diff --git a/docs/47_clustering/umap.ipynb b/docs/47_clustering/umap.ipynb
index 3f98810f..2a5230fa 100644
--- a/docs/47_clustering/umap.ipynb
+++ b/docs/47_clustering/umap.ipynb
@@ -1101,7 +1101,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,
diff --git a/docs/51_plotting/feature_correlation.ipynb b/docs/51_plotting/feature_correlation.ipynb
new file mode 100644
index 00000000..17cab728
--- /dev/null
+++ b/docs/51_plotting/feature_correlation.ipynb
@@ -0,0 +1,845 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bea6da31-a5ef-4b44-b96c-7570e8659b34",
+   "metadata": {},
+   "source": [
+    "# Feature correlation\n",
+    "\n",
+    "When inspecting feature extraction results, it is often important to take releationships between features into account. Therefore, a feature correlation matrix is a useful tool. Visualizing it in color is recommended."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "307300eb-b787-48a7-b7a5-1fbb8b5266e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from napari_simpleitk_image_processing import label_statistics\n",
+    "import numpy as np\n",
+    "import seaborn\n",
+    "import pyclesperanto_prototype as cle\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "61828c9a-b6bc-4623-b391-88a35f112ff9",
+   "metadata": {},
+   "source": [
+    "### Load data\n",
+    "We first load the image data that will be used for feature extraction."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "63828c9a-b6bc-4623-b391-88a35f112ff9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\haase\\miniconda3\\envs\\bio311\\Lib\\site-packages\\pyclesperanto_prototype\\_tier9\\_imread.py:5: UserWarning: cle.imread is deprecated, use skimage.io.imread instead.\n",
+      "  warnings.warn(\"cle.imread is deprecated, use skimage.io.imread instead.\")\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>label</th>\n",
+       "      <th>maximum</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>minimum</th>\n",
+       "      <th>variance</th>\n",
+       "      <th>elongation</th>\n",
+       "      <th>feret_diameter</th>\n",
+       "      <th>flatness</th>\n",
+       "      <th>roundness</th>\n",
+       "      <th>equivalent_spherical_radius</th>\n",
+       "      <th>number_of_pixels</th>\n",
+       "      <th>perimeter</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>143.0</td>\n",
+       "      <td>117.489451</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>90.056032</td>\n",
+       "      <td>1.228690</td>\n",
+       "      <td>8.774964</td>\n",
+       "      <td>1.153618</td>\n",
+       "      <td>0.965657</td>\n",
+       "      <td>3.839016</td>\n",
+       "      <td>237</td>\n",
+       "      <td>191.790349</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>83.052219</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>94.086271</td>\n",
+       "      <td>1.325096</td>\n",
+       "      <td>13.152946</td>\n",
+       "      <td>1.215572</td>\n",
+       "      <td>0.818905</td>\n",
+       "      <td>4.505089</td>\n",
+       "      <td>383</td>\n",
+       "      <td>311.446414</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>130.0</td>\n",
+       "      <td>108.930403</td>\n",
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+       "      <td>1.565911</td>\n",
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+       "      <td>1.434476</td>\n",
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+       "      <td>4.024309</td>\n",
+       "      <td>273</td>\n",
+       "      <td>252.130963</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>129.0</td>\n",
+       "      <td>94.576991</td>\n",
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+       "      <td>565</td>\n",
+       "      <td>396.766310</td>\n",
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+       "      <th>4</th>\n",
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+       "      <td>149.0</td>\n",
+       "      <td>119.454545</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>144.431321</td>\n",
