diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index 701d1ad..412c730 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -9,23 +9,18 @@ on:
         type: boolean
         default: false
   pull_request:
+    types: [opened, reopened, synchronize, closed]
     paths:
-      - docs/**.rst
-      - docs/conf.py
-      - docs/make.bat
-      - docs/Makefile
-      - docs/requirements.txt
-      - docs/_static/**.css
-      - src/khisto/**.py
+      - docs/**
+      - pyproject.toml
+      - src/khisto/**/*.py
       - .github/workflows/docs.yaml
   push:
     tags: ['*']
-# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
+# Keep default workflow permissions read-only; deployment jobs elevate explicitly.
 permissions:
   contents: read
-  id-token: write
   packages: read
-  pages: write
 # Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest
 # queued. However, do NOT cancel in-progress runs as we want to allow these production deployments
 # to complete.
@@ -34,6 +29,7 @@ concurrency:
   cancel-in-progress: false
 jobs:
   build:
+    if: github.event_name != 'pull_request' || github.event.action != 'closed'
     runs-on: ubuntu-22.04
     steps:
       - name: Checkout khisto-python
@@ -61,7 +57,34 @@ jobs:
         with:
           name: khisto-python-docs
           path: ./docs/_build/html/
-  # Publish to GH pages on Git tag push
+  preview:
+    if: >-
+      always() &&
+      github.event_name == 'pull_request' &&
+      github.event.pull_request.head.repo.full_name == github.repository &&
+      (github.event.action == 'closed' || needs.build.result == 'success')
+    needs: build
+    runs-on: ubuntu-22.04
+    permissions:
+      contents: write
+      pull-requests: write
+    steps:
+      - name: Checkout khisto-python
+        uses: actions/checkout@v4
+      - name: Download the docs artifact
+        if: github.event.action != 'closed'
+        uses: actions/download-artifact@v4
+        with:
+          name: khisto-python-docs
+          path: ./docs/_build/html
+      - name: Deploy PR preview
+        uses: rossjrw/pr-preview-action@v1
+        with:
+          source-dir: ./docs/_build/html
+          preview-branch: gh-pages
+          wait-for-pages-deployment: true
+          qr-code: false
+  # Publish production docs to GitHub Pages on manual request.
   publish:
     if: github.event_name == 'workflow_dispatch' && inputs.deploy-gh-pages == true
     needs: build
@@ -77,9 +100,9 @@ jobs:
           name: khisto-python-docs
           path: ./docs/_build/html
       - name: Deploy web site
-        run: |
-          # Install tool for pushing to GH pages
-          pip install ghp-import
-
-          # Push built site directory contents to GH pages
-          ghp-import -m "Deployed ${GITHUB_SHA:0:7}" --push --force --no-jekyll ./docs/_build/html/
\ No newline at end of file
+        uses: JamesIves/github-pages-deploy-action@v4
+        with:
+          folder: ./docs/_build/html
+          branch: gh-pages
+          clean-exclude: pr-preview
+          force: false
diff --git a/README.md b/README.md
index 05fa3e3..64bff31 100644
--- a/README.md
+++ b/README.md
@@ -54,6 +54,10 @@ plt.show()
 
 ## Development
 
+On Windows, install [Visual Studio Build Tools 2022](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
+with the **Desktop development with C++** workload before running the commands
+below.
