From f2e6e55bdd956e31f221d55c38170bc37db1d34e Mon Sep 17 00:00:00 2001
From: ajoubrel-ensae <antoine.joubrel@ensae.fr>
Date: Tue, 13 Feb 2024 17:45:33 +0000
Subject: [PATCH] Ajout graphique evolution

---
 0_Cleaning_and_merge.ipynb     |  20 +-
 1_Descriptive_Statistics.ipynb | 502 ++++++++++++++++++++++++++-------
 2 files changed, 417 insertions(+), 105 deletions(-)

diff --git a/0_Cleaning_and_merge.ipynb b/0_Cleaning_and_merge.ipynb
index 3211835..169cd23 100644
--- a/0_Cleaning_and_merge.ipynb
+++ b/0_Cleaning_and_merge.ipynb
@@ -1278,7 +1278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 44,
    "id": "89dc9685-1de9-4ce3-a6c0-8d7f1931a951",
    "metadata": {},
    "outputs": [
@@ -1517,7 +1517,7 @@
        "[5 rows x 21 columns]"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 44,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1541,6 +1541,22 @@
     "df1_products_purchased_reduced = df1_products_purchased[['ticket_id', 'customer_id', 'purchase_id' ,'event_type_id', 'supplier_name', 'purchase_date', 'type_of_ticket_name', 'amount', 'children', 'is_full_price', 'name_event_types', 'name_facilities', 'name_categories', 'name_events', 'name_seasons']]"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "6d2d2aaa-3c28-4e74-88ec-db48830018f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Exportation \n",
+    "BUCKET_OUT = \"projet-bdc2324-team1\"\n",
+    "FILE_KEY_OUT_S3 = \"0_Temp/Company 1 - Purchases.csv\"\n",
+    "FILE_PATH_OUT_S3 = BUCKET_OUT + \"/\" + FILE_KEY_OUT_S3\n",
+    "\n",
+    "with fs.open(FILE_PATH_OUT_S3, 'w') as file_out:\n",
+    "    df1_products_purchased_reduced.to_csv(file_out, index = False)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "d7c3668a-c016-4bd0-837e-04af328ff14f",
diff --git a/1_Descriptive_Statistics.ipynb b/1_Descriptive_Statistics.ipynb
index 19b7854..3f6584d 100644
--- a/1_Descriptive_Statistics.ipynb
+++ b/1_Descriptive_Statistics.ipynb
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 1,
    "id": "abfaf341-7b35-4407-9133-d21336c04027",
    "metadata": {},
    "outputs": [],
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 2,
    "id": "7fb72fa3-7940-496f-ac78-c2837f65eefa",
    "metadata": {},
    "outputs": [],
@@ -89,6 +89,7 @@
        "      <th>customer_id</th>\n",
        "      <th>event_type_id</th>\n",
        "      <th>nb_tickets</th>\n",
+       "      <th>nb_purchases</th>\n",
        "      <th>total_amount</th>\n",
        "      <th>nb_suppliers</th>\n",
        "      <th>vente_internet_max</th>\n",
@@ -96,6 +97,8 @@
        "      <th>purchase_date_max</th>\n",
        "      <th>time_between_purchase</th>\n",
        "      <th>nb_tickets_internet</th>\n",
+       "      <th>name_event_types</th>\n",
+       "      <th>avg_amount</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -104,91 +107,113 @@
        "      <td>1</td>\n",
        "      <td>2</td>\n",
        "      <td>384226</td>\n",
+       "      <td>194790</td>\n",
        "      <td>2686540.5</td>\n",
        "      <td>7</td>\n",
        "      <td>1</td>\n",
-       "      <td>2014-12-03 14:55:37+00:00</td>\n",
-       "      <td>2023-11-04 15:12:16+00:00</td>\n",
-       "      <td>3258 days 00:16:39</td>\n",
+       "      <td>3262.190868</td>\n",
+       "      <td>4.179306</td>\n",
+       "      <td>3258.011562</td>\n",
        "      <td>51.0</td>\n",
+       "      <td>offre muséale individuel</td>\n",
+       "      <td>6.150659</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>4</td>\n",
        "      <td>453242</td>\n",
+       "      <td>228945</td>\n",
        "      <td>3248965.5</td>\n",
        "      <td>6</td>\n",
        "      <td>1</td>\n",
-       "      <td>2013-09-23 14:45:01+00:00</td>\n",
-       "      <td>2023-11-03 14:11:01+00:00</td>\n",
-       "      <td>3692 days 23:26:00</td>\n",
+       "      <td>3698.198229</td>\n",
+       "      <td>5.221840</td>\n",
+       "      <td>3692.976389</td>\n",
        "      <td>2988.0</td>\n",
