diff --git a/Sport/Descriptive_statistics/stat_desc_sport.ipynb b/Sport/Descriptive_statistics/stat_desc_sport.ipynb
index 87ded22..981fe1c 100644
--- a/Sport/Descriptive_statistics/stat_desc_sport.ipynb
+++ b/Sport/Descriptive_statistics/stat_desc_sport.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 31,
    "id": "dd143b00-1989-44cf-8558-a30087d17f70",
    "metadata": {},
    "outputs": [],
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 32,
    "id": "08c63120-1b56-4145-9014-18a637b22876",
    "metadata": {},
    "outputs": [],
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 33,
    "id": "f8bd679d-fa76-49d4-9ec1-9f15516f16d3",
    "metadata": {},
    "outputs": [],
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 34,
    "id": "945c59bb-05b4-4f21-82f0-0db40d7957b3",
    "metadata": {},
    "outputs": [],
@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 35,
    "id": "41a67995-0a08-45c0-bbad-6e6cee5474c8",
    "metadata": {},
    "outputs": [
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 36,
    "id": "c4d4b2ad-8a3c-477b-bc52-dd4860527bfe",
    "metadata": {},
    "outputs": [
@@ -169,7 +169,7 @@
        "array([5, 6, 7, 8, 9])"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -181,7 +181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 37,
    "id": "97a9e235-1c04-46bf-9f3c-5496e141cc40",
    "metadata": {},
    "outputs": [],
@@ -220,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 38,
    "id": "770cd3fc-bfe2-4a69-89bc-0eb946311130",
    "metadata": {},
    "outputs": [
@@ -230,7 +230,7 @@
        "['5_191835', '6_591412', '7_49632', '8_1942', '9_19683']"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -242,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 39,
    "id": "70b6e961-c303-465e-93f4-609721d38454",
    "metadata": {},
    "outputs": [
@@ -258,7 +258,7 @@
     "# On filtre les outliers\n",
     "\n",
     "def remove_elements(lst, elements_to_remove):\n",
-    "    return [x for x in lst if x not in elements_to_remove]\n",
+    "    return ''.join([x for x in lst if x not in elements_to_remove])\n",
     "    \n",
     "databases = [customer_sport, campaigns_sport, tickets_sport, products_sport]\n",
     "\n",
@@ -274,7 +274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 40,
    "id": "b54b920a-7b46-490f-ba7e-d1859055a4e3",
    "metadata": {},
    "outputs": [
@@ -325,7 +325,7 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>[5, _, 6, 0, 0, 9, 7, 4, 5]</td>\n",
+       "      <td>5_6009745</td>\n",
        "      <td>1372685</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -349,7 +349,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>[5, _, 6, 0, 1, 1, 2, 2, 8]</td>\n",
+       "      <td>5_6011228</td>\n",
        "      <td>1372685</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -373,7 +373,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>[5, _, 6, 0, 5, 8, 9, 5, 0]</td>\n",
+       "      <td>5_6058950</td>\n",
        "      <td>1372685</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -397,7 +397,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>[5, _, 6, 0, 6, 2, 4, 0, 4]</td>\n",
+       "      <td>5_6062404</td>\n",
        "      <td>1372685</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -421,7 +421,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>[5, _, 2, 5, 0, 2, 1, 7]</td>\n",
+       "      <td>5_250217</td>\n",
        "      <td>78785</td>\n",
        "      <td>NaN</td>\n",
        "      <td>11035.0</td>\n",
@@ -449,38 +449,38 @@
        "</div>"
       ],
       "text/plain": [
-       "                   customer_id  street_id  structure_id  mcp_contact_id  \\\n",
-       "0  [5, _, 6, 0, 0, 9, 7, 4, 5]    1372685           NaN             NaN   \n",
-       "1  [5, _, 6, 0, 1, 1, 2, 2, 8]    1372685           NaN             NaN   \n",
-       "2  [5, _, 6, 0, 5, 8, 9, 5, 0]    1372685           NaN             NaN   \n",
-       "3  [5, _, 6, 0, 6, 2, 4, 0, 4]    1372685           NaN             NaN   \n",
-       "4     [5, _, 2, 5, 0, 2, 1, 7]      78785           NaN         11035.0   \n",
+       "  customer_id  street_id  structure_id  mcp_contact_id  fidelity  tenant_id  \\\n",
+       "0   5_6009745    1372685           NaN             NaN         0       1771   \n",
+       "1   5_6011228    1372685           NaN             NaN         0       1771   \n",
+       "2   5_6058950    1372685           NaN             NaN         0       1771   \n",
+       "3   5_6062404    1372685           NaN             NaN         0       1771   \n",
+       "4    5_250217      78785           NaN         11035.0         0       1771   \n",
        "\n",
-       "   fidelity  tenant_id  is_partner  deleted_at  gender  is_email_true  ...  \\\n",
-       "0         0       1771       False         NaN       2           True  ...   \n",
-       "1         0       1771       False         NaN       2           True  ...   \n",
