diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7107261c9f..0583fec45c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,6 +6,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 
 ### Fixed
 - Fix concurrent first access to lazily initialized graph object properties, which could raise `ValueError("Invalid value")` [[#3441](https://github.com/plotly/plotly.py/issues/3441)], with thanks to @hb1915 for the contribution!
+- Fix `px.sunburst`, `px.treemap` and `px.icicle` listing sectors in a different order on every run when `path` is used with a Polars DataFrame; sectors now follow their order of first appearance for all dataframe backends [[#5765](https://github.com/plotly/plotly.py/issues/5765)], with thanks to @Irahan2 for the contribution!
 
 
 ## [7.1.0] - 2026-09-15
diff --git a/plotly/express/_core.py b/plotly/express/_core.py
index 027df9e5aa..b354ed6f8f 100644
--- a/plotly/express/_core.py
+++ b/plotly/express/_core.py
@@ -1958,7 +1958,10 @@ def process_dataframe_hierarchy(args):
     _check_dataframe_all_leaves(df[path[::-1]])
     discrete_color = not _is_continuous(df, args["color"]) if args["color"] else False
 
-    df = df.lazy()
+    # Keep track of the original row order, so that the sectors can be sorted by
+    # first appearance after each group_by (Polars' group_by does not keep order).
+    row_index_colname = _generate_temporary_column_name(n_bytes=16, columns=df.columns)
+    df = df.with_row_index(row_index_colname).lazy()
 
     new_path = [col_name + "_path_copy" for col_name in path]
     df = df.with_columns(
@@ -1997,6 +2000,7 @@ def process_dataframe_hierarchy(args):
     # Since count_colname is always in agg_f, it can be used later to normalize color
     # in the continuous case after some gymnastic
     agg_f[count_colname] = nw.sum(count_colname)
+    agg_f[row_index_colname] = nw.min(row_index_colname)
 
     discrete_aggs = []
     continuous_aggs = []
@@ -2049,7 +2053,7 @@ def process_dataframe_hierarchy(args):
             agg_f[args["color"]] = nw.sum(args["color"])
 
     #  Other columns (for color, hover_data, custom_data etc.)
-    cols = list(set(df.collect_schema().names()).difference(path))
+    cols = list(set(df.collect_schema().names()).difference([*path, row_index_colname]))
     df = df.with_columns(nw.col(c).cast(nw.String()) for c in cols if c not in agg_f)
 
     for col in cols:  # for hover_data, custom_data etc.
@@ -2092,6 +2096,7 @@ def post_agg(dframe: nw.LazyFrame, continuous_aggs, discrete_aggs) -> nw.LazyFra
         dfg = (
             df.group_by(path[i:], drop_null_keys=True)
             .agg(**agg_f)
+            .sort(row_index_colname)
             .pipe(post_agg, continuous_aggs, discrete_aggs)
         )
 
diff --git a/tests/test_optional/test_px/test_px_functions.py b/tests/test_optional/test_px/test_px_functions.py
index fed8183aca..0371248658 100644
--- a/tests/test_optional/test_px/test_px_functions.py
+++ b/tests/test_optional/test_px/test_px_functions.py
@@ -233,6 +233,32 @@ def test_sunburst_treemap_with_path(constructor):
     assert fig.data[0].values[-1] == 8
 
 
+@pytest.mark.parametrize("px_fn", [px.sunburst, px.treemap, px.icicle])
+def test_sunburst_treemap_with_path_order(constructor, px_fn):
+    # Sectors should follow the order of first appearance in the data, whatever
+    # the dataframe backend (Polars' group_by does not keep the row order).
+    df = constructor(
+        dict(
+            regions=["South", "North", "South", "West", "North", "West"],
+            sectors=["Tech", "Finance", "Finance", "Tech", "Tech", "Finance"],
+            values=[1, 2, 3, 4, 5, 6],
+        )
+    )
+    fig = px_fn(df, path=["regions", "sectors"], values="values")
+    assert list(fig.data[0].ids) == [
+        "South/Tech",
+        "North/Finance",
+        "South/Finance",
+        "West/Tech",
+        "North/Tech",
+        "West/Finance",
+        "South",
+        "North",
+        "West",
+    ]
+    assert list(fig.data[0].values) == [1, 2, 3, 4, 5, 6, 4, 7, 10]
+
+
 def test_sunburst_treemap_with_path_and_hover(backend):
     df = px.data.tips(return_type=backend)
     fig = px.sunburst(