+       "      <td>spectacle vivant</td>\n",
+       "      <td>7.762474</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>5</td>\n",
        "      <td>201750</td>\n",
+       "      <td>107110</td>\n",
        "      <td>1459190.0</td>\n",
        "      <td>6</td>\n",
        "      <td>1</td>\n",
-       "      <td>2013-06-10 10:37:58+00:00</td>\n",
-       "      <td>2023-11-08 15:59:45+00:00</td>\n",
-       "      <td>3803 days 05:21:47</td>\n",
+       "      <td>3803.369792</td>\n",
+       "      <td>0.146331</td>\n",
+       "      <td>3803.223461</td>\n",
        "      <td>9.0</td>\n",
+       "      <td>offre muséale groupe</td>\n",
+       "      <td>4.452618</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>6</td>\n",
        "      <td>217356</td>\n",
+       "      <td>111786</td>\n",
        "      <td>1435871.5</td>\n",
        "      <td>5</td>\n",
        "      <td>1</td>\n",
-       "      <td>2017-01-01 02:20:08+00:00</td>\n",
-       "      <td>2019-12-31 02:20:06+00:00</td>\n",
-       "      <td>1093 days 23:59:58</td>\n",
+       "      <td>2502.715509</td>\n",
+       "      <td>1408.715532</td>\n",
+       "      <td>1093.999977</td>\n",
        "      <td>5.0</td>\n",
+       "      <td>formule adhésion</td>\n",
+       "      <td>6.439463</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>2</td>\n",
        "      <td>2</td>\n",
        "      <td>143</td>\n",
+       "      <td>143</td>\n",
        "      <td>0.0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>2018-04-07 12:55:07+00:00</td>\n",
-       "      <td>2020-03-08 12:06:43+00:00</td>\n",
-       "      <td>700 days 23:11:36</td>\n",
+       "      <td>2041.274549</td>\n",
+       "      <td>1340.308160</td>\n",
+       "      <td>700.966389</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>offre muséale individuel</td>\n",
+       "      <td>6.150659</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "   customer_id  event_type_id  nb_tickets  total_amount  nb_suppliers  \\\n",
-       "0            1              2      384226     2686540.5             7   \n",
-       "1            1              4      453242     3248965.5             6   \n",
-       "2            1              5      201750     1459190.0             6   \n",
-       "3            1              6      217356     1435871.5             5   \n",
-       "4            2              2         143           0.0             1   \n",
+       "   customer_id  event_type_id  nb_tickets  nb_purchases  total_amount  \\\n",
+       "0            1              2      384226        194790     2686540.5   \n",
+       "1            1              4      453242        228945     3248965.5   \n",
+       "2            1              5      201750        107110     1459190.0   \n",
+       "3            1              6      217356        111786     1435871.5   \n",
+       "4            2              2         143           143           0.0   \n",
        "\n",
-       "   vente_internet_max          purchase_date_min          purchase_date_max  \\\n",
-       "0                   1  2014-12-03 14:55:37+00:00  2023-11-04 15:12:16+00:00   \n",
-       "1                   1  2013-09-23 14:45:01+00:00  2023-11-03 14:11:01+00:00   \n",
-       "2                   1  2013-06-10 10:37:58+00:00  2023-11-08 15:59:45+00:00   \n",
-       "3                   1  2017-01-01 02:20:08+00:00  2019-12-31 02:20:06+00:00   \n",
-       "4                   0  2018-04-07 12:55:07+00:00  2020-03-08 12:06:43+00:00   \n",
+       "   nb_suppliers  vente_internet_max  purchase_date_min  purchase_date_max  \\\n",
+       "0             7                   1        3262.190868           4.179306   \n",
+       "1             6                   1        3698.198229           5.221840   \n",
+       "2             6                   1        3803.369792           0.146331   \n",
+       "3             5                   1        2502.715509        1408.715532   \n",