+       "      <td>1.429829</td>\n",
+       "      <td>10.723805</td>\n",
+       "      <td>1.269121</td>\n",
+       "      <td>0.871680</td>\n",
+       "      <td>4.034113</td>\n",
+       "      <td>275</td>\n",
+       "      <td>234.611278</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
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+       "      <td>29.0</td>\n",
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+       "      <td>1.107046</td>\n",
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+       "      <td>1.307962</td>\n",
+       "      <td>0.976306</td>\n",
+       "      <td>4.863917</td>\n",
+       "      <td>482</td>\n",
+       "      <td>304.506355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1196</th>\n",
+       "      <td>1197</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>47.673267</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>159.330772</td>\n",
+       "      <td>1.046951</td>\n",
+       "      <td>12.409674</td>\n",
+       "      <td>1.236147</td>\n",
+       "      <td>0.962602</td>\n",
+       "      <td>5.526416</td>\n",
+       "      <td>707</td>\n",
+       "      <td>398.703613</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1197</th>\n",
+       "      <td>1198</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>41.502890</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>28.123180</td>\n",
+       "      <td>1.042599</td>\n",
+       "      <td>9.643651</td>\n",
+       "      <td>1.330995</td>\n",
+       "      <td>0.965376</td>\n",
+       "      <td>4.355077</td>\n",
+       "      <td>346</td>\n",
+       "      <td>246.890816</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1198</th>\n",
+       "      <td>1199</td>\n",
+       "      <td>72.0</td>\n",
+       "      <td>45.091570</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>106.316202</td>\n",
+       "      <td>1.114285</td>\n",
+       "      <td>12.961481</td>\n",
+       "      <td>1.269182</td>\n",
+       "      <td>0.962037</td>\n",
+       "      <td>5.476460</td>\n",
+       "      <td>688</td>\n",
+       "      <td>391.758021</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1199</th>\n",
+       "      <td>1200</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>44.232682</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>67.484909</td>\n",
+       "      <td>1.203239</td>\n",
+       "      <td>12.206556</td>\n",
+       "      <td>1.381601</td>\n",
+       "      <td>0.961668</td>\n",
+       "      <td>5.122397</td>\n",
+       "      <td>563</td>\n",
+       "      <td>342.871234</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1200 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      label  maximum        mean  minimum    variance  elongation  \\\n",
+       "0         1    143.0  117.489451     93.0   90.056032    1.228690   \n",
+       "1         2    113.0   83.052219     65.0   94.086271    1.325096   \n",
+       "2         3    130.0  108.930403     92.0   57.109109    1.565911   \n",
+       "3         4    129.0   94.576991     70.0  130.716136    1.227027   \n",
+       "4         5    149.0  119.454545     89.0  144.431321    1.429829   \n",
+       "...     ...      ...         ...      ...         ...         ...   \n",
+       "1195   1196     60.0   42.118257     29.0   50.270809    1.107046   \n",
+       "1196   1197     83.0   47.673267     29.0  159.330772    1.046951   \n",
+       "1197   1198     53.0   41.502890     30.0   28.123180    1.042599   \n",
+       "1198   1199     72.0   45.091570     29.0  106.316202    1.114285   \n",
+       "1199   1200     66.0   44.232682     29.0   67.484909    1.203239   \n",
+       "\n",
+       "      feret_diameter  flatness  roundness  equivalent_spherical_radius  \\\n",
+       "0           8.774964  1.153618   0.965657                     3.839016   \n",
+       "1          13.152946  1.215572   0.818905                     4.505089   \n",
