diff --git a/geopandas/plotting.py b/geopandas/plotting.py
index b3b6460..463ebd4 100644
--- a/geopandas/plotting.py
+++ b/geopandas/plotting.py
@@ -773,9 +773,11 @@ GON (((-122.84000 49.00000, -120.0000...
             if not show_interval:
                 labels = [c[1:-1] for c in labels]
 
-        values = pd.Categorical([np.nan] * len(values), categories=labels, ordered=True)
+        values = pd.Categorical(
+            [np.nan] * len(values), categories=binning.bins, ordered=True
+        )
         values[~nan_idx] = pd.Categorical.from_codes(
-            binning.yb, categories=labels, ordered=True
+            binning.yb, categories=binning.bins, ordered=True
         )
         if cmap is None:
             cmap = "viridis"
@@ -884,6 +886,8 @@ GON (((-122.84000 49.00000, -120.0000...
             norm = Normalize(vmin=mn, vmax=mx)
         n_cmap = cm.ScalarMappable(norm=norm, cmap=cmap)
         if categorical:
+            if scheme is not None:
+                categories = labels
             patches = []
             for value, cat in enumerate(categories):
                 patches.append(
diff --git a/geopandas/tests/test_plotting.py b/geopandas/tests/test_plotting.py
index 8e91ba1..cce912f 100644
--- a/geopandas/tests/test_plotting.py
+++ b/geopandas/tests/test_plotting.py
@@ -1073,6 +1073,8 @@ class TestMapclassifyPlotting:
         cls.df["mid_vals"] = np.linspace(0.3, 0.7, cls.df.shape[0])
         cls.df["high_vals"] = np.linspace(0.7, 1.0, cls.df.shape[0])
         cls.df.loc[cls.df.index[:20:2], "high_vals"] = np.nan
+        cls.nybb = read_file(get_path("nybb"))
+        cls.nybb["vals"] = [0.001, 0.002, 0.003, 0.004, 0.005]
 
     def test_legend(self):
         with warnings.catch_warnings(record=True) as _:  # don't print warning
@@ -1333,6 +1335,35 @@ class TestMapclassifyPlotting:
             line.get_markerfacecolor() for line in ax3.get_legend().get_lines()
         ] == legend_colors_exp
 
+    def test_equally_formatted_bins(self):
+        ax = self.nybb.plot(
+            "vals",
+            scheme="quantiles",
+            legend=True,
+        )
+        labels = [t.get_text() for t in ax.get_legend().get_texts()]
+        expected = [
+            "0.00, 0.00",
+            "0.00, 0.00",
+            "0.00, 0.00",
+            "0.00, 0.00",
+            "0.00, 0.01",
+        ]
+        assert labels == expected
+
+        ax2 = self.nybb.plot(
+            "vals", scheme="quantiles", legend=True, legend_kwds=dict(fmt="{:.3f}")
+        )
+        labels = [t.get_text() for t in ax2.get_legend().get_texts()]
+        expected = [
+            "0.001, 0.002",
+            "0.002, 0.003",
+            "0.003, 0.003",
+            "0.003, 0.004",
+            "0.004, 0.005",
+        ]
+        assert labels == expected
+
 
 class TestPlotCollections:
     def setup_method(self):