+       "4             1                   0        2041.274549        1340.308160   \n",
        "\n",
-       "  time_between_purchase  nb_tickets_internet  \n",
-       "0    3258 days 00:16:39                 51.0  \n",
-       "1    3692 days 23:26:00               2988.0  \n",
-       "2    3803 days 05:21:47                  9.0  \n",
-       "3    1093 days 23:59:58                  5.0  \n",
-       "4     700 days 23:11:36                  0.0  "
+       "   time_between_purchase  nb_tickets_internet          name_event_types  \\\n",
+       "0            3258.011562                 51.0  offre muséale individuel   \n",
+       "1            3692.976389               2988.0          spectacle vivant   \n",
+       "2            3803.223461                  9.0      offre muséale groupe   \n",
+       "3            1093.999977                  5.0          formule adhésion   \n",
+       "4             700.966389                  0.0  offre muséale individuel   \n",
+       "\n",
+       "   avg_amount  \n",
+       "0    6.150659  \n",
+       "1    7.762474  \n",
+       "2    4.452618  \n",
+       "3    6.439463  \n",
+       "4    6.150659  "
       ]
      },
      "execution_count": 4,
@@ -209,9 +234,10 @@
     {
      "data": {
       "text/plain": [
-       "Index(['customer_id', 'event_type_id', 'nb_tickets', 'total_amount',\n",
-       "       'nb_suppliers', 'vente_internet_max', 'purchase_date_min',\n",
-       "       'purchase_date_max', 'time_between_purchase', 'nb_tickets_internet'],\n",
+       "Index(['customer_id', 'event_type_id', 'nb_tickets', 'nb_purchases',\n",
+       "       'total_amount', 'nb_suppliers', 'vente_internet_max',\n",
+       "       'purchase_date_min', 'purchase_date_max', 'time_between_purchase',\n",
+       "       'nb_tickets_internet', 'name_event_types', 'avg_amount'],\n",
        "      dtype='object')"
       ]
      },
@@ -254,6 +280,7 @@
        "      <th>customer_id</th>\n",
        "      <th>event_type_id</th>\n",
        "      <th>nb_tickets</th>\n",
+       "      <th>nb_purchases</th>\n",
        "      <th>total_amount</th>\n",
        "      <th>nb_suppliers</th>\n",
        "      <th>vente_internet_max</th>\n",
@@ -261,6 +288,8 @@
        "      <th>purchase_date_max</th>\n",
        "      <th>time_between_purchase</th>\n",
        "      <th>nb_tickets_internet</th>\n",
+       "      <th>name_event_types</th>\n",
+       "      <th>avg_amount</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -269,171 +298,213 @@
        "      <td>1</td>\n",
        "      <td>4</td>\n",
        "      <td>453242</td>\n",
+       "      <td>228945</td>\n",
        "      <td>3248965.5</td>\n",
        "      <td>6</td>\n",
        "      <td>1</td>\n",
-       "      <td>2013-09-23 14:45:01+00:00</td>\n",
-       "      <td>2023-11-03 14:11:01+00:00</td>\n",
-       "      <td>3692 days 23:26:00</td>\n",
+       "      <td>3698.198229</td>\n",
+       "      <td>5.221840</td>\n",
+       "      <td>3692.976389</td>\n",
        "      <td>2988.0</td>\n",
+       "      <td>spectacle vivant</td>\n",
+       "      <td>7.762474</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>2</td>\n",
        "      <td>384226</td>\n",
+       "      <td>194790</td>\n",
        "      <td>2686540.5</td>\n",
        "      <td>7</td>\n",
        "      <td>1</td>\n",
-       "      <td>2014-12-03 14:55:37+00:00</td>\n",
-       "      <td>2023-11-04 15:12:16+00:00</td>\n",
-       "      <td>3258 days 00:16:39</td>\n",
+       "      <td>3262.190868</td>\n",
+       "      <td>4.179306</td>\n",
+       "      <td>3258.011562</td>\n",
        "      <td>51.0</td>\n",
+       "      <td>offre muséale individuel</td>\n",
+       "      <td>6.150659</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>6</td>\n",
        "      <td>217356</td>\n",
+       "      <td>111786</td>\n",
        "      <td>1435871.5</td>\n",
        "      <td>5</td>\n",
        "      <td>1</td>\n",
-       "      <td>2017-01-01 02:20:08+00:00</td>\n",
