Use local CSV instead of downloading each time

module2/exo1/toy_notebook_fr.ipynb

 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# À propos de pi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The number $\\pi$ is defined as the ratio of a circle's circumference to its diameter.\n",
+    "\n",
+    "\\[\n",
+    "\\pi \\approx 3.141592653589793\n",
+    "\\]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3.141592653589793\n"
+     ]
+    }
+   ],
+   "source": [
+    "import math\n",
+    "print(math.pi)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A classical method to estimate $\\pi$ is\n",
+    "[Buffon's needle experiment](https://en.wikipedia.org/wiki/Buffon%27s_needle_problem)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3.143863179074447\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "import math\n",
+    "\n",
+    "def buffon_pi(n=100000):\n",
+    "    hits = 0\n",
+    "    for _ in range(n):\n",
+    "        y = random.random() / 2\n",
+    "        theta = random.random() * math.pi / 2\n",
+    "        if y <= 0.5 * math.sin(theta):\n",
+    "            hits += 1\n",
+    "    return (2 * n) / hits\n",
+    "\n",
+    "random.seed(1)\n",
+    "print(buffon_pi(50000))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "for _ in range(50):\n",
+    "    x = random.random()\n",
+    "    y = random.random()\n",
+    "    theta = random.random() * math.pi\n",
+    "    dx = 0.05 * math.cos(theta)\n",
+    "    dy = 0.05 * math.sin(theta)\n",
+    "    plt.plot([x-dx, x+dx], [y-dy, y+dy])\n",
+    "\n",
+    "plt.hlines([0.25, 0.75], 0, 1, linestyles=\"dashed\")\n",
+    "plt.axis(\"equal\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +136,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-

module2/exo4/Untitled.ipynb

+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}