+
 ```bash
 # Clone repository
 git clone https://github.com/KhiopsML/khisto-python.git
diff --git a/docs/_static/css/custom.css b/docs/_static/css/custom.css
index d03f79a..9f0afde 100644
--- a/docs/_static/css/custom.css
+++ b/docs/_static/css/custom.css
@@ -40,6 +40,53 @@ img.sidebar-logo {
   box-shadow: 0 4px 16px rgba(0, 0, 0, 0.12) !important;
 }
 
+@media (prefers-reduced-motion: reduce) {
+  .sd-card {
+    transition: none;
+  }
+}
+
+.histogram-guide-card {
+  border-color: #4170d8 !important;
+  background: #4170d8 !important;
+  color: #ffffff !important;
+}
+
+.histogram-guide-card .sd-card-title,
+.histogram-guide-card .sd-card-text {
+  color: #ffffff;
+}
+
+[data-theme="dark"] .histogram-guide-card {
+  border-color: #6699ff !important;
+  background: #6699ff !important;
+  color: #000000 !important;
+}
+
+[data-theme="dark"] .histogram-guide-card .sd-card-title,
+[data-theme="dark"] .histogram-guide-card .sd-card-text {
+  color: #000000;
+}
+
+.histogram-guide-card:hover {
+  border-color: #f16e00 !important;
+}
+
+[data-theme="dark"] .histogram-guide-card:hover {
+  border-color: #ff7900 !important;
+}
+
+.histogram-guide-card:focus-within {
+  outline: 3px solid #000000;
+  outline-offset: 2px;
+  box-shadow: 0 0 0 2px #ffffff !important;
+}
+
+[data-theme="dark"] .histogram-guide-card:focus-within {
+  outline-color: #ffffff;
+  box-shadow: 0 0 0 2px #000000 !important;
+}
+
 /* Gallery images */
 .sd-card img {
   border-radius: 4px;
diff --git a/docs/conf.py b/docs/conf.py
index 81de350..62ed8d2 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -72,6 +72,9 @@
 
 html_theme = 'furo'
 html_theme_options = {
+    "source_repository": "https://github.com/KhiopsML/khisto-python/",
+    "source_branch": "main",
+    "source_directory": "docs/",
     "light_css_variables": {
         "color-brand-primary": "#FF7900",
         "color-brand-content": "#F16E00",
@@ -80,7 +83,7 @@
         "color-highlighted-background": "#FFD200",
         "color-admonition-title--note": "#FF7900",
         "color-admonition-title-background--note": "#FFF0E2",
-        "font-stack": "Helvetica Neue, Helvetica, sans-serif",
+        "font-stack": "Helvetica Neue, Helvetica, Arial, sans-serif",
     },
     "dark_css_variables": {
         "color-brand-primary": "#FF7900",
@@ -90,7 +93,7 @@
         "color-highlighted-background": "#FFD200",
         "color-admonition-title--note": "#FF7900",
         "color-admonition-title-background--note": "#CC6100",
-        "font-stack": "Helvetica Neue, Helvetica, sans-serif",
+        "font-stack": "Helvetica Neue, Helvetica, Arial, sans-serif",
     },
     # Sets the Github Icon (the SVG is embedded, copied from furo's repo)
     "footer_icons": [
diff --git a/docs/counts_vs_density.rst b/docs/counts_vs_density.rst
new file mode 100644
index 0000000..a0cbf6a
--- /dev/null
+++ b/docs/counts_vs_density.rst
@@ -0,0 +1,27 @@
+Counts vs Density
+=================
+
+Both columns show the same 500 observations with two different binning schemes.
+With equal-width bins, counts and density have the same shape. With variable-width
+bins, raw counts favor wider intervals and can distort the visual comparison.
+
+.. image:: images/counts-vs-density.png
+
+With equal-width bins, taller bars indicate a greater probability of falling
+within that interval. When bin widths vary, height alone is not enough:
+probability is represented by the bar's area, calculated as density multiplied
+by bin width.
+
+Note that variable-width bins are ideal for unbalanced distributions and outliers,
+as shown in `Histograms - Khiops <https://khiops.org/learn/histograms/>`_.
+
+Reading variable-width histograms
+---------------------------------
+
+.. csv-table::
+   :header: "Question", "Use", "What to compare"
+   :widths: 35, 35, 30
+
+   "How many observations?", "Counts (``density=False``)", "Bar heights"
+   "What fraction of observations?", "Counts divided by :math:`N`, or density", "Bar areas"
+   "Where are values concentrated?", "Density (``density=True``, the Khisto default)", "Bar heights"
\ No newline at end of file
diff --git a/docs/demo.ipynb b/docs/demo.ipynb
index c20702e..f9e75e5 100644
--- a/docs/demo.ipynb
+++ b/docs/demo.ipynb
@@ -25,8 +25,8 @@
     "short-but-wide bin can hold the *same* number of points, so only the density\n",
     "(count divided by bin width) shows the true shape of the distribution.\n",
     "\n",
-    "> 📚 For a didactic walk-through of optimal histograms — from the simplest to the\n",
-    "> most complex — see the histogram documentation in [Khiops fundations](https://khiops.org/learn/understand/)"
+    "> 📚 Go further with [Histograms - Khiops](https://khiops.org/learn/histograms/),\n",
+    "a didactic walk-through from the simplest histogram to the most complex."