-       "      <td>2019-12-31 02:20:06+00:00</td>\n",
-       "      <td>1093 days 23:59:58</td>\n",
+       "      <td>2502.715509</td>\n",
+       "      <td>1408.715532</td>\n",
+       "      <td>1093.999977</td>\n",
        "      <td>5.0</td>\n",
+       "      <td>formule adhésion</td>\n",
+       "      <td>6.439463</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>5</td>\n",
        "      <td>201750</td>\n",
+       "      <td>107110</td>\n",
        "      <td>1459190.0</td>\n",
        "      <td>6</td>\n",
        "      <td>1</td>\n",
-       "      <td>2013-06-10 10:37:58+00:00</td>\n",
-       "      <td>2023-11-08 15:59:45+00:00</td>\n",
-       "      <td>3803 days 05:21:47</td>\n",
+       "      <td>3803.369792</td>\n",
+       "      <td>0.146331</td>\n",
+       "      <td>3803.223461</td>\n",
        "      <td>9.0</td>\n",
+       "      <td>offre muséale groupe</td>\n",
+       "      <td>4.452618</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5032</th>\n",
        "      <td>6733</td>\n",
        "      <td>6</td>\n",
        "      <td>14208</td>\n",
+       "      <td>114</td>\n",
        "      <td>0.0</td>\n",
        "      <td>3</td>\n",
        "      <td>1</td>\n",
-       "      <td>2017-01-11 15:00:54+00:00</td>\n",
-       "      <td>2019-11-27 09:47:06+00:00</td>\n",
-       "      <td>1049 days 18:46:12</td>\n",
+       "      <td>2492.187199</td>\n",
+       "      <td>1442.405116</td>\n",
+       "      <td>1049.782083</td>\n",
        "      <td>13497.0</td>\n",
+       "      <td>formule adhésion</td>\n",
+       "      <td>6.439463</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5029</th>\n",
        "      <td>6733</td>\n",
        "      <td>2</td>\n",
        "      <td>11656</td>\n",
+       "      <td>158</td>\n",
        "      <td>471.0</td>\n",
        "      <td>3</td>\n",
        "      <td>1</td>\n",
-       "      <td>2015-09-09 13:48:38+00:00</td>\n",
-       "      <td>2022-07-07 07:37:12+00:00</td>\n",
-       "      <td>2492 days 17:48:34</td>\n",
+       "      <td>2982.237384</td>\n",
+       "      <td>489.495324</td>\n",
+       "      <td>2492.742060</td>\n",
        "      <td>9815.0</td>\n",
+       "      <td>offre muséale individuel</td>\n",
+       "      <td>6.150659</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5030</th>\n",
        "      <td>6733</td>\n",
        "      <td>4</td>\n",
        "      <td>7440</td>\n",
+       "      <td>162</td>\n",
        "      <td>0.0</td>\n",
        "      <td>2</td>\n",
        "      <td>1</td>\n",
-       "      <td>2021-01-06 10:05:01+00:00</td>\n",
-       "      <td>2022-09-08 14:39:40+00:00</td>\n",
-       "      <td>610 days 04:34:39</td>\n",
+       "      <td>1036.392674</td>\n",
+       "      <td>426.201944</td>\n",
+       "      <td>610.190729</td>\n",
        "      <td>7419.0</td>\n",
+       "      <td>spectacle vivant</td>\n",
+       "      <td>7.762474</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>60</th>\n",
        "      <td>41</td>\n",
        "      <td>6</td>\n",
        "      <td>6583</td>\n",
+       "      <td>634</td>\n",
        "      <td>12546.5</td>\n",
        "      <td>4</td>\n",
        "      <td>1</td>\n",
-       "      <td>2017-01-02 11:23:53+00:00</td>\n",
-       "      <td>2019-12-30 10:36:55+00:00</td>\n",
-       "      <td>1091 days 23:13:02</td>\n",
+       "      <td>2501.337905</td>\n",
+       "      <td>1409.370521</td>\n",
+       "      <td>1091.967384</td>\n",
        "      <td>6391.0</td>\n",
+       "      <td>formule adhésion</td>\n",
+       "      <td>6.439463</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>57</th>\n",
        "      <td>41</td>\n",
        "      <td>2</td>\n",
        "      <td>6514</td>\n",
+       "      <td>812</td>\n",
        "      <td>22423.0</td>\n",
        "      <td>6</td>\n",
        "      <td>1</td>\n",
-       "      <td>2014-01-23 16:56:57+00:00</td>\n",
-       "      <td>2023-03-06 13:55:23+00:00</td>\n",