-       "2         0       1771       False         NaN       2           True  ...   \n",
-       "3         0       1771       False         NaN       2           True  ...   \n",
-       "4         0       1771       False         NaN       0           True  ...   \n",
+       "   is_partner  deleted_at  gender  is_email_true  ...  purchase_count  \\\n",
+       "0       False         NaN       2           True  ...               0   \n",
+       "1       False         NaN       2           True  ...               0   \n",
+       "2       False         NaN       2           True  ...               0   \n",
+       "3       False         NaN       2           True  ...               0   \n",
+       "4       False         NaN       0           True  ...               0   \n",
        "\n",
-       "   purchase_count first_buying_date  country  gender_label  gender_female  \\\n",
-       "0               0               NaN       af         other              0   \n",
-       "1               0               NaN       af         other              0   \n",
-       "2               0               NaN       af         other              0   \n",
-       "3               0               NaN       af         other              0   \n",
-       "4               0               NaN       fr        female              1   \n",
+       "  first_buying_date  country  gender_label  gender_female  gender_male  \\\n",
+       "0               NaN       af         other              0            0   \n",
+       "1               NaN       af         other              0            0   \n",
+       "2               NaN       af         other              0            0   \n",
+       "3               NaN       af         other              0            0   \n",
+       "4               NaN       fr        female              1            0   \n",
        "\n",
-       "   gender_male  gender_other  country_fr  has_tags  number_company  \n",
-       "0            0             1         0.0         0               5  \n",
-       "1            0             1         0.0         0               5  \n",
-       "2            0             1         0.0         0               5  \n",
-       "3            0             1         0.0         0               5  \n",
-       "4            0             0         1.0         0               5  \n",
+       "   gender_other  country_fr  has_tags  number_company  \n",
+       "0             1         0.0         0               5  \n",
+       "1             1         0.0         0               5  \n",
+       "2             1         0.0         0               5  \n",
+       "3             1         0.0         0               5  \n",
+       "4             0         1.0         0               5  \n",
        "\n",
        "[5 rows x 29 columns]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -499,7 +499,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 45,
    "id": "eec1ac0b-2502-452b-97e6-69ffb77156d6",
    "metadata": {},
    "outputs": [],
@@ -511,7 +511,7 @@
     "    # Ajout de titres et d'étiquettes\n",
     "    plt.xlabel('Company')\n",
     "    plt.ylabel(\"Nombre de clients (milliers)\")\n",
-    "    plt.title(\"Nombre de clients de chaque compagnie de spectacle\")\n",
+    "    plt.title(\"Nombre de clients de chaque compagnie de sport\")\n",
     "    \n",
     "    # Affichage du barplot\n",
     "    plt.show()"
@@ -519,7 +519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 46,
    "id": "db4494e7-6f65-4f7e-bf8c-8ec321d0b02d",
    "metadata": {},
    "outputs": [
@@ -540,7 +540,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 47,
    "id": "a12a59a0-edfe-4e52-8037-9b875f823b33",
    "metadata": {},
    "outputs": [],
@@ -553,7 +553,7 @@
     "    # Ajout de titres et d'étiquettes\n",
     "    plt.xlabel('Company')\n",
     "    plt.ylabel(\"Prix maximal d'un billet vendu\")\n",
-    "    plt.title(\"Prix maximal de vente observé par compagnie de spectacle\")\n",
+    "    plt.title(\"Prix maximal de vente observé par compagnie de sport\")\n",
     "    \n",
     "    # Affichage du barplot\n",
     "    plt.show()"
@@ -561,7 +561,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 48,
    "id": "2c7c2d26-4e35-4163-b771-fa4d3e8ca83e",
    "metadata": {},
    "outputs": [
@@ -582,7 +582,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 49,
    "id": "597d4361-8beb-43f4-9224-8f7dc34b187c",
    "metadata": {},
    "outputs": [
@@ -703,7 +703,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 50,
    "id": "5058d3c9-73a0-4e01-881e-4d2423f0d291",
    "metadata": {},
    "outputs": [],
@@ -713,405 +713,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
-   "id": "986a0e41-ae31-46c5-a009-861530d85f45",
-   "metadata": {},
-   "outputs": [
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-       "      <th>998843</th>\n",
-       "      <td>[9, _, 8, 4, 4, 3, 0, 2]</td>\n",
