Add variableName and valueName to unpivot

__tests__/dataframe.test.ts

@@ -664,6 +664,28 @@ describe("dataframe", () => {
     });
     expect(actual).toFrameEqual(expected);
   });
+  test("unpivot renamed", () => {
+    const df = pl.DataFrame({
+      id: [1],
+      asset_key_1: ["123"],
+      asset_key_2: ["456"],
+      asset_key_3: ["abc"],
+    });
+    const actual = df.unpivot(
+      "id",
+      ["asset_key_1", "asset_key_2", "asset_key_3"],
+      {
+        variableName: "foo",
+        valueName: "bar",
+      },
+    );
+    const expected = pl.DataFrame({
+      id: [1, 1, 1],
+      foo: ["asset_key_1", "asset_key_2", "asset_key_3"],
+      bar: ["123", "456", "abc"],
+    });
+    expect(actual).toFrameEqual(expected);
+  });
   test("min:axis:0", () => {
     const actual = pl
       .DataFrame({

__tests__/lazyframe.test.ts

@@ -1347,4 +1347,29 @@ describe("lazyframe", () => {
     expect(newDF.sort("foo")).toFrameEqual(actualDf);
     fs.rmSync("./test.parquet");
   });
+  test("unpivot renamed", () => {
+    const ldf = pl
+      .DataFrame({
+        id: [1],
+        asset_key_1: ["123"],
+        asset_key_2: ["456"],
+        asset_key_3: ["abc"],
+      })
+      .lazy();
+    const actual = ldf.unpivot(
+      "id",
+      ["asset_key_1", "asset_key_2", "asset_key_3"],
+      {
+        variableName: "foo",
+        valueName: "bar",
+        streamable: true,
+      },
+    );
+    const expected = pl.DataFrame({
+      id: [1, 1, 1],
+      foo: ["asset_key_1", "asset_key_2", "asset_key_3"],
+      bar: ["123", "456", "abc"],
+    });
+    expect(actual.collectSync()).toFrameEqual(expected);
+  });
 });

polars/dataframe.ts

@@ -924,10 +924,8 @@ export interface DataFrame
    *
    * @param idVars - Columns to use as identifier variables.
    * @param valueVars - Values to use as value variables.
-   * @param variableName - Name to give to the `variable` column. Defaults to "variable"
-   * @param valueName - Name to give to the `value` column. Defaults to "value"
-   * @param streamable - Allow this node to run in the streaming engine.
-                         If this runs in streaming, the output of the unpivot operation will not have a stable ordering.
+   * @param options.variableName - Name to give to the `variable` column. Defaults to "variable"
+   * @param options.valueName - Name to give to the `value` column. Defaults to "value"
    * @example
    * ```
    * > const df1 = pl.DataFrame({
@@ -951,7 +949,14 @@ export interface DataFrame
    * └─────┴─────────────┴───────┘
    * ```
    */
-  unpivot(idVars: ColumnSelection, valueVars: ColumnSelection): DataFrame;
+  unpivot(
+    idVars: ColumnSelection,
+    valueVars: ColumnSelection,
+    options?: {
+      variableName?: string | null;
+      valueName?: string | null;
+    },
+  ): DataFrame;
   /**
    * Aggregate the columns of this DataFrame to their minimum value.
    * ___
@@ -1751,7 +1756,7 @@ export interface DataFrame
     Or combine them:
     - "3d12h4m25s" # 3 days, 12 hours, 4 minutes, and 25 seconds
 
-    By "calendar day", we mean the corresponding time on the next day (which may not be 24 hours, due to daylight savings). 
+    By "calendar day", we mean the corresponding time on the next day (which may not be 24 hours, due to daylight savings).
     Similarly for "calendar week", "calendar month", "calendar quarter", and "calendar year".
 