+       "2          12.884099  1.434476   0.807173                     4.024309   \n",
+       "3          14.352700  1.397276   0.833006                     5.128456   \n",
+       "4          10.723805  1.269121   0.871680                     4.034113   \n",
+       "...              ...       ...        ...                          ...   \n",
+       "1195       11.090537  1.307962   0.976306                     4.863917   \n",
+       "1196       12.409674  1.236147   0.962602                     5.526416   \n",
+       "1197        9.643651  1.330995   0.965376                     4.355077   \n",
+       "1198       12.961481  1.269182   0.962037                     5.476460   \n",
+       "1199       12.206556  1.381601   0.961668                     5.122397   \n",
+       "\n",
+       "      number_of_pixels   perimeter  \n",
+       "0                  237  191.790349  \n",
+       "1                  383  311.446414  \n",
+       "2                  273  252.130963  \n",
+       "3                  565  396.766310  \n",
+       "4                  275  234.611278  \n",
+       "...                ...         ...  \n",
+       "1195               482  304.506355  \n",
+       "1196               707  398.703613  \n",
+       "1197               346  246.890816  \n",
+       "1198               688  391.758021  \n",
+       "1199               563  342.871234  \n",
+       "\n",
+       "[1200 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Load data\n",
+    "image = cle.imread(\"../../data/Lund-25MB.tif\")\n",
+    "\n",
+    "# Segment nuclei\n",
+    "background_subtracted = cle.top_hat_box(image, radius_x=5, radius_y=5)\n",
+    "labels = cle.voronoi_otsu_labeling(background_subtracted, spot_sigma=1)\n",
+    "\n",
+    "# Feature extraction\n",
+    "nuclei_statistics = label_statistics(image, labels, \n",
+    "                                     intensity=True, \n",
+    "                                     size=True, \n",
+    "                                     shape=True, \n",
+    "                                     perimeter=True,\n",
+    "                                     moments=True)\n",
+    "\n",
+    "# Feature selection\n",
+    "selected_table = nuclei_statistics[\n",
+    "    [\n",
+    "       # likely unrelated features\n",
+    "       'label', \n",
+    "        \n",
+    "       # intensity releated features\n",
+    "       'maximum', 'mean', 'minimum', 'variance',\n",
+    "        \n",
+    "       # shape related features \n",
+    "       'elongation', 'feret_diameter', 'flatness', 'roundness',\n",
+    "\n",
+    "       # size related features\n",
+    "       'equivalent_spherical_radius', 'number_of_pixels', 'perimeter'\n",
+    "    ]\n",
+    "]\n",
+    "selected_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1efc67e1-3919-4141-b881-0323cfd6f5cb",
+   "metadata": {},
+   "source": [
+    "### Correlation matrix\n",
+    "We examine the correlation between the selected features to understand their relationships."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5efc67e1-3919-4141-b881-0323cfd6f5cb",
+   "metadata": {},
+   "outputs": [
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+       "  background-color: #9bbcff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row2_col7, #T_36ff2_row7_col2 {\n",
+       "  background-color: #d3dbe7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row2_col9, #T_36ff2_row9_col2 {\n",
+       "  background-color: #5f7fe8;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row2_col10, #T_36ff2_row10_col2 {\n",
+       "  background-color: #5a78e4;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row2_col11, #T_36ff2_row11_col2 {\n",
+       "  background-color: #7295f4;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row3_col4, #T_36ff2_row4_col3 {\n",
+       "  background-color: #85a8fc;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row3_col5, #T_36ff2_row5_col3 {\n",
+       "  background-color: #e3d9d3;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row3_col6, #T_36ff2_row6_col3 {\n",