-       "      <td>484177</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1490</td>\n",
-       "      <td>False</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2022-03-27 12:15:02+00:00</td>\n",
-       "      <td>de</td>\n",
-       "      <td>male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>9</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>998844</th>\n",
-       "      <td>[9, _, 9, 4, 1, 2, 6, 0]</td>\n",
-       "      <td>564032</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1490</td>\n",
-       "      <td>False</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2022-04-20 15:12:38+00:00</td>\n",
-       "      <td>ch</td>\n",
-       "      <td>male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>9</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>998845</th>\n",
-       "      <td>[9, _, 8, 0, 9, 7, 4, 2]</td>\n",
-       "      <td>453747</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1490</td>\n",
-       "      <td>False</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2022-03-07 20:42:07+00:00</td>\n",
-       "      <td>fr</td>\n",
-       "      <td>male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>9</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>998846 rows × 29 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                        customer_id  street_id  structure_id  mcp_contact_id  \\\n",
-       "0       [5, _, 6, 0, 0, 9, 7, 4, 5]    1372685           NaN             NaN   \n",
-       "1       [5, _, 6, 0, 1, 1, 2, 2, 8]    1372685           NaN             NaN   \n",
-       "2       [5, _, 6, 0, 5, 8, 9, 5, 0]    1372685           NaN             NaN   \n",
-       "3       [5, _, 6, 0, 6, 2, 4, 0, 4]    1372685           NaN             NaN   \n",
-       "4          [5, _, 2, 5, 0, 2, 1, 7]      78785           NaN         11035.0   \n",
-       "...                             ...        ...           ...             ...   \n",
-       "998841     [9, _, 9, 9, 5, 1, 4, 6]     607676           NaN             NaN   \n",
-       "998842     [9, _, 9, 7, 0, 8, 9, 1]     587855           NaN             NaN   \n",
-       "998843     [9, _, 8, 4, 4, 3, 0, 2]     484177           NaN             NaN   \n",
-       "998844     [9, _, 9, 4, 1, 2, 6, 0]     564032           NaN             NaN   \n",
-       "998845     [9, _, 8, 0, 9, 7, 4, 2]     453747           NaN             NaN   \n",
-       "\n",
-       "        fidelity  tenant_id  is_partner  deleted_at  gender  is_email_true  \\\n",
-       "0              0       1771       False         NaN       2           True   \n",
-       "1              0       1771       False         NaN       2           True   \n",
-       "2              0       1771       False         NaN       2           True   \n",
-       "3              0       1771       False         NaN       2           True   \n",
-       "4              0       1771       False         NaN       0           True   \n",
-       "...          ...        ...         ...         ...     ...            ...   \n",
-       "998841         1       1490       False         NaN       1           True   \n",
-       "998842         1       1490       False         NaN       1           True   \n",
-       "998843         1       1490       False         NaN       1           True   \n",
-       "998844         1       1490       False         NaN       1           True   \n",
-       "998845         1       1490       False         NaN       1           True   \n",
-       "\n",
-       "        ...  purchase_count          first_buying_date  country  gender_label  \\\n",
-       "0       ...               0                        NaN       af         other   \n",
-       "1       ...               0                        NaN       af         other   \n",
-       "2       ...               0                        NaN       af         other   \n",
-       "3       ...               0                        NaN       af         other   \n",
-       "4       ...               0                        NaN       fr        female   \n",
-       "...     ...             ...                        ...      ...           ...   \n",
-       "998841  ...               1  2022-05-12 06:20:49+00:00      NaN          male   \n",
-       "998842  ...               1  2022-05-03 04:20:43+00:00       fr          male   \n",
-       "998843  ...               1  2022-03-27 12:15:02+00:00       de          male   \n",
-       "998844  ...               1  2022-04-20 15:12:38+00:00       ch          male   \n",
-       "998845  ...               1  2022-03-07 20:42:07+00:00       fr          male   \n",
-       "\n",
-       "        gender_female  gender_male  gender_other  country_fr  has_tags  \\\n",
-       "0                   0            0             1         0.0         0   \n",
-       "1                   0            0             1         0.0         0   \n",