     Parameters
@@ -2177,8 +2182,19 @@ export const _DataFrame = (_df: any): DataFrame => {
     melt(ids, values) {
       return wrap("unpivot", columnOrColumns(ids), columnOrColumns(values));
     },
-    unpivot(ids, values) {
-      return wrap("unpivot", columnOrColumns(ids), columnOrColumns(values));
+    unpivot(ids, values, options) {
+      options = {
+        variableName: null,
+        valueName: null,
+        ...options,
+      };
+      return wrap(
+        "unpivot",
+        columnOrColumns(ids),
+        columnOrColumns(values),
+        options.variableName,
+        options.valueName,
+      );
     },
     min(axis = 0) {
       if (axis === 1) {

polars/lazy/dataframe.ts

@@ -126,7 +126,7 @@ export interface LazyDataFrame extends Serialize, GroupByOps<LazyGroupBy> {
             .. warning::
                 Streaming mode is considered **unstable**. It may be changed
                 at any point without it being considered a breaking change.
-   * 
+   *
    */
   fetch(numRows?: number): Promise<DataFrame>;
   fetch(numRows: number, opts: LazyOptions): Promise<DataFrame>;
@@ -369,7 +369,21 @@ export interface LazyDataFrame extends Serialize, GroupByOps<LazyGroupBy> {
    * @deprecated *since 0.13.0* use {@link unpivot}
    */
   melt(idVars: ColumnSelection, valueVars: ColumnSelection): LazyDataFrame;
-  unpivot(idVars: ColumnSelection, valueVars: ColumnSelection): LazyDataFrame;
+  /**
+   * @see {@link DataFrame.unpivot}
+   * @param options.streamable - Allow this node to run in the streaming engine.
+   *                             If this runs in streaming, the output of the unpivot operation will not have a stable
+   *                             ordering.
+   */
+  unpivot(
+    idVars: ColumnSelection,
+    valueVars: ColumnSelection,
+    options?: {
+      variableName?: string | null;
+      valueName?: string | null;
+      streamable?: boolean;
+    },
+  ): LazyDataFrame;
   /**
    * @see {@link DataFrame.min}
    */
@@ -982,9 +996,21 @@ export const _LazyDataFrame = (_ldf: any): LazyDataFrame => {
         _ldf.unpivot(columnOrColumnsStrict(ids), columnOrColumnsStrict(values)),
       );
     },
-    unpivot(ids, values) {
+    unpivot(ids, values, options) {
+      options = {
+        variableName: null,
+        valueName: null,
+        streamable: false,
+        ...options,
+      };
       return _LazyDataFrame(
-        _ldf.unpivot(columnOrColumnsStrict(ids), columnOrColumnsStrict(values)),
+        _ldf.unpivot(
+          columnOrColumnsStrict(ids),
+          columnOrColumnsStrict(values),
+          options.variableName,
+          options.valueName,
+          options.streamable,
+        ),
       );
     },
     min() {

src/dataframe.rs

@@ -925,15 +925,15 @@ impl JsDataFrame {
         &self,
         id_vars: Vec<String>,
         value_vars: Vec<String>,
-        value_name: Option<String>,
         variable_name: Option<String>,
+        value_name: Option<String>,
         streamable: Option<bool>,
     ) -> napi::Result<JsDataFrame> {
         let args = UnpivotArgs {
             index: strings_to_smartstrings(id_vars),
             on: strings_to_smartstrings(value_vars),
-            value_name: value_name.map(|s| s.into()),
             variable_name: variable_name.map(|s| s.into()),
+            value_name: value_name.map(|s| s.into()),
             streamable: streamable.unwrap_or(false),
         };
 

src/lazy/dataframe.rs

@@ -504,15 +504,15 @@ impl JsLazyFrame {
         &self,
         id_vars: Vec<&str>,
         value_vars: Vec<&str>,
-        value_name: Option<&str>,
         variable_name: Option<&str>,
+        value_name: Option<&str>,
         streamable: Option<bool>,
     ) -> JsLazyFrame {
         let args = UnpivotArgs {
             index: strings_to_smartstrings(id_vars),
             on: strings_to_smartstrings(value_vars),
-            value_name: value_name.map(|s| s.into()),
             variable_name: variable_name.map(|s| s.into()),
+            value_name: value_name.map(|s| s.into()),
             streamable: streamable.unwrap_or(false),
         };
         let ldf = self.ldf.clone();