+       "  background-color: #7da0f9;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row3_col9, #T_36ff2_row9_col3 {\n",
+       "  background-color: #4055c8;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row3_col11, #T_36ff2_row11_col3 {\n",
+       "  background-color: #536edd;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row4_col5, #T_36ff2_row5_col4 {\n",
+       "  background-color: #97b8ff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row4_col6, #T_36ff2_row6_col4 {\n",
+       "  background-color: #f4c6af;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row4_col7, #T_36ff2_row5_col11, #T_36ff2_row7_col4, #T_36ff2_row7_col11, #T_36ff2_row11_col5, #T_36ff2_row11_col7 {\n",
+       "  background-color: #adc9fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row4_col9, #T_36ff2_row4_col10, #T_36ff2_row9_col4, #T_36ff2_row10_col4 {\n",
+       "  background-color: #f7b093;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row4_col11, #T_36ff2_row11_col4 {\n",
+       "  background-color: #f7ad90;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row5_col6, #T_36ff2_row6_col5 {\n",
+       "  background-color: #dedcdb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row5_col7, #T_36ff2_row7_col5 {\n",
+       "  background-color: #cfdaea;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row5_col8, #T_36ff2_row8_col5 {\n",
+       "  background-color: #6788ee;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row5_col9, #T_36ff2_row9_col5 {\n",
+       "  background-color: #9fbfff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row5_col10, #T_36ff2_row10_col5 {\n",
+       "  background-color: #a5c3fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row6_col7, #T_36ff2_row7_col6 {\n",
+       "  background-color: #cdd9ec;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row6_col8, #T_36ff2_row8_col6 {\n",
+       "  background-color: #94b6ff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row6_col9, #T_36ff2_row9_col6 {\n",
+       "  background-color: #d24b40;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row6_col10, #T_36ff2_row10_col6 {\n",
+       "  background-color: #df634e;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row6_col11, #T_36ff2_row11_col6 {\n",
+       "  background-color: #cb3e38;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row7_col8, #T_36ff2_row8_col7 {\n",
+       "  background-color: #6282ea;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row7_col9, #T_36ff2_row9_col7 {\n",
+       "  background-color: #a7c5fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row7_col10, #T_36ff2_row10_col7 {\n",
+       "  background-color: #a2c1ff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row8_col9, #T_36ff2_row9_col8 {\n",
+       "  background-color: #e4d9d2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row8_col10, #T_36ff2_row10_col8 {\n",
+       "  background-color: #f1ccb8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row8_col11, #T_36ff2_row11_col8 {\n",
+       "  background-color: #d7dce3;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_36ff2_row9_col10, #T_36ff2_row10_col9 {\n",
+       "  background-color: #c0282f;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row9_col11, #T_36ff2_row11_col9 {\n",
+       "  background-color: #b8122a;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_36ff2_row10_col11, #T_36ff2_row11_col10 {\n",
+       "  background-color: #bb1b2c;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "</style>\n",
+       "<table id=\"T_36ff2\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th class=\"blank level0\" >&nbsp;</th>\n",
+       "      <th id=\"T_36ff2_level0_col0\" class=\"col_heading level0 col0\" >label</th>\n",
+       "      <th id=\"T_36ff2_level0_col1\" class=\"col_heading level0 col1\" >maximum</th>\n",
+       "      <th id=\"T_36ff2_level0_col2\" class=\"col_heading level0 col2\" >mean</th>\n",
