fix: Allow index=None in pivot()

crates/polars-lazy/src/frame/pivot.rs

@@ -33,7 +33,7 @@ impl PhysicalAggExpr for PivotExpr {
 
 pub fn pivot<I0, I1, I2, S0, S1, S2>(
     df: &DataFrame,
-    index: I0,
+    index: Option<I0>,
     columns: I1,
     values: Option<I2>,
     sort_columns: bool,
@@ -67,7 +67,7 @@ where
 
 pub fn pivot_stable<I0, I1, I2, S0, S1, S2>(
     df: &DataFrame,
-    index: I0,
+    index: Option<I0>,
     columns: I1,
     values: Option<I2>,
     sort_columns: bool,

crates/polars-ops/src/frame/pivot/mod.rs

@@ -84,7 +84,7 @@ fn restore_logical_type(s: &Series, logical_type: &DataType) -> Series {
 /// If you have a relatively large table, consider using a group_by over a pivot.
 pub fn pivot<I0, I1, I2, S0, S1, S2>(
     pivot_df: &DataFrame,
-    index: I0,
+    index: Option<I0>,
     columns: I1,
     values: Option<I2>,
     sort_columns: bool,
@@ -99,10 +99,10 @@ where
     S1: AsRef<str>,
     S2: AsRef<str>,
 {
-    let index = index
-        .into_iter()
-        .map(|s| s.as_ref().to_string())
-        .collect::<Vec<_>>();
+    let index = match index {
+        Some(i) => i.into_iter().map(|s| s.as_ref().to_string()).collect(),
+        None => Vec::new(),
+    };
     let columns = columns
         .into_iter()
         .map(|s| s.as_ref().to_string())
@@ -127,7 +127,7 @@ where
 /// If you have a relatively large table, consider using a group_by over a pivot.
 pub fn pivot_stable<I0, I1, I2, S0, S1, S2>(
     pivot_df: &DataFrame,
-    index: I0,
+    index: Option<I0>,
     columns: I1,
     values: Option<I2>,
     sort_columns: bool,
@@ -142,10 +142,10 @@ where
     S1: AsRef<str>,
     S2: AsRef<str>,
 {
-    let index = index
-        .into_iter()
-        .map(|s| s.as_ref().to_string())
-        .collect::<Vec<_>>();
+    let index = match index {
+        Some(i) => i.into_iter().map(|s| s.as_ref().to_string()).collect(),
+        None => Vec::new(),
+    };
     let columns = columns
         .into_iter()
         .map(|s| s.as_ref().to_string())
@@ -205,7 +205,6 @@ fn pivot_impl(
     // used as separator/delimiter in generated column names.
     separator: Option<&str>,
 ) -> PolarsResult<DataFrame> {
-    polars_ensure!(!index.is_empty(), ComputeError: "index cannot be zero length");
     polars_ensure!(!columns.is_empty(), ComputeError: "columns cannot be zero length");
     if !stable {
         println!("unstable pivot not yet supported, using stable pivot");
@@ -262,12 +261,24 @@ fn pivot_impl_single_column(
 
         let groups = pivot_df.group_by_stable(group_by)?.take_groups();
 
-        let (col, row) = POOL.join(
-            || positioning::compute_col_idx(pivot_df, column, &groups),
-            || positioning::compute_row_idx(pivot_df, index, &groups, count),
-        );
-        let (col_locations, column_agg) = col?;
-        let (row_locations, n_rows, mut row_index) = row?;
+        let (col, row) = match index.len() {
+            0 => {
+                let col = POOL.install(
+                    || positioning::compute_col_idx(pivot_df, column, &groups)
+                )?;
+                let row = (vec![0; col.0.len()], 1, None);
+                (col, row)
+            },
+            _ => {
+                let (col, row) = POOL.join(
+                    || positioning::compute_col_idx(pivot_df, column, &groups),
+                    || positioning::compute_row_idx(pivot_df, index, &groups, count),
+                );
+                (col?, row?)
+            },
+        };
+        let (col_locations, column_agg) = col;
+        let (row_locations, n_rows, mut row_index) = row;
 
         for value_col_name in values {
             let value_col = pivot_df.column(value_col_name)?;
@@ -347,7 +358,7 @@ fn pivot_impl_single_column(
             }
 
             let cols = if count == 0 {
-                let mut final_cols = row_index.take().unwrap();
+                let mut final_cols = row_index.take().unwrap_or_else(Vec::new);
                 final_cols.extend(cols);
                 final_cols
             } else {

crates/polars/tests/it/core/pivot.rs

@@ -15,7 +15,7 @@ fn test_pivot_date_() -> PolarsResult<()> {
     // Test with date as the `columns` input
     let out = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["values1"],
         Some(["values2"]),
         true,
@@ -33,7 +33,7 @@ fn test_pivot_date_() -> PolarsResult<()> {
     // Test with date as the `values` input.
     let mut out = pivot_stable(
         &df,
-        ["index"],
+        Some(["index"]),
         ["values2"],
         Some(["values1"]),
         true,
@@ -63,7 +63,7 @@ fn test_pivot_old() {
 
     let pvt = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,
@@ -78,7 +78,7 @@ fn test_pivot_old() {
     );
     let pvt = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,
@@ -92,7 +92,7 @@ fn test_pivot_old() {
     );
     let pvt = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,
@@ -106,7 +106,7 @@ fn test_pivot_old() {
     );
     let pvt = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,
@@ -120,7 +120,7 @@ fn test_pivot_old() {
     );
     let pvt = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,
@@ -148,7 +148,7 @@ fn test_pivot_categorical() -> PolarsResult<()> {
 
