matplotlib · livlutz · May 24, 2025 · May 24, 2025 · May 25, 2025 · May 25, 2025
diff --git a/galleries/examples/color/colorbar_histogram.py b/galleries/examples/color/colorbar_histogram.py
@@ -0,0 +1,62 @@
+"""
+=========================
+Histogram as Colorbar
+=========================
+
+This example demonstrates how to create a colorbar for an image and
+add a histogram of the data values alongside it. This is useful for
+visualizing the distribution of values mapped to colors.
+
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as mcolors
+from matplotlib.ticker import MaxNLocator
+
+# === Surface Data ===
+delta = 0.025
+x = y = np.arange(-3.0, 3.0, delta)
+X, Y = np.meshgrid(x, y)
+Z1 = np.exp(-X**2 - Y**2)
+Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+Z = (Z1 - Z2) * 2
+
+# === Histogram from actual Z data ===
+counts, bins = np.histogram(Z, bins=30)
+
+# === Colormap & Normalization ===
+cmap = plt.get_cmap('RdYlBu')
+norm = mcolors.BoundaryNorm(bins, cmap.N)
+
+# === Main Plot ===
+fig, ax = plt.subplots()
+im = ax.imshow(Z, interpolation='bilinear', cmap=cmap,
+               origin='lower', extent=[-3, 3, -3, 3],
+               norm=norm)
+
+# Adjust image position to allow space
+plt.subplots_adjust(right=0.78, top=0.92, bottom=0.08)
+
+# === Inset Histogram – Positioning adjusted ===
+cax = ax.inset_axes([1.18, 0.02, 0.25, 0.95])  # left, bottom, width, height
+
+# === Plot Histogram ===
+midpoints = bins[:-1] + np.diff(bins) / 2
+bar_height = 1 / len(counts)
+cax.barh(midpoints, counts, height=np.median(np.diff(bins))*0.8, color=cmap(norm(midpoints)))
+
+# === Clean up ===
+cax.spines[:].set_visible(False)
+cax.margins(0)
+cax.tick_params(axis='both', which='both', length=0)
+
+# === Axis labels ===
+cax.set_xlabel('Count', labelpad=10)
+cax.set_ylabel('Value', labelpad=6) 
+
+# === Ticks ===
+cax.set_yticks(bins)
+cax.yaxis.set_major_locator(MaxNLocator(nbins=8))
+
+plt.show()
+