diff --git a/ultraplot/colors.py b/ultraplot/colors.py
index 6d1c18cc4..bab2f5c7a 100644
--- a/ultraplot/colors.py
+++ b/ultraplot/colors.py
@@ -17,6 +17,7 @@
 # colors or truncate colors. So we translate the relevant ListedColormaps to
 # LinearSegmentedColormaps for consistency. See :rc:`cmap.listedthresh`
 import functools
+import itertools
 import json
 import os
 import re
@@ -1715,6 +1716,20 @@ def __repr__(self):
         string += "})"
         return string
 
+    @property
+    def monochrome(self):
+        """Whether every color is identical, normalized to a Python boolean."""
+        if hasattr(self, "_monochrome"):
+            return self._monochrome
+        try:
+            return bool(super().monochrome)
+        except AttributeError:
+            return False
+
+    @monochrome.setter
+    def monochrome(self, value):
+        self._monochrome = bool(value)
+
     def __init__(self, colors, name=None, N=None, alpha=None, **kwargs):
         """
         Parameters
@@ -1748,7 +1763,13 @@ def __init__(self, colors, name=None, N=None, alpha=None, **kwargs):
         # identical monochromatic ListedColormaps when it receives scalar colors.
         N = _not_none(N, len(colors))
         name = _not_none(name, DEFAULT_NAME)
-        super().__init__(colors, name=name, N=N, **kwargs)
+        if isinstance(colors, str):
+            colors = [colors] * N
+        elif np.iterable(colors):
+            colors = list(itertools.islice(itertools.cycle(colors), N))
+        else:
+            colors = [colors] * N
+        super().__init__(colors, name=name, **kwargs)
         if alpha is not None:
             self.set_alpha(alpha)
         for i, color in enumerate(self.colors):
diff --git a/ultraplot/tests/test_colors.py b/ultraplot/tests/test_colors.py
index 407edbd0c..b1e78e009 100644
--- a/ultraplot/tests/test_colors.py
+++ b/ultraplot/tests/test_colors.py
@@ -1,12 +1,83 @@
 import os
+import warnings
+
+import matplotlib as mpl
+import matplotlib.colors as mcolors
 import pytest
 import numpy as np
-import matplotlib.colors as mcolors
 
 from ultraplot import colors as pcolors
 from ultraplot import config
 
 
+@pytest.mark.parametrize(
+    ("N", "expected"),
+    (
+        (None, ["#ff0000", "#0000ff"]),
+        (0, []),
+        (1, ["#ff0000"]),
+        (3, ["#ff0000", "#0000ff", "#ff0000"]),
+    ),
+)
+def test_discrete_colormap_resizes_without_listed_n_warning(N, expected):
+    """DiscreteColormap preserves N semantics without deprecated mpl input."""
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "error",
+            message=r"Passing 'N' to ListedColormap.*",
+            category=mpl.MatplotlibDeprecationWarning,
+        )
+        cmap = pcolors.DiscreteColormap(["red", "blue"], N=N)
+
+    assert cmap.N == len(expected)
+    assert [mcolors.to_hex(color) for color in cmap.colors] == expected
+
+
+@pytest.mark.parametrize(
+    ("N", "expected_size"),
+    (
+        (None, 3),
+        (1, 1),
+        (4, 4),
+    ),
+)
+def test_discrete_colormap_expands_scalar_color(N, expected_size):
+    """Scalar color strings produce the requested monochromatic colormap."""
+    cmap = pcolors.DiscreteColormap("red", N=N)
+
+    assert cmap.N == expected_size
+    assert [mcolors.to_hex(color) for color in cmap.colors] == [
+        "#ff0000"
+    ] * expected_size
+    assert cmap.monochrome is True
+
+
+def test_discrete_colormap_resizing_preserves_alpha_override():
+    """Alpha replacement is applied to every color after cycling the input."""
+    cmap = pcolors.DiscreteColormap([(1, 0, 0, 0.2), (0, 0, 1, 0.8)], N=3, alpha=0.5)
+
+    assert [mcolors.to_hex(color, keep_alpha=True) for color in cmap.colors] == [
+        "#ff000080",
+        "#0000ff80",
+        "#ff000080",
+    ]
+    assert cmap.monochrome is False
+
+
+@pytest.mark.parametrize(
+    ("colors", "expected"),
+    (
+        (["red", "red"], True),
+        (["red", "blue"], False),
+    ),
+)
+def test_discrete_colormap_monochrome_is_python_bool(colors, expected):
+    """Monochrome detection remains available across matplotlib versions."""
+    cmap = pcolors.DiscreteColormap(colors)
+
+    assert cmap.monochrome is expected
+
+
 @pytest.fixture(autouse=True)
 def setup_teardown():
     """