From 2df04e04ecdf42386836b373b317326879ea512f Mon Sep 17 00:00:00 2001
From: Marco Gorelli <33491632+MarcoGorelli@users.noreply.github.com>
Date: Fri, 21 Jun 2024 17:38:34 +0100
Subject: [PATCH] more reordering and fixup rust test

---
 crates/polars/tests/it/core/pivot.rs                | 2 +-
 docs/src/python/user-guide/transformations/pivot.py | 2 +-
 py-polars/polars/dataframe/frame.py                 | 6 +++---
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/crates/polars/tests/it/core/pivot.rs b/crates/polars/tests/it/core/pivot.rs
index fc0e8481aa8f..144c3291a54e 100644
--- a/crates/polars/tests/it/core/pivot.rs
+++ b/crates/polars/tests/it/core/pivot.rs
@@ -120,8 +120,8 @@ fn test_pivot_old() {
     );
     let pvt = pivot(
         &df,
-        ["index"],
         ["columns"],
+        ["index"],
         Some(["values"]),
         false,
         Some(PivotAgg::Count),
diff --git a/docs/src/python/user-guide/transformations/pivot.py b/docs/src/python/user-guide/transformations/pivot.py
index a51db55bbdf4..95354072d24e 100644
--- a/docs/src/python/user-guide/transformations/pivot.py
+++ b/docs/src/python/user-guide/transformations/pivot.py
@@ -15,7 +15,7 @@
 # --8<-- [end:df]
 
 # --8<-- [start:eager]
-out = df.pivot(index="foo", on="bar", values="N", aggregate_function="first")
+out = df.pivot("bar", index="foo", values="N", aggregate_function="first")
 print(out)
 # --8<-- [end:eager]
 
diff --git a/py-polars/polars/dataframe/frame.py b/py-polars/polars/dataframe/frame.py
index 9cc63ceb9590..357731cdf952 100644
--- a/py-polars/polars/dataframe/frame.py
+++ b/py-polars/polars/dataframe/frame.py
@@ -7609,10 +7609,10 @@ def pivot(
         on
             Name of the column(s) whose values will be used as the header of the output
             DataFrame.
-        values
-            Column values to aggregate. If None, all remaining columns will be used.
         index
             One or multiple keys to group by.
+        values
+            Column values to aggregate. If None, all remaining columns will be used.
         aggregate_function
             Choose from:
 
@@ -7644,7 +7644,7 @@ def pivot(
         ...         "baz": [1, 2, 3, 4, 5, 6],
         ...     }
         ... )
-        >>> df.pivot(index="foo", on="bar", values="baz", aggregate_function="sum")
+        >>> df.pivot("bar", index="foo", values="baz", aggregate_function="sum")
         shape: (2, 3)
         ┌─────┬─────┬─────┐
         │ foo ┆ y   ┆ x   │