From fe049764cb3723a33c1009bd356dc51ae6bc9af3 Mon Sep 17 00:00:00 2001 From: arevelle-ensae Date: Tue, 6 Feb 2024 10:16:42 +0000 Subject: [PATCH 1/3] try k-means --- Notebook_AR.ipynb | 1695 +++++++++++++++++++++++++++++++++++++++++---- 1 file changed, 1555 insertions(+), 140 deletions(-) diff --git a/Notebook_AR.ipynb b/Notebook_AR.ipynb index 18b06d1..c808ce7 100644 --- a/Notebook_AR.ipynb +++ b/Notebook_AR.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 98, "id": "20eeb149-6618-4ef2-9cfd-ff062950f36c", "metadata": {}, "outputs": [], @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 99, "id": "30494c5e-9649-4fff-8708-617544188b20", "metadata": {}, "outputs": [ @@ -46,7 +46,7 @@ " 'bdc2324-data/9']" ] }, - "execution_count": 2, + "execution_count": 99, "metadata": {}, "output_type": "execute_result" } @@ -78,7 +78,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 100, "id": "f1cce705-46e1-42de-8e93-2ee15312d288", "metadata": {}, "outputs": [], @@ -88,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 101, "id": "82d4db0e-0cd5-49af-a4d3-f17f54b1c03c", "metadata": {}, "outputs": [ @@ -136,7 +136,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 102, "id": "65cb38ad-52ae-4266-85d8-c47d81b00283", "metadata": {}, "outputs": [], @@ -165,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 103, "id": "0214d30d-5f83-498f-867f-e67b5793b731", "metadata": {}, "outputs": [ @@ -316,7 +316,7 @@ "4 e11943a6031a0e6114ae69c257617980 2022-01-27 00:00:00+01:00 " ] }, - "execution_count": 6, + "execution_count": 103, "metadata": {}, "output_type": "execute_result" } @@ -328,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 104, "id": "e7982be4-2c42-4a91-be5a-329a999644cc", "metadata": {}, "outputs": [ @@ -454,7 +454,7 @@ "4 2022-02-02 17:19:36.557473+01:00 " ] }, - "execution_count": 7, + "execution_count": 104, "metadata": {}, "output_type": "execute_result" } @@ -482,7 +482,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 105, "id": "e973575b-4ed6-4b23-8024-f383ac82e87c", "metadata": {}, "outputs": [ @@ -589,7 +589,7 @@ "4 2022-02-02 17:34:22.300427+01:00 2022-02-02 17:34:22.300427+01:00 " ] }, - "execution_count": 8, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" } @@ -609,7 +609,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 106, "id": "3b523575-c779-451c-a12e-a36fb4ad232c", "metadata": {}, "outputs": [ @@ -624,7 +624,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_513/2210053343.py:5: DtypeWarning: Columns (20) have mixed types. Specify dtype option on import or set low_memory=False.\n", + "/tmp/ipykernel_703/2210053343.py:5: DtypeWarning: Columns (20) have mixed types. Specify dtype option on import or set low_memory=False.\n", " customersplus = pd.read_csv(file_in, sep=\",\")\n" ] }, @@ -837,7 +837,7 @@ "[5 rows x 43 columns]" ] }, - "execution_count": 9, + "execution_count": 106, "metadata": {}, "output_type": "execute_result" } @@ -862,7 +862,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 107, "id": "87d801fc-d19a-4c45-9b21-9b6d7a8451fd", "metadata": {}, "outputs": [ @@ -904,7 +904,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 108, "id": "b6e4c3ea-5ccf-4aec-bd2d-79a5a1194178", "metadata": {}, "outputs": [ @@ -1017,7 +1017,7 @@ "4 2021-09-17 20:20:24.703110+02:00 NaN NaN " ] }, - "execution_count": 11, + "execution_count": 108, "metadata": {}, "output_type": "execute_result" } @@ -1039,7 +1039,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 109, "id": "6e81a35c-3c6f-403d-9ebd-e8399ecd4263", "metadata": {}, "outputs": [ @@ -1140,7 +1140,7 @@ "4 2021-09-17 18:10:40.945476+02:00 2021-09-17 18:10:40.945476+02:00 " ] }, - "execution_count": 12, + "execution_count": 109, "metadata": {}, "output_type": "execute_result" } @@ -1162,7 +1162,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 110, "id": "85696d74-3b2f-4368-9045-44db5322b60d", "metadata": {}, "outputs": [ @@ -1258,7 +1258,7 @@ "3 2022-05-06 14:26:01.923160+02:00 12213df2ce68a624e4c0070521437bac " ] }, - "execution_count": 13, + "execution_count": 110, "metadata": {}, "output_type": "execute_result" } @@ -1298,7 +1298,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 111, "id": "7c57529b-2ffb-4039-9795-b27c6fbd54a4", "metadata": {}, "outputs": [ @@ -1418,7 +1418,7 @@ "4 193e41eae8ee078537107a569c0426ef " ] }, - "execution_count": 14, + "execution_count": 111, "metadata": {}, "output_type": "execute_result" } @@ -1430,7 +1430,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 112, "id": "903321fb-99f8-475d-b4a6-c70ec2efe190", "metadata": {}, "outputs": [ @@ -1581,7 +1581,7 @@ "4 1a6342ad2c213b626aa55e5374cd661a " ] }, - "execution_count": 15, + "execution_count": 112, "metadata": {}, "output_type": "execute_result" } @@ -1593,7 +1593,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 113, "id": "243e6942-0233-4cd5-b32b-e005457131d2", "metadata": {}, "outputs": [ @@ -1725,7 +1725,7 @@ "4 NaN b144dd617807b02e0d9002fac6c61768 " ] }, - "execution_count": 16, + "execution_count": 113, "metadata": {}, "output_type": "execute_result" } @@ -1745,7 +1745,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 114, "id": "6b82efce-1dee-4d89-8585-28c4ad477eef", "metadata": {}, "outputs": [ @@ -1914,7 +1914,7 @@ "4 NaN 07a5dd9e125345b9458651ab73605255 " ] }, - "execution_count": 17, + "execution_count": 114, "metadata": {}, "output_type": "execute_result" } @@ -1942,7 +1942,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 115, "id": "daf37bff-a26d-4ff5-ad50-c90f917164bd", "metadata": {}, "outputs": [ @@ -2056,7 +2056,7 @@ "4 478eb63c71ba35d8d3d64c8637dafdee " ] }, - "execution_count": 18, + "execution_count": 115, "metadata": {}, "output_type": "execute_result" } @@ -2068,7 +2068,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 116, "id": "cdb14488-b093-4b39-84fa-1c2b4576208f", "metadata": {}, "outputs": [ @@ -2175,7 +2175,7 @@ "4 2021-09-03 14:18:03.616081+02:00 0a2b941c46b31258c03b316aa064e86a " ] }, - "execution_count": 19, + "execution_count": 116, "metadata": {}, "output_type": "execute_result" } @@ -2203,7 +2203,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 117, "id": "6582694d-5339-4f33-a943-c73033121a90", "metadata": {}, "outputs": [ @@ -2323,7 +2323,7 @@ "4 349e6a59585d78d80d46acbc6a520c50 " ] }, - "execution_count": 20, + "execution_count": 117, "metadata": {}, "output_type": "execute_result" } @@ -2335,7 +2335,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 118, "id": "589076df-1958-42de-9941-1aff9fa8536f", "metadata": {}, "outputs": [ @@ -2442,7 +2442,7 @@ "4 2021-09-02 17:35:37.396740+02:00 c05b0061d2a875adbc35d3dfa6a50a12 " ] }, - "execution_count": 21, + "execution_count": 118, "metadata": {}, "output_type": "execute_result" } @@ -2472,7 +2472,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 119, "id": "6f06d72a-5725-4eee-8e4c-e9ef5820f346", "metadata": {}, "outputs": [ @@ -2585,7 +2585,7 @@ "4 9 23 NaN NaN " ] }, - "execution_count": 22, + "execution_count": 119, "metadata": {}, "output_type": "execute_result" } @@ -2597,7 +2597,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 120, "id": "bd405913-033d-4f15-a5b9-103d577baaff", "metadata": {}, "outputs": [ @@ -2785,7 +2785,7 @@ "4 733104286519c0614b2d45470eb180a1 " ] }, - "execution_count": 23, + "execution_count": 120, "metadata": {}, "output_type": "execute_result" } @@ -2797,7 +2797,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 121, "id": "0f2c7ea3-6964-48fd-9411-17547b2c3a3f", "metadata": {}, "outputs": [], @@ -2823,7 +2823,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 122, "id": "cba22ee2-338d-4ce1-a1e8-829a11a94bcf", "metadata": {}, "outputs": [ @@ -2980,7 +2980,7 @@ "4 17b91f19c71ff6287ffc1f44af952576 " ] }, - "execution_count": 25, + "execution_count": 122, "metadata": {}, "output_type": "execute_result" } @@ -2992,7 +2992,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 123, "id": "3db00b9d-2187-4cb6-980d-8ac6ab9eb460", "metadata": {}, "outputs": [ @@ -3106,7 +3106,7 @@ "4 732cfdcf2065fa0005faf42793ddd76c " ] }, - "execution_count": 26, + "execution_count": 123, "metadata": {}, "output_type": "execute_result" } @@ -3118,7 +3118,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 124, "id": "cba0ee58-6280-45fe-99b3-0be09db5922b", "metadata": {}, "outputs": [ @@ -3232,7 +3232,7 @@ "4 7ccc51049a85e0df9b80662e45b6ddb8 " ] }, - "execution_count": 27, + "execution_count": 124, "metadata": {}, "output_type": "execute_result" } @@ -3244,7 +3244,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 125, "id": "6fa82fd7-d6d3-4857-af24-ea573b1129d0", "metadata": {}, "outputs": [ @@ -3364,7 +3364,7 @@ "4 89feffd283ebdabdc3b81fb62ea4f6f0 " ] }, - "execution_count": 28, + "execution_count": 125, "metadata": {}, "output_type": "execute_result" } @@ -3408,7 +3408,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 126, "id": "c240b811-48a6-4501-9e70-bc51d69e3ac4", "metadata": {}, "outputs": [], @@ -3424,7 +3424,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 127, "id": "54057367-9df9-42f4-aa07-bf524bb76462", "metadata": {}, "outputs": [ @@ -3445,7 +3445,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 128, "id": "63914e20-9efc-4088-877b-edab5f225d00", "metadata": {}, "outputs": [ @@ -3493,7 +3493,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 129, "id": "590a132a-4f57-4ea3-a282-2ef913e4b753", "metadata": {}, "outputs": [], @@ -3503,7 +3503,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 130, "id": "0fbebfb7-a827-46b1-890b-86c9def7cdbb", "metadata": {}, "outputs": [], @@ -3513,7 +3513,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 131, "id": "b8aa5f8f-845e-4ee5-b80d-38b7061a94a2", "metadata": {}, "outputs": [], @@ -3528,7 +3528,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 132, "id": "2c478213-09ae-44ef-8c7c-125bcb571642", "metadata": {}, "outputs": [], @@ -3546,7 +3546,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 133, "id": "327e44b0-eb99-4022-b4ca-79548072f0f0", "metadata": {}, "outputs": [], @@ -3561,7 +3561,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 134, "id": "10926def-267f-4e86-b2c9-72e27ff9a9df", "metadata": {}, "outputs": [], @@ -3585,7 +3585,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 135, "id": "862a7658-0602-4d94-bb58-d23774c00d32", "metadata": {}, "outputs": [ @@ -3755,7 +3755,7 @@ "4 NaN f1c4689bc47dee6f60b56d74b593dd46 " ] }, - "execution_count": 38, + "execution_count": 135, "metadata": {}, "output_type": "execute_result" } @@ -3768,7 +3768,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 136, "id": "f0db8c51-2792-4d49-9b1a-d98ce0d9ea28", "metadata": {}, "outputs": [ @@ -3921,7 +3921,7 @@ "4 8.5 False 0.0 NaN NaN " ] }, - "execution_count": 39, + "execution_count": 136, "metadata": {}, "output_type": "execute_result" } @@ -3936,7 +3936,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 137, "id": "a383474f-7da9-422c-bb69-3f0cc0b7053f", "metadata": {}, "outputs": [ @@ -3966,7 +3966,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 138, "id": "460749ac-aa26-4216-8667-518546f72f72", "metadata": {}, "outputs": [ @@ -4005,7 +4005,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 139, "id": "3efce2b6-2d2f-4da9-98ed-1aae17da624c", "metadata": {}, "outputs": [], @@ -4015,7 +4015,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 140, "id": "38aa39fd-58af-4fb8-98f2-4269dbaf35de", "metadata": {}, "outputs": [ @@ -4136,7 +4136,7 @@ "4 ff48df4b2dd5a14116bf4d280b31621e " ] }, - "execution_count": 43, + "execution_count": 140, "metadata": {}, "output_type": "execute_result" } @@ -4149,7 +4149,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 141, "id": "99eb6d14-8b4b-4d55-8fc7-ddf2726096f4", "metadata": {}, "outputs": [ @@ -4256,7 +4256,7 @@ "4 NaN NaN " ] }, - "execution_count": 44, + "execution_count": 141, "metadata": {}, "output_type": "execute_result" } @@ -4268,7 +4268,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 142, "id": "c5f39cc9-dff8-452c-9a3e-9f7df81a8a19", "metadata": {}, "outputs": [ @@ -4283,7 +4283,7 @@ "dtype: object" ] }, - "execution_count": 45, + "execution_count": 142, "metadata": {}, "output_type": "execute_result" } @@ -4326,7 +4326,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 143, "id": "2d52d6da-cca5-4abd-be05-2f00fd3eca8e", "metadata": {}, "outputs": [], @@ -4336,7 +4336,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 144, "id": "6cab507d-8b11-404d-9286-5cc205228af9", "metadata": {}, "outputs": [ @@ -4494,7 +4494,7 @@ "4 1 bfa22f5a2364a2dacfc45cca1c8d3215 " ] }, - "execution_count": 47, + "execution_count": 144, "metadata": {}, "output_type": "execute_result" } @@ -4507,7 +4507,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 145, "id": "9fe57873-8108-44c9-b8a5-f58d3cbb6d17", "metadata": {}, "outputs": [ @@ -4658,7 +4658,7 @@ "4 jeff koons épisodes 4 False True " ] }, - "execution_count": 48, + "execution_count": 145, "metadata": {}, "output_type": "execute_result" } @@ -4670,7 +4670,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 146, "id": "7fd9e5bd-baac-4b3b-9ffb-5a9baa18399b", "metadata": {}, "outputs": [ @@ -4690,7 +4690,7 @@ "dtype: object" ] }, - "execution_count": 49, + "execution_count": 146, "metadata": {}, "output_type": "execute_result" } @@ -4709,7 +4709,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 147, "id": "90ab62d4-a086-4469-961c-67eefb375388", "metadata": {}, "outputs": [], @@ -4719,7 +4719,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 148, "id": "58db1751-fd56-4c28-b49e-bc8235bb0dc8", "metadata": {}, "outputs": [ @@ -4834,7 +4834,7 @@ "4 d41d8cd98f00b204e9800998ecf8427e " ] }, - "execution_count": 51, + "execution_count": 148, "metadata": {}, "output_type": "execute_result" } @@ -4847,7 +4847,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 149, "id": "ac93382c-0b5f-462d-8021-0dd1e7201b8c", "metadata": {}, "outputs": [ @@ -4940,7 +4940,7 @@ "4 2723 36 d41d8cd98f00b204e9800998ecf8427e NaN" ] }, - "execution_count": 52, + "execution_count": 149, "metadata": {}, "output_type": "execute_result" } @@ -4952,7 +4952,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 150, "id": "18cbd630-3c7d-49e1-932b-9460badf3758", "metadata": {}, "outputs": [ @@ -4966,7 +4966,7 @@ "dtype: object" ] }, - "execution_count": 53, + "execution_count": 150, "metadata": {}, "output_type": "execute_result" } @@ -4985,7 +4985,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 151, "id": "ae544dcc-f23d-4216-bb5b-597cc1b3765e", "metadata": {}, "outputs": [], @@ -4995,7 +4995,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 152, "id": "1ac97963-9208-4329-be41-d71a5797487f", "metadata": {}, "outputs": [ @@ -5110,7 +5110,7 @@ "4 8d8818c8e140c64c743113f563cf750f " ] }, - "execution_count": 55, + "execution_count": 152, "metadata": {}, "output_type": "execute_result" } @@ -5123,7 +5123,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 153, "id": "b4593d46-105c-47dd-aa71-babd8e63e65b", "metadata": {}, "outputs": [ @@ -5216,7 +5216,7 @@ "4 4 8d8818c8e140c64c743113f563cf750f 2017 NaN" ] }, - "execution_count": 56, + "execution_count": 153, "metadata": {}, "output_type": "execute_result" } @@ -5228,7 +5228,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 154, "id": "5d3b096d-8e73-4514-94e5-f2dcd4d0a89c", "metadata": {}, "outputs": [ @@ -5242,7 +5242,7 @@ "dtype: object" ] }, - "execution_count": 57, + "execution_count": 154, "metadata": {}, "output_type": "execute_result" } @@ -5261,7 +5261,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 155, "id": "d95ef015-d44c-4353-8761-771b910d21c9", "metadata": {}, "outputs": [], @@ -5271,7 +5271,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 156, "id": "ef5fe794-8df7-4f27-8554-ecdc4074ac0b", "metadata": {}, "outputs": [ @@ -5353,7 +5353,7 @@ "1 702bd76fe3dd5dbcf118a6965a946f54 " ] }, - "execution_count": 59, + "execution_count": 156, "metadata": {}, "output_type": "execute_result" } @@ -5366,7 +5366,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 157, "id": "e3621201-fab9-49fd-95c1-0b9d5da76e50", "metadata": {}, "outputs": [ @@ -5439,7 +5439,7 @@ "1 1 1 702bd76fe3dd5dbcf118a6965a946f54 mucem NaN" ] }, - "execution_count": 60, + "execution_count": 157, "metadata": {}, "output_type": "execute_result" } @@ -5451,7 +5451,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 158, "id": "1b198b92-8654-4531-a0dd-8f2e01c2e6c1", "metadata": {}, "outputs": [ @@ -5466,7 +5466,7 @@ "dtype: object" ] }, - "execution_count": 61, + "execution_count": 158, "metadata": {}, "output_type": "execute_result" } @@ -5485,7 +5485,7 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 159, "id": "43576244-c8cf-4ca0-b056-7aea1fbf0bc7", "metadata": {}, "outputs": [], @@ -5500,7 +5500,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 160, "id": "0fad097e-474c-4af7-b1e1-7d8dda3f09ea", "metadata": {}, "outputs": [], @@ -5526,7 +5526,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 161, "id": "6213b1eb-c5f8-49dd-ab69-366542380e80", "metadata": {}, "outputs": [], @@ -5563,7 +5563,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 162, "id": "b853e020-f73d-44e8-b086-e5548ce21011", "metadata": {}, "outputs": [ @@ -5716,7 +5716,7 @@ "4 indiv entrées tp " ] }, - "execution_count": 85, + "execution_count": 162, "metadata": {}, "output_type": "execute_result" } @@ -5736,7 +5736,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 163, "id": "6ed0ad20-8315-4112-9a85-10e5f04ef852", "metadata": {}, "outputs": [], @@ -5779,7 +5779,7 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 164, "id": "98ef0636-8c45-4a23-a62a-1fbe1544f8ce", "metadata": {}, "outputs": [ @@ -5949,7 +5949,7 @@ "4 spectacle vivant mucem " ] }, - "execution_count": 87, + "execution_count": 164, "metadata": {}, "output_type": "execute_result" } @@ -5969,7 +5969,7 @@ }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 165, "id": "481dddd6-80a8-4b9e-a05e-ed06fa3ed7a6", "metadata": {}, "outputs": [], @@ -5994,7 +5994,7 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 166, "id": "677f4ed8-ef58-45f2-9056-ede0898c6a64", "metadata": {}, "outputs": [ @@ -6093,7 +6093,7 @@ "4 37 383 269 1" ] }, - "execution_count": 97, + "execution_count": 166, "metadata": {}, "output_type": "execute_result" } @@ -6113,7 +6113,7 @@ }, { "cell_type": "code", - "execution_count": 112, + "execution_count": 167, "id": "c52621e7-01de-48dc-b572-2974542a8be5", "metadata": {}, "outputs": [ @@ -6169,7 +6169,7 @@ "0 1 NaN 0" ] }, - "execution_count": 112, + "execution_count": 167, "metadata": {}, "output_type": "execute_result" } @@ -6181,7 +6181,7 @@ }, { "cell_type": "code", - "execution_count": 114, + "execution_count": 168, "id": "9e4f60ab-9a2c-4090-b0c4-f9a1530b2d39", "metadata": {}, "outputs": [ @@ -6265,7 +6265,7 @@ "4 1496 billet nb famille mecene 1a NaN" ] }, - "execution_count": 114, + "execution_count": 168, "metadata": {}, "output_type": "execute_result" } @@ -6277,7 +6277,7 @@ }, { "cell_type": "code", - "execution_count": 115, + "execution_count": 169, "id": "247b5c45-a18a-4cfd-86b4-d3453e157bcd", "metadata": {}, "outputs": [ @@ -6361,7 +6361,7 @@ "4 5 1 7" ] }, - "execution_count": 115, + "execution_count": 169, "metadata": {}, "output_type": "execute_result" } @@ -6373,7 +6373,7 @@ }, { "cell_type": "code", - "execution_count": 117, + "execution_count": 170, "id": "4b48f7b3-0f06-4ef6-9355-5016af82f49c", "metadata": {}, "outputs": [ @@ -6490,7 +6490,7 @@ "4 0.0 0.0 " ] }, - "execution_count": 117, + "execution_count": 170, "metadata": {}, "output_type": "execute_result" } @@ -6510,7 +6510,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 171, "id": "b26f4e7e-134d-4e32-a615-4b0e6bb80b25", "metadata": {}, "outputs": [ @@ -6542,7 +6542,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 172, "id": "d40b1e3b-b1f3-4915-8ebc-6bb7856da42a", "metadata": {}, "outputs": [ @@ -6684,7 +6684,7 @@ "4 indiv entrées tp 8 21 " ] }, - "execution_count": 99, + "execution_count": 172, "metadata": {}, "output_type": "execute_result" } @@ -6699,7 +6699,7 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 173, "id": "78d75a08-e959-429c-847a-7d70a2804806", "metadata": {}, "outputs": [ @@ -6919,7 +6919,7 @@ "[5 rows x 22 columns]" ] }, - "execution_count": 100, + "execution_count": 173, "metadata": {}, "output_type": "execute_result" } @@ -6933,7 +6933,7 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 174, "id": "4a6950e8-4818-4df2-afa9-562e0921698c", "metadata": {}, "outputs": [ @@ -6949,7 +6949,7 @@ " dtype='object')" ] }, - "execution_count": 101, + "execution_count": 174, "metadata": {}, "output_type": "execute_result" } @@ -6960,7 +6960,7 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 175, "id": "b18f6428-90e0-4b1b-9b8d-bad995fb6c98", "metadata": {}, "outputs": [ @@ -6970,7 +6970,7 @@ "(94803, 22)" ] }, - "execution_count": 102, + "execution_count": 175, "metadata": {}, "output_type": "execute_result" } @@ -6989,7 +6989,7 @@ }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 176, "id": "33ee07a2-d871-4436-9860-9be389bc4902", "metadata": {}, "outputs": [ @@ -7021,7 +7021,7 @@ "dtype: int64" ] }, - "execution_count": 103, + "execution_count": 176, "metadata": {}, "output_type": "execute_result" } @@ -7032,7 +7032,7 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": 177, "id": "557fc475-4417-4d9f-8d4e-8c49bc42367f", "metadata": {}, "outputs": [ @@ -7043,7 +7043,7 @@ " 'offre muséale groupe', 'formule adhésion'], dtype=object)" ] }, - "execution_count": 105, + "execution_count": 177, "metadata": {}, "output_type": "execute_result" } @@ -7056,7 +7056,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 178, "id": "a9b9a23c-b0de-4685-97e5-d52dd78349f5", "metadata": {}, "outputs": [ @@ -7066,7 +7066,7 @@ "644" ] }, - "execution_count": 107, + "execution_count": 178, "metadata": {}, "output_type": "execute_result" } @@ -7079,7 +7079,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 179, "id": "fb374c72-58ca-404d-a86b-e834a2fc4a34", "metadata": {}, "outputs": [ @@ -7099,7 +7099,7 @@ " 'groupe forfait etudiant'], dtype=object)" ] }, - "execution_count": 108, + "execution_count": 179, "metadata": {}, "output_type": "execute_result" } @@ -7111,7 +7111,7 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 180, "id": "11f89771-8d50-4ef4-b34e-53e4f6b419bb", "metadata": {}, "outputs": [ @@ -7121,7 +7121,7 @@ "27" ] }, - "execution_count": 109, + "execution_count": 180, "metadata": {}, "output_type": "execute_result" } @@ -7132,7 +7132,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 181, "id": "8add1ff2-b7e8-4381-90d8-d18d8660ed39", "metadata": {}, "outputs": [], @@ -7158,6 +7158,1421 @@ " return products_global\n", " " ] + }, + { + "cell_type": "markdown", + "id": "b9303d35-4449-4cb6-887b-73a75f3cb868", + "metadata": {}, + "source": [ + "# Investigate Customer Plus" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "id": "1fd9dcb0-164a-4fd0-90c3-2fd9e7b44016", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "File path : bdc2324-data/1/1customersplus.csv\n", + "Shape : (151866, 43)\n", + "Number of columns : 41\n", + "Columns : Index(['id', 'street_id', 'identifier', 'structure_id', 'mcp_contact_id',\n", + " 'fidelity', 'tenant_id', 'lastname', 'firstname', 'birthdate', 'email',\n", + " 'civility', 'is_partner', 'extra', 'deleted_at', 'reference', 'gender',\n", + " 'is_email_true', 'extra_field', 'opt_in', 'note', 'profession',\n", + " 'language', 'need_reload', 'last_buying_date', 'max_price',\n", + " 'ticket_sum', 'average_price', 'average_purchase_delay',\n", + " 'average_price_basket', 'average_ticket_basket', 'total_price',\n", + " 'preferred_category', 'preferred_supplier', 'preferred_formula',\n", + " 'purchase_count', 'first_buying_date', 'last_visiting_date', 'zipcode',\n", + " 'country', 'age'],\n", + " dtype='object')\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " customer_id birthdate street_id_x is_partner gender is_email_true \\\n", + "0 12751 NaN 2 False 1 True \n", + "1 12825 NaN 2 False 2 True \n", + "2 11261 NaN 2 False 1 True \n", + "3 13071 NaN 2 False 2 True \n", + "4 653061 NaN 10 False 2 True \n", + "\n", + " opt_in structure_id profession language ... season_id facility_id \\\n", + "0 True NaN NaN NaN ... NaN NaN \n", + "1 True NaN NaN NaN ... NaN NaN \n", + "2 True NaN NaN NaN ... NaN NaN \n", + "3 True NaN NaN NaN ... NaN NaN \n", + "4 False NaN NaN NaN ... NaN NaN \n", + "\n", + " event_type_id event_type_key_id facility_key_id street_id_y amount \\\n", + "0 NaN NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN NaN \n", + "\n", + " is_full_price name_event_types name_facilities \n", + "0 NaN NaN NaN \n", + "1 NaN NaN NaN \n", + "2 NaN NaN NaN \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", + "\n", + "[5 rows x 52 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer_product = pd.read_csv(\"customer_product.csv\")\n", + "customer_product.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "bdd582af-0cf1-4e04-90ad-7165b8a36ac8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(206713, 52)\n", + "Index(['customer_id', 'birthdate', 'street_id_x', 'is_partner', 'gender',\n", + " 'is_email_true', 'opt_in', 'structure_id', 'profession', 'language',\n", + " 'mcp_contact_id', 'last_buying_date', 'max_price', 'ticket_sum',\n", + " 'average_price', 'fidelity', 'average_purchase_delay',\n", + " 'average_price_basket', 'average_ticket_basket', 'total_price',\n", + " 'purchase_count', 'first_buying_date', 'country', 'age', 'tenant_id',\n", + " 'nb_campaigns', 'nb_campaigns_opened', 'time_to_open', 'product_id',\n", + " 'nb_tickets', 'nb_suppliers', 'purchase_date_max', 'purchase_date_min',\n", + " 'time_between_purchase', 'id_products', 'representation_id',\n", + " 'pricing_formula_id', 'category_id', 'products_group_id',\n", + " 'product_pack_id', 'event_id', 'id_representation_cap', 'season_id',\n", + " 'facility_id', 'event_type_id', 'event_type_key_id', 'facility_key_id',\n", + " 'street_id_y', 'amount', 'is_full_price', 'name_event_types',\n", + " 'name_facilities'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "# Shape :\n", + "print(customer_product.shape)\n", + "# columns : \n", + "print(customer_product.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "55fa2361-ebde-4472-b8d2-521a20be766d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "customer_id 0\n", + "birthdate 195073\n", + "street_id_x 0\n", + "is_partner 0\n", + "gender 0\n", + "is_email_true 0\n", + "opt_in 0\n", + "structure_id 171660\n", + "profession 199762\n", + "language 205574\n", + "mcp_contact_id 81495\n", + "last_buying_date 78450\n", + "max_price 78450\n", + "ticket_sum 0\n", + "average_price 13122\n", + "fidelity 0\n", + "average_purchase_delay 78450\n", + "average_price_basket 78450\n", + "average_ticket_basket 78450\n", + "total_price 65328\n", + "purchase_count 0\n", + "first_buying_date 78450\n", + "country 8490\n", + "age 195073\n", + "tenant_id 0\n", + "nb_campaigns 46315\n", + "nb_campaigns_opened 46315\n", + "time_to_open 100811\n", + "product_id 78355\n", + "nb_tickets 78355\n", + "nb_suppliers 78355\n", + "purchase_date_max 78355\n", + "purchase_date_min 78355\n", + "time_between_purchase 78355\n", + "id_products 78355\n", + "representation_id 78355\n", + "pricing_formula_id 78355\n", + "category_id 78355\n", + "products_group_id 78355\n", + "product_pack_id 78355\n", + "event_id 78355\n", + "id_representation_cap 78355\n", + "season_id 78355\n", + "facility_id 78355\n", + "event_type_id 78355\n", + "event_type_key_id 78355\n", + "facility_key_id 78355\n", + "street_id_y 78355\n", + "amount 78355\n", + "is_full_price 78355\n", + "name_event_types 78355\n", + "name_facilities 78355\n", + "dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# check NA\n", + "\n", + "customer_product.isna().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 234, + "id": "76fbd8d5-443c-43b7-976d-b0028cd90d5e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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customer_idgenderis_partneris_email_truenb_campaignsnb_campaigns_openedfidelityproduct_idnb_ticketsticket_sumaverage_priceamountevent_type_idname_event_types
0127511FalseTrueNaNNaN0NaNNaN00.0NaNNaNNaN
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46530612FalseTrue80.02.00NaNNaN00.0NaNNaNNaN
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" + ], + "text/plain": [ + " customer_id gender is_partner is_email_true nb_campaigns \\\n", + "0 12751 1 False True NaN \n", + "1 12825 2 False True NaN \n", + "2 11261 1 False True NaN \n", + "3 13071 2 False True NaN \n", + "4 653061 2 False True 80.0 \n", + "\n", + " nb_campaigns_opened fidelity product_id nb_tickets ticket_sum \\\n", + "0 NaN 0 NaN NaN 0 \n", + "1 NaN 0 NaN NaN 0 \n", + "2 NaN 0 NaN NaN 0 \n", + "3 NaN 0 NaN NaN 0 \n", + "4 2.0 0 NaN NaN 0 \n", + "\n", + " average_price amount event_type_id name_event_types \n", + "0 0.0 NaN NaN NaN \n", + "1 0.0 NaN NaN NaN \n", + "2 0.0 NaN NaN NaN \n", + "3 0.0 NaN NaN NaN \n", + "4 0.0 NaN NaN NaN " + ] + }, + "execution_count": 234, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## Investigate a subset of variables\n", + "\n", + "df = customer_product[[\"customer_id\", \"gender\", \"is_partner\", \"is_email_true\",\"nb_campaigns\", \"nb_campaigns_opened\", \"fidelity\", \"product_id\",\n", + " \"nb_tickets\", \"ticket_sum\", \"average_price\", \"amount\", \"event_type_id\", \"name_event_types\"]]\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 235, + "id": "80120f51-f91e-4d4d-9578-1dc88cd94754", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape : (206713, 14)\n", + "Nombre de customer unique : 151866\n", + "Nombre de ligne où produit est non nul : 128358\n" + ] + } + ], + "source": [ + "print(\"shape : \", df.shape)\n", + "print(\"Nombre de customer unique : \", len(df[\"customer_id\"].unique()))\n", + "print(\"Nombre de ligne où produit est non nul : \", df[\"product_id\"].count())" + ] + }, + { + "cell_type": "code", + "execution_count": 236, + "id": "ae277ede-cc97-4303-a2d4-3381ccb98a5c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "78355" + ] + }, + "execution_count": 236, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "206713-128358" + ] + }, + { + "cell_type": "code", + "execution_count": 237, + "id": "0d56bfa9-c93c-42ee-bec2-96f0598fce2c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Nombre de consommateur unique : 73511\n", + "Nombre de type d'évènement : 4\n", + "Nombre de type d'évènement (nom) : 4\n" + ] + }, + { + "data": { + "text/html": [ + "
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customer_idgenderis_partneris_email_truenb_campaignsnb_campaigns_openedfidelityproduct_idnb_ticketsticket_sumaverage_priceamountevent_type_idname_event_types
1623092552FalseTrue2.02.00264371.02.000.011.04.0spectacle vivant
19577720FalseTrue133.019.00222125.01.052.86.04.0spectacle vivant
19677720FalseTrue133.019.00222126.02.052.84.04.0spectacle vivant
19777720FalseTrue133.019.00222571.02.052.80.04.0spectacle vivant
1992800090FalseTrue116.032.01266306.01.0111.011.04.0spectacle vivant
.............................................
