diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index d796f36e46550c633c3f80b7e7dc0f7e40ebd82b..f4a2047f42c8ca1bb373de50bae6f9d365602d03 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -445,14 +445,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 178,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['    HARPAGON.\\n', '    CLÉANTE.\\n', '    ÉLISE.\\n', '    VALÈRE.\\n', '    MARIANE.\\n', '    ANSELME.\\n', '    FROSINE.\\n', '    MAITRE SIMON.\\n', '    MAITRE JACQUES.\\n', '    LA FLÈCHE.\\n', '    DAME CLAUDE.\\n', '    BRINDAVOINE.\\n', '    LA MERLUCHE.\\n', '    LE COMMISSAIRE.\\n']\n"
+      "['HARPAGON', 'CLÉANTE', 'ÉLISE', 'VALÈRE', 'MARIANE', 'ANSELME', 'FROSINE', 'MAITRE SIMON', 'MAITRE JACQUES', 'LA FLÈCHE', 'DAME CLAUDE', 'BRINDAVOINE', 'LA MERLUCHE', 'LE COMMISSAIRE']\n"
      ]
     }
    ],
@@ -465,10 +465,10 @@
     "    while l[i] != \",\" :\n",
     "        perso += l[i]\n",
     "        i+=1\n",
-    "    persos.append(\"    \"+perso.upper()+\".\\n\")\n",
+    "    persos.append(perso.upper())\n",
     "print(persos)\n",
-    "persos[7] = '    MAÎTRE SIMON.\\n'\n",
-    "persos[8] = '    MAÎTRE JACQUES.\\n'\n",
+    "persos[7] = 'MAÎTRE SIMON'\n",
+    "persos[8] = 'MAÎTRE JACQUES'\n",
     "Nombre_repliques = {}\n",
     "for perso in persos :\n",
     "    Nombre_repliques[perso] = 0\n",
@@ -488,12 +488,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
-    "dico_acte = {}\n",
-    "acte_courant = 0\n",
     "k = 33\n",
     "non_habituel = []\n",
     "nontraitée = []\n",
@@ -519,7 +517,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'    VALÈRE.\\n'"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lignes[47]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'    VALÈRE.\\n'"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lignes[47]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -577,7 +615,7 @@
        " 'Fin du Quatrième Acte.\\n']"
       ]
      },
-     "execution_count": 98,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -588,7 +626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -624,7 +662,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -641,29 +679,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'    DAME CLAUDE.\\n': 0,\n",
-       " '    BRINDAVOINE.\\n': 81,\n",
-       " '    LA MERLUCHE.\\n': 103,\n",
-       " '    MAÎTRE SIMON.\\n': 383,\n",
-       " '    LE COMMISSAIRE.\\n': 575,\n",
-       " '    ANSELME.\\n': 1005,\n",
-       " '    MARIANE.\\n': 1748,\n",
-       " '    ÉLISE.\\n': 1820,\n",
-       " '    MAÎTRE JACQUES.\\n': 2767,\n",
-       " '    LA FLÈCHE.\\n': 2922,\n",
-       " '    FROSINE.\\n': 4177,\n",
-       " '    VALÈRE.\\n': 5205,\n",
-       " '    CLÉANTE.\\n': 6501,\n",
-       " '    HARPAGON.\\n': 10649}"
+       "{'    HARPAGON.\\n': 0,\n",
+       " '    CLÉANTE.\\n': 0,\n",
+       " '    ÉLISE.\\n': 0,\n",
+       " '    VALÈRE.\\n': 0,\n",
+       " '    MARIANE.\\n': 0,\n",
+       " '    ANSELME.\\n': 0,\n",
+       " '    FROSINE.\\n': 0,\n",
+       " '    MAÎTRE SIMON.\\n': 0,\n",
+       " '    MAÎTRE JACQUES.\\n': 0,\n",
+       " '    LA FLÈCHE.\\n': 0,\n",
+       " '    DAME CLAUDE.\\n': 0,\n",
+       " '    BRINDAVOINE.\\n': 0,\n",
+       " '    LA MERLUCHE.\\n': 0,\n",
+       " '    LE COMMISSAIRE.\\n': 0}"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -674,29 +712,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'    DAME CLAUDE.\\n': 0,\n",
-       " '    BRINDAVOINE.\\n': 6,\n",
-       " '    MAÎTRE SIMON.\\n': 10,\n",
-       " '    LA MERLUCHE.\\n': 10,\n",
-       " '    LE COMMISSAIRE.\\n': 34,\n",
-       " '    ANSELME.\\n': 40,\n",
-       " '    MARIANE.\\n': 54,\n",
-       " '    ÉLISE.\\n': 100,\n",
-       " '    FROSINE.\\n': 118,\n",
-       " '    LA FLÈCHE.\\n': 128,\n",
-       " '    MAÎTRE JACQUES.\\n': 166,\n",
-       " '    VALÈRE.\\n': 198,\n",
-       " '    CLÉANTE.\\n': 320,\n",
-       " '    HARPAGON.\\n': 688}"
+       "{'    HARPAGON.\\n': 0,\n",
+       " '    CLÉANTE.\\n': 0,\n",
+       " '    ÉLISE.\\n': 0,\n",