     let out = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         true,
@@ -173,7 +173,7 @@ fn test_pivot_new() -> PolarsResult<()> {
 
     let out = (pivot_stable(
         &df,
-        ["index1", "index2"],
+        Some(["index1", "index2"]),
         ["cols1"],
         Some(["values1"]),
         true,
@@ -190,7 +190,7 @@ fn test_pivot_new() -> PolarsResult<()> {
 
     let out = pivot_stable(
         &df,
-        ["index1", "index2"],
+        Some(["index1", "index2"]),
         ["cols1", "cols2"],
         Some(["values1"]),
         true,
@@ -221,7 +221,7 @@ fn test_pivot_2() -> PolarsResult<()> {
 
     let out = pivot_stable(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,
@@ -254,7 +254,7 @@ fn test_pivot_datetime() -> PolarsResult<()> {
 
     let out = pivot(
         &df,
-        ["index"],
+        Some(["index"]),
         ["columns"],
         Some(["values"]),
         false,

docs/src/rust/user-guide/transformations/pivot.rs

@@ -14,15 +14,15 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
     // --8<-- [end:df]
 
     // --8<-- [start:eager]
-    let out = pivot(&df, ["foo"], ["bar"], Some(["N"]), false, None, None)?;
+    let out = pivot(&df, Some(["foo"]), ["bar"], Some(["N"]), false, None, None)?;
     println!("{}", &out);
     // --8<-- [end:eager]
 
     // --8<-- [start:lazy]
     let q = df.lazy();
     let q2 = pivot(
         &q.collect()?,
-        ["foo"],
+        Some(["foo"]),
         ["bar"],
         Some(["N"]),
         false,

py-polars/polars/dataframe/frame.py

@@ -7017,7 +7017,7 @@ def pivot(
         self,
         values: ColumnNameOrSelector | Sequence[ColumnNameOrSelector] | None,
         index: ColumnNameOrSelector | Sequence[ColumnNameOrSelector] | None,
-        columns: ColumnNameOrSelector | Sequence[ColumnNameOrSelector] | None,
+        columns: ColumnNameOrSelector | Sequence[ColumnNameOrSelector],
         aggregate_function: PivotAgg | Expr | None = None,
         *,
         maintain_order: bool = True,
@@ -7037,7 +7037,7 @@ def pivot(
             arguments contains multiple columns as well. If None, all remaining columns
             will be used.
         index
-            One or multiple keys to group by.
+            One or multiple keys to group by. If None, a single output row is produced.
         columns
             Name of the column(s) whose values will be used as the header of the output
             DataFrame.
@@ -7128,6 +7128,30 @@ def pivot(
         │ b    ┆ 0.964028 ┆ 0.999954 │
         └──────┴──────────┴──────────┘
 
+        Set the index to None to output a single row.
+
+        >>> df = pl.DataFrame(
+        ...     {
+        ...         "col1": ["a", "a", "a", "b", "b", "b"],
+        ...         "col2": ["x", "x", "x", "x", "y", "y"],
+        ...         "col3": [6, 7, 3, 2, 5, 7],
+        ...     }
+        ... )
+        >>> df.pivot(
+        ...     index=None,
+        ...     columns="col2",
+        ...     values="col3",
+        ...     aggregate_function=pl.element().tanh().mean(),
+        ... )
+        shape: (1, 2)
+        ┌──────────┬──────────┐
+        │ x        ┆ y        │
+        │ ---      ┆ ---      │
+        │ f64      ┆ f64      │
+        ╞══════════╪══════════╡
+        │ 0.989767 ┆ 0.999954 │
+        └──────────┴──────────┘
+
         Note that `pivot` is only available in eager mode. If you know the unique
         column values in advance, you can use :meth:`polars.LazyFrame.groupby` to
         get the same result as above in lazy mode:
@@ -7151,7 +7175,8 @@ def pivot(
         │ b    ┆ 0.964028 ┆ 0.999954 │
         └──────┴──────────┴──────────┘
         """  # noqa: W505
-        index = _expand_selectors(self, index)
+        if index is not None:
+            index = _expand_selectors(self, index)
         columns = _expand_selectors(self, columns)
         if values is not None:
             values = _expand_selectors(self, values)

py-polars/src/dataframe/general.rs

@@ -399,7 +399,7 @@ impl PyDataFrame {
     #[pyo3(signature = (index, columns, values, maintain_order, sort_columns, aggregate_expr, separator))]
     pub fn pivot_expr(
         &self,
-        index: Vec<String>,
+        index: Option<Vec<String>>,
         columns: Vec<String>,
         values: Option<Vec<String>>,
         maintain_order: bool,

py-polars/tests/unit/operations/test_pivot.py

@@ -64,6 +64,31 @@ def test_pivot_no_values() -> None:
     assert_frame_equal(result, expected)
 
 
+def test_pivot_no_index() -> None:
+    df = pl.DataFrame(
+        {
+            "foo": ["A", "B", "C"],
+            "N": [1, 2, 3],
+            "M": [4, 5, 6],
+        }
+    )
+    result = df.pivot(
+        index=None, columns="foo", values=["N", "M"], aggregate_function=None
+    )
+
+    expected = pl.DataFrame(
+        {
+            "N_foo_A": [1],
+            "N_foo_B": [2],
+            "N_foo_C": [3],
+            "M_foo_A": [4],
+            "M_foo_B": [5],
+            "M_foo_C": [6],
+        }
+    )
+    assert_frame_equal(result, expected)
+
+
 def test_pivot_list() -> None:
     df = pl.DataFrame({"a": [1, 2, 3], "b": [[1, 1], [2, 2], [3, 3]]})