Tarea 6 Reloaded

06-LinearAlgebra&Statistics.ipynb

@@ -1672,6 +1672,56 @@
     "utilice custom_rand_var para simular la distribución de una ruleta de casino y grafique las probabilidades para cada número.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.47368421052631576\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy import stats \n",
+    "plt.rcParams['figure.figsize']=[15, 5]\n",
+    "\n",
+    "numeros = list(range(1,37,1))\n",
+    "prob=[]\n",
+    "for n in numeros:\n",
+    "    prob.append(1/len(numeros))\n",
+    "\n",
+    "custom_rand_var = stats.rv_discrete(name='custom', values = (numeros,prob))\n",
+    "\n",
+    "apuesta = ['rojo/negro', 'par/impar', 'docena', 'columna', 'linea', 'cuadro', 'calle', 'caballo', 'pleno']\n",
+    "prob = [  18/38,       18/38,      12/38,     12/38,     6/38,    4/38,     3/38,     2/38,     1/38] \n",
+    "\n",
+    "plt.subplots(1,1)\n",
+    "plt.bar(roulette_bet, np.array(prob)*100, color='r')\n",
+    "plt.xlabel('Apuesta')\n",
+    "plt.ylabel('Prob ganar(%)')\n",
+    "plt.title('Probabilidad de ganar según la elección de apuesta')\n",
+    "plt.xticks(apuesta)\n",
+    "plt.show()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},