-       "2                   0            0             1         0.0         0   \n",
-       "3                   0            0             1         0.0         0   \n",
-       "4                   1            0             0         1.0         0   \n",
-       "...               ...          ...           ...         ...       ...   \n",
-       "998841              0            1             0         NaN         0   \n",
-       "998842              0            1             0         1.0         0   \n",
-       "998843              0            1             0         0.0         0   \n",
-       "998844              0            1             0         0.0         0   \n",
-       "998845              0            1             0         1.0         0   \n",
-       "\n",
-       "        number_company  \n",
-       "0                    5  \n",
-       "1                    5  \n",
-       "2                    5  \n",
-       "3                    5  \n",
-       "4                    5  \n",
-       "...                ...  \n",
-       "998841               9  \n",
-       "998842               9  \n",
-       "998843               9  \n",
-       "998844               9  \n",
-       "998845               9  \n",
-       "\n",
-       "[998846 rows x 29 columns]"
-      ]
-     },
-     "execution_count": 69,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "customer_sport"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 52,
    "id": "848963c9-6129-4106-80b5-76bf814b70d1",
    "metadata": {},
    "outputs": [],
@@ -1150,7 +752,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 54,
+   "id": "b78ef715-c645-4625-a128-4f5b49e5339d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "mailing_consent(customer_sport)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
    "id": "d8071891-e6f5-4d93-b039-9e99c20ec4b0",
    "metadata": {},
    "outputs": [],
@@ -1166,7 +789,7 @@
     "    # Ajout de titres et d'étiquettes\n",
     "    plt.xlabel('Company')\n",
     "    plt.ylabel(\"Part de clients de chaque sexe\")\n",
-    "    plt.title(\"Sexe des clients de chaque compagnie de spectacle\")\n",
+    "    plt.title(\"Sexe des clients de chaque compagnie de sport\")\n",
     "    plt.legend()\n",
     "    \n",
     "    # Affichage du barplot\n",
@@ -1175,30 +798,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 57,
    "id": "2fc30f1d-cf64-4efb-9442-4d97bb50b29f",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "gender_bar()"
+    "gender_bar(customer_sport)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 62,
    "id": "4b3bb641-814b-4679-9a67-4eca87a920a6",
    "metadata": {},
    "outputs": [],
    "source": [
     "def country_bar(customer_sport):\n",
-    "    company_country_fr = customer_sport.groupby(\"number_compagny\")[\"country_fr\"].mean().reset_index()\n",
+    "    company_country_fr = customer_sport.groupby(\"number_company\")[\"country_fr\"].mean().reset_index()\n",
     "    # Création du barplot\n",
     "    plt.bar(company_country_fr[\"number_company\"], company_country_fr[\"country_fr\"])\n",
     "    \n",
     "    # Ajout de titres et d'étiquettes\n",
     "    plt.xlabel('Company')\n",
     "    plt.ylabel(\"Part de clients français\")\n",
-    "    plt.title(\"Nationalité des clients de chaque compagnie de spectacle\")\n",
+    "    plt.title(\"Nationalité des clients de chaque compagnie de sport\")\n",
     "    \n",
     "    # Affichage du barplot\n",
     "    plt.show()"
@@ -1206,12 +840,110 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 63,
    "id": "01258674-6b98-49e4-93f4-f4185964999f",
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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sfv366cKFC/ka9/jx44qMjHRoL1WqlO31fwoLC7N7nrMLMGf87OxstWzZUocPH9bw4cNVvXp1FS1aVNnZ2WrQoEG+68zNkSNHtGTJkjwPc13tQ52zXCVLlrRr9/HxcVhGZ8d56qmnlJWVpQ8++EDt2rVTdna27rrrLo0ePVoJCQl51nLs2DGVKlWqQJevS5eXKSsrS++++67efffdq9aa41rv59Xkd3mPHz+uiIgIh/Yr34sjR45IkgYPHqzBgwc7tTz/5Mp6vXI9SJfXxT/XQ2Jiot577z29+OKLio+P12233SYvLy/16tXLrt/x48cVGxvrML8rl88VR44c0e7du/O1rR87dkySrnohQc7nIa+/BdnZ2Tp58qQCAwNt7aGhoXb9/Pz8FBgYqICAAIf2jIwMh/nmtj5Klixpd3FF586dtXLlSg0fPlx33XWXgoODZbFYdP/99zus89y2qdzaJOfe7ysVdHu8Xtu9K5/LvN6DnO0hp5bHHnssz/FOnDghLy8vWa3WfF+s4uz3xsmTJ/M1TkHX6bUQbq7CYrFo3LhxSkhI0LRp0xxe//LLL3Xu3DktWrTIlmYlaevWrQUaNywsTKmpqQ7thw8fliS7/wk5Y/v27dq2bZtmzZqlrl272tp3795doDpzU6JECdWoUUNjxozJ9fWcgJabnD9uaWlpKl26tK09KyvLIdC5Mk737t3VvXt3nTt3Tv/73/80YsQIPfDAA9q1a5fd+/ZPt99+u9auXavs7OwCBZzbbrtN3t7eeuqpp9SvX79c++T2pVsQ+VnesLCwXE/cvvLEypxtb+jQobkGfkm281xy4671miPn3IPXXnvNrj09Pd3uKr2wsLBcTxLNrS0gICDXkyDT09PtPnslSpRQkSJFHE56/efrecn5H+5ff/2VZ5+cz0Nefwu8vLx022235Tl9fuS1jnJqOX36tJYuXaoRI0ZoyJAhtj6ZmZk6ceKE3XRhYWG2L7BrjZFfBd0er9d2Lzn/uczrPShXrpxdLe+++64aNGiQ61gRERGyWq3y9va+6jZ2Nc5+b4SGhuZrHHes06sh3FxDixYtlJCQoFGjRjkcJsrZffvPk6UMw9AHH3zgMJ9r/Q/kn5o3b64vvvhChw8ftvuSnjNnjgIDA/PcoPOSW52S9P7777s0n3/Ka3keeOABLVu2THfeeafLf3hzrkSZN2+e6tata2v/7LPPHK6Ays84RYsWVevWrXXx4kU9/PDD+v333/P8sm/durU++eQTzZo1q0CHpgIDA9W0aVNt2bJFNWrUkJ+fX77n9U/ObE+uLG/Tpk312WefafHixXa76D/++GO7fhUrVlT58uW1bds2h0DhDHet1xwWi8Vhu/7666916NAh25eBdHn5xo8fr23bttkdmrpy+aTLV+78+uuvdm27du3Szp077QLLAw88oNdee01hYWEuB9S4uDiFhIRo6tSp6tSpU66HpipWrKjSpUvr448/1uDBg219zp07p4ULF9quoHKnTz75RImJibaxDhw4oHXr1qlLly6SLq9vwzAc1vmHH34oq9Vq1xYfH69ly5bZhcLs7GwtWLDAbfUWdHu8Xtv9P13rczlv3jy1a9fO9nzdunU6cOCA7V5ojRo1UvHixbVjx45rnhAfHx+vBQsWaMyYMXmG7bz2DDv7vZFzVd21xrmSO9dpbgg3Thg3bpzq1q2ro0ePqmrVqrb2hIQE+fn56fHHH9cLL7ygv//+W1OmTNHJkycd5lG9enUtWrRIU6ZMUd26deXl5aV69erlOt6IESNs55S88sorCg0N1bx58/T1119r/PjxCgkJcan+SpUq6c4779SQIUNkGIZCQ0O1ZMkSJSUlubYirlieH374QUuWLFFkZKSCgoJUsWJFjRo1SklJSYqLi1P//v1VsWJF/f3339q/f7+WLVumqVOn5rn7snLlynryySc1ceJE+fr6qkWLFtq+fbvefPNNh/taODvO008/rSJFiqhRo0aKjIxUWlqaxo4dq5CQEN111115Lt/jjz+umTNnqk+fPtq5c6eaNm2q7Oxs/fTTT6pcubI6derk9Lp655131LhxYzVp0kTPPPOMYmJidObMGe3evVtLlizR999/7/S8cuS1PeV3ebt06aK3335bXbp00ZgxY1S+fHktW7ZMy5cvd+j7/vvvq3Xr1mrVqpW6deum0qVL68SJE0pOTtYvv/xy1S8vd65X6XLAmDVrlipVqqQaNWpo8+bNeuONNxy2sQEDBmjGjBlq06aNRo8ebbta6o8//nCY51NPPaUnn3xSffv2Vbt27XTgwAGNHz/e4XyCAQMGaOHChbrnnns0cOBA1ahRQ9nZ2UpJSdGKFSs0aNAg1a9fP9e6ixUrprfeeku9evVSixYtbHfy3r17t7Zt26b//ve/8vLy0vjx4/XEE0/ogQceUO/evZWZmak33nhDp06d0uuvv+7SunLG0aNH9cgjj+jpp5/W6dOnNWLECAUEBGjo0KGSLl8Vec899+iNN95QiRIlFBMTo9WrV2v69OkO97MaNmyYlixZoubNm2vYsGEqUqSIpk6dartM3h177qSCbY/Xa7t35XO5adMm9erVS+3bt9fBgwc1bNgwlS5dWn379pV0edt599131bVrV504cUKPPfaYwsPDdezYMW3btk3Hjh3TlClTJMl2ZVP9+vU1ZMgQlStXTkeOHNHixYv1/vvvKygoyHbX/WnTpikoKEgBAQGKjY116XvDmXHc/d5dU75PRTahf14tdaXOnTsbkhyullqyZIlRs2ZNIyAgwChdurTx/PPPG998843DWeEnTpwwHnvsMaN48eKGxWIx/rnqdcXVUoZhGL/99pvRtm1bIyQkxPDz8zNq1qxpd+a+Yfz/2ecLFiywa8/tip0dO3YYCQkJRlBQkHHbbbcZ7du3N1JSUhzGdvZqqa1btxqNGjUyAgMDDUl2V5EcO3bM6N+/vxEbG2v4+voaoaGhRt26dY1hw4YZZ8+edVi3/5SZmWkMGjTICA8PNwICAowGDRoY69evz/UKFmfGmT17ttG0aVMjIiLC8PPzM0qVKmV06NDB+PXXX69ah2FcvlrjlVdeMcqXL2/4+fkZYWFhRrNmzYx169bZ+jhztVROe48ePYzSpUsbvr6+xu23327ExcXZroAwDNfez7y2p4Is719//WW0a9fOKFasmBEUFGS0a9fOWLduXa7Ls23bNqNDhw5GeHi44evra5QsWdJo1qyZMXXq1GuO48x6lWT069fPYdor1/fJkyeNnj17GuHh4UZgYKDRuHFjY82aNQ5XNhnG/38GAgICjNDQUKNnz57GV1995fBZzc7ONsaPH2+ULVvWCAgIMOrVq2d8//33uc7z7Nmzxssvv2xUrFjR8PPzM0JCQozq1asbAwcONNLS0q65LpYtW2bEx8cbRYsWNQIDA40qVaoY48aNs+vz5ZdfGvXr1zcCAgKMokWLGs2bNzd+/PFHuz45V0v988okw7j82S1atKjDuFde+Zmz7X300UdG//79jdtvv93w9/c3mjRpYmzatMlu2pzt5LbbbjOCgoKM++67z9i+fXuun9E1a9YY9evXN/z9/Y2SJUsazz//vDFu3DhDku2qT8O4/L62adMm1zr/uc5zu+LGMAq2PV6P7d6Zz2XO394VK1YYTz31lFG8eHGjSJEixv3332/8+eefDvNcvXq10aZNGyM0NNTw9fU1SpcubbRp08bh78eOHTuM9u3bG2FhYYafn59RpkwZo1u3bsbff/9t6zNx4kQjNjbW8Pb2tltuZ783nBmnMN67q7EYhmHkPxoBwM3rhx9+UNOmTbVq1SqHG/TdSnLWw4IFC656oqo7tGzZUvv378/31aRmNWvWLHXv3l0bN27Mc68+nMdhKQBAoUhMTFTt2rUVFRWlEydOaN68eUpKStL06dM9XRpMjnADACgUVqtVr7zyitLS0mSxWFSlShV99NFHevLJJz1dGkyOw1IAAMBUuEMxAAAwFcINAAAwFcINAAAwlVvuhOLs7GwdPnxYQUFBef5gHQAAuLEYhqEzZ8449ft0t1y4OXz4sMPPKAAAgJvDwYMHr/lDnbdcuMm5DfTBgwcdbukPAABuTBkZGYqKisrz5xz+6ZYLNzmHooKDgwk3AADcZJw5pYQTigEAgKkQbgAAgKkQbgAAgKkQbgAAgKkQbgAAgKl4NNz873//U9u2bVWqVClZLBZ9+eWX15xm9erVqlu3rgICAlS2bFlNnTq18AsFAAA3DY+Gm3PnzqlmzZr673//61T/ffv26f7771eTJk20ZcsWvfTSS+rfv78WLlxYyJUCAICbhUfvc9O6dWu1bt3a6f5Tp05VmTJlNHHiRElS5cqVtWnTJr355ptq165dIVUJAABuJjfVOTfr169Xy5Yt7dpatWqlTZs26dKlSx6qCgAA3EhuqjsUp6WlKSIiwq4tIiJCWVlZSk9PV2RkpMM0mZmZyszMtD3PyMgo9DoBAIDn3FR7biTH2y4bhpFre46xY8cqJCTE9uBHMwEAMLebKtyULFlSaWlpdm1Hjx6Vj4+PwsLCcp1m6NChOn36tO1x8ODB61EqAADwkJvqsFTDhg21ZMkSu7YVK1aoXr168vX1zXUaf39/+fv7X4/yAADADcCje27Onj2rrVu3auvWrZIuX+q9detWpaSkSLq816VLly62/n369NGBAweUmJio5ORkzZgxQ9OnT9fgwYM9UT4AALgBeXTPzaZNm9S0aVPb88TERElS165dNWvWLKWmptqCjiTFxsZq2bJlGjhwoN577z2VKlVKkyZN4jJwAABgYzFyzsi9RWRkZCgkJESnT59WcHCwp8sBAJfFDPna0yXcNPa/3sbTJcBNXPn+vqlOKAYAALgWwg0AADAVwg0AADAVwg0AADAVwg0AADCVm+omfkBeuHrEeVw9AsDs2HMDAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMxePhZvLkyYqNjVVAQIDq1q2rNWvWXLX/vHnzVLNmTQUGBioyMlLdu3fX8ePHr1O1AADgRufRcDN//nwNGDBAw4YN05YtW9SkSRO1bt1aKSkpufZfu3atunTpop49e+r333/XggULtHHjRvXq1es6Vw4AAG5UHg03EyZMUM+ePdWrVy9VrlxZEydOVFRUlKZMmZJr/w0bNigmJkb9+/dXbGysGjdurN69e2vTpk3XuXIAAHCj8li4uXjxojZv3qyWLVvatbds2VLr1q3LdZq4uDj99ddfWrZsmQzD0JEjR/T555+rTZs2eY6TmZmpjIwMuwcAADAvj4Wb9PR0Wa1WRURE2LVHREQoLS0t12ni4uI0b948dezYUX5+fipZsqSKFy+ud999N89xxo4dq5CQENsjKirKrcsBAABuLB4/odhisdg9NwzDoS3Hjh071L9/f73yyivavHmzvv32W+3bt099+vTJc/5Dhw7V6dOnbY+DBw+6tX4AAHBj8fHUwCVKlJC3t7fDXpqjR4867M3JMXbsWDVq1EjPP/+8JKlGjRoqWrSomjRpotGjRysyMtJhGn9/f/n7+7t/AQAAwA3JY3tu/Pz8VLduXSUlJdm1JyUlKS4uLtdpzp8/Ly8v+5K9vb0lXd7jAwAA4NHDUomJifrwww81Y8YMJScna+DAgUpJSbEdZho6dKi6dOli69+2bVstWrRIU6ZM0d69e/Xjjz+qf//+uvvuu1WqVClPLQYAALiBeOywlCR17NhRx48f16hRo5Samqpq1app2bJlio6OliSlpqba3fOmW7duOnPmjP773/9q0KBBKl68uJo1a6Zx48Z5ahEAAMANxmLcYsdzMjIyFBISotOnTys4ONjT5cBNYoZ87ekSbhr7X8/71gm4ObC9O4/t3Txc+f72+NVSAAAA7kS4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAApkK4AQAAplLgcGO1WrV161adPHnSHfUAAAAUiMvhZsCAAZo+fbqky8EmPj5ederUUVRUlH744Qd31wcAAOASl8PN559/rpo1a0qSlixZon379umPP/7QgAEDNGzYMLcXCAAA4AqXw016erpKliwpSVq2bJnat2+vChUqqGfPnvrtt9/cXiAAAIArXA43ERER2rFjh6xWq7799