diff --git a/module2/exo1/toy_notebook_fr.ipynb b/module2/exo1/toy_notebook_fr.ipynb
index 06ae3e830892f678e2eba9e368ad992e225a8d61..96689e29dd4d9ecbd10f124317e384db4100109f 100644
--- a/module2/exo1/toy_notebook_fr.ipynb
+++ b/module2/exo1/toy_notebook_fr.ipynb
@@ -6,20 +6,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import random\n",
-    "import math\n",
+    "import matplotlib.pyplot as plt\n",
     "\n",
-    "def buffon_needle(n_drops=100000):\n",
-    "    hits = 0\n",
-    "    for _ in range(n_drops):\n",
-    "        y = random.random()\n",
-    "        theta = random.uniform(0, math.pi / 2)\n",
-    "        if y <= (math.sin(theta) / 2):\n",
-    "            hits += 1\n",
-    "    return (2 * n_drops) / hits\n",
+    "# Exemple : afficher la convergence de l'estimation de π\n",
+    "import numpy as np\n",
     "\n",
-    "pi_est = buffon_needle()\n",
-    "print(f\"Estimation de π par la méthode de Buffon : {pi_est}\")\n"
+    "n_values = np.arange(1000, 20000, 1000)\n",
+    "pi_estimations = [buffon_needle(n) for n in n_values]\n",
+    "\n",
+    "plt.plot(n_values, pi_estimations)\n",
+    "plt.axhline(y=math.pi, color='r', linestyle='--', label='π réel')\n",
+    "plt.xlabel(\"Nombre d'expériences\")\n",
+    "plt.ylabel(\"Estimation de π\")\n",
+    "plt.legend()\n",
+    "plt.title(\"Convergence de la méthode de Buffon\")\n",
+    "plt.show()\n"
    ]
   }
  ],