+       "      <th id=\"T_36ff2_level0_col3\" class=\"col_heading level0 col3\" >minimum</th>\n",
+       "      <th id=\"T_36ff2_level0_col4\" class=\"col_heading level0 col4\" >variance</th>\n",
+       "      <th id=\"T_36ff2_level0_col5\" class=\"col_heading level0 col5\" >elongation</th>\n",
+       "      <th id=\"T_36ff2_level0_col6\" class=\"col_heading level0 col6\" >feret_diameter</th>\n",
+       "      <th id=\"T_36ff2_level0_col7\" class=\"col_heading level0 col7\" >flatness</th>\n",
+       "      <th id=\"T_36ff2_level0_col8\" class=\"col_heading level0 col8\" >roundness</th>\n",
+       "      <th id=\"T_36ff2_level0_col9\" class=\"col_heading level0 col9\" >equivalent_spherical_radius</th>\n",
+       "      <th id=\"T_36ff2_level0_col10\" class=\"col_heading level0 col10\" >number_of_pixels</th>\n",
+       "      <th id=\"T_36ff2_level0_col11\" class=\"col_heading level0 col11\" >perimeter</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row0\" class=\"row_heading level0 row0\" >label</th>\n",
+       "      <td id=\"T_36ff2_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row0_col1\" class=\"data row0 col1\" >-0.605035</td>\n",
+       "      <td id=\"T_36ff2_row0_col2\" class=\"data row0 col2\" >-0.651268</td>\n",
+       "      <td id=\"T_36ff2_row0_col3\" class=\"data row0 col3\" >-0.581233</td>\n",
+       "      <td id=\"T_36ff2_row0_col4\" class=\"data row0 col4\" >-0.134539</td>\n",
+       "      <td id=\"T_36ff2_row0_col5\" class=\"data row0 col5\" >-0.014857</td>\n",
+       "      <td id=\"T_36ff2_row0_col6\" class=\"data row0 col6\" >0.105859</td>\n",
+       "      <td id=\"T_36ff2_row0_col7\" class=\"data row0 col7\" >-0.066384</td>\n",
+       "      <td id=\"T_36ff2_row0_col8\" class=\"data row0 col8\" >0.381267</td>\n",
+       "      <td id=\"T_36ff2_row0_col9\" class=\"data row0 col9\" >0.251968</td>\n",
+       "      <td id=\"T_36ff2_row0_col10\" class=\"data row0 col10\" >0.246869</td>\n",
+       "      <td id=\"T_36ff2_row0_col11\" class=\"data row0 col11\" >0.190365</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row1\" class=\"row_heading level0 row1\" >maximum</th>\n",
+       "      <td id=\"T_36ff2_row1_col0\" class=\"data row1 col0\" >-0.605035</td>\n",
+       "      <td id=\"T_36ff2_row1_col1\" class=\"data row1 col1\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row1_col2\" class=\"data row1 col2\" >0.824653</td>\n",
+       "      <td id=\"T_36ff2_row1_col3\" class=\"data row1 col3\" >0.577706</td>\n",
+       "      <td id=\"T_36ff2_row1_col4\" class=\"data row1 col4\" >0.563160</td>\n",
+       "      <td id=\"T_36ff2_row1_col5\" class=\"data row1 col5\" >-0.028076</td>\n",
+       "      <td id=\"T_36ff2_row1_col6\" class=\"data row1 col6\" >0.144944</td>\n",
+       "      <td id=\"T_36ff2_row1_col7\" class=\"data row1 col7\" >0.025563</td>\n",
+       "      <td id=\"T_36ff2_row1_col8\" class=\"data row1 col8\" >-0.485114</td>\n",
+       "      <td id=\"T_36ff2_row1_col9\" class=\"data row1 col9\" >-0.011892</td>\n",
+       "      <td id=\"T_36ff2_row1_col10\" class=\"data row1 col10\" >-0.035078</td>\n",
+       "      <td id=\"T_36ff2_row1_col11\" class=\"data row1 col11\" >0.068570</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row2\" class=\"row_heading level0 row2\" >mean</th>\n",
+       "      <td id=\"T_36ff2_row2_col0\" class=\"data row2 col0\" >-0.651268</td>\n",
+       "      <td id=\"T_36ff2_row2_col1\" class=\"data row2 col1\" >0.824653</td>\n",
+       "      <td id=\"T_36ff2_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row2_col3\" class=\"data row2 col3\" >0.918750</td>\n",
+       "      <td id=\"T_36ff2_row2_col4\" class=\"data row2 col4\" >0.052848</td>\n",
+       "      <td id=\"T_36ff2_row2_col5\" class=\"data row2 col5\" >0.122359</td>\n",
+       "      <td id=\"T_36ff2_row2_col6\" class=\"data row2 col6\" >-0.173872</td>\n",
+       "      <td id=\"T_36ff2_row2_col7\" class=\"data row2 col7\" >0.112322</td>\n",
+       "      <td id=\"T_36ff2_row2_col8\" class=\"data row2 col8\" >-0.644827</td>\n",
