diff --git a/notebooks/example-workflows/part1_radar_image_processing.ipynb b/notebooks/example-workflows/part1_radar_image_processing.ipynb
new file mode 100644
index 0000000..e768dd5
--- /dev/null
+++ b/notebooks/example-workflows/part1_radar_image_processing.ipynb
@@ -0,0 +1,249 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8e1316f1-3245-48e3-894d-73c906430829",
+   "metadata": {},
+   "source": [
+    "## Image Processing with Radar Reflectivity\n",
+    "This program accepts radar scans plotted onto a cartesian grid. The program then thresholds the image to perform image processing and analysis on the largest echo of reflectivity within the image, and outputs a CSV file with the parameters that were calculated for each radar file. </br>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "20d8b66a-458c-4b3f-9653-c65191fc4262",
+   "metadata": {},
+   "source": [
+    "#### Author\n",
+    "<b>Maggie Zoerner</b></br>\n",
+    "Argonne National Laboratory, <i>Environmental Science Division</i></br>\n",
+    "Student Undergraduate Laboratory Intern </br>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0f532b2-9a88-4fc5-a852-dfd37f3e5225",
+   "metadata": {},
+   "source": [
+    "#### Import the libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "47afec8d-2dfa-4503-ad82-cd9212719502",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from netCDF4 import Dataset\n",
+    "from scipy import ndimage\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import cv2\n",
+    "import csv\n",
+    "from glob import glob"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f32221d3-af43-4bd6-9a18-23cc4585f5c3",
+   "metadata": {},
+   "source": [
+    "#### Import the files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "716d89f4-6f90-48a8-8d6b-b95bbbc7d69d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "files = glob('season_grids/KILX2020*')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "12f7b207-62e5-4eeb-8ee8-d625d1d7e2ab",
+   "metadata": {},
+   "source": [
+    "#### In the below step: </br>\n",
+    "\n",
+    "- Go through the data set.\n",
+    "- Remove reflectivities smaller than 35 dBz to remove non-convective precip.\n",
+    "- Clear smaller echoes to remove noise.\n",
+    "- Calculate the raw, central, normalized central, and invariant moments.\n",
+    "- Perform shape computations based on the moments.\n",
+    "- Find the largest external contour of the echo.\n",
+    "- Perform shape computations based on the contours.\n",
+    "- Export computations to CSV file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "63ae9194-7cb8-4b9d-9022-ceacc2280bd6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# LOOP THROUGH THE DATASET\n",
+    "\n",
+    "header_added = False\n",
+    "    \n",
+    "for file in files:\n",
+    "    ncfile = Dataset(file, \"r\")\n",
+    "    ref = ncfile.variables['reflectivity'][:]\n",
+    "    ref = ref.squeeze()\n",
+    "    ref_thre = np.where(ref < 35, 0, ref)\n",
+    "    labeled_echo = ndimage.label(ref_thre)[0]\n",
+    "\n",
+    "    # Remove smaller echoes \n",
+    "    \n",
+    "    def clear_small_echoes(label_image, min_size):\n",
+    "        \"\"\" Takes in binary image and clears objects less than min_size. \"\"\"\n",
+    "        flat_image = pd.Series(label_image.flatten())\n",
+    "        flat_image = flat_image[flat_image > 0]\n",
+    "        size_table = flat_image.value_counts(sort=False)\n",
+    "        small_objects = size_table.keys()[size_table < min_size]\n",
+    "\n",
+    "        for obj in small_objects:\n",
+    "            label_image[label_image == obj] = 0\n",
+    "        label_image = ndimage.label(label_image)\n",
+    "        return label_image[0]\n",
+    "    \n",
+    "    max_echo = clear_small_echoes(labeled_echo, 175)\n",
+    "    \n",
+    "    # Convert to float\n",
+    "\n",
+    "    max_echo = max_echo.astype('float32')\n",
+    "    \n",
+    "    # Calculate geometric moments and moment invariants\n",
+    "    \n",
+    "    moments =cv2.moments(max_echo)\n",
+    "\n",
+    "    Hu_moments = cv2.HuMoments(moments)\n",
+    "    \n",
+    "    # The 0th moment gives the area\n",
+    "    \n",
+    "    M = moments\n",
+    "    area = M['m00']\n",
+    "    \n",
+    "    # Ensure that the area is not equal to zero (as this will mess up future calculations)\n",