+       " '    VALÈRE.\\n': 0,\n",
+       " '    MARIANE.\\n': 0,\n",
+       " '    ANSELME.\\n': 0,\n",
+       " '    FROSINE.\\n': 0,\n",
+       " '    MAÎTRE SIMON.\\n': 0,\n",
+       " '    MAÎTRE JACQUES.\\n': 0,\n",
+       " '    LA FLÈCHE.\\n': 0,\n",
+       " '    DAME CLAUDE.\\n': 0,\n",
+       " '    BRINDAVOINE.\\n': 0,\n",
+       " '    LA MERLUCHE.\\n': 0,\n",
+       " '    LE COMMISSAIRE.\\n': 0}"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -707,67 +745,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "ename": "NameError",
+     "evalue": "name 'dico_acte' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-21-50173e3dc1a0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0macte\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m     \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdico_acte\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0macte\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpersos\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m     \u001b[0mlabels\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpersos\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mscene\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdico_acte\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0macte\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'dico_acte' is not defined"
+     ]
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
+       "<Figure size 576x576 with 0 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -800,6 +798,265 @@
     "    plt.legend(handles=patches,bbox_to_anchor=(1.05, 1),loc='upper left', borderaxespad=0.)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "acte = 0\n",
+    "perso_prec = 0\n",
+    "scene = 0\n",
+    "k = 40\n",
+    "non_habituel = []\n",
+    "new_scene = False\n",
+    "while k < len(lignes) :\n",
+    "    l = lignes[k]\n",
+    "    est_perso = False\n",
+    "    for perso in persos :\n",
+    "        if perso[4:-2] in l :\n",
+    "            if not new_scene :\n",
+    "                if (k-perso_prec) != 3 :\n",
+    "                    non_habituel.append((acte,scene,k,perso_prec))\n",
+    "            else :\n",
+    "                new_scene = False\n",
+    "            perso_prec = k\n",
+    "            k+=2\n",
+    "    if l[:3] == '###' :\n",
+    "        scene +=1\n",
+    "        new_scene = True\n",
+    "        k+=4\n",
+    "    elif l[:2] == '##' :\n",
+    "        scene = 0\n",
+    "        acte +=1\n",
+    "        k+=3\n",
+    "    else :\n",
+    "        k+=1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'    VALÈRE.\\n'"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lignes[47]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "6"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scene"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3171"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "k"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(1, 3, 207, 198),\n",
+       " (1, 3, 216, 210),\n",
+       " (1, 3, 254, 249),\n",
+       " (1, 3, 274, 269),\n",
+       " (1, 4, 387, 381),\n",
+       " (1, 4, 626, 621),\n",
+       " (1, 4, 631, 626),\n",
+       " (1, 5, 785, 780),\n",
+       " (1, 5, 818, 812),\n",
+       " (2, 5, 1286, 1277),\n",
+       " (2, 5, 1297, 1289),\n",
+       " (2, 5, 1305, 1300),\n",
+       " (3, 1, 1345, 1339),\n",
+       " (3, 1, 1372, 1366),\n",
+       " (3, 1, 1413, 1408),\n",
+       " (3, 1, 1530, 1524),\n",
+       " (3, 2, 1612, 1607),\n",
+       " (3, 2, 1635, 1630),\n",
+       " (3, 2, 1668, 1662),\n",
+       " (3, 7, 1869, 1864),\n",
+       " (3, 7, 1877, 1872),\n",
+       " (3, 9, 1973, 1968),\n",
+       " (4, 4, 2301, 2296),\n",
+       " (4, 4, 2322, 2316),\n",
+       " (4, 4, 2330, 2325),\n",
+       " (4, 4, 2359, 2354)]"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "non_habituel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 181,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Ajouter = {}\n",
+    "\n",
+    "## Harpagon\n",
+    "Ajouter['HARPAGON'] = {}\n",