+       "      <td id=\"T_36ff2_row2_col9\" class=\"data row2 col9\" >-0.451865</td>\n",
+       "      <td id=\"T_36ff2_row2_col10\" class=\"data row2 col10\" >-0.478943</td>\n",
+       "      <td id=\"T_36ff2_row2_col11\" class=\"data row2 col11\" >-0.362011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row3\" class=\"row_heading level0 row3\" >minimum</th>\n",
+       "      <td id=\"T_36ff2_row3_col0\" class=\"data row3 col0\" >-0.581233</td>\n",
+       "      <td id=\"T_36ff2_row3_col1\" class=\"data row3 col1\" >0.577706</td>\n",
+       "      <td id=\"T_36ff2_row3_col2\" class=\"data row3 col2\" >0.918750</td>\n",
+       "      <td id=\"T_36ff2_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row3_col4\" class=\"data row3 col4\" >-0.273489</td>\n",
+       "      <td id=\"T_36ff2_row3_col5\" class=\"data row3 col5\" >0.217240</td>\n",
+       "      <td id=\"T_36ff2_row3_col6\" class=\"data row3 col6\" >-0.311868</td>\n",
+       "      <td id=\"T_36ff2_row3_col7\" class=\"data row3 col7\" >0.148296</td>\n",
+       "      <td id=\"T_36ff2_row3_col8\" class=\"data row3 col8\" >-0.600965</td>\n",
+       "      <td id=\"T_36ff2_row3_col9\" class=\"data row3 col9\" >-0.615060</td>\n",
+       "      <td id=\"T_36ff2_row3_col10\" class=\"data row3 col10\" >-0.604247</td>\n",
+       "      <td id=\"T_36ff2_row3_col11\" class=\"data row3 col11\" >-0.521081</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row4\" class=\"row_heading level0 row4\" >variance</th>\n",
+       "      <td id=\"T_36ff2_row4_col0\" class=\"data row4 col0\" >-0.134539</td>\n",
+       "      <td id=\"T_36ff2_row4_col1\" class=\"data row4 col1\" >0.563160</td>\n",
+       "      <td id=\"T_36ff2_row4_col2\" class=\"data row4 col2\" >0.052848</td>\n",
+       "      <td id=\"T_36ff2_row4_col3\" class=\"data row4 col3\" >-0.273489</td>\n",
+       "      <td id=\"T_36ff2_row4_col4\" class=\"data row4 col4\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row4_col5\" class=\"data row4 col5\" >-0.191963</td>\n",
+       "      <td id=\"T_36ff2_row4_col6\" class=\"data row4 col6\" >0.370870</td>\n",
+       "      <td id=\"T_36ff2_row4_col7\" class=\"data row4 col7\" >-0.084841</td>\n",
+       "      <td id=\"T_36ff2_row4_col8\" class=\"data row4 col8\" >0.069065</td>\n",
+       "      <td id=\"T_36ff2_row4_col9\" class=\"data row4 col9\" >0.485770</td>\n",
+       "      <td id=\"T_36ff2_row4_col10\" class=\"data row4 col10\" >0.490167</td>\n",
+       "      <td id=\"T_36ff2_row4_col11\" class=\"data row4 col11\" >0.500228</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row5\" class=\"row_heading level0 row5\" >elongation</th>\n",
+       "      <td id=\"T_36ff2_row5_col0\" class=\"data row5 col0\" >-0.014857</td>\n",
+       "      <td id=\"T_36ff2_row5_col1\" class=\"data row5 col1\" >-0.028076</td>\n",
+       "      <td id=\"T_36ff2_row5_col2\" class=\"data row5 col2\" >0.122359</td>\n",
+       "      <td id=\"T_36ff2_row5_col3\" class=\"data row5 col3\" >0.217240</td>\n",
+       "      <td id=\"T_36ff2_row5_col4\" class=\"data row5 col4\" >-0.191963</td>\n",
+       "      <td id=\"T_36ff2_row5_col5\" class=\"data row5 col5\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row5_col6\" class=\"data row5 col6\" >0.184445</td>\n",
+       "      <td id=\"T_36ff2_row5_col7\" class=\"data row5 col7\" >0.091196</td>\n",
+       "      <td id=\"T_36ff2_row5_col8\" class=\"data row5 col8\" >-0.418459</td>\n",
+       "      <td id=\"T_36ff2_row5_col9\" class=\"data row5 col9\" >-0.152117</td>\n",
+       "      <td id=\"T_36ff2_row5_col10\" class=\"data row5 col10\" >-0.125144</td>\n",
+       "      <td id=\"T_36ff2_row5_col11\" class=\"data row5 col11\" >-0.083723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row6\" class=\"row_heading level0 row6\" >feret_diameter</th>\n",
+       "      <td id=\"T_36ff2_row6_col0\" class=\"data row6 col0\" >0.105859</td>\n",
+       "      <td id=\"T_36ff2_row6_col1\" class=\"data row6 col1\" >0.144944</td>\n",