2067032952242FalseTrue10.00.01340286.03.0980.00.02.0offre muséale individuel
2067042952242FalseTrue10.00.01340287.062.0980.00.02.0offre muséale individuel
2067052952242FalseTrue10.00.01340288.033.0980.00.02.0offre muséale individuel
2067112953662FalseTrue5.00.01216060.03.0311.011.04.0spectacle vivant
2067122953682FalseTrue5.00.01264331.02.0211.011.04.0spectacle vivant
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128358 rows × 14 columns

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" + ], + "text/plain": [ + " customer_id gender is_partner is_email_true nb_campaigns \\\n", + "162 309255 2 False True 2.0 \n", + "195 7772 0 False True 133.0 \n", + "196 7772 0 False True 133.0 \n", + "197 7772 0 False True 133.0 \n", + "199 280009 0 False True 116.0 \n", + "... ... ... ... ... ... \n", + "206703 295224 2 False True 10.0 \n", + "206704 295224 2 False True 10.0 \n", + "206705 295224 2 False True 10.0 \n", + "206711 295366 2 False True 5.0 \n", + "206712 295368 2 False True 5.0 \n", + "\n", + " nb_campaigns_opened fidelity product_id nb_tickets ticket_sum \\\n", + "162 2.0 0 264371.0 2.0 0 \n", + "195 19.0 0 222125.0 1.0 5 \n", + "196 19.0 0 222126.0 2.0 5 \n", + "197 19.0 0 222571.0 2.0 5 \n", + "199 32.0 1 266306.0 1.0 1 \n", + "... ... ... ... ... ... \n", + "206703 0.0 1 340286.0 3.0 98 \n", + "206704 0.0 1 340287.0 62.0 98 \n", + "206705 0.0 1 340288.0 33.0 98 \n", + "206711 0.0 1 216060.0 3.0 3 \n", + "206712 0.0 1 264331.0 2.0 2 \n", + "\n", + " average_price amount event_type_id name_event_types \n", + "162 0.0 11.0 4.0 spectacle vivant \n", + "195 2.8 6.0 4.0 spectacle vivant \n", + "196 2.8 4.0 4.0 spectacle vivant \n", + "197 2.8 0.0 4.0 spectacle vivant \n", + "199 11.0 11.0 4.0 spectacle vivant \n", + "... ... ... ... ... \n", + "206703 0.0 0.0 2.0 offre muséale individuel \n", + "206704 0.0 0.0 2.0 offre muséale individuel \n", + "206705 0.0 0.0 2.0 offre muséale individuel \n", + "206711 11.0 11.0 4.0 spectacle vivant \n", + "206712 11.0 11.0 4.0 spectacle vivant \n", + "\n", + "[128358 rows x 14 columns]" + ] + }, + "execution_count": 237, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Filter only customer that buy tickets\n", + "\n", + "df_purchase = df.dropna(subset= [\"product_id\"])\n", + "print(\"Nombre de consommateur unique : \", len(df_purchase[\"customer_id\"].unique()))\n", + "print(\"Nombre de type d'évènement : \", len(df_purchase[\"event_type_id\"].unique()))\n", + "print(\"Nombre de type d'évènement (nom) : \", len(df_purchase[\"name_event_types\"].unique()))\n", + "df_purchase" + ] + }, + { + "cell_type": "code", + "execution_count": 239, + "id": "0cc96c4e-f3f3-43d2-94b5-a11719f09607", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "event_counts = df_purchase.groupby('name_event_types')['customer_id'].nunique()\n", + "\n", + "event_counts.plot(kind='bar')\n", + "plt.xlabel(\"Type d'évènement\")\n", + "plt.ylabel('Nombre de consommateurs uniques')\n", + "plt.title(\"Nombre de consommateurs uniques par type d'évènement\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 238, + "id": "e37ad847-7ea5-4afe-9c6d-e07a668d2a27", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "average_tickets_by_event = df_purchase.groupby('name_event_types')['nb_tickets'].mean()\n", + "\n", + "average_tickets_by_event.plot(kind='bar', figsize=(8, 5))\n", + "plt.xlabel(\"Type d'évènements\")\n", + "plt.ylabel('Nombre moyen de tickets achetés')\n", + "plt.title(\"Nombre moyen de tickets achetés par Type d'évènements\")\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 241, + "id": "e02b260a-fcb7-418b-87a8-de2bb4e6eb0a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "customer_id 0\n", + "gender 0\n", + "is_partner 0\n", + "is_email_true 0\n", + "nb_campaigns 34417\n", + "nb_campaigns_opened 34417\n", + "fidelity 0\n", + "product_id 0\n", + "nb_tickets 0\n", + "ticket_sum 0\n", + "average_price 22\n", + "amount 0\n", + "event_type_id 0\n", + "name_event_types 0\n", + "dtype: int64" + ] + }, + "execution_count": 241, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_purchase.isna().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 242, + "id": "daef46cd-f6a5-4282-ac0a-83fde277edec", + "metadata": {}, + "outputs": [], + "source": [ + "df_purchase = df_purchase.fillna(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 243, + "id": "e34437e6-a57d-4d10-ac62-5c43cdda6892", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.cluster import KMeans\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "columns_for_clustering = ['gender', 'is_partner', 'is_email_true', 'nb_campaigns', 'nb_campaigns_opened', 'fidelity', 'nb_tickets', 'ticket_sum', 'average_price', 'amount']\n", + "\n", + "scaler = StandardScaler()\n", + "X = scaler.fit_transform(df_purchase[columns_for_clustering])\n", + "\n", + "inertia = []\n", + "for i in range(1, 11):\n", + " kmeans = KMeans(n_clusters=i, random_state=42)\n", + " kmeans.fit(X)\n", + " inertia.append(kmeans.inertia_)\n", + "\n", + "# Plot the elbow curve to find the optimal k\n", + "plt.figure(figsize=(8, 6))\n", + "plt.plot(range(1, 11), inertia, marker='o', linestyle='-', color='b')\n", + "plt.xlabel('Number of clusters (k)')\n", + "plt.ylabel('Inertia (Within-cluster sum of squares)')\n", + "plt.title('Elbow Method for Optimal k')\n", + "plt.grid()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 246, + "id": "4da7d97e-9128-4e4a-a454-1451d2dfee40", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/mamba/lib/python3.10/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cluster 1:\n", + "gender 0.893962\n", + "is_partner 0.000000\n", + "is_email_true 1.000000\n", + "nb_campaigns 231.270802\n", + "nb_campaigns_opened 99.261042\n", + "fidelity 30.193383\n", + "nb_tickets 10.965757\n", + "ticket_sum 2604.072622\n", + "average_price 9.781489\n", + "amount 16.114144\n", + "Name: 0, dtype: float64\n", + "Size: 6045\n", + "\n", + "Cluster 2:\n", + "gender 1.999420e+00\n", + "is_partner 0.000000e+00\n", + "is_email_true 9.998067e-01\n", + "nb_campaigns 1.048816e-02\n", + "nb_campaigns_opened 1.159981e-03\n", + "fidelity 3.305112e+05\n", + "nb_tickets 6.141087e+01\n", + "ticket_sum 1.253568e+06\n", + "average_price 7.031328e+00\n", + "amount 6.880643e+00\n", + "Name: 1, dtype: float64\n", + "Size: 20690\n", + "\n", + "Cluster 3:\n", + "gender 1.311996\n", + "is_partner 0.000000\n", + "is_email_true 0.982297\n", + "nb_campaigns 11.520089\n", + "nb_campaigns_opened 2.922872\n", + "fidelity 4.664367\n", + "nb_tickets 4.819549\n", + "ticket_sum 184.855712\n", + "average_price 9.696602\n", + "amount 11.980846\n", + "Name: 2, dtype: float64\n", + "Size: 101623\n", + "\n" + ] + } + ], + "source": [ + "k = 3 \n", + "\n", + "kmeans = KMeans(n_clusters=k, random_state=42)\n", + "df_purchase['cluster'] = kmeans.fit_predict(X)\n", + "\n", + "cluster_means = df_purchase.groupby('cluster')[columns_for_clustering].mean()\n", + "cluster_sizes = df_purchase['cluster'].value_counts()\n", + "\n", + "for cluster in range(k):\n", + " print(f\"Cluster {cluster + 1}:\")\n", + " print(cluster_means.loc[cluster])\n", + " print(f\"Size: {cluster_sizes[cluster]}\\n\")" + ] } ], "metadata": { -- 2.34.1 From 7dff6886a308b11fc8124655b2d225ec37a7f4ea Mon Sep 17 00:00:00 2001 From: arevelle-ensae Date: Thu, 8 Feb 2024 11:30:31 +0000 Subject: [PATCH 2/3] compute tickets by customer-event --- 0_Cleaning_and_merge.ipynb | 1899 +++++++++++++++++++++++++++++++----- Notebook_AR.ipynb | 883 ++++++++--------- 2 files changed, 2039 insertions(+), 743 deletions(-) diff --git a/0_Cleaning_and_merge.ipynb b/0_Cleaning_and_merge.ipynb index 99d5ea7..ba13c22 100644 --- a/0_Cleaning_and_merge.ipynb +++ b/0_Cleaning_and_merge.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 80, "id": "15103481-8d74-404c-aa09-7601fe7730da", "metadata": {}, "outputs": [], @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 82, "id": "5d83bb1a-d341-446e-91f6-1c428607f6d4", "metadata": {}, "outputs": [], @@ -60,7 +60,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 84, "id": "699664b9-eee4-4f8d-a207-e524526560c5", "metadata": {}, "outputs": [], @@ -71,7 +71,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 86, "id": "dd6a3518-b752-4a1e-b77b-9e03e853c3ed", "metadata": {}, "outputs": [ @@ -79,7 +79,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_15815/4081512283.py:10: DtypeWarning: Columns (1) have mixed types. Specify dtype option on import or set low_memory=False.\n", + "/tmp/ipykernel_1018/4081512283.py:10: DtypeWarning: Columns (1) have mixed types. Specify dtype option on import or set low_memory=False.