+    "    \n",
+    "    try:\n",
+    "        \n",
+    "        # Calculate the center of mass\n",
+    "        Cx = int(M['m10'] / M['m00'])\n",
+    "        Cy = int(M['m01'] / M['m00'])\n",
+    "        \n",
+    "        # The 3rd normalized central moment gives the skewness (the deviation of the respective projection from symmetry)\n",
+    "    \n",
+    "        skewness_x = (M['nu30'])\n",
+    "        skewness_y = (M['nu03'])\n",
+    "\n",
+    "        # Find the deviation from circlular shape\n",
+    "    \n",
+    "        dev_circ = abs(M['nu11'])\n",
+    "    \n",
+    "        # Convert to a format accepted by OpenCV contour analysis\n",
+    "    \n",
+    "        max_echo_u8 = max_echo.astype(np.uint8)\n",
+    "    \n",
+    "        # Find and draw the contours in the image\n",
+    "    \n",
+    "        u8_copy = max_echo_u8.copy()\n",
+    "        contours, hierarchy = cv2.findContours(u8_copy, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
+    "    \n",
+    "        cnt = contours[0]\n",
+    "        contour_image = cv2.drawContours(u8_copy, cnt, -1, (0,255,0),3)\n",
+    "\n",
+    "        # Find the perimeter of the shape\n",
+    "\n",
+    "        perimeter = cv2.arcLength(cnt,True)\n",
+    "    \n",
+    "        # Find the elongation (aspect ratio) of the shape \n",
+    "    \n",
+    "        x,y,w,h = cv2.boundingRect(cnt)\n",
+    "    \n",
+    "        elongation = float(w)/h\n",
+    "\n",
+    "        # Find the equivalent diameter: diameter of a circle whose diameter is the same as the contour area\n",
+    "    \n",
+    "        area = cv2.contourArea(cnt)\n",
+    "        equi_diameter = np.sqrt(4*area/np.pi)\n",
+    "    \n",
+    "        # Find the roundness \n",
+    "    \n",
+    "        roundness = (4*np.pi*(area))/((perimeter)**2)\n",
+    "    \n",
+    "        # Find the compactness \n",
+    "    \n",
+    "        compactness = ((perimeter)**2)/(4*np.pi*(area))\n",
+    "    \n",
+    "        # Find the eccentricity \n",
+    "    \n",
+    "        (x,y),(MA,ma),angle = cv2.fitEllipse(cnt)\n",
+    "        ecc = ma/MA\n",
+    "        \n",
+    "\n",
+    "        # WRITING TO A CSV FILE\n",
+    "    \n",
+    "        # Define header names\n",
+    "    \n",
+    "        headers = ['File Name', 'Area', 'Perimeter', 'Center of Mass (X)', 'Center of Mass (Y)', 'Skewness (X)', 'Skewness (Y)', \n",
+    "                   'Elongation','Equivalent Diameter','Compactness', 'Roundness', 'Eccentricity', 'Deviation from Circle']\n",
+    " \n",
+    "        # Define data to include\n",
+    "    \n",
+    "        rows = [(file), (area), (perimeter), (Cx), (Cy), (skewness_x), (skewness_y), (elongation), (equi_diameter), \n",
+    "                (compactness), (roundness), (ecc), (dev_circ)]\n",
+    " \n",
+    "        # Name the CSV file\n",
+    "    \n",
+    "        filename = \"parameter_computations.csv\"\n",
+    "    \n",
+    "        # Ensure header does not duplicate in loop and populate file\n",
+    "        \n",
+    "        with open(filename, 'a') as csvfile:\n",
+    "            csvwriter = csv.writer(csvfile)\n",
+    "            if not header_added:\n",
+    "                csvwriter.writerow(headers)\n",
+    "                header_added = True\n",
+    "            csvwriter.writerow(rows)\n",
+    "        \n",
+    "    except ZeroDivisionError:\n",
+    "        pass"
+   ]
+  }
+ ],
+ "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": "3.9.12"
+  },
+  "toc-autonumbering": true,
+  "toc-showcode": true,
+  "toc-showmarkdowntxt": false,
+  "toc-showtags": false
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/example-workflows/part2_radar_clustering.ipynb b/notebooks/example-workflows/part2_radar_clustering.ipynb
new file mode 100644
index 0000000..13ff341
--- /dev/null
+++ b/notebooks/example-workflows/part2_radar_clustering.ipynb
@@ -0,0 +1,673 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "120154a7-7e36-44d0-91db-6d29f3751fa5",
+   "metadata": {},
+   "source": [
+    "## Principal Component Analysis and Clustering of Radar Data based on Morphological Parameters\n",
