mortality rate

module3/exo3/exercice.ipynb

@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -539,7 +539,7 @@
        "[1314 rows x 3 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -558,7 +558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -598,7 +598,7 @@
        "Index: []"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -616,7 +616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -646,7 +646,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -695,7 +695,7 @@
        "Dead      139         230"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -706,6 +706,79 @@
     "pd.DataFrame(data, columns=[\"Smoker\", \"Non-Smoker\"], index = [\"Alive\", \"Dead\"])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A present, nous allons calculer le taux de mortalite dans chacun de ces deux groupes. Pour cela, nous allons determiner le rapport entre le nombre de femmes décédées dans un groupe et le nombre total de femmes dans ce groupe. Dans le groupe des femmes fumeuses, le taux de mortalite est 0,24 tandis que dans le groupe des femmes non fumeuses, le taux de mortalite est 0,31."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Taux de mortalite fumeuses : 0.23883161512027493\n",
+      "Taux de mortalite non-fumeuses : 0.31420765027322406\n"
+     ]
+    }
+   ],
+   "source": [
+    "mortality_rate_smoker = dead_and_smoker/(alive_and_smoker+dead_and_smoker)\n",
+    "mortality_rate_non_smoker = dead_and_non_smoker /(alive_and_non_smoker + dead_and_non_smoker)\n",
+    "print(\"Taux de mortalite fumeuses :\", mortality_rate_smoker)\n",
+    "print(\"Taux de mortalite non-fumeuses :\", mortality_rate_non_smoker)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous representons les taux de mortalite calcules precedemment dans un diagramme de barres afin d'illustrer visuellement nos resultats."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0,0.5,'Mortality Rate')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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": [
+    "mortality_rate = [mortality_rate_smoker,mortality_rate_non_smoker]\n",
+    "smoking = ['smoker', 'non-smoker']\n",
+    "plt.bar(smoking, mortality_rate,color=['blue', 'green'])\n",
+    "plt.xticks(smoking)\n",
+    "plt.yticks(mortality_rate)\n",
+    "plt.xlabel('Smoking')\n",
+    "plt.ylabel('Mortality Rate')"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,