\n", " df = pd.read_csv(file_in)\n" ] } @@ -110,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 88, "id": "d237be96-8c86-4a91-b7a1-487e87a16c3d", "metadata": {}, "outputs": [], @@ -151,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 90, "id": "7e7b90ce-da54-4f00-bc34-64c543b0858f", "metadata": {}, "outputs": [], @@ -173,7 +173,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 92, "id": "03329e32-00a5-42c8-9470-75f7b6216ccd", "metadata": {}, "outputs": [], @@ -191,7 +191,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 94, "id": "b95464b1-26bc-4aac-84b4-45da83b92251", "metadata": {}, "outputs": [], @@ -234,7 +234,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 96, "id": "3e1d2ba7-ff4f-48eb-93a8-2bb648c70396", "metadata": {}, "outputs": [ @@ -242,17 +242,17 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_15815/1591303091.py:5: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/1591303091.py:5: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " tickets.rename(columns = {'id' : 'ticket_id'}, inplace = True)\n", - "/tmp/ipykernel_15815/1591303091.py:9: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/1591303091.py:9: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " suppliers.rename(columns = {'name' : 'supplier_name'}, inplace = True)\n", - "/tmp/ipykernel_15815/1591303091.py:13: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/1591303091.py:13: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", @@ -266,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 98, "id": "4b18edfc-6450-4c6a-9e7b-ee5a5808c8c9", "metadata": {}, "outputs": [ @@ -377,7 +377,7 @@ "4 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 " ] }, - "execution_count": 10, + "execution_count": 98, "metadata": {}, "output_type": "execute_result" } @@ -396,7 +396,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 100, "id": "baed146a-9d3a-4397-a812-3d50c9a2f038", "metadata": {}, "outputs": [], @@ -425,7 +425,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 102, "id": "5fbfd88b-b94c-489c-9201-670e96e453e7", "metadata": {}, "outputs": [ @@ -433,7 +433,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_15815/3848597476.py:4: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/3848597476.py:4: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", @@ -447,7 +447,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 104, "id": "b4f05142-2a22-42ef-a60d-f23cc4b5cb09", "metadata": {}, "outputs": [ @@ -514,7 +514,7 @@ "consentement optout b2c 34523" ] }, - "execution_count": 13, + "execution_count": 104, "metadata": {}, "output_type": "execute_result" } @@ -525,7 +525,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 106, "id": "4417ff51-f501-4ab9-a192-4ab75764a8ed", "metadata": { "scrolled": true @@ -594,7 +594,7 @@ "DDCP MD Procès du Siècle 1684" ] }, - "execution_count": 14, + "execution_count": 106, "metadata": {}, "output_type": "execute_result" } @@ -614,7 +614,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 108, "id": "d883cc7b-ac43-4485-b86f-eaf595fbad85", "metadata": {}, "outputs": [], @@ -639,7 +639,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 110, "id": "c8552dd6-52c5-4431-b43d-3cd6c578fd9f", "metadata": {}, "outputs": [ @@ -647,19 +647,19 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_15815/1967867975.py:15: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/1967867975.py:15: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " df[column_name] = pd.to_datetime(df[column_name], utc = True, format = 'ISO8601')\n", - "/tmp/ipykernel_15815/1967867975.py:15: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/1967867975.py:15: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " df[column_name] = pd.to_datetime(df[column_name], utc = True, format = 'ISO8601')\n", - "/tmp/ipykernel_15815/1967867975.py:15: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/1967867975.py:15: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", @@ -674,7 +674,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 112, "id": "c24457e7-3cad-451a-a65b-7373b656bd6e", "metadata": { "scrolled": true @@ -794,7 +794,7 @@ "4 404 2021-03-27 23:00:00+00:00 " ] }, - "execution_count": 17, + "execution_count": 112, "metadata": {}, "output_type": "execute_result" } @@ -805,7 +805,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 114, "id": "e2c88552-b863-47a2-be23-8d2898fb28bc", "metadata": {}, "outputs": [], @@ -839,7 +839,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 116, "id": "24537647-bc29-4777-9848-ac4120a4aa60", "metadata": {}, "outputs": [ @@ -847,7 +847,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_15815/3700263836.py:11: SettingWithCopyWarning: \n", + "/tmp/ipykernel_1018/3700263836.py:11: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", @@ -861,7 +861,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 118, "id": "6be2a9a6-056b-4e19-8c26-a18ba3df36b3", "metadata": {}, "outputs": [ @@ -941,7 +941,7 @@ "4 6 20 0.0 NaT" ] }, - "execution_count": 20, + "execution_count": 118, "metadata": {}, "output_type": "execute_result" } @@ -968,7 +968,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 120, "id": "30488a40-1b38-4b9a-9d3b-26a0597c5e6d", "metadata": {}, "outputs": [], @@ -979,7 +979,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 122, "id": "607eb4b4-eed9-4b50-b823-f75c116dd37c", "metadata": {}, "outputs": [], @@ -1050,7 +1050,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 124, "id": "350b09b9-451f-4d47-81fe-f34b892db027", "metadata": {}, "outputs": [], @@ -1138,7 +1138,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 126, "id": "0fccc8ef-e575-4857-a401-94a7274394df", "metadata": {}, "outputs": [ @@ -1291,7 +1291,7 @@ "4 indiv entrées tp " ] }, - "execution_count": 24, + "execution_count": 126, "metadata": {}, "output_type": "execute_result" } @@ -1303,7 +1303,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 128, "id": "779d8aaf-6668-4f66-8852-847304407ea3", "metadata": {}, "outputs": [ @@ -1473,7 +1473,7 @@ "4 spectacle vivant mucem " ] }, - "execution_count": 25, + "execution_count": 128, "metadata": {}, "output_type": "execute_result" } @@ -1485,7 +1485,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 130, "id": "7714fa32-303b-4ea7-b174-3fd0fcab5af0", "metadata": {}, "outputs": [ @@ -1584,7 +1584,7 @@ "4 37 383 269 1" ] }, - "execution_count": 26, + "execution_count": 130, "metadata": {}, "output_type": "execute_result" } @@ -1604,7 +1604,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 132, "id": "15a62ed6-35e4-4abc-aeef-a7daeec0a4ba", "metadata": {}, "outputs": [], @@ -1632,7 +1632,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 134, "id": "89dc9685-1de9-4ce3-a6c0-8d7f1931a951", "metadata": {}, "outputs": [ @@ -1686,7 +1686,7 @@ " id_representation_cap\n", " season_id\n", " facility_id\n", - " ...\n", + " event_type_id\n", " event_type_key_id\n", " facility_key_id\n", " street_id\n", @@ -1712,7 +1712,7 @@ " 8789\n", " 4\n", " 1\n", - " ...\n", + " 2\n", " 5\n", " 1\n", " 1\n", @@ -1736,7 +1736,7 @@ " 390\n", " 2\n", " 1\n", - " ...\n", + " 2\n", " 2\n", " 1\n", " 1\n", @@ -1760,7 +1760,7 @@ " 395\n", " 2\n", " 1\n", - " ...\n", + " 2\n", " 2\n", " 1\n", " 1\n", @@ -1784,7 +1784,7 @@ " 120199\n", " 1754\n", " 1\n", - " ...\n", + " 2\n", " 4\n", " 1\n", " 1\n", @@ -1808,7 +1808,7 @@ " 21\n", " 4\n", " 1\n", - " ...\n", + " 3\n", " 6\n", " 1\n", " 1\n", @@ -1822,7 +1822,6 @@ " \n", " \n", "\n", - "

5 rows × 21 columns

\n", "" ], "text/plain": [ @@ -1840,19 +1839,19 @@ "3 156773 1 12365 120199 \n", "4 1175 1 8 21 \n", "\n", - " season_id facility_id ... event_type_key_id facility_key_id street_id \\\n", - "0 4 1 ... 5 1 1 \n", - "1 2 1 ... 2 1 1 \n", - "2 2 1 ... 2 1 1 \n", - "3 1754 1 ... 4 1 1 \n", - "4 4 1 ... 6 1 1 \n", + " season_id facility_id event_type_id event_type_key_id facility_key_id \\\n", + "0 4 1 2 5 1 \n", + "1 2 1 2 2 1 \n", + "2 2 1 2 2 1 \n", + "3 1754 1 2 4 1 \n", + "4 4 1 3 6 1 \n", "\n", - " amount is_full_price name_categories \\\n", - "0 9.0 False indiv activité tr \n", - "1 9.5 False indiv entrées tp \n", - "2 11.5 False indiv entrées tp \n", - "3 8.0 False indiv entrées tr \n", - "4 8.5 False indiv entrées tp \n", + " street_id amount is_full_price name_categories \\\n", + "0 1 9.0 False indiv activité tr \n", + "1 1 9.5 False indiv entrées tp \n", + "2 1 11.5 False indiv entrées tp \n", + "3 1 8.0 False indiv entrées tr \n", + "4 1 8.5 False indiv entrées tp \n", "\n", " name_events name_seasons \\\n", "0 visite-jeu \"le classico des minots\" (1h30) 2017 \n", @@ -1866,12 +1865,10 @@ "1 offre muséale individuel mucem \n", "2 offre muséale individuel mucem \n", "3 offre muséale individuel mucem \n", - "4 non défini mucem \n", - "\n", - "[5 rows x 21 columns]" + "4 non défini mucem " ] }, - "execution_count": 28, + "execution_count": 134, "metadata": {}, "output_type": "execute_result" } @@ -1883,7 +1880,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 136, "id": "98f78cd5-b694-4cc6-b033-20170aa13e8d", "metadata": {}, "outputs": [], @@ -1894,11 +1891,286 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 137, "id": "52db7bcb-3fb7-48e5-b612-4e22bdab4a94", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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ticket_idproduct_idis_from_subscriptionsupplier_nametype_of_ticket_namechildrenpurchase_datecustomer_idid_productsrepresentation_idpricing_formula_idcategory_idproducts_group_idproduct_pack_idevent_idid_representation_capseason_idfacility_idevent_type_idevent_type_key_idfacility_key_idstreet_idamountis_full_pricename_categoriesname_eventsname_seasonsname_event_typesname_facilities
013070859225251Falsevente en ligneAtelierpricing_formula2018-12-28 14:47:50+00:00481872252511136762813224768119717274216144118.0Falseindiv prog enfantl'école des magiciens2018spectacle vivantmucem
113070855225251Falsevente en ligneAtelierpricing_formula2018-12-28 14:47:50+00:00481872252511136762813224768119717274216144118.0Falseindiv prog enfantl'école des magiciens2018spectacle vivantmucem