+    "This program acceps a CSV file containing radar files with associated shape parameters. The program then performs principal component analysis to reduce the dimensionality of the dataset and clusters the data based on their similar shape characteristics. The program also creates a correlation matrix to visualize the relationship between the shape parameters."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "45ba1665-aada-428e-8cb9-25355fee401f",
+   "metadata": {},
+   "source": [
+    "#### Author\n",
+    "<b>Maggie Zoerner</b></br>\n",
+    "Argonne National Laboratory, <i>Environmental Science Division</i></br>\n",
+    "Student Undergraduate Laboratory Intern </br>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75a1485d-65d7-45e5-8b9c-a01537488bf8",
+   "metadata": {},
+   "source": [
+    "#### Import the libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "34082550-1012-4307-ab75-f4dd6d2a3a56",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.cluster import KMeans\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.decomposition import PCA\n",
+    "from matplotlib.colors import TwoSlopeNorm\n",
+    "\n",
+    "import pandas as pd\n",
+    "from matplotlib import pyplot as plt\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "\n",
+    "import warnings \n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "548b6efb-1188-4e0f-a6ad-97d99feca55f",
+   "metadata": {},
+   "source": [
+    "#### Read in the file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "55d6feac-4c88-4384-b01d-f32c1758653f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "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>File Name</th>\n",
+       "      <th>Area</th>\n",
+       "      <th>Perimeter</th>\n",
+       "      <th>Center of Mass (X)</th>\n",
+       "      <th>Center of Mass (Y)</th>\n",
+       "      <th>Skewness (X)</th>\n",
+       "      <th>Skewness (Y)</th>\n",
+       "      <th>Elongation</th>\n",
+       "      <th>Equivalent Diameter</th>\n",
+       "      <th>Compactness</th>\n",
+       "      <th>Roundness</th>\n",
+       "      <th>Eccentricity</th>\n",
+       "      <th>Deviation from Circle</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>season_grids\\KILX20200601_171444_V06.nc</td>\n",
+       "      <td>152.5</td>\n",
+       "      <td>109.296463</td>\n",
+       "      <td>96</td>\n",
+       "      <td>280</td>\n",
+       "      <td>-0.023510</td>\n",
+       "      <td>0.004469</td>\n",
+       "      <td>1.250000</td>\n",
+       "      <td>13.934455</td>\n",
+       "      <td>6.233508</td>\n",
+       "      <td>0.160423</td>\n",
+       "      <td>1.237183</td>\n",
+       "      <td>0.043546</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>season_grids\\KILX20200601_171922_V06.nc</td>\n",
+       "      <td>192.0</td>\n",
+       "      <td>115.195958</td>\n",
+       "      <td>101</td>\n",
+       "      <td>279</td>\n",
+       "      <td>-0.029894</td>\n",
+       "      <td>-0.004799</td>\n",
+       "      <td>1.526316</td>\n",
+       "      <td>15.635280</td>\n",
+       "      <td>5.500009</td>\n",
+       "      <td>0.181818</td>\n",
+       "      <td>1.652990</td>\n",
+       "      <td>0.022373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>season_grids\\KILX20200601_173319_V06.nc</td>\n",
+       "      <td>254.5</td>\n",
+       "      <td>195.178713</td>\n",
+       "      <td>115</td>\n",
+       "      <td>275</td>\n",
+       "      <td>-0.041922</td>\n",
+       "      <td>-0.013057</td>\n",
+       "      <td>1.541667</td>\n",
+       "      <td>18.001096</td>\n",
+       "      <td>11.911522</td>\n",
+       "      <td>0.083952</td>\n",
+       "      <td>1.485470</td>\n",
+       "      <td>0.024556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>season_grids\\KILX20200601_181948_V06.nc</td>\n",
+       "      <td>172.0</td>\n",
+       "      <td>101.396968</td>\n",
+       "      <td>159</td>\n",
+       "      <td>255</td>\n",
+       "      <td>-0.031203</td>\n",
+       "      <td>-0.001754</td>\n",
+       "      <td>1.250000</td>\n",
+       "      <td>14.798554</td>\n",
+       "      <td>4.756764</td>\n",
+       "      <td>0.210227</td>\n",
+       "      <td>1.470806</td>\n",
+       "      <td>0.036197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>season_grids\\KILX20200601_183106_V06.nc</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>99.882250</td>\n",