-       "      <td>3328 days 20:58:26</td>\n",
+       "      <td>3576.106609</td>\n",
+       "      <td>247.232697</td>\n",
+       "      <td>3328.873912</td>\n",
        "      <td>5321.0</td>\n",
+       "      <td>offre muséale individuel</td>\n",
+       "      <td>6.150659</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>36376</th>\n",
        "      <td>63488</td>\n",
        "      <td>4</td>\n",
        "      <td>5750</td>\n",
+       "      <td>9</td>\n",
        "      <td>63250.0</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
-       "      <td>2021-06-04 12:20:39+00:00</td>\n",
-       "      <td>2022-08-25 13:08:38+00:00</td>\n",
-       "      <td>447 days 00:47:59</td>\n",
+       "      <td>887.298484</td>\n",
+       "      <td>440.265162</td>\n",
+       "      <td>447.033322</td>\n",
        "      <td>5750.0</td>\n",
+       "      <td>spectacle vivant</td>\n",
+       "      <td>7.762474</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "       customer_id  event_type_id  nb_tickets  total_amount  nb_suppliers  \\\n",
-       "1                1              4      453242     3248965.5             6   \n",
-       "0                1              2      384226     2686540.5             7   \n",
-       "3                1              6      217356     1435871.5             5   \n",
-       "2                1              5      201750     1459190.0             6   \n",
-       "5032          6733              6       14208           0.0             3   \n",
-       "5029          6733              2       11656         471.0             3   \n",
-       "5030          6733              4        7440           0.0             2   \n",
-       "60              41              6        6583       12546.5             4   \n",
-       "57              41              2        6514       22423.0             6   \n",
-       "36376        63488              4        5750       63250.0             1   \n",
+       "       customer_id  event_type_id  nb_tickets  nb_purchases  total_amount  \\\n",
+       "1                1              4      453242        228945     3248965.5   \n",
+       "0                1              2      384226        194790     2686540.5   \n",
+       "3                1              6      217356        111786     1435871.5   \n",
+       "2                1              5      201750        107110     1459190.0   \n",
+       "5032          6733              6       14208           114           0.0   \n",
+       "5029          6733              2       11656           158         471.0   \n",
+       "5030          6733              4        7440           162           0.0   \n",
+       "60              41              6        6583           634       12546.5   \n",
+       "57              41              2        6514           812       22423.0   \n",
+       "36376        63488              4        5750             9       63250.0   \n",
        "\n",
-       "       vente_internet_max          purchase_date_min  \\\n",
-       "1                       1  2013-09-23 14:45:01+00:00   \n",
-       "0                       1  2014-12-03 14:55:37+00:00   \n",
-       "3                       1  2017-01-01 02:20:08+00:00   \n",
-       "2                       1  2013-06-10 10:37:58+00:00   \n",
-       "5032                    1  2017-01-11 15:00:54+00:00   \n",
-       "5029                    1  2015-09-09 13:48:38+00:00   \n",
-       "5030                    1  2021-01-06 10:05:01+00:00   \n",
-       "60                      1  2017-01-02 11:23:53+00:00   \n",
-       "57                      1  2014-01-23 16:56:57+00:00   \n",
-       "36376                   1  2021-06-04 12:20:39+00:00   \n",
+       "       nb_suppliers  vente_internet_max  purchase_date_min  purchase_date_max  \\\n",
+       "1                 6                   1        3698.198229           5.221840   \n",
+       "0                 7                   1        3262.190868           4.179306   \n",