    ]
   },
   {
@@ -43,7 +43,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 28,
    "id": "d9b9b33b",
    "metadata": {},
    "outputs": [],
@@ -70,7 +70,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 29,
    "id": "9e8eff47",
    "metadata": {},
    "outputs": [
@@ -112,7 +112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 30,
    "id": "e8a48420",
    "metadata": {},
    "outputs": [
@@ -161,7 +161,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 31,
    "id": "8b183e7b",
    "metadata": {},
    "outputs": [
@@ -202,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 32,
    "id": "c8ed6f75",
    "metadata": {},
    "outputs": [
@@ -250,7 +250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 33,
    "id": "48c3b0aa",
    "metadata": {},
    "outputs": [
@@ -302,7 +302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 34,
    "id": "d0e40b1c",
    "metadata": {},
    "outputs": [
@@ -322,7 +322,7 @@
     }
    ],
    "source": [
-    "hist_counts, bin_edges = histogram(data)\n",
+    "hist_counts, bin_edges = histogram(data, density=False)\n",
     "\n",
     "print(f\"Number of bins: {len(hist_counts)}\")\n",
     "print(f\"Bin edges: {bin_edges}\")\n",
@@ -331,7 +331,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 35,
    "id": "55ee75b7",
    "metadata": {},
    "outputs": [
@@ -354,7 +354,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 36,
    "id": "33828aaa",
    "metadata": {},
    "outputs": [
@@ -398,7 +398,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 37,
    "id": "247c1571",
    "metadata": {},
    "outputs": [
@@ -408,7 +408,7 @@
        "Text(0, 0.5, 'Cumulative probability')"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -446,7 +446,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 38,
    "id": "03285190",
    "metadata": {},
    "outputs": [
@@ -486,13 +486,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 39,
    "id": "b93b2015",
    "metadata": {},
    "outputs": [
     {
      "data": {
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",
       "text/plain": [
        "<Figure size 1500x800 with 6 Axes>"
       ]
@@ -502,25 +502,39 @@
     }
    ],
    "source": [
-    "# Each level carries densities, so we visualize the series as densities\n",
-    "n_levels = min(6, len(results))\n",
+    "# Visualize selected resolutions through the public plotting API\n",
+    "best_result = next(result for result in results if result.is_best)\n",
+    "coarser_limits = sorted(\n",
+    "    {\n",
+    "        len(result)\n",
+    "        for result in results\n",
+    "        if result.granularity < best_result.granularity\n",
+    "        and len(result) < len(best_result)\n",
+    "    }\n",
+    ")\n",
+    "max_bins_values = coarser_limits[-5:] + [None]\n",
+    "\n",
     "fig, axes = plt.subplots(2, 3, figsize=(15, 8))\n",
     "axes = axes.flatten()\n",
     "\n",
-    "for i, result in enumerate(results[n_levels:]):\n",
-    "    ax = axes[i]\n",
-    "    ax.stairs(result.densities, result.bin_edges, fill=True, alpha=0.7,\n",
-    "              color=\"steelblue\")\n",
-    "    title = f\"Granularity {result.granularity} ({len(result.frequencies)} bins)\"\n",
-    "    if result.is_best:\n",
-    "        title += \" — BEST\"\n",
+    "for ax, max_bins in zip(axes, max_bins_values, strict=False):\n",
+    "    density, _, _ = hist(\n",
+    "        data,\n",
+    "        max_bins=max_bins,\n",
+    "        density=True,\n",
+    "        ax=ax,\n",
+    "        color=\"steelblue\",\n",
+    "        alpha=0.7,\n",
+    "    )\n",
+    "    if max_bins is None:\n",
+    "        ax.set_title(f\"Best histogram ({len(density)} bins)\")\n",
     "        ax.set_facecolor(\"aliceblue\")\n",
-    "    ax.set_title(title)\n",
+    "    else:\n",
+    "        ax.set_title(f\"max_bins={max_bins} ({len(density)} bins selected)\")\n",
     "    ax.set_xlabel(\"Value\")\n",
     "    ax.set_ylabel(\"Density\")\n",
     "\n",
-    "# Hide any unused axes\n",
-    "for ax in axes[n_levels:]:\n",
+    "for ax in axes[len(max_bins_values):]:\n",
     "    ax.set_visible(False)\n",
     "\n",
     "plt.tight_layout()\n",
@@ -542,8 +556,7 @@
     "3. **`khisto.core.compute_histograms`** — full control over the granularity\n",
     "   series, with `HistogramResult` exposing counts, probabilities and densities.\n",
     "\n",
-    "To go further, the\n",
-    "[Khiops histograms guide](https://github.com/KhiopsML/khiops-doc/blob/dev/docs/learn/histograms.md)\n",
+    "To go further, [Histograms - Khiops](https://khiops.org/learn/histograms/)\n",
     "builds the intuition from the simplest histogram to the most complex."