+       "      <td>172</td>\n",
+       "      <td>249</td>\n",
+       "      <td>-0.043504</td>\n",
+       "      <td>0.004506</td>\n",
+       "      <td>1.705882</td>\n",
+       "      <td>15.430353</td>\n",
+       "      <td>4.245464</td>\n",
+       "      <td>0.235546</td>\n",
+       "      <td>1.857598</td>\n",
+       "      <td>0.003848</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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1686</th>\n",
+       "      <td>season_grids\\KILX20200829_063543_V06.nc</td>\n",
+       "      <td>419.5</td>\n",
+       "      <td>151.923880</td>\n",
+       "      <td>285</td>\n",
+       "      <td>210</td>\n",
+       "      <td>-0.027301</td>\n",
+       "      <td>-0.000971</td>\n",
+       "      <td>1.583333</td>\n",
+       "      <td>23.111123</td>\n",
+       "      <td>4.378348</td>\n",
+       "      <td>0.228397</td>\n",
+       "      <td>2.237020</td>\n",
+       "      <td>0.015023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1687</th>\n",
+       "      <td>season_grids\\KILX20200829_065440_V06.nc</td>\n",
+       "      <td>328.0</td>\n",
+       "      <td>135.195958</td>\n",
+       "      <td>289</td>\n",
+       "      <td>200</td>\n",
+       "      <td>-0.072692</td>\n",
+       "      <td>-0.000646</td>\n",
+       "      <td>1.545455</td>\n",
+       "      <td>20.435816</td>\n",
+       "      <td>4.434490</td>\n",
+       "      <td>0.225505</td>\n",
+       "      <td>4.179422</td>\n",
+       "      <td>0.002019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1688</th>\n",
+       "      <td>season_grids\\KILX20200829_070346_V06.nc</td>\n",
+       "      <td>199.5</td>\n",
+       "      <td>123.639609</td>\n",
+       "      <td>289</td>\n",
+       "      <td>194</td>\n",
+       "      <td>-0.109829</td>\n",
+       "      <td>-0.002774</td>\n",
+       "      <td>1.450000</td>\n",
+       "      <td>15.937732</td>\n",
+       "      <td>6.097650</td>\n",
+       "      <td>0.163998</td>\n",
+       "      <td>2.105569</td>\n",
+       "      <td>0.023927</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1689</th>\n",
+       "      <td>season_grids\\KILX20200831_174103_V06.nc</td>\n",
+       "      <td>326.0</td>\n",
+       "      <td>128.710677</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0.035990</td>\n",
+       "      <td>-0.001812</td>\n",
+       "      <td>1.363636</td>\n",
+       "      <td>20.373416</td>\n",
+       "      <td>4.043912</td>\n",
+       "      <td>0.247285</td>\n",
+       "      <td>3.047072</td>\n",
+       "      <td>0.013473</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1690</th>\n",
+       "      <td>season_grids\\KILX20200831_180654_V06.nc</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>186.651801</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.151829</td>\n",
+       "      <td>0.014317</td>\n",
+       "      <td>2.150000</td>\n",
+       "      <td>19.248707</td>\n",
+       "      <td>9.527117</td>\n",
+       "      <td>0.104964</td>\n",
+       "      <td>1.901905</td>\n",
+       "      <td>0.043544</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1691 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                    File Name   Area   Perimeter  \\\n",
+       "0     season_grids\\KILX20200601_171444_V06.nc  152.5  109.296463   \n",
+       "1     season_grids\\KILX20200601_171922_V06.nc  192.0  115.195958   \n",
+       "2     season_grids\\KILX20200601_173319_V06.nc  254.5  195.178713   \n",
+       "3     season_grids\\KILX20200601_181948_V06.nc  172.0  101.396968   \n",
+       "4     season_grids\\KILX20200601_183106_V06.nc  187.0   99.882250   \n",
+       "...                                       ...    ...         ...   \n",
+       "1686  season_grids\\KILX20200829_063543_V06.nc  419.5  151.923880   \n",
+       "1687  season_grids\\KILX20200829_065440_V06.nc  328.0  135.195958   \n",
+       "1688  season_grids\\KILX20200829_070346_V06.nc  199.5  123.639609   \n",
+       "1689  season_grids\\KILX20200831_174103_V06.nc  326.0  128.710677   \n",
+       "1690  season_grids\\KILX20200831_180654_V06.nc  291.0  186.651801   \n",
+       "\n",
+       "      Center of Mass (X)  Center of Mass (Y)  Skewness (X)  Skewness (Y)  \\\n",
