({
-                        "execution_count": self.execution_count,
-                        "data": display_data["data"],
-                        "metadata": display_data["metadata"]
-                    });
-
-                    // Add output_location for Positron routing (e.g., to Plots pane)
-                    if let Some(location) = display_data.get("output_location") {
-                        content["output_location"] = location.clone();
-                        tracing::info!("Setting output_location: {}", location);
+                        self.send_iopub("execute_result", content, parent).await?;
                     }
-
-                    self.send_iopub("execute_result", content, parent).await?;
                 }
 
                 // Send execute_reply