+    "#Harpagon, acte 1\n",
+    "Ajouter['HARPAGON'][1] = {}\n",
+    "#Harpagon, acte 1, scène 3\n",
+    "Ajouter['HARPAGON'][1][3] = 0\n",
+    "for k in [199,202,205,211,214,252,270] :\n",
+    "    Ajouter['HARPAGON'][1][3] += len(split_string(lignes[k]))\n",
+    "#Harpagon, acte 1, scène 4\n",
+    "Ajouter['HARPAGON'][1][4] = 0\n",
+    "for k in [382,385,629] :\n",
+    "    Ajouter['HARPAGON'][1][4] += len(split_string(lignes[k]))\n",
+    "#Harpagon, acte 1, scène 5\n",
+    "Ajouter['HARPAGON'][1][5] = 0\n",
+    "for k in [783] :\n",
+    "    Ajouter['HARPAGON'][1][5] += len(split_string(lignes[k]))\n",
+    "\n",
+    "#Harpagon, acte 3\n",
+    "Ajouter['HARPAGON'] = {}\n",
+    "Ajouter['HARPAGON'][3] = {}\n",
+    "#Harpagon, acte 3, scène 1\n",
+    "Ajouter['HARPAGON'][3][1] = 0\n",
+    "for k in [1340,1343,1367,1370] :\n",
+    "    Ajouter['HARPAGON'][3][1] += len(split_string(lignes[k]))\n",
+    "\n",
+    "#Harpagon, acte 4\n",
+    "Ajouter['HARPAGON'] = {}\n",
+    "Ajouter['HARPAGON'][4] = {}\n",
+    "#Harpagon, acte 4, scène 4\n",
+    "Ajouter['HARPAGON'][4][4] = 0\n",
+    "for k in [2355] :\n",
+    "    Ajouter['HARPAGON'][4][4] += len(split_string(lignes[k]))\n",
+    "\n",
+    "## Elise\n",
+    "Ajouter['ÉLISE'] = {}\n",
+    "#Elise, acte 1\n",
+    "Ajouter['ÉLISE'][1] = {}\n",
+    "#Elise, acte 1, scène 4\n",
+    "Ajouter['ÉLISE'][1][4] = 0\n",
+    "for k in [624] :\n",
+    "    Ajouter['ÉLISE'][1][4] += len(split_string(lignes[k]))\n",
+    "\n",
+    "##Valère\n",
+    "Ajouter['VALÈRE'] = {}\n",
+    "#Valère, acte 1\n",
+    "Ajouter['VALÈRE'][1] = {}\n",
+    "#Valère, acte 1, scène 5\n",
+    "Ajouter['VALÈRE'][1][5] = 0\n",
+    "for k in [813,816] :\n",
+    "    Ajouter['VALÈRE'][1][5] += len(split_string(lignes[k]))\n",
+    "\n",
+    "#Valère, acte 3\n",
+    "Ajouter['VALÈRE'][3] = {}\n",
+    "#Valère, acte 3, scène 2\n",
+    "Ajouter['VALÈRE'][3][2] = 0\n",
+    "for k in [1631,1663,1666] :\n",
+    "    Ajouter['VALÈRE'][3][2] += len(split_string(lignes[k]))\n",
+    "\n",
+    "##Frosine\n",
+    "Ajouter['FROSINE'] = {}\n",
+    "#Frosine, acte 2\n",
+    "Ajouter['FROSINE'][2] = {}\n",
+    "#Frosine, acte 2, scène 5\n",
+    "Ajouter['FROSINE'][2][5] = 0\n",
+    "for k in [1278,1281,1284,1292,1295,1303] :\n",
+    "    Ajouter['FROSINE'][2][5] += len(split_string(lignes[k]))\n",
+    "\n",
+    "## Maître Jacques\n",
+    "Ajouter['MAÎTRE JACQUES'] = {}\n",
+    "## Maître Jacques, acte 3\n",
+    "Ajouter['MAÎTRE JACQUES'][3] = {}\n",
+    "## Maître Jacques, acte 3, scène 1\n",
+    "Ajouter['MAÎTRE JACQUES'][3][1] = 0\n",
+    "for k in [1409,1525,1528] :\n",
+    "    Ajouter['MAÎTRE JACQUES'][3][1] += len(split_string(lignes[k]))\n",
+    "## Maître Jacques, acte 3, scène 2\n",
+    "Ajouter['MAÎTRE JACQUES'][3][2] = 0\n",
+    "for k in [1608] :\n",
+    "    Ajouter['MAÎTRE JACQUES'][3][2] += len(split_string(lignes[k]))\n",
+    "\n",
+    "## Maître Jacques, acte 4\n",
+    "Ajouter['MAÎTRE JACQUES'][4] = {}\n",
+    "## Maître Jacques, acte 4, scène 4\n",
+    "Ajouter['MAÎTRE JACQUES'][4][4] = 0\n",
+    "for k in [2297,2317,2320,2328] :\n",
+    "    Ajouter['MAÎTRE JACQUES'][4][4] += len(split_string(lignes[k]))\n",
+    "\n",
+    "## Cléante\n",
+    "Ajouter['CLÉANTE'] = {}\n",
+    "#Cléante, acte 3\n",
+    "Ajouter['CLÉANTE'][3] = {}\n",
+    "#Cléante, acte 3, scène 4\n",
+    "Ajouter['CLÉANTE'][3][4] = 0\n",
+    "for k in [1867] :\n",
+    "    Ajouter['CLÉANTE'][3][4] += len(split_string(lignes[k]))\n",
+    "#Cléante, acte 3, scène 7\n",
+    "Ajouter['CLÉANTE'][3][7] = 0\n",
+    "for k in [1875] :\n",
+    "    Ajouter['CLÉANTE'][3][7] += len(split_string(lignes[k]))\n",
+    "\n",
+    "##La merluche\n",
+    "Ajouter['LA MERLUCHE'] = {}\n",
+    "#La merluche, acte 3\n",
+    "Ajouter['LA MERLUCHE'][3] = {}\n",
+    "#La merluche, acte 3, scène 9\n",
+    "Ajouter['LA MERLUCHE'][3][9] = 0\n",
+    "for k in [1971] :\n",
+    "    Ajouter['LA MERLUCHE'][3][9] += len(split_string(lignes[k]))"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,