+       "      <td id=\"T_36ff2_row6_col2\" class=\"data row6 col2\" >-0.173872</td>\n",
+       "      <td id=\"T_36ff2_row6_col3\" class=\"data row6 col3\" >-0.311868</td>\n",
+       "      <td id=\"T_36ff2_row6_col4\" class=\"data row6 col4\" >0.370870</td>\n",
+       "      <td id=\"T_36ff2_row6_col5\" class=\"data row6 col5\" >0.184445</td>\n",
+       "      <td id=\"T_36ff2_row6_col6\" class=\"data row6 col6\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row6_col7\" class=\"data row6 col7\" >0.083095</td>\n",
+       "      <td id=\"T_36ff2_row6_col8\" class=\"data row6 col8\" >-0.201787</td>\n",
+       "      <td id=\"T_36ff2_row6_col9\" class=\"data row6 col9\" >0.854090</td>\n",
+       "      <td id=\"T_36ff2_row6_col10\" class=\"data row6 col10\" >0.785360</td>\n",
+       "      <td id=\"T_36ff2_row6_col11\" class=\"data row6 col11\" >0.896780</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row7\" class=\"row_heading level0 row7\" >flatness</th>\n",
+       "      <td id=\"T_36ff2_row7_col0\" class=\"data row7 col0\" >-0.066384</td>\n",
+       "      <td id=\"T_36ff2_row7_col1\" class=\"data row7 col1\" >0.025563</td>\n",
+       "      <td id=\"T_36ff2_row7_col2\" class=\"data row7 col2\" >0.112322</td>\n",
+       "      <td id=\"T_36ff2_row7_col3\" class=\"data row7 col3\" >0.148296</td>\n",
+       "      <td id=\"T_36ff2_row7_col4\" class=\"data row7 col4\" >-0.084841</td>\n",
+       "      <td id=\"T_36ff2_row7_col5\" class=\"data row7 col5\" >0.091196</td>\n",
+       "      <td id=\"T_36ff2_row7_col6\" class=\"data row7 col6\" >0.083095</td>\n",
+       "      <td id=\"T_36ff2_row7_col7\" class=\"data row7 col7\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row7_col8\" class=\"data row7 col8\" >-0.438565</td>\n",
+       "      <td id=\"T_36ff2_row7_col9\" class=\"data row7 col9\" >-0.111196</td>\n",
+       "      <td id=\"T_36ff2_row7_col10\" class=\"data row7 col10\" >-0.137907</td>\n",
+       "      <td id=\"T_36ff2_row7_col11\" class=\"data row7 col11\" >-0.085824</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row8\" class=\"row_heading level0 row8\" >roundness</th>\n",
+       "      <td id=\"T_36ff2_row8_col0\" class=\"data row8 col0\" >0.381267</td>\n",
+       "      <td id=\"T_36ff2_row8_col1\" class=\"data row8 col1\" >-0.485114</td>\n",
+       "      <td id=\"T_36ff2_row8_col2\" class=\"data row8 col2\" >-0.644827</td>\n",
+       "      <td id=\"T_36ff2_row8_col3\" class=\"data row8 col3\" >-0.600965</td>\n",
+       "      <td id=\"T_36ff2_row8_col4\" class=\"data row8 col4\" >0.069065</td>\n",
+       "      <td id=\"T_36ff2_row8_col5\" class=\"data row8 col5\" >-0.418459</td>\n",
+       "      <td id=\"T_36ff2_row8_col6\" class=\"data row8 col6\" >-0.201787</td>\n",
+       "      <td id=\"T_36ff2_row8_col7\" class=\"data row8 col7\" >-0.438565</td>\n",
+       "      <td id=\"T_36ff2_row8_col8\" class=\"data row8 col8\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row8_col9\" class=\"data row8 col9\" >0.225241</td>\n",
+       "      <td id=\"T_36ff2_row8_col10\" class=\"data row8 col10\" >0.330182</td>\n",
+       "      <td id=\"T_36ff2_row8_col11\" class=\"data row8 col11\" >0.137811</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row9\" class=\"row_heading level0 row9\" >equivalent_spherical_radius</th>\n",
+       "      <td id=\"T_36ff2_row9_col0\" class=\"data row9 col0\" >0.251968</td>\n",
+       "      <td id=\"T_36ff2_row9_col1\" class=\"data row9 col1\" >-0.011892</td>\n",
+       "      <td id=\"T_36ff2_row9_col2\" class=\"data row9 col2\" >-0.451865</td>\n",
+       "      <td id=\"T_36ff2_row9_col3\" class=\"data row9 col3\" >-0.615060</td>\n",
+       "      <td id=\"T_36ff2_row9_col4\" class=\"data row9 col4\" >0.485770</td>\n",
+       "      <td id=\"T_36ff2_row9_col5\" class=\"data row9 col5\" >-0.152117</td>\n",
+       "      <td id=\"T_36ff2_row9_col6\" class=\"data row9 col6\" >0.854090</td>\n",