213070856225251Falsevente en ligneAtelierpricing_formula2018-12-28 14:47:50+00:00481872252511136762813224768119717274216144118.0Falseindiv prog enfantl'école des magiciens2018spectacle vivantmucem
313070857225251Falsevente en ligneAtelierpricing_formula2018-12-28 14:47:50+00:00481872252511136762813224768119717274216144118.0Falseindiv prog enfantl'école des magiciens2018spectacle vivantmucem
413070858225251Falsevente en ligneAtelierpricing_formula2018-12-28 14:47:50+00:00481872252511136762813224768119717274216144118.0Falseindiv prog enfantl'école des magiciens2018spectacle vivantmucem
\n", + "
" + ], + "text/plain": [ + " ticket_id product_id is_from_subscription supplier_name \\\n", + "0 13070859 225251 False vente en ligne \n", + "1 13070855 225251 False vente en ligne \n", + "2 13070856 225251 False vente en ligne \n", + "3 13070857 225251 False vente en ligne \n", + "4 13070858 225251 False vente en ligne \n", + "\n", + " type_of_ticket_name children purchase_date customer_id \\\n", + "0 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 \n", + "1 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 \n", + "2 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 \n", + "3 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 \n", + "4 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 \n", + "\n", + " id_products representation_id pricing_formula_id category_id \\\n", + "0 225251 113676 28 13 \n", + "1 225251 113676 28 13 \n", + "2 225251 113676 28 13 \n", + "3 225251 113676 28 13 \n", + "4 225251 113676 28 13 \n", + "\n", + " products_group_id product_pack_id event_id id_representation_cap \\\n", + "0 224768 1 197 172742 \n", + "1 224768 1 197 172742 \n", + "2 224768 1 197 172742 \n", + "3 224768 1 197 172742 \n", + "4 224768 1 197 172742 \n", + "\n", + " season_id facility_id event_type_id event_type_key_id facility_key_id \\\n", + "0 16 1 4 4 1 \n", + "1 16 1 4 4 1 \n", + "2 16 1 4 4 1 \n", + "3 16 1 4 4 1 \n", + "4 16 1 4 4 1 \n", + "\n", + " street_id amount is_full_price name_categories name_events \\\n", + "0 1 8.0 False indiv prog enfant l'école des magiciens \n", + "1 1 8.0 False indiv prog enfant l'école des magiciens \n", + "2 1 8.0 False indiv prog enfant l'école des magiciens \n", + "3 1 8.0 False indiv prog enfant l'école des magiciens \n", + "4 1 8.0 False indiv prog enfant l'école des magiciens \n", + "\n", + " name_seasons name_event_types name_facilities \n", + "0 2018 spectacle vivant mucem \n", + "1 2018 spectacle vivant mucem \n", + "2 2018 spectacle vivant mucem \n", + "3 2018 spectacle vivant mucem \n", + "4 2018 spectacle vivant mucem " + ] + }, + "execution_count": 137, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1_products_purchased.head()" + ] }, { "cell_type": "markdown", @@ -1910,7 +2182,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 138, "id": "665a5925-9c0e-425a-8f11-c33a0a9ec444", "metadata": {}, "outputs": [ @@ -1928,7 +2200,7 @@ " dtype='object')" ] }, - "execution_count": 30, + "execution_count": 138, "metadata": {}, "output_type": "execute_result" } @@ -1939,7 +2211,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 139, "id": "b913a69e-3146-4919-b5f6-a6108532bffa", "metadata": {}, "outputs": [ @@ -1950,7 +2222,7 @@ " 'offre muséale groupe'], dtype=object)" ] }, - "execution_count": 31, + "execution_count": 139, "metadata": {}, "output_type": "execute_result" } @@ -1961,17 +2233,17 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 140, "id": "e01e8cf9-1187-4a4b-993d-b7b4321cd8f0", "metadata": {}, "outputs": [], "source": [ - "df1_products_purchased_reduced = df1_products_purchased[['ticket_id', 'customer_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']]" + "df1_products_purchased_reduced = df1_products_purchased[['ticket_id', 'customer_id', 'product_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": 53, + "execution_count": 141, "id": "3d8b0875-b409-44ce-b688-d9d6758782d3", "metadata": {}, "outputs": [ @@ -1998,6 +2270,7 @@ " \n", " ticket_id\n", " customer_id\n", + " product_id\n", " event_type_id\n", " supplier_name\n", " purchase_date\n", @@ -2017,6 +2290,7 @@ " 0\n", " 13070859\n", " 48187\n", + " 225251\n", " 4\n", " vente en ligne\n", " 2018-12-28 14:47:50+00:00\n", @@ -2034,6 +2308,7 @@ " 1\n", " 13070855\n", " 48187\n", + " 225251\n", " 4\n", " vente en ligne\n", " 2018-12-28 14:47:50+00:00\n", @@ -2051,6 +2326,7 @@ " 2\n", " 13070856\n", " 48187\n", + " 225251\n", " 4\n", " vente en ligne\n", " 2018-12-28 14:47:50+00:00\n", @@ -2068,6 +2344,7 @@ " 3\n", " 13070857\n", " 48187\n", + " 225251\n", " 4\n", " vente en ligne\n", " 2018-12-28 14:47:50+00:00\n", @@ -2085,6 +2362,7 @@ " 4\n", " 13070858\n", " 48187\n", + " 225251\n", " 4\n", " vente en ligne\n", " 2018-12-28 14:47:50+00:00\n", @@ -2098,182 +2376,827 @@ " l'école des magiciens\n", " 2018\n", " \n", - " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " \n", - " \n", - " 1826667\n", - " 18643494\n", - " 81\n", - " 4\n", - " vad\n", - " 2022-08-02 12:18:16+00:00\n", - " Billet en nombre\n", - " 11.0\n", - " pricing_formula\n", - " False\n", - " spectacle vivant\n", - " mucem\n", - " en nb entrées tr\n", - " NaN\n", - " 2022\n", - " \n", - " \n", - " 1826668\n", - " 18643495\n", - " 81\n", - " 4\n", - " vad\n", - " 2022-08-02 12:18:16+00:00\n", - " Billet en nombre\n", - " 11.0\n", - " pricing_formula\n", - " False\n", - " spectacle vivant\n", - " mucem\n", - " en nb entrées tr\n", - " NaN\n", - " 2022\n", - " \n", - " \n", - " 1826669\n", - " 18643496\n", - " 81\n", - " 4\n", - " vad\n", - " 2022-08-02 12:18:16+00:00\n", - " Billet en nombre\n", - " 11.0\n", - " pricing_formula\n", - " False\n", - " spectacle vivant\n", - " mucem\n", - " en nb entrées tr\n", - " NaN\n", - " 2022\n", - " \n", - " \n", - " 1826670\n", - " 18643497\n", - " 81\n", - " 4\n", - " vad\n", - " 2022-08-02 12:18:16+00:00\n", - " Billet en nombre\n", - " 11.0\n", - " pricing_formula\n", - " False\n", - " spectacle vivant\n", - " mucem\n", - " en nb entrées tr\n", - " NaN\n", - " 2022\n", - " \n", - " \n", - " 1826671\n", - " 19853111\n", - " 62763\n", - " 4\n", - " vad\n", - " 2022-11-04 14:25:42+00:00\n", - " Billet en nombre\n", - " 0.0\n", - " pricing_formula\n", - " False\n", - " spectacle vivant\n", - " mucem\n", - " indiv entrées gr\n", - " NaN\n", - " 2022\n", - " \n", " \n", "\n", - "

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\n", "" ], "text/plain": [ - " ticket_id customer_id event_type_id supplier_name \\\n", - "0 13070859 48187 4 vente en ligne \n", - "1 13070855 48187 4 vente en ligne \n", - "2 13070856 48187 4 vente en ligne \n", - "3 13070857 48187 4 vente en ligne \n", - "4 13070858 48187 4 vente en ligne \n", - "... ... ... ... ... \n", - "1826667 18643494 81 4 vad \n", - "1826668 18643495 81 4 vad \n", - "1826669 18643496 81 4 vad \n", - "1826670 18643497 81 4 vad \n", - "1826671 19853111 62763 4 vad \n", + " ticket_id customer_id product_id event_type_id supplier_name \\\n", + "0 13070859 48187 225251 4 vente en ligne \n", + "1 13070855 48187 225251 4 vente en ligne \n", + "2 13070856 48187 225251 4 vente en ligne \n", + "3 13070857 48187 225251 4 vente en ligne \n", + "4 13070858 48187 225251 4 vente en ligne \n", "\n", - " purchase_date type_of_ticket_name amount \\\n", - "0 2018-12-28 14:47:50+00:00 Atelier 8.0 \n", - "1 2018-12-28 14:47:50+00:00 Atelier 8.0 \n", - "2 2018-12-28 14:47:50+00:00 Atelier 8.0 \n", - "3 2018-12-28 14:47:50+00:00 Atelier 8.0 \n", - "4 2018-12-28 14:47:50+00:00 Atelier 8.0 \n", - "... ... ... ... \n", - "1826667 2022-08-02 12:18:16+00:00 Billet en nombre 11.0 \n", - "1826668 2022-08-02 12:18:16+00:00 Billet en nombre 11.0 \n", - "1826669 2022-08-02 12:18:16+00:00 Billet en nombre 11.0 \n", - "1826670 2022-08-02 12:18:16+00:00 Billet en nombre 11.0 \n", - "1826671 2022-11-04 14:25:42+00:00 Billet en nombre 0.0 \n", + " purchase_date type_of_ticket_name amount children \\\n", + "0 2018-12-28 14:47:50+00:00 Atelier 8.0 pricing_formula \n", + "1 2018-12-28 14:47:50+00:00 Atelier 8.0 pricing_formula \n", + "2 2018-12-28 14:47:50+00:00 Atelier 8.0 pricing_formula \n", + "3 2018-12-28 14:47:50+00:00 Atelier 8.0 pricing_formula \n", + "4 2018-12-28 14:47:50+00:00 Atelier 8.0 pricing_formula \n", "\n", - " children is_full_price name_event_types name_facilities \\\n", - "0 pricing_formula False spectacle vivant mucem \n", - "1 pricing_formula False spectacle vivant mucem \n", - "2 pricing_formula False spectacle vivant mucem \n", - "3 pricing_formula False spectacle vivant mucem \n", - "4 pricing_formula False spectacle vivant mucem \n", - "... ... ... ... ... \n", - "1826667 pricing_formula False spectacle vivant mucem \n", - "1826668 pricing_formula False spectacle vivant mucem \n", - "1826669 pricing_formula False spectacle vivant mucem \n", - "1826670 pricing_formula False spectacle vivant mucem \n", - "1826671 pricing_formula False spectacle vivant mucem \n", + " is_full_price name_event_types name_facilities name_categories \\\n", + "0 False spectacle vivant mucem indiv prog enfant \n", + "1 False spectacle vivant mucem indiv prog enfant \n", + "2 False spectacle vivant mucem indiv prog enfant \n", + "3 False spectacle vivant mucem indiv prog enfant \n", + "4 False spectacle vivant mucem indiv prog enfant \n", "\n", - " name_categories name_events name_seasons \n", - "0 indiv prog enfant l'école des magiciens 2018 \n", - "1 indiv prog enfant l'école des magiciens 2018 \n", - "2 indiv prog enfant l'école des