+       "0                     96                 280     -0.023510      0.004469   \n",
+       "1                    101                 279     -0.029894     -0.004799   \n",
+       "2                    115                 275     -0.041922     -0.013057   \n",
+       "3                    159                 255     -0.031203     -0.001754   \n",
+       "4                    172                 249     -0.043504      0.004506   \n",
+       "...                  ...                 ...           ...           ...   \n",
+       "1686                 285                 210     -0.027301     -0.000971   \n",
+       "1687                 289                 200     -0.072692     -0.000646   \n",
+       "1688                 289                 194     -0.109829     -0.002774   \n",
+       "1689                  10                  10      0.035990     -0.001812   \n",
+       "1690                  16                   6      0.151829      0.014317   \n",
+       "\n",
+       "      Elongation  Equivalent Diameter  Compactness  Roundness  Eccentricity  \\\n",
+       "0       1.250000            13.934455     6.233508   0.160423      1.237183   \n",
+       "1       1.526316            15.635280     5.500009   0.181818      1.652990   \n",
+       "2       1.541667            18.001096    11.911522   0.083952      1.485470   \n",
+       "3       1.250000            14.798554     4.756764   0.210227      1.470806   \n",
+       "4       1.705882            15.430353     4.245464   0.235546      1.857598   \n",
+       "...          ...                  ...          ...        ...           ...   \n",
+       "1686    1.583333            23.111123     4.378348   0.228397      2.237020   \n",
+       "1687    1.545455            20.435816     4.434490   0.225505      4.179422   \n",
+       "1688    1.450000            15.937732     6.097650   0.163998      2.105569   \n",
+       "1689    1.363636            20.373416     4.043912   0.247285      3.047072   \n",
+       "1690    2.150000            19.248707     9.527117   0.104964      1.901905   \n",
+       "\n",
+       "      Deviation from Circle  \n",
+       "0                  0.043546  \n",
+       "1                  0.022373  \n",
+       "2                  0.024556  \n",
+       "3                  0.036197  \n",
+       "4                  0.003848  \n",
+       "...                     ...  \n",
+       "1686               0.015023  \n",
+       "1687               0.002019  \n",
+       "1688               0.023927  \n",
+       "1689               0.013473  \n",
+       "1690               0.043544  \n",
+       "\n",
+       "[1691 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(\"parameter_computations.csv\")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "627acd46-b4f0-41fa-9bd3-f14ab8d51794",
+   "metadata": {},
+   "source": [
+    "#### Normalize the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "dbbd59a9-9ac1-412f-8cc4-c6a4b291b33c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scaler = StandardScaler()\n",
+    "x = df[['Area','Perimeter','Center of Mass (X)','Center of Mass (Y)', 'Skewness (X)',\n",
+    "    'Skewness (Y)','Elongation', 'Equivalent Diameter', 'Compactness', 'Roundness',\n",
+    "    'Eccentricity', 'Deviation from Circle']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8ce74132-b57d-4a70-9315-6b05a52ab2ad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = scaler.fit_transform(x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0b1f7be-769f-4122-a070-9db6253e188e",
+   "metadata": {},
+   "source": [
+    "#### Perform principal component analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "6a909d4a-5f9c-4675-8a51-a9cee4187eb7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# PCA projection to 2D\n",
+    "\n",
+    "pca = PCA(n_components=2)\n",
+    "principalComponents = pca.fit_transform(x)\n",
+    "principalDf = pd.DataFrame(data = principalComponents, columns = ['Principal Component 1', 'Principal Component 2'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d8e86994-28c6-4d1d-89ec-bae99a137456",
+   "metadata": {},
+   "outputs": [
+    {
+     "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>Principal Component 1</th>\n",
+       "      <th>Principal Component 2</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-0.869689</td>\n",
