Update exercice_fr.ipynb

module2/exo4/exercice_fr.ipynb

 {
- "cells": [],
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Calcul de statistiques basiques"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"data.csv\", sep=\";\")\n",
+    "data = df.value"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Moyenne et écart type"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.113000000000007"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.mean(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.3340944553014475"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.std(data, ddof=1)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Minimum et maximum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2.8 , 23.4\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(min(data), ',', max(data))"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Médiane"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.5"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.median(data)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Histogramme"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "n, bins, patches = plt.hist(data, histtype='bar', ec='black')\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +177,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-