+       "      <td id=\"T_36ff2_row9_col7\" class=\"data row9 col7\" >-0.111196</td>\n",
+       "      <td id=\"T_36ff2_row9_col8\" class=\"data row9 col8\" >0.225241</td>\n",
+       "      <td id=\"T_36ff2_row9_col9\" class=\"data row9 col9\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row9_col10\" class=\"data row9 col10\" >0.948357</td>\n",
+       "      <td id=\"T_36ff2_row9_col11\" class=\"data row9 col11\" >0.976222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row10\" class=\"row_heading level0 row10\" >number_of_pixels</th>\n",
+       "      <td id=\"T_36ff2_row10_col0\" class=\"data row10 col0\" >0.246869</td>\n",
+       "      <td id=\"T_36ff2_row10_col1\" class=\"data row10 col1\" >-0.035078</td>\n",
+       "      <td id=\"T_36ff2_row10_col2\" class=\"data row10 col2\" >-0.478943</td>\n",
+       "      <td id=\"T_36ff2_row10_col3\" class=\"data row10 col3\" >-0.604247</td>\n",
+       "      <td id=\"T_36ff2_row10_col4\" class=\"data row10 col4\" >0.490167</td>\n",
+       "      <td id=\"T_36ff2_row10_col5\" class=\"data row10 col5\" >-0.125144</td>\n",
+       "      <td id=\"T_36ff2_row10_col6\" class=\"data row10 col6\" >0.785360</td>\n",
+       "      <td id=\"T_36ff2_row10_col7\" class=\"data row10 col7\" >-0.137907</td>\n",
+       "      <td id=\"T_36ff2_row10_col8\" class=\"data row10 col8\" >0.330182</td>\n",
+       "      <td id=\"T_36ff2_row10_col9\" class=\"data row10 col9\" >0.948357</td>\n",
+       "      <td id=\"T_36ff2_row10_col10\" class=\"data row10 col10\" >1.000000</td>\n",
+       "      <td id=\"T_36ff2_row10_col11\" class=\"data row10 col11\" >0.964439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_36ff2_level0_row11\" class=\"row_heading level0 row11\" >perimeter</th>\n",
+       "      <td id=\"T_36ff2_row11_col0\" class=\"data row11 col0\" >0.190365</td>\n",
+       "      <td id=\"T_36ff2_row11_col1\" class=\"data row11 col1\" >0.068570</td>\n",
+       "      <td id=\"T_36ff2_row11_col2\" class=\"data row11 col2\" >-0.362011</td>\n",
+       "      <td id=\"T_36ff2_row11_col3\" class=\"data row11 col3\" >-0.521081</td>\n",
+       "      <td id=\"T_36ff2_row11_col4\" class=\"data row11 col4\" >0.500228</td>\n",
+       "      <td id=\"T_36ff2_row11_col5\" class=\"data row11 col5\" >-0.083723</td>\n",
+       "      <td id=\"T_36ff2_row11_col6\" class=\"data row11 col6\" >0.896780</td>\n",
+       "      <td id=\"T_36ff2_row11_col7\" class=\"data row11 col7\" >-0.085824</td>\n",
+       "      <td id=\"T_36ff2_row11_col8\" class=\"data row11 col8\" >0.137811</td>\n",
+       "      <td id=\"T_36ff2_row11_col9\" class=\"data row11 col9\" >0.976222</td>\n",
+       "      <td id=\"T_36ff2_row11_col10\" class=\"data row11 col10\" >0.964439</td>\n",
+       "      <td id=\"T_36ff2_row11_col11\" class=\"data row11 col11\" >1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x1d12d58b790>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = selected_table.corr()\n",
+    "\n",
+    "def colorize(styler):\n",
+    "    styler.background_gradient(axis=None, cmap=\"coolwarm\")\n",
+    "    return styler\n",
+    "df.style.pipe(colorize)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f3d87b8d-19b5-44cf-986b-20c01a40b217",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/_toc.yml b/docs/_toc.yml
index ddd14861..73c44020 100644
--- a/docs/_toc.yml
+++ b/docs/_toc.yml
@@ -400,7 +400,7 @@ parts:
       #- file: 47_clustering/dens_map
       #- file: 47_clustering/tissue_clustering
       - file: 47_clustering/interactive_dimensionality_reduction_and_clustering/readme
-      - file: 47_clustering/feature_selection
+      #- file: 47_clustering/feature_selection
       
     - file: 51_plotting/readme
       sections:
@@ -408,6 +408,7 @@ parts:
       - file: 51_plotting/plotting_seaborn
       - file: 51_plotting/plotting_distributions
       - file: 51_plotting/multivariate_views
+      - file: 51_plotting/feature_correlation
       - file: 51_plotting/interpolating_between_feature_spaces
     # plotly