+       "3                 5                   1        2502.715509        1408.715532   \n",
+       "2                 6                   1        3803.369792           0.146331   \n",
+       "5032              3                   1        2492.187199        1442.405116   \n",
+       "5029              3                   1        2982.237384         489.495324   \n",
+       "5030              2                   1        1036.392674         426.201944   \n",
+       "60                4                   1        2501.337905        1409.370521   \n",
+       "57                6                   1        3576.106609         247.232697   \n",
+       "36376             1                   1         887.298484         440.265162   \n",
        "\n",
-       "               purchase_date_max time_between_purchase  nb_tickets_internet  \n",
-       "1      2023-11-03 14:11:01+00:00    3692 days 23:26:00               2988.0  \n",
-       "0      2023-11-04 15:12:16+00:00    3258 days 00:16:39                 51.0  \n",
-       "3      2019-12-31 02:20:06+00:00    1093 days 23:59:58                  5.0  \n",
-       "2      2023-11-08 15:59:45+00:00    3803 days 05:21:47                  9.0  \n",
-       "5032   2019-11-27 09:47:06+00:00    1049 days 18:46:12              13497.0  \n",
-       "5029   2022-07-07 07:37:12+00:00    2492 days 17:48:34               9815.0  \n",
-       "5030   2022-09-08 14:39:40+00:00     610 days 04:34:39               7419.0  \n",
-       "60     2019-12-30 10:36:55+00:00    1091 days 23:13:02               6391.0  \n",
-       "57     2023-03-06 13:55:23+00:00    3328 days 20:58:26               5321.0  \n",
-       "36376  2022-08-25 13:08:38+00:00     447 days 00:47:59               5750.0  "
+       "       time_between_purchase  nb_tickets_internet          name_event_types  \\\n",
+       "1                3692.976389               2988.0          spectacle vivant   \n",
+       "0                3258.011562                 51.0  offre muséale individuel   \n",
+       "3                1093.999977                  5.0          formule adhésion   \n",
+       "2                3803.223461                  9.0      offre muséale groupe   \n",
+       "5032             1049.782083              13497.0          formule adhésion   \n",
+       "5029             2492.742060               9815.0  offre muséale individuel   \n",
+       "5030              610.190729               7419.0          spectacle vivant   \n",
+       "60               1091.967384               6391.0          formule adhésion   \n",
+       "57               3328.873912               5321.0  offre muséale individuel   \n",
+       "36376             447.033322               5750.0          spectacle vivant   \n",
+       "\n",
+       "       avg_amount  \n",
+       "1        7.762474  \n",
+       "0        6.150659  \n",
+       "3        6.439463  \n",
+       "2        4.452618  \n",
+       "5032     6.439463  \n",
+       "5029     6.150659  \n",
+       "5030     7.762474  \n",
+       "60       6.439463  \n",
+       "57       6.150659  \n",
+       "36376    7.762474  "
       ]
      },
      "execution_count": 6,
@@ -470,7 +541,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 300x300 with 1 Axes>"
       ]
@@ -510,6 +581,231 @@
     "tickets_kpi_filtered  = tickets_kpi[tickets_kpi['customer_id'] != 1]"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "736fbb88-5904-49eb-94a6-dfb4e1ff0051",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Evolution vente \n",
+    "\n",
+    "# Importation\n",
+    "# Chargement des données temporaires\n",
+    "BUCKET = \"projet-bdc2324-team1\"\n",
+    "FILE_KEY_S3 = \"0_Temp/Company 1 - Purchases.csv\"\n",
+    "FILE_PATH_S3 = BUCKET + \"/\" + FILE_KEY_S3\n",
+    "\n",
+    "with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n",
+    "    purchases = pd.read_csv(file_in, sep=\",\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "3b633603-82b3-4694-bb4b-03be8c45ecc1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['ticket_id', 'customer_id', 'purchase_id', 'event_type_id',\n",