magiciens 2018 \n", - "3 indiv prog enfant l'école des magiciens 2018 \n", - "4 indiv prog enfant l'école des magiciens 2018 \n", - "... ... ... ... \n", - "1826667 en nb entrées tr NaN 2022 \n", - "1826668 en nb entrées tr NaN 2022 \n", - "1826669 en nb entrées tr NaN 2022 \n", - "1826670 en nb entrées tr NaN 2022 \n", - "1826671 indiv entrées gr NaN 2022 \n", - "\n", - "[1826672 rows x 14 columns]" + " name_events name_seasons \n", + "0 l'école des magiciens 2018 \n", + "1 l'école des magiciens 2018 \n", + "2 l'école des magiciens 2018 \n", + "3 l'école des magiciens 2018 \n", + "4 l'école des magiciens 2018 " ] }, - "execution_count": 53, + "execution_count": 141, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Importance des suppliers\n", - "df1_products_purchased_reduced" + "df1_products_purchased_reduced.head()" + ] + }, + { + "cell_type": "markdown", + "id": "9354b283-9e00-4aa9-a017-d7dd11fdf745", + "metadata": {}, + "source": [ + "## Alexis' work" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 142, + "id": "cfbeaf0b-64ea-4abf-b785-57e43e651108", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " customer_id event_type_id nb_tickets avg_amount\n", + "0 1 2 384226 6.150659\n", + "1 1 4 453242 7.762474\n", + "2 1 5 201750 4.452618\n", + "3 1 6 217356 6.439463\n", + "4 2 2 143 6.150659" + ] + }, + "execution_count": 143, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nb_tickets = (df1_products_purchased_reduced.groupby([\"customer_id\", \"event_type_id\"])\n", + " .agg({\"ticket_id\" : \"count\"}).reset_index()\n", + " .rename(columns = {'ticket_id' : 'nb_tickets'})\n", + " .merge(avg_amount, how='left', on='event_type_id'))\n", + "nb_tickets.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "id": "28fd3b8c-0caf-4d4e-9c39-9c1cd2bab126", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " customer_id birthdate street_id is_partner gender is_email_true \\\n", + "0 12751 NaN 2 False 1 True \n", + "1 12825 NaN 2 False 2 True \n", + "2 11261 NaN 2 False 1 True \n", + "3 13071 NaN 2 False 2 True \n", + "4 653061 NaN 10 False 2 True \n", + "\n", + " opt_in structure_id profession language mcp_contact_id last_buying_date \\\n", + "0 True NaN NaN NaN NaN NaN \n", + "1 True NaN NaN NaN NaN NaN \n", + "2 True NaN NaN NaN NaN NaN \n", + "3 True NaN NaN NaN NaN NaN \n", + "4 False NaN NaN NaN NaN NaN \n", + "\n", + " max_price ticket_sum average_price fidelity average_purchase_delay \\\n", + "0 NaN 0 0.0 0 NaN \n", + "1 NaN 0 0.0 0 NaN \n", + "2 NaN 0 0.0 0 NaN \n", + "3 NaN 0 0.0 0 NaN \n", + "4 NaN 0 0.0 0 NaN \n", + "\n", + " average_price_basket average_ticket_basket total_price purchase_count \\\n", + "0 NaN NaN NaN 0 \n", + "1 NaN NaN NaN 0 \n", + "2 NaN NaN NaN 0 \n", + "3 NaN NaN NaN 0 \n", + "4 NaN NaN NaN 0 \n", + "\n", + " first_buying_date country age tenant_id nb_campaigns \\\n", + "0 NaT fr NaN 1311 NaN \n", + "1 NaT fr NaN 1311 NaN \n", + "2 NaT fr NaN 1311 NaN \n", + "3 NaT fr NaN 1311 NaN \n", + "4 NaT NaN NaN 1311 80.0 \n", + "\n", + " nb_campaigns_opened time_to_open \n", + "0 NaN NaT \n", + "1 NaN NaT \n", + "2 NaN NaT \n", + "3 NaN NaT \n", + "4 2.0 0 days 19:53:02.500000 " + ] + }, + "execution_count": 144, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Fusion avec KPI campaigns liés au customer\n", + "df1_customer = pd.merge(df1_customerplus_clean, df1_campaigns_kpi, on = 'customer_id', how = 'left')\n", + "df1_customer.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "id": "b438c563-e6c1-4b10-bedf-3b251f97018d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape : (156289, 31)\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " customer_id birthdate street_id is_partner gender is_email_true \\\n", + "0 12751 NaN 2 False 1 True \n", + "1 12825 NaN 2 False 2 True \n", + "2 11261 NaN 2 False 1 True \n", + "3 13071 NaN 2 False 2 True \n", + "4 653061 NaN 10 False 2 True \n", + "\n", + " opt_in structure_id profession language mcp_contact_id last_buying_date \\\n", + "0 True NaN NaN NaN NaN NaN \n", + "1 True NaN NaN NaN NaN NaN \n", + "2 True NaN NaN NaN NaN NaN \n", + "3 True NaN NaN NaN NaN NaN \n", + "4 False NaN NaN NaN NaN NaN \n", + "\n", + " max_price ticket_sum average_price fidelity average_purchase_delay \\\n", + "0 NaN 0 0.0 0 NaN \n", + "1 NaN 0 0.0 0 NaN \n", + "2 NaN 0 0.0 0 NaN \n", + "3 NaN 0 0.0 0 NaN \n", + "4 NaN 0 0.0 0 NaN \n", + "\n", + " average_price_basket average_ticket_basket total_price purchase_count \\\n", + "0 NaN NaN NaN 0 \n", + "1 NaN NaN NaN 0 \n", + "2 NaN NaN NaN 0 \n", + "3 NaN NaN NaN 0 \n", + "4 NaN NaN NaN 0 \n", + "\n", + " first_buying_date country age tenant_id nb_campaigns \\\n", + "0 NaT fr NaN 1311 NaN \n", + "1 NaT fr NaN 1311 NaN \n", + "2 NaT fr NaN 1311 NaN \n", + "3 NaT fr NaN 1311 NaN \n", + "4 NaT NaN NaN 1311 80.0 \n", + "\n", + " nb_campaigns_opened time_to_open event_type_id nb_tickets \\\n", + "0 NaN NaT NaN NaN \n", + "1 NaN NaT NaN NaN \n", + "2 NaN NaT NaN NaN \n", + "3 NaN NaT NaN NaN \n", + "4 2.0 0 days 19:53:02.500000 NaN NaN \n", + "\n", + " avg_amount \n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN " + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1_customer_product = pd.merge(df1_customer, nb_tickets, on = 'customer_id', how = 'left')\n", + "print(\"shape : \", df1_customer_product.shape)\n", + "df1_customer_product.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "id": "afcfe12d-f840-4886-a08b-13a69f022f4c", + "metadata": {}, + "outputs": [], + "source": [ + "df1_customer_product.to_csv(\"customer_product.csv\", index = False)" + ] + }, + { + "cell_type": "markdown", + "id": "8e763591-1802-4f5b-8285-1cf980de541a", + "metadata": {}, + "source": [ + "## End of Alexis' work" + ] + }, + { + "cell_type": "code", + "execution_count": 36, "id": "2bda0b97-b28b-4070-a57d-aeab0e2f7dfe", "metadata": {}, "outputs": [], @@ -2284,7 +3207,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 37, "id": "043303fe-e90f-4689-a2a9-5d690555a045", "metadata": {}, "outputs": [], @@ -2315,7 +3238,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 38, "id": "5882234a-1ed5-4269-87a6-0d75613476e3", "metadata": {}, "outputs": [], @@ -2325,7 +3248,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 39, "id": "a7a452a6-cd5e-4c8b-b250-8a7d26e48fad", "metadata": {}, "outputs": [ @@ -2762,7 +3685,7 @@ "36478 1973 days 22:16:24 " ] }, - "execution_count": 52, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -2781,7 +3704,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 40, "id": "46de1912-4a66-46e5-8b9e-7768b2d2723b", "metadata": {}, "outputs": [], @@ -2792,7 +3715,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 41, "id": "9740d64a-e5eb-4967-a534-ca6177546465", "metadata": {}, "outputs": [ @@ -2998,7 +3921,7 @@ "[5 rows x 28 columns]" ] }, - "execution_count": 40, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -3009,7 +3932,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 42, "id": "b5c4418c-ad2e-4bb9-bd5c-3b769e9c87d4", "metadata": {}, "outputs": [ @@ -3120,7 +4043,7 @@ "58201 1311 NaN NaN NaT " ] }, - "execution_count": 49, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -3134,13 +4057,495 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 43, + "id": "2b161dfb-1593-4f1e-870b-de24735e4968", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " customer_id birthdate street_id_x is_partner gender is_email_true \\\n", + "0 12751 NaN 2 False 1 True \n", + "1 12825 NaN 2 False 2 True \n", + "2 11261 NaN 2 False 1 True \n", + "3 13071 NaN 2 False 2 True \n", + "4 653061 NaN 10 False 2 True \n", + "\n", + " opt_in structure_id profession language mcp_contact_id last_buying_date \\\n", + "0 True NaN NaN NaN NaN NaN \n", + "1 True NaN NaN NaN NaN NaN \n", + "2 True NaN NaN NaN NaN NaN \n", + "3 True NaN NaN NaN NaN NaN \n", + "4 False NaN NaN NaN NaN NaN \n", + "\n", + " max_price ticket_sum average_price fidelity average_purchase_delay \\\n", + "0 NaN 0 0.0 0 NaN \n", + "1 NaN 0 0.0 0 NaN \n", + "2 NaN 0 0.0 0 NaN \n", + "3 NaN 0 0.0 0 NaN \n", + "4 NaN 0 0.0 0 NaN \n", + "\n", + " average_price_basket average_ticket_basket total_price purchase_count \\\n", + "0 NaN NaN NaN 0 \n", + "1 NaN NaN NaN 0 \n", + "2 NaN NaN NaN 0 \n", + "3 NaN NaN NaN 0 \n", + "4 NaN NaN NaN 0 \n", + "\n", + " first_buying_date country age tenant_id nb_campaigns \\\n", + "0 NaT fr NaN 1311 NaN \n", + "1 NaT fr NaN 1311 NaN \n", + "2 NaT fr NaN 1311 NaN \n", + "3 NaT fr NaN 1311 NaN \n", + "4 NaT NaN NaN 1311 80.0 \n", + "\n", + " nb_campaigns_opened time_to_open ticket_id product_id \\\n", + "0 NaN NaT NaN NaN \n", + "1 NaN NaT NaN NaN \n", + "2 NaN NaT NaN NaN \n", + "3 NaN NaT NaN NaN \n", + "4 2.0 0 days 19:53:02.500000 NaN NaN \n", + "\n", + " is_from_subscription supplier_name type_of_ticket_name children \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " purchase_date id_products representation_id pricing_formula_id \\\n", + "0 NaT NaN NaN NaN \n", + "1 NaT NaN NaN NaN \n", + "2 NaT NaN NaN NaN \n", + "3 NaT NaN NaN NaN \n", + "4 NaT NaN NaN NaN \n", + "\n", + " category_id products_group_id product_pack_id event_id \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " id_representation_cap season_id facility_id event_type_id \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " event_type_key_id facility_key_id street_id_y amount is_full_price \\\n", + "0 NaN NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN NaN \n", + "\n", + " name_categories name_events name_seasons name_event_types name_facilities \n", + "0 NaN NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN NaN " + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Fusion avec KPI liés au comportement d'achat,\n", + "df1_customer_product = pd.merge(df1_customer, df1_products_purchased, on = 'customer_id', how = 'left')\n", + "df1_customer_product.