    ]
   }
diff --git a/docs/images/counts-vs-density.png b/docs/images/counts-vs-density.png
new file mode 100644
index 0000000..2b8bfbd
Binary files /dev/null and b/docs/images/counts-vs-density.png differ
diff --git a/docs/index.rst b/docs/index.rst
index f9709e7..cc53208 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -28,6 +28,12 @@ Khisto — Histograms that fit your data
 Get started
 -----------
 
+.. admonition:: Density by default
+   :class: important
+
+   Unlike NumPy and Matplotlib, Khisto uses density by default.
+   :doc:`Learn how to read variable-width histograms <counts_vs_density>`.
+
 .. div:: install-cmd
 
    .. code-block:: bash
@@ -74,6 +80,23 @@ Get started
 
       A runnable notebook tour covering all features.
 
+.. grid:: 1 1 2 2
+   :gutter: 3
+   :class-container: sd-mt-3
+
+   .. grid-item-card:: :octicon:`law;1.5em` Counts or density?
+      :link: counts_vs_density
+      :link-type: doc
+
+      See why counts mislead when bins have different widths.
+
+   .. grid-item-card:: :octicon:`info;1.5em` Histograms - Khiops
+      :link: https://khiops.org/learn/histograms/
+      :link-type: url
+      :class-card: histogram-guide-card
+
+      Go further, from the simplest histogram to the most complex.
+
 .. toctree::
    :maxdepth: 2
    :caption: API Reference
@@ -89,3 +112,4 @@ Get started
    :hidden:
 
    Demo <demo>
+   Counts vs density <counts_vs_density>
diff --git a/pyproject.toml b/pyproject.toml
index 6e723c7..2479c45 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -131,7 +131,6 @@ ignore = [
 [tool.scikit-build]
 wheel.py-api = "py3"             # We specify full compatibility with all Python 3 releases
 cmake.version = "CMakeLists.txt" # Read CMake minimal version from file
-cmake.args = ["-G", "Ninja"]     # Generator specification and build configuration
 
 # CMake variables
 # Build khisto binary in Release mode for better performance, as it is not intended for debugging
@@ -143,7 +142,7 @@ cmake.define.BUILD_LEX_YACC = false
 cmake.define.BUILD_JARS = false
 cmake.define.GENERATE_VIEWS = false
 cmake.define.C11 = true
-ninja.make-fallback = false
+ninja.make-fallback = true
 build.targets = ["khisto"]      # Build only khisto
 install.components = ["KHISTO"] # Only install KHISTO component in wheel
 
diff --git a/scripts/generate_distribution_examples.py b/scripts/generate_distribution_examples.py
index 9942102..37b8331 100644
--- a/scripts/generate_distribution_examples.py
+++ b/scripts/generate_distribution_examples.py
@@ -11,7 +11,6 @@
 
 from khisto.matplotlib import hist
 
-
 SEED = 42
 SAMPLE_SIZE = 10_000
 PARETO_SHAPE = 3.0
@@ -42,6 +41,86 @@ def save_gaussian_figure(data: np.ndarray, output_path: Path) -> None:
     plt.close(fig)
 
 
+def save_counts_density_comparison_figure(output_path: Path) -> None:
+    equal_edges = np.array([0, 10, 20, 30, 40])
+    equal_counts = np.array([90, 110, 100, 200])
+    variable_edges = np.array([0, 30, 40])
+    variable_counts = np.array([300, 200])
+    total_count = equal_counts.sum()
+
+    fig, axes = plt.subplots(2, 2, figsize=(9, 5.5), sharex=True)
+    configurations = (
+        (equal_edges, equal_counts, "Without Khisto\nEqual-width bins"),
+        (variable_edges, variable_counts, "With Khisto\nVariable-width bins"),