+       "       'supplier_name', 'purchase_date', 'type_of_ticket_name', 'amount',\n",
+       "       'children', 'is_full_price', 'name_event_types', 'name_facilities',\n",
+       "       'name_categories', 'name_events', 'name_seasons'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "purchases.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "aa6264be-b9c3-4bc3-a1a7-c8db94ff10ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "purchases['purchase_date'] = pd.to_datetime(purchases['purchase_date'])\n",
+    "\n",
+    "purchases_filtered = purchases[purchases['event_type_id'] == 5]\n",
+    "\n",
+    "purchases_graph = purchases_filtered[['purchase_id', 'purchase_date']].drop_duplicates()\n",
+    "\n",
+    "purchases_graph['month'] = purchases['purchase_date'].dt.strftime('%Y-%m')\n",
+    "\n",
+    "purchases_graph = purchases_graph.groupby('month')['purchase_id'].count().reset_index()\n",
+    "\n",
+    "purchases_graph['month'] = pd.to_datetime(purchases_graph['month'])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "5f5bf6bb-848c-470b-b22f-c46ad8cc381f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>month</th>\n",
+       "      <th>purchase_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2013-06-01</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2013-07-01</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2013-09-01</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2013-10-01</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2013-11-01</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>106</th>\n",
+       "      <td>2023-07-01</td>\n",
+       "      <td>14269</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>107</th>\n",
+       "      <td>2023-08-01</td>\n",
+       "      <td>20739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>108</th>\n",
+       "      <td>2023-09-01</td>\n",
+       "      <td>9854</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>109</th>\n",
+       "      <td>2023-10-01</td>\n",
+       "      <td>11934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>110</th>\n",
+       "      <td>2023-11-01</td>\n",
+       "      <td>3213</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>111 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         month  purchase_id\n",
+       "0   2013-06-01            1\n",
+       "1   2013-07-01            1\n",
+       "2   2013-09-01            2\n",
+       "3   2013-10-01            1\n",
+       "4   2013-11-01            5\n",
+       "..         ...          ...\n",
+       "106 2023-07-01        14269\n",
+       "107 2023-08-01        20739\n",
+       "108 2023-09-01         9854\n",
+       "109 2023-10-01        11934\n",
+       "110 2023-11-01         3213\n",
+       "\n",
+       "[111 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "purchases_graph"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "5e0ff216-bc82-4b02-81b3-6786b2d3ba75",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.dates as mdates\n",
+    "from datetime import datetime\n",
+    "\n",
+    "# Créer le graphique\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.plot(purchases_graph['month'], purchases_graph['purchase_id'])\n",
+    "\n",
+    "# Définir le format de l'axe des x en fonction des dates\n",
+    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
+    "plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=5)) # Ajustez l'intervalle selon vos besoins\n",
+    "\n",
+    "# Rotation des étiquettes de l'axe x pour une meilleure lisibilité\n",
+    "plt.xticks(rotation=45)\n",
+    "\n",
+    "\n",
+    "# Titres et labels\n",
+    "plt.title('Évolution des données')\n",
+    "plt.xlabel('Date')\n",
+    "plt.ylabel('Valeurs')\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b8a90eaa-c383-4f73-9fd6-6fbbe8eeefb8",
@@ -1374,7 +1670,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,