diff --git a/module2/exo4/exercice.ipynb b/module2/exo4/exercice.ipynb
index 15db27e73f0e747e868267d9616e791d411bd522..3b38e22e192b7a793a2f48e7cb0552d85a5c0c8c 100644
--- a/module2/exo4/exercice.ipynb
+++ b/module2/exo4/exercice.ipynb
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -45,6 +45,137 @@
     "                    sortie.write(f\"{date};{mot}\\n\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Analyse des données\n",
+    "On peut regarder l'aspect des données."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "            0             1\n",
+      "0  12/07/2020          Mooc\n",
+      "1  12/07/2020  Installation\n",
+      "2  12/07/2020        Python\n",
+      "3  12/07/2020       Jupiter\n",
+      "4  12/07/2020             R \n",
+      "...\n",
+      "              0        1\n",
+      "33  22/08/2020  Réunion\n",
+      "34  22/08/2020   Python\n",
+      "35  28/08/2020  Lecture\n",
+      "36  28/08/2020   Python\n",
+      "37  28/08/2020      GUI\n"
+     ]
+    }
+   ],
+   "source": [
+    "NomFichentree = \"./Info_Journal.csv\"\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "donnees = pd.read_csv(NomFichentree, sep=';', header=None,\n",
+    "                      infer_datetime_format=True, keep_date_col=True,\n",
+    "                      dayfirst=True)\n",
+    "\n",
+    "print(donnees.head(), '\\n...\\n', donnees.tail())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous pouvons ensuite regarder:\n",
+    "- le nombre total de données (le même que le nombre de lignes),\n",
+    "- le nombre de données uniques (pour les dates et pour les mots-clés),\n",
+    "- la date et le mot-clé les plus fréquents, avec leur fréquences respectives."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                 0     1\n",
+      "count           38    38\n",
+      "unique          13    15\n",
+      "top     12/07/2020  Mooc\n",
+      "freq             5     7\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(donnees.describe())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous pouvons regarder, également les fréquences respectives de chaque date et de chaque mot-clé."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "12/07/2020    5\n",
+      "17/07/2020    5\n",
+      "28/08/2020    3\n",
+      "13/08/2020    3\n",
+      "23/07/2020    3\n",
+      "08/08/2020    3\n",
+      "17/08/2020    3\n",
+      "10/08/2020    3\n",
+      "21/07/2020    2\n",
+      "20/07/2020    2\n",
+      "25/07/2020    2\n",
+      "02/08/2020    2\n",
+      "22/08/2020    2\n",
+      "Name: 0, dtype: int64\n",
+      "Mooc                    7\n",
+      "Python                  5\n",
+      "Lecture                 3\n",
+      "Module 2                3\n",
+      "Réunion                 3\n",
+      "GUI                     3\n",
+      "Exercices               3\n",
+      "Module 1                2\n",
+      "R                       2\n",
+      "Jupiter                 2\n",
+      "Git                     1\n",
+      "Pannes oscillatoires    1\n",
+      "Génération ACS          1\n",
+      "Configuration           1\n",
+      "Installation            1\n",
+      "Name: 1, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(pd.value_counts(donnees[0]))\n",
+    "print(pd.value_counts(donnees[1]))"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,