lu1aNFCknT+/Hl5e3u7vUAAAABX+Lg6Qffu3dWhQwdFRkbKYrEoISFBkvTTTz+pUqVKbi8QAADAFS6Hm5EjR6patWo6ePCg2rdvL39/f0mSt7e3hgwZ4vYCAQAAXOFyuJGkxx57zKGta9euBS4GAACgoJwKN5MmTdK//vUvBQQEaNKkSVft279/f7cUBgAAkB9OhZu3335bTzzxhAICAvT222/n2c9isRBuAACARzkVbvbt25frvwEAAG40/LYUAAAwlXydUPzXX39p8eLFSklJ0cWLF+1emzBhglsKAwAAyA+Xw83KlSv14IMPKjY2Vjt37lS1atW0f/9+GYahOnXqFEaNAAAATnP5sNTQoUM1aNAgbd++XQEBAVq4cKEOHjyo+Ph4tW/fvjBqBAAAcJrL4SY5Odl2TxsfHx9duHBBxYoV06hRozRu3Di3FwgAAOAKl8NN0aJFlZmZKUkqVaqU9uzZY3stPT3dfZUBAADkg8vn3DRo0EA//vijqlSpojZt2mjQoEH67bfftGjRIjVo0KAwagQAAHCay+FmwoQJOnv2rKTLvzN19uxZzZ8/X+XKlbvqDf4AAACuB5fDTdmyZW3/DgwM1OTJk91aEAAAQEG4fM7Nxo0b9dNPPzm0//TTT9q0aZNbigIAAMgvl8NNv379dPDgQYf2Q4cOqV+/fjp58qS++uorpaamuqVAAAAAV7h8WGrHjh253qyvdu3a2rhxo9q2bSur1aqMjAz9/vvvbikSAADAWS6HG39/fx05csTu3BtJSk1Nlb+/v9auXau9e/eqSpUqbisSAADAWS4flkpISNDQoUN1+vRpW9upU6c0dOhQtW3bVtLlADRlyhT3VQkAAOAkl/fcvPXWW7rnnnsUHR2t2rVrS5K2bt2qiIgIzZ07V5JUunRpde/e3b2VAgAAOMHlcFO6dGn9+uuvmjdvnrZt26YiRYqoe/fuevzxx+Xr61sYNQIAADjN5XAjXf4Jhn/961/urgUAAKDA8hVudu3apR9++EFHjx5Vdna23WuvvPKKWwoDAADID5fDzQcffKBnnnlGJUqUUMmSJWWxWGyvWSwWwg0AAPAol8PN6NGjNWbMGL344ouFUQ8AAECBuHwp+MmTJ9W+ffvCqAUAAKDAXA437du314oVKwqjFgAAgAJz+bBUuXLlNHz4cG3YsEHVq1d3uPy7f//+bisOAADAVS6Hm2nTpqlYsWJavXq1Vq9ebfeaxWIh3AAAAI9yOdzs27evMOoAAABwC5fPuQEAALiR5esmfn/99ZcWL16slJQUXbx40e61CRMmuKUwAACA/HA53KxcuVIPPvigYmNjtXPnTlWrVk379++XYRiqU6dOYdQIAADgNJcPSw0dOlSDBg3S9u3bFRAQoIULF+rgwYOKj4/n/jcAAMDjXA43ycnJ6tq1qyTJx8dHFy5cULFixTRq1CiNGzfO7QUCAAC4wuVwU7RoUWVmZkqSSpUqpT179theS09Pd19lAAAA+eDyOTcNGjTQjz/+qCpVqqhNmzYaNGiQfvvtNy1atEgNGjQojBoBAACc5nK4mTBhgs6ePStJGjlypM6ePav58+erXLlyevvtt91eIAAAgCtcOixltVp18OBBRUVFSZICAwM1efJk/frrr1q0aJGio6NdLmDy5MmKjY1VQECA6tatqzVr1ly1f2ZmpoYNG6bo6Gj5+/vrzjvv1IwZM1weFwAAmJNLe268vb3VqlUrJScn67bbbivw4PPnz9eAAQM0efJkNWrUSO+//75at26tHTt2qEyZMrlO06FDBx05ckTTp09XuXLldPToUWVlZRW4FgAAYA4uH5aqXr269u7dq9jY2AIPPmHCBPXs2VO9evWSJE2cOFHLly/XlClTNHbsWIf+3377rVavXq29e/cqNDRUkhQTE1PgOgAAgHm4fLXUmDFjNHjwYC1dulSpqanKyMiwezjr4sWL2rx5s1q2bGnX3rJlS61bty7XaRYvXqx69epp/PjxKl26tCpUqKDBgwfrwoULeY6TmZmZ7xoBAMDNx+U9N/fdd58k6cEHH5TFYrG1G4Yhi8Uiq9Xq1HzS09NltVoVERFh1x4REaG0tLRcp9m7d6/Wrl2rgIAAffHFF0pPT1ffvn114sSJPM+7GTt2rF599VWnagIAADc/l8PNqlWr3FrAPwOS9P8hKTfZ2dmyWCyaN2+eQkJCJF0+tPXYY4/pvffeU5EiRRymGTp0qBITE23PMzIybCdEAwAA83Eq3Dz66KOaNWuWgoODdeDAAXXs2FH+/v4FGrhEiRLy9vZ22Etz9OhRh705OSIjI1W6dGlbsJGkypUryzAM/fXXXypfvrzDNP7+/gWuFQAA3DycOudm6dKlOnfunCSpe/fuOn36dIEH9vPzU926dZWUlGTXnpSUpLi4uFynadSokQ4fPmy7z44k7dq1S15eXrrjjjsKXBMAALj5ObXnplKlSho6dKiaNm0qwzD02WefKTg4ONe+Xbp0cXrwxMREPfXUU6pXr54aNmyoadOmKSUlRX369JF0+ZDSoUOHNGfOHElS586d9Z///Efdu3fXq6++qvT0dD3//PPq0aNHroekAADArcepcDN16lQlJibq66+/lsVi0csvv5zreTEWi8WlcNOxY0cdP35co0aNUmpqqqpVq6Zly5bZbgaYmpqqlJQUW/9ixYopKSlJ//73v1WvXj2FhYWpQ4cOGj16tNNjAgAAc7MYhmG4MoGXl5fS0tIUHh5eWDUVqoyMDIWEhOj06dN57n3CzSdmyNeeLuGmsf/1Np4uAQXE9u48tnfzcOX72+X73Ozbt0+33357vosDAAAoTC5fCp6f348CAAC4XlzecwMAAHAjI9wAAABTcfmwFK6OE/2cx4l+AIDC4PKemwsXLuj8+fO25wcOHNDEiRO1YsUKtxYGAACQHy6Hm4ceesh2U71Tp06pfv36euutt/TQQw9pypQpbi8QAADAFS6Hm19++UVNmjSRJH3++eeKiIjQgQMHNGfOHE2aNMntBQIAALjC5XBz/vx5BQUFSZJWrFihRx99VF5eXmrQoIEOHDjg9gIBAABc4XK4KVeunL788ksdPHhQy5cvV8uWLSVd/jVv7vgLAAA8zeVw88orr2jw4MGKiYlR/fr11bBhQ0mX9+LUrl3b7QUCAAC4wuVLwR977DE1btxYqampqlmzpq29efPmevTRR91aHAAAgKtc3nPTo0cPFS1aVLVr15aX1/9PXrVqVY0bN86txQEAALjK5XAze/ZsXbhwwaH9woULtkvEAQAAPMXpw1IZGRkyDEOGYejMmTMKCAiwvWa1WrVs2TKFh4cXSpEAAADOcjrcFC9eXBaLRRaLRRUqVHB43WKx6NVXX3VrcQAAAK5yOtysWrVKhmGoWbNmWrhwoUJDQ22v+fn5KTo6WqVKlSqUIgEAAJzldLiJj4+XJO3bt09RUVF2JxMDAADcKFy+FDw6OlqnTp3Szz//rKNHjyo7O9vu9S5duritOAAAAFe5HG6WLFmiJ554QufOnVNQUJAsFovtNYvFQrgBAAAe5fKxpUGDBqlHjx46c+aMTp06pZMnT9oeJ06cKIwaAQAAnOZyuDl06JD69++vwMDAwqgHAACgQFwON61atdKmTZsKoxYAAIACc/mcmzZt2uj555/Xjh07VL16dfn6+tq9/uCDD7qtOAAAAFe5HG6efvppSdKoUaMcXrNYLLJarQWvCgAAIJ9cDjdXXvoNAABwIynQnfj+/vtvd9UBAADgFi6HG6vVqv/85z8qXbq0ihUrpr1790qShg8frunTp7u9QAAAAFe4HG7GjBmjWbNmafz48fLz87O1V69eXR9++KFbiwMAAHCVy+Fmzpw5mjZtmp544gl5e3vb2mvUqKE//vjDrcUBAAC4Kl838StXrpxDe3Z2ti5duuSWogAAAPLL5XBTtWpVrVmzxqF9wYIFql27tluKAgAAyC+XLwUfMWKEnnrqKR06dEjZ2dlatGiRdu7cqTlz5mjp0qWFUSMAAIDTXN5z07ZtW82fP1/Lli2TxWLRK6+8ouTkZC1ZskQJCQmFUSMAAIDTXN5zI13+falWrVq5uxYAAIACK9BN/AAAAG40Tu25CQ0N1a5du1SiRAnddtttslgsefY9ceKE24oDAABwlVPh5u2331ZQUJAkaeLEiYVZDwAAQIE4FW66du2a678BAABuNE6Fm4yMDKdnGBwcnO9iAAAACsqpcFO8ePGrnmcjSYZhyGKxyGq1uqUwAACA/HAq3Kxataqw6wAAAHALp8JNfHx8YdcBAADgFi7f52bmzJlasGCBQ/uCBQs0e/ZstxQFAACQXy6Hm9dff10lSpRwaA8PD9drr73mlqIAAADyy+Vwc+DAAcXGxjq0R0dHKyUlxS1FAQAA5JfL4SY8PFy//vqrQ/u2bdsUFhbmlqIAAADyy+Vw06lTJ/Xv31+rVq2S1WqV1WrV999/r+eee06dOnUqjBoBAACc5vKvgo8ePVoHDhxQ8+bN5eNzefLs7Gx16dKFc24AAIDHuRxu/Pz8NH/+fI0ePVpbt25VkSJFVL16dUVHRxdGfQAAAC5xOdzkKF++vMqXL+/OWgAAAArM5XNuAAAAbmSEGwAAYCqEGwAAYCqEGwAAYCr5Cjdr1qzRk08+qYYNG+rQoUOSpI8++khr1651a3EAAACucjncLFy4UK1atVKRIkW0ZcsWZWZmSpLOnDnDfW4AAIDHuRxuRo8eralTp+qDDz6Qr6+vrT0uLk6//PKLW4sDAABwlcvhZufOnbrnnnsc2oODg3Xq1Cl31AQAAJBvLoebyMhI7d6926F97dq1Klu2rFuKAgAAyC+Xw03v3r313HPP6aeffpLFYtHhw4c1b948DR48WH379i2MGgEAAJzmcrh54YUX9PDDD6tp06Y6e/as7rnnHvXq1Uu9e/fWs88+63IBkydPVmxsrAICAlS3bl2tWbPGqel+/PFH+fj4qFatWi6PCQAAzCtfl4KPGTNG6enp+vnnn7VhwwYdO3ZM//nPf1yez/z58zVgwAANGzZMW7ZsUZMmTdS6dWulpKRcdbrTp0+rS5cuat68eX7KBwAAJpbvm/gFBgaqXr16uvvuu1WsWLF8zWPChAnq2bOnevXqpcqVK2vixImKiorSlClTrjpd79691blzZzVs2DBf4wIAAPNy6lfBH330UadnuGjRIqf6Xbx4UZs3b9aQIUPs2lu2bKl169blOd3MmTO1Z88ezZ07V6NHj77mOJmZmbZ78UhSRkaGU/UBAICbk1N7bkJCQmyP4OBgrVy5Ups2bbK9vnnzZq1cuVIhISFOD5yeni6r1aqIiAi79oiICKWlpeU6zZ9//qkhQ4Zo3rx58vFxKpdp7NixdvVHRUU5XSMAALj5OJUQZs6cafv3iy++qA4dOmjq1Kny9vaWJFmtVvXt21fBwcEuF2CxWOyeG4bh0JYzRufOnfXqq6+qQoUKTs9/6NChSkxMtD3PyMgg4AAAYGLO7f74hxkzZmjt2rW2YCNJ3t7eSkxMVFxcnN544w2n5lOiRAl5e3s77KU5evSow94c6fLPO2zatElbtmyxXZWVnZ0twzDk4+OjFStWqFmzZg7T+fv7y9/f35VFBAAANzGXTyjOyspScnKyQ3tycrKys7Odno+fn5/q1q2rpKQku/akpCTFxcU59A8ODtZvv/2mrVu32h59+vRRxYoVtXXrVtWvX9/VRQEAACbk8p6b7t27q0ePHtq9e7caNGggSdqwYYNef/11de/e3aV5JSYm6qmnnlK9evXUsGFDTZs2TSkpKerTp4+ky4eUDh06pDlz5sjLy0vVqlWzmz48PFwBAQEO7QAA4Nblcrh58803VbJkSb399ttKTU2VdPknGV544QUNGjTIpXl17NhRx48f16hRo5Samqpq1app2bJlio6OliSlpqZe8543AAAA/2QxDMPI78Q5l1Xn50RiT8nIyFBISIhOnz5dKHXHDPna7fM0q/2vt3HbvFjvznPneodnsL07j+3dPFz5/nZ5z80/3UyhBgAA3BryfYdiAACAGxHhBgAAmArhBgAAmIrL4WbOnDl2v9WU4+LFi5ozZ45bigIAAMgvl8NN9+7ddfr0aYf2M2fOuHyfGwAAAHdzOdzk9dtPf/31l0s/nAkAAFAYnL4UvHbt2rJYLLJYLGrevLndr3JbrVbt27dP9913X6EUCQAA4Cynw83DDz8sSdq6datatWqlYsWK2V7z8/NTTEyM2rVr5/YCAQAAXOF0uBkxYoSsVquio6PVqlUrRUZGFmZdAAAA+eLSOTfe3t7q06eP/v7778KqBwAAoEBcPqG4evXq2rt3b2HUAgAAUGAuh5sxY8Zo8ODBWrp0qVJTU5WRkWH3AAAA8CSXfzgz54qoBx980O6S8JxLxK1Wq/uqAwAAcJHL4WbVqlWFUQcAAIBbuBxu4uPjC6MOAAAAt3A53OQ4f/68UlJSdPHiRbv2GjVqFLgoAACA/HI53Bw7dkzdu3fXN998k+vrnHMDAAA8yeWrpQYMGKCTJ09qw4YNKlKkiL799lvNnj1b5cuX1+LFiwujRgAAAKe5vOfm+++/11dffaW77rpLXl5eio6OVkJCgoKDgzV27Fi1adOmMOoEAABwist7bs6dO6fw8HBJUmhoqI4dOybp8s39fvnlF/dWBwAA4CKXw03FihW1c+dOSVKtWrX0/vvv69ChQ5o6dSq/NwUAADzO5cNSAwYM0OHDhyVd/jHNVq1aad68efLz89OsWbPcXR8AAIBLXA43TzzxhO3ftWvX1v79+/XHH3+oTJkyKlGihFuLAwAAcJXTh6XOnz+vfv36qXTp0goPD1fnzp2Vnp6uwMBA1alTh2ADAABuCE6HmxEjRmjWrFlq06aNOnXqpKSkJD3zzDOFWRsAAIDLnD4stWjRIk2fPl2dOnWSJD355JNq1KiRrFarvL29C61AAAAAVzi95+bgwYNq0qSJ7fndd98tHx8f28nFAAAANwKnw43VapWfn59dm4+Pj7KystxeFAAAQH45fVjKMAx169ZN/v7+tra///5bffr0UdGiRW1tixYtcm+FAAAALnA63HTt2tWh7cknn3RrMQAAAAXldLiZOXNmYdYBAADgFi7//AIAAMCNjHADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMxcfTBQAAcDOIGfK1p0u4aex/vY1Hx2fPDQAAMBXCDQAAMBWPh5vJkycrNjZWAQEBqlu3rtasWZNn30WLFikhIUG33367goOD1bBhQy1fvvw6VgsAAG50Hg038+fP14ABAzRs2DBt2bJFTZo0UevWrZWSkpJr///9739KSEjQsmXLtHnzZjVt2lRt27bVli1brnPlAADgRuXRcDNhwgT17NlTvXr1UuXKlTVx4kRFRUVpypQpufafOHGiXnjhBd11110qX768XnvtNZUvX15Lliy5zpUDAIAblcfCzcWLF7V582a1bNnSrr1ly5Zat26dU/PIzs7WmTNnFBoammefzMxMZWRk2D0AAIB5eSzcpKeny2q1KiIiwq49IiJCaWlpTs3jrbfe0rlz59ShQ4c8+4wdO1YhISG2R1RUVIHqBgAANzaPn1BssVjsnhuG4dCWm08++UQjR47U/PnzFR4enme/oUOH6vTp07bHwYMHC1wzAAC4cXnsJn4lSpSQt7e3w16ao0ePOuzNudL8+fPVs2dPLViwQC1atLhqX39/f/n7+xe4XgAAcHPw2J4bPz8/1a1bV0lJSXbtSUlJiouLy3O6Tz75RN26ddPHH3+sNm08ewdEAABw4/Hozy8kJibqqaeeUr169dSwYUNNmzZNKSkp6tOnj6TLh5QOHTqkOXPmSLocbLp06aJ33nlHDRo0sO31KVKkiEJCQjy2HAAA4Mbh0XDTsWNHHT9+XKNGjVJqaqqqVaumZcuWKTo6WpKUmppqd8+b999/X1lZWerXr5/69etna+/atatmzZp1vcsHAAA3II//cGbfvn3Vt2/fXF+7MrD88MMPhV8QAAC4qXn8aikAAAB3ItwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABT8fF0AQBuXjFDvvZ0CTeN/a+38XQJwC2DPTcAAMBUCDcAAMBUPB5uJk+erNjYWAUEBKhu3bpas2bNVfuvXr1adevWVUBAgMqWLaupU6dep0oBAMDNwKPhZv78+RowYICGDRumLVu2qEmTJmrdurVSUlJy7b9v3z7df//9atKkibZs2aKXXnpJ/fv318KFC69z5QAA4Ebl0XAzYcIE9ezZU7169VLlypU1ceJERUVFacqUKbn2nzp1qsqUKaOJEyeqcuXK6tWrl3r06KE333zzOlcOAABuVB4LNxcvXtTmzZvVsmVLu/aWLVtq3bp1uU6zfv16h/6tWrXSpk2bdOnSpUKrFQAA3Dw8dil4enq6rFarIiIi7NojIiKUlpaW6zRpaWm59s/KylJ6eroiIyMdpsnMzFRmZqbt+enTpyVJGRkZBV2EXGVnni+U+ZqRO98D1rvzWO+ewXr3DNa7ZxTGd2zOPA3DuGZfj9/nxmKx2D03DMOh7Vr9c2vPMXbsWL366qsO7VFRUa6WCjcLmejpCm5NrHfPYL17BuvdMwpzvZ85c0YhISFX7eOxcFOiRAl5e3s77KU5evSow96ZHCVLlsy1v4+Pj8LCwnKdZujQoUpMTLQ9z87O1okTJxQWFnbVEGUmGRkZioqK0sGDBxUcHOzpcm4JrHPPYL17BuvdM2619W4Yhs6cOaNSpUpds6/Hwo2fn5/q1q2rpKQkPfLII7b2pKQkPfTQQ7lO07BhQy1ZssSubcWKFapXr558fX1zncbf31/+/v52bcWLFy9Y8Tep4ODgW+IDcCNhnXsG690zWO+ecSut92vtscnh0aulEhMT9eGHH2rGjBlKTk7WwIEDlZKSoj59+ki6vNelS5cutv59+vTRgQMHlJiYqOTkZM2YMUPTp0/X4MGDPbUIAADgBuPRc246duyo48ePa9SoUUpNTVW1atW0bNkyRUdHS5JSU1Pt7nkTGxurZcuWaeDAgXrvvfdUqlQpTZo0Se3atfPUIgAAgBuMx08o7tu3r/r27Zvra7NmzXJoi4+P1y+//FLIVZmLv7+/RowY4XB4DoWHde4ZrHfPYL17Bus9bxbDmWuqAAAAbhIe/20pAAAAdyLcAAAAUyHcAAAAUyHcAAAAUyHcmNTIkSNlsVjsHiVLlvR0WbeEQ4cO6cknn1RYWJgCAwNVq1Ytbd682dNlmVpMTIzD9m6xWNSvXz9Pl2ZqWVlZevnllxUbG6siRYqobNmyGjVqlLKzsz1dmumdOXNGAwYMUHR0tIoUKaK4uDht3LjR02XdMDx+KTgKT9WqVfXdd9/Znnt7e3uwmlvDyZMn1ahRIzVt2lTffPONwsPDtWfPnlv2rtjXy8aNG2W1Wm3Pt2/froSEBLVv396DVZnfuHHjNHXqVM2ePVtVq1bVpk2b1L17d4WEhOi5557zdHmm1qtXL23fvl0fffSRSpUqpblz56pFixbasWOHSpcu7enyPI5LwU1q5MiR+vLLL7V161ZPl3JLGTJkiH788UetWbPG06Xc0gYMGKClS5fqzz//vGV+Q84THnjgAUVERGj69Om2tnbt2ikwMFAfffSRBysztwsXLigoKEhfffWV2rRpY2uvVauWHnjgAY0ePdqD1d0YOCxlYn/++adKlSql2NhYderUSXv37vV0Saa3ePFi1atXT+3bt1d4eLhq166tDz74wNNl3VIuXryouXPnqkePHgSbQta4cWOtXLlSu3btkiRt27ZNa9eu1f333+/hyswtKytLVqtVAQEBdu1FihTR2