fix create_hexbin_map truncating aggregated values to integers

The aggregated "color" column was cast to Int64, so any non-integer
result of agg_func (e.g. the mean of a column with values between 0
and 1) got truncated and np.min/np.mean/np.max all produced the same
map. The cast came in with the narwhals port; before that the column
went through pd.to_numeric and kept its float values. Drop the cast.

Closes #4632

Author: Belagum

CHANGELOG.md

@@ -4,6 +4,8 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 
 ## Unreleased
 
+### Fixed
+- Fix `create_hexbin_map` truncating aggregated values to integers, which made `agg_func` results such as the mean of a float column come out wrong [[#4632](https://github.com/plotly/plotly.py/issues/4632)], with thanks to @Belagum for the contribution!
 
 ## [7.1.0] - 2026-09-15
 

plotly/figure_factory/_hexbin_map.py

@@ -437,9 +437,7 @@ def create_hexbin_map(
             )
         )
 
-    agg_data_frame = nw.concat(agg_data_frame_list, how="vertical").with_columns(
-        color=nw.col("color").cast(nw.Int64)
-    )
+    agg_data_frame = nw.concat(agg_data_frame_list, how="vertical")
 
     if range_color is None:
         range_color = [

tests/test_optional/test_figure_factory/test_figure_factory.py

@@ -1275,6 +1275,30 @@ def test_aggregation(self):
 
         assert fig3.data[0].z.sum() == 1000
 
+    def test_aggregation_keeps_float_values(self):
+        lat = [0, 1, 1, 2, 4, 5, 1, 2, 4, 5, 2, 3, 2, 1, 5, 3, 5]
+        lon = [1, 2, 3, 3, 0, 4, 5, 0, 5, 3, 1, 5, 4, 0, 1, 2, 5]
+
+        fig = ff.create_hexbin_map(
+            lat=lat,
+            lon=lon,
+            nx_hexagon=1,
+            color=0.5 * np.ones(len(lat)),
+            agg_func=np.mean,
+        )
+        assert np.array_equal(fig.data[0].z, 0.5 * np.ones(5))
+
+        color = np.linspace(0.1, 0.9, len(lat))
+        fig_min = ff.create_hexbin_map(
+            lat=lat, lon=lon, nx_hexagon=1, color=color, agg_func=np.min
+        )
+        fig_max = ff.create_hexbin_map(
+            lat=lat, lon=lon, nx_hexagon=1, color=color, agg_func=np.max
+        )
+        z_min, z_max = fig_min.data[0].z, fig_max.data[0].z
+        assert np.all(z_min >= 0.1) and np.all(z_max <= 0.9)
+        assert np.all(z_min <= z_max) and np.any(z_min < z_max)
+
     def test_build_dataframe(self):
         np.random.seed(0)
         N = 10000