+    )
+    for column, (edges, counts, title) in enumerate(configurations):
+        widths = np.diff(edges)
+        densities = counts / (total_count * widths)
+        colors = ["darkorange" if edge >= 30 else "steelblue" for edge in edges[:-1]]
+        count_bars = axes[0, column].bar(
+            edges[:-1], counts, width=widths, align="edge", color=colors,
+            edgecolor="white",
+        )
+        density_bars = axes[1, column].bar(
+            edges[:-1], densities, width=widths, align="edge", color=colors,
+            edgecolor="white",
+        )
+        axes[0, column].bar_label(count_bars, labels=[str(count) for count in counts], padding=3)
+        axes[1, column].bar_label(
+            density_bars,
+            labels=[f"{density:.3f}" for density in densities],
+            padding=3,
+        )
+        axes[0, column].set_title(title)
+        for row in range(2):
+            axes[row, column].set_xticks([0, 10, 20, 30, 40])
+            axes[row, column].tick_params(axis="x", labelbottom=True)
+            axes[row, column].set_xlabel("Value")
+        axes[0, column].set_ylim(0, 350)
+        axes[1, column].set_ylim(0, 0.048)
+
+    axes[0, 0].set_ylabel("Count")
+    axes[1, 0].set_ylabel("Density")
+    axes[0, 0].text(
+        15,
+        165,
+        "Small local fluctuation",
+        ha="center",
+    )
+    axes[0, 1].text(
+        15,
+        245,
+        "Counts apply to the whole interval;\ndo not rely on rectangle area",
+        color="white",
+        ha="center",
+        va="center",
+        weight="bold",
+        fontsize=9,
+    )
+    axes[1, 1].text(
+        15,
+        0.012,
+        "Fluctuation smoothed out\nin the wider bin",
+        color="white",
+        ha="center",
+        va="center",
+        weight="bold",
+    )
+    axes[1, 1].annotate(
+        "bin 30–40 is twice \nas dense as bin 0-30",
+        xy=(35, 0.034),
+        xytext=(15, 0.034),
+        arrowprops={"arrowstyle": "->", "color": "#333333"},
+        ha="center",
+        va="center",
+        weight="bold",
+    )
+    fig.suptitle("Same 500 observations, two binning choices")
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=180)
+    plt.close(fig)
+
+
 def save_pareto_figure(data: np.ndarray, output_path: Path) -> None:
     fig, ax = plt.subplots(figsize=(7, 4.5))
     hist(data, density=True, ax=ax, color="darkorange", edgecolor="white", linewidth=0.8)
@@ -64,6 +143,9 @@ def main() -> None:
     pareto_data = generate_pareto_data()
 
     save_gaussian_figure(gaussian_data, images_dir / "gaussian-quick-start.png")
+    save_counts_density_comparison_figure(
+        images_dir / "counts-vs-density.png"
+    )
     save_pareto_figure(pareto_data, images_dir / "pareto-quick-start.png")
 
     print(f"Gaussian sample: size={gaussian_data.size}, mean={gaussian_data.mean():.4f}, std={gaussian_data.std():.4f}")
@@ -72,6 +154,7 @@ def main() -> None:
         f"size={pareto_data.size}, min={pareto_data.min():.4f}, max={pareto_data.max():.4f}, shape={PARETO_SHAPE:.1f}"
     )
     print(f"Wrote {images_dir / 'gaussian-quick-start.png'}")
+    print(f"Wrote {images_dir / 'counts-vs-density.png'}")
     print(f"Wrote {images_dir / 'pareto-quick-start.png'}")