rVrPVTVjYVwY1L169fXnDlztHz5cn3wwQdKS0tTXFycjh8/7unSTG3v3r2aMmWKypcvr+XLl6tPnz7q37+/5syZ4+nSbhlffvmlTp06pW7dunm6FNN78cUX9fjjj6tSpUry9fVV7dq1NWDAAD3++OOeLs3UgoKC1LBhQ/3nP//R4cOHZbVaNXfuXP30009KTU31dHk3BA5L3SLOnTunO++8Uy+88IISExM9XY5p+fn5qV69elq3bp2trX///tq4caPWr1/vwcpuHa1atZKfn5+WLFni6VJM79NPP9Xzzz+vN954Q1WrVtXWrVs1YMAATZgwQV27dvV0eaa2Z88e9ejRQ//73//k7e2tOnXqqEKFCvrll1+0Y8cOT5fncZxQfIsoWrSoqlevrj///NPTpZhaZGSkqlSpYtdWuXJlLVy40EMV3VoOHDig7777TosWLfJ0KbeE559/XkOGDFGnTp0kSdWrV9eBAwc0duxYwk0hu/POO7V69WqdO3dOGRkZioyMVMeOHRUbG+vp0m4IHJa6RWRmZio5OVmRkZGeLsXUGjVqpJ07d9q17dq1y/ZL9yhcM2fOVHh4uN1Jlig858+fl5eX/deIt7c3l4JfR0WLFlVkZKROnjyp5cuX66GHHvJ0STcE9tyY1ODBg9W2bVuVKVNGR48e1ejRo5WRkcH/pgrZwIEDFRcXp9dee00dOnTQzz//rGnTpmnatGmeLs30srOzNXPmTHXt2lU+Pvxpux7atm2rMWPGqEyZMqpataq2bNmiCRMmqEePHp4uzfSWL18uwzBUsWJF7d69W88//7wqVqyo7t27e7q0G4MBU+rYsaMRGRlp+Pr6GqVKlTIeffRR4/fff/d0WbeEJUuWGNWqVTP8/f2NSpUqGdOmTfN0SbeE5cuXG5KMnTt3erqUW0ZGRobx3HPPGWXKlDECAgKMsmXLGsOGDTMyMzM9XZrpzZ8/3yhbtqzh5+dnlCxZ0ujXr59x6tQpT5d1w+CEYgAAYCqccwMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAOgUKSlpenf//63ypYtK39/f0VFRalt27ZauXKlp0sDYHL8AAsAt9u/f78aNWqk4sWLa/z48apRo4YuXbqk5cuXq1+/fvrjjz88XSIAE2PPDQC369u3rywWi37++Wc99thjqlChgqpWrarExERt2LBBkpSSkqKHHnpIxYoVU3BwsDp06KAjR47Y5jFy5EjVqlVLM2bMUJkyZVSsWDE988wzslqtGj9+vEqWLKnw8HCNGTPGbmyLxaIpU6aodevWKlKkiGJjY7VgwQK7Pi+++KIqVKigwMBAlS1bVsOHD9elS5ccxv7oo48UExOjkJAQderUSWfOnJEkzZkzR2FhYcrMzLSbb7t27dSlSxe3rksAriPcAHCrEydO6Ntvv1W/fv1UtGhRh9eLFy8uwzD08MMP68SJE1q9erWSkpK0Z88edezY0a7vnj179M033+jbb7/VJ598ohkzZqhNmzb666+/tHr1ao0bN04vv/yyLTDlGD58uNq1a6dt27bpySef1OOPP67k5GTb60FBQZo1a5Z27Nihd955Rx988IHefvtth7G//PJLLV26VEuXLtXq1av1+uuvS5Lat28vq9WqxYsX2/qnp6dr6dKl/CozcCPw8A93AjCZn376yZBkLFq0KM8+K1asMLy9vY2UlBRb2++//25IMn7++WfDMAxjxIgRRmBgoJGRkWHr06pVKyMmJsawWq22tooVKxpjx461PZdk9OnTx268+vXrG88880ye9YwfP96oW7eu7XluYz///PNG/fr1bc+feeYZo3Xr1rbnEydONMqWLWtkZ2fnOQ6A64NzbgC4lWEYki4fHspLcnKyoqKiFBUVZWurUqWKihcvruTkZN11112SpJiYGAUFBdn6REREyNvbW15eXnZtR48etZt/w4YNHZ5v3brV9vzzzz/XxIkTtXv3bp09e1ZZWVkKDg62m+bKsSMjI+3Gefrpp3XXXXfp0KFDKl26tGbOnKlu3bpddbkBXB8clgLgVuXLl5fFYrE7DHQlwzByDQFXtvv6+tq9brFYcm3Lzs6+Zl05892wYYM6deqk1q1ba+nSpdqyZYuGDRumixcv2vW/1ji1a9dWzZo1NWfOHP3yyy/67bff1K1bt2vWAaDwEW4AuFVoaKhatWql9957T+fOnXN4/dSpU6pSpYpSUlJ08OBBW/uOHTt0+vRpVa5cucA1XHkOzoYNG1SpUiVJ0o8//qjo6GgNGzZM9erVU/ny5XXgwIF8jdOrVy/NnDlTM2bMUIsWLez2RAHwHMINALebPHmyrFar7r77bi1cuFB//vmnkpOTNWnSJDVs2FAtWrRQjRo19MQTT+iXX37Rzz//rC5duig+Pl716tUr8PgLFizQjBkztGvXLo0YMUI///yznn32WUlSuXLllJKSok8//VR79uzRpEmT9MUXX+RrnCeeeEKHDh3SBx98oB49ehS4bgDuQbgB4HaxsbH65Zdf1LRpUw0aNEjVqlVTQkKCVq5cqSlTpshisejLL7/UbbfdpnvuuUctWrRQ2bJlNX/+fLeM/+qrr+rTTz9VjRo1NHv2bM2bN09VqlSRJD300EMaOHCgnn32WdWqVUvr1q3T8OHD8zVOcHCw2rVrp2LFiunhhx92S+0ACs5i5Jz9BwAmYLFY9MUXX1y3sJGQkKDKlStr0qRJ12U8ANfG1VIAkA8nTpzQihUr9P333+u///2vp8sB8A+EGwDIhzp16ujkyZMaN26cKlas6OlyAPwDh6UAAICpcEIxAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwlf8DNQlGe3xOUnMAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "country_bar(customer_sport)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43d63ea3-75f4-4356-a7e9-35905d86baa5",
+   "metadata": {},
+   "source": [
+    "### 2. campaigns_information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "8d116e34-cdd6-4ef9-8622-474da79f79ef",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre de lignes de la table :  463098\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "customer_id                 0\n",
+       "nb_campaigns                0\n",
+       "nb_campaigns_opened         0\n",
+       "time_to_open           178826\n",
+       "number_company              0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(\"Nombre de lignes de la table : \",campaigns_sport.shape[0])\n",
+    "campaigns_sport.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "724d3c33-c219-4212-b8b6-dd78481674cb",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "country_bar()"
+    "campaigns_sport[\"no_campaign_opened\"] = pd.isna(campaigns_sport[\"time_to_open\"])\n",
+    "company_lazy_customers = campaigns_sport.groupby(\"number_company\")[\"no_campaign_opened\"].mean().reset_index()\n",
+    "\n",
+    "def lazy_customer_plot(campaigns_sport):\n",
+    "    company_lazy_customers = campaigns_sport.groupby(\"number_company\")[\"no_campaign_opened\"].mean().reset_index()\n",
+    "    # Création du barplot\n",
+    "    plt.bar(company_lazy_customers[\"number_company\"], company_lazy_customers[\"no_campaign_opened\"])\n",
+    "    \n",
+    "    # Ajout de titres et d'étiquettes\n",
+    "    plt.xlabel('Company')\n",
+    "    plt.ylabel(\"Part de clients n'ayant ouvert aucun mail\")\n",
+    "    plt.title(\"Part de clients n'ayant ouvert aucun mail pour les compagnies de sport\")\n",
+    "    \n",
+    "    # Affichage du barplot\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "e513f308-3a9c-40ed-99d5-ed420bd67384",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "lazy_customer_plot(campaigns_sport)"
    ]
   }
  ],