"Completed mean, std, min, median, and max calculations"

module2/exo2/exercice.ipynb

 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "data = np.array([\n",
+    "    14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2,\n",
+    "    14.9, 18.1, 7.3, 9.8, 10.9, 12.2, 9.9, 2.9, 2.8, 15.4, 15.7,\n",
+    "    9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 3.2, 16.2, 12.3,\n",
+    "    18.7, 8.9, 11.9, 12.1, 14.1, 8.8, 3.9, 16.9, 16.8, 11.3, 14.4,\n",
+    "    15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9,\n",
+    "    12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 9.2, 12.8, 15.5,\n",
+    "    16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 16.3, 11.3, 15.1, 10.4,\n",
+    "    13.4, 16.8, 20.4, 4.4, 16.4, 16.4, 18.7, 16.8, 15.8, 20.4,\n",
+    "    15.5, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7,\n",
+    "    10.2, 8.9, 21.0\n",
+    "])\n",
+    "mean = np.mean(data)\n",
+    "std_dev = np.std(data, ddof=1)  # ddof=1 for corrected standard deviation\n",
+    "minimum = np.min(data)\n",
+    "median = np.median(data)\n",
+    "maximum = np.max(data)\n",
+    "\n",
+    "print(f\"Mean: {mean}\")\n",
+    "print(f\"Standard Deviation: {std_dev}\")\n",
+    "print(f\"Minimum: {minimum}\")\n",
+    "print(f\"Median: {median}\")\n",
+    "print(f\"Maximum: {maximum}\")\n"
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +49,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-