+       "      <td>-0.335356</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-0.933045</td>\n",
+       "      <td>-0.366956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.362193</td>\n",
+       "      <td>-0.234775</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-1.154073</td>\n",
+       "      <td>-0.317920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-1.261497</td>\n",
+       "      <td>-0.366325</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Principal Component 1  Principal Component 2\n",
+       "0              -0.869689              -0.335356\n",
+       "1              -0.933045              -0.366956\n",
+       "2               0.362193              -0.234775\n",
+       "3              -1.154073              -0.317920\n",
+       "4              -1.261497              -0.366325"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "principalDf.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e6f0c661-3c4d-4cef-bdbb-54dd58a839f0",
+   "metadata": {},
+   "source": [
+    "#### Determine the optimal number of clusters using the elbow method"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c30fba95-c8bd-4508-a3ba-cc20aeb8053c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def optimise_k_means(data, max_k):\n",
+    "    means = []\n",
+    "    inertias = []\n",
+    "    \n",
+    "    for k in range(1, max_k):\n",
+    "        kmeans = KMeans(n_clusters = k)\n",
+    "        kmeans.fit(data)\n",
+    "        \n",
+    "        means.append(k)\n",
+    "        inertias.append(kmeans.inertia_)\n",
+    "        \n",
+    "    # Generate the elbow plot\n",
+    "    fig = plt.subplots(figsize = (10,5))\n",
+    "    plt.plot(means, inertias, 'o-')\n",
+    "    plt.xlabel('Number of Clusters', fontsize =12)\n",
+    "    plt.ylabel('Inertia', fontsize =12)\n",
+    "    plt.xticks(fontsize =12)\n",
+    "    plt.yticks(fontsize=12)\n",
+    "    plt.grid(True)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "dcd56dd8-8e9c-4f6c-b3af-e9e85664b34e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "optimise_k_means(principalComponents, 10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ad41ae09-8d3e-4534-a26a-c34ba905a8db",
+   "metadata": {},
+   "source": [
+    "#### Create the cluster plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2b172233-21c9-4050-a83a-105eab780ec6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kmeans = KMeans(n_clusters = 4).fit(principalComponents)\n",
+    "label = kmeans.labels_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "07da42ec-98d5-4934-a99d-91f3fadd3a14",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plotting with centroids\n",
+    "centroids = kmeans.cluster_centers_\n",
+    "u_labels = np.unique(label)\n",
+    "colors = ['dodgerblue', 'firebrick', 'lightskyblue', 'indianred']\n",
+    "#plotting the results:\n",
+    "for i in u_labels:\n",
+    "    plt.scatter(principalComponents[label == i , 0] , principalComponents[label == i , 1] , label = i+1, color = colors[i])\n",
+    "plt.scatter(centroids[:,0] , centroids[:,1] , s = 80, color = 'k')\n",
+    "plt.title(\"Clustering of PCA\", fontsize = 12)\n",
+    "plt.xlabel('Principal Component 1', fontsize = 12)\n",
+    "plt.ylabel('Principal Component 2', fontsize = 12)\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c50d594-a288-44ab-a1e6-e99d976ca635",
+   "metadata": {},
+   "source": [
+    "#### Create the Correlation Matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "e0395761-e9c0-40a4-8e51-32506f02bed0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "corrM = df.corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "947aba81-a219-4375-ba09-84f1920e46e6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(15,15))\n",
+    "rdbu = sns.diverging_palette(h_neg=-1, h_pos=1, as_cmap=True)\n",
+    "res = sns.heatmap(corrM, cmap='RdBu', center=0.00, annot=True, fmt='.2f', \n",
+    "            linewidths=1, linecolor='black', cbar=True, ax=ax, annot_kws={\"size\": 16})\n",
+    "res.set_xticklabels(res.get_xmajorticklabels(), fontsize = 18)\n",
+    "res.set_yticklabels(res.get_ymajorticklabels(), fontsize = 18)\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "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": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}