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, "id": "1e42a790-b215-4107-a969-85005da06ebd", "metadata": {}, "outputs": [], "source": [ "# Fusion avec KPI liés au comportement d'achat\n", - "# df1_customer_product = pd.merge(df1_products_purchased_reduced, df1_products_purchased, on = 'customer_id', how = 'outer')" + "#df1_customer_product = pd.merge(df1_products_purchased_reduced, df1_products_purchased, on = 'customer_id', how = 'outer')" ] }, { @@ -3150,7 +4555,7 @@ "metadata": {}, "outputs": [], "source": [ - "# df1_customer_product" + "#df1_customer_product.head()" ] } ], diff --git a/Notebook_AR.ipynb b/Notebook_AR.ipynb index c808ce7..0ad1826 100644 --- a/Notebook_AR.ipynb +++ b/Notebook_AR.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 274, "id": "20eeb149-6618-4ef2-9cfd-ff062950f36c", "metadata": {}, "outputs": [], @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 275, "id": "30494c5e-9649-4fff-8708-617544188b20", "metadata": {}, "outputs": [ @@ -46,7 +46,7 @@ " 'bdc2324-data/9']" ] }, - "execution_count": 99, + "execution_count": 275, "metadata": {}, "output_type": "execute_result" } @@ -78,7 +78,7 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 276, "id": "f1cce705-46e1-42de-8e93-2ee15312d288", "metadata": {}, "outputs": [], @@ -88,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 277, "id": "82d4db0e-0cd5-49af-a4d3-f17f54b1c03c", "metadata": {}, "outputs": [ @@ -136,7 +136,7 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 278, "id": "65cb38ad-52ae-4266-85d8-c47d81b00283", "metadata": {}, "outputs": [], @@ -165,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 279, "id": "0214d30d-5f83-498f-867f-e67b5793b731", "metadata": {}, "outputs": [ @@ -316,7 +316,7 @@ "4 e11943a6031a0e6114ae69c257617980 2022-01-27 00:00:00+01:00 " ] }, - "execution_count": 103, + "execution_count": 279, "metadata": {}, "output_type": "execute_result" } @@ -328,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": 104, + "execution_count": 280, "id": "e7982be4-2c42-4a91-be5a-329a999644cc", "metadata": {}, "outputs": [ @@ -454,7 +454,7 @@ "4 2022-02-02 17:19:36.557473+01:00 " ] }, - "execution_count": 104, + "execution_count": 280, "metadata": {}, "output_type": "execute_result" } @@ -482,7 +482,7 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": 281, "id": "e973575b-4ed6-4b23-8024-f383ac82e87c", "metadata": {}, "outputs": [ @@ -589,7 +589,7 @@ "4 2022-02-02 17:34:22.300427+01:00 2022-02-02 17:34:22.300427+01:00 " ] }, - "execution_count": 105, + "execution_count": 281, "metadata": {}, "output_type": "execute_result" } @@ -609,7 +609,7 @@ }, { "cell_type": "code", - "execution_count": 106, + "execution_count": 282, "id": "3b523575-c779-451c-a12e-a36fb4ad232c", "metadata": {}, "outputs": [ @@ -624,7 +624,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_703/2210053343.py:5: DtypeWarning: Columns (20) have mixed types. Specify dtype option on import or set low_memory=False.\n", + "/tmp/ipykernel_548/2210053343.py:5: DtypeWarning: Columns (20) have mixed types. Specify dtype option on import or set low_memory=False.\n", " customersplus = pd.read_csv(file_in, sep=\",\")\n" ] }, @@ -837,7 +837,7 @@ "[5 rows x 43 columns]" ] }, - "execution_count": 106, + "execution_count": 282, "metadata": {}, "output_type": "execute_result" } @@ -862,7 +862,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 283, "id": "87d801fc-d19a-4c45-9b21-9b6d7a8451fd", "metadata": {}, "outputs": [ @@ -904,7 +904,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 284, "id": "b6e4c3ea-5ccf-4aec-bd2d-79a5a1194178", "metadata": {}, "outputs": [ @@ -1017,7 +1017,7 @@ "4 2021-09-17 20:20:24.703110+02:00 NaN NaN " ] }, - "execution_count": 108, + "execution_count": 284, "metadata": {}, "output_type": "execute_result" } @@ -1039,7 +1039,7 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 285, "id": "6e81a35c-3c6f-403d-9ebd-e8399ecd4263", "metadata": {}, "outputs": [ @@ -1140,7 +1140,7 @@ "4 2021-09-17 18:10:40.945476+02:00 2021-09-17 18:10:40.945476+02:00 " ] }, - "execution_count": 109, + "execution_count": 285, "metadata": {}, "output_type": "execute_result" } @@ -1162,7 +1162,7 @@ }, { "cell_type": "code", - "execution_count": 110, + "execution_count": 286, "id": "85696d74-3b2f-4368-9045-44db5322b60d", "metadata": {}, "outputs": [ @@ -1258,7 +1258,7 @@ "3 2022-05-06 14:26:01.923160+02:00 12213df2ce68a624e4c0070521437bac " ] }, - "execution_count": 110, + "execution_count": 286, "metadata": {}, "output_type": "execute_result" } @@ -1298,7 +1298,7 @@ }, { "cell_type": "code", - "execution_count": 111, + "execution_count": 287, "id": "7c57529b-2ffb-4039-9795-b27c6fbd54a4", "metadata": {}, "outputs": [ @@ -1418,7 +1418,7 @@ "4 193e41eae8ee078537107a569c0426ef " ] }, - "execution_count": 111, + "execution_count": 287, "metadata": {}, "output_type": "execute_result" } @@ -1430,7 +1430,7 @@ }, { "cell_type": "code", - "execution_count": 112, + "execution_count": 288, "id": "903321fb-99f8-475d-b4a6-c70ec2efe190", "metadata": {}, "outputs": [ @@ -1581,7 +1581,7 @@ "4 1a6342ad2c213b626aa55e5374cd661a " ] }, - "execution_count": 112, + "execution_count": 288, "metadata": {}, "output_type": "execute_result" } @@ -1593,7 +1593,7 @@ }, { "cell_type": "code", - "execution_count": 113, + "execution_count": 289, "id": "243e6942-0233-4cd5-b32b-e005457131d2", "metadata": {}, "outputs": [ @@ -1725,7 +1725,7 @@ "4 NaN b144dd617807b02e0d9002fac6c61768 " ] }, - "execution_count": 113, + "execution_count": 289, "metadata": {}, "output_type": "execute_result" } @@ -1745,7 +1745,7 @@ }, { "cell_type": "code", - "execution_count": 114, + "execution_count": 290, "id": "6b82efce-1dee-4d89-8585-28c4ad477eef", "metadata": {}, "outputs": [ @@ -1914,7 +1914,7 @@ "4 NaN 07a5dd9e125345b9458651ab73605255 " ] }, - "execution_count": 114, + "execution_count": 290, "metadata": {}, "output_type": "execute_result" } @@ -1942,7 +1942,7 @@ }, { "cell_type": "code", - "execution_count": 115, + "execution_count": 291, "id": "daf37bff-a26d-4ff5-ad50-c90f917164bd", "metadata": {}, "outputs": [ @@ -2056,7 +2056,7 @@ "4 478eb63c71ba35d8d3d64c8637dafdee " ] }, - "execution_count": 115, + "execution_count": 291, "metadata": {}, "output_type": "execute_result" } @@ -2068,7 +2068,7 @@ }, { "cell_type": "code", - "execution_count": 116, + "execution_count": 292, "id": "cdb14488-b093-4b39-84fa-1c2b4576208f", "metadata": {}, "outputs": [ @@ -2175,7 +2175,7 @@ "4 2021-09-03 14:18:03.616081+02:00 0a2b941c46b31258c03b316aa064e86a " ] }, - "execution_count": 116, + "execution_count": 292, "metadata": {}, "output_type": "execute_result" } @@ -2203,7 +2203,7 @@ }, { "cell_type": "code", - "execution_count": 117, + "execution_count": 293, "id": "6582694d-5339-4f33-a943-c73033121a90", "metadata": {}, "outputs": [ @@ -2323,7 +2323,7 @@ "4 349e6a59585d78d80d46acbc6a520c50 " ] }, - "execution_count": 117, + "execution_count": 293, "metadata": {}, "output_type": "execute_result" } @@ -2335,7 +2335,7 @@ }, { "cell_type": "code", - "execution_count": 118, + "execution_count": 294, "id": "589076df-1958-42de-9941-1aff9fa8536f", "metadata": {}, "outputs": [ @@ -2442,7 +2442,7 @@ "4 2021-09-02 17:35:37.396740+02:00 c05b0061d2a875adbc35d3dfa6a50a12 " ] }, - "execution_count": 118, + "execution_count": 294, "metadata": {}, "output_type": "execute_result" } @@ -2472,7 +2472,7 @@ }, { "cell_type": "code", - "execution_count": 119, + "execution_count": 295, "id": "6f06d72a-5725-4eee-8e4c-e9ef5820f346", "metadata": {}, "outputs": [ @@ -2585,7 +2585,7 @@ "4 9 23 NaN NaN " ] }, - "execution_count": 119, + "execution_count": 295, "metadata": {}, "output_type": "execute_result" } @@ -2597,7 +2597,7 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": 296, "id": "bd405913-033d-4f15-a5b9-103d577baaff", "metadata": {}, "outputs": [ @@ -2785,7 +2785,7 @@ "4 733104286519c0614b2d45470eb180a1 " ] }, - "execution_count": 120, + "execution_count": 296, "metadata": {}, "output_type": "execute_result" } @@ -2797,7 +2797,7 @@ }, { "cell_type": "code", - "execution_count": 121, + "execution_count": 297, "id": "0f2c7ea3-6964-48fd-9411-17547b2c3a3f", "metadata": {}, "outputs": [], @@ -2823,7 +2823,7 @@ }, { "cell_type": "code", - "execution_count": 122, + "execution_count": 298, "id": "cba22ee2-338d-4ce1-a1e8-829a11a94bcf", "metadata": {}, "outputs": [ @@ -2980,7 +2980,7 @@ "4 17b91f19c71ff6287ffc1f44af952576 " ] }, - "execution_count": 122, + "execution_count": 298, "metadata": {}, "output_type": "execute_result" } @@ -2992,7 +2992,7 @@ }, { "cell_type": "code", - "execution_count": 123, + "execution_count": 299, "id": "3db00b9d-2187-4cb6-980d-8ac6ab9eb460", "metadata": {}, "outputs": [ @@ -3106,7 +3106,7 @@ "4 732cfdcf2065fa0005faf42793ddd76c " ] }, - "execution_count": 123, + "execution_count": 299, "metadata": {}, "output_type": "execute_result" } @@ -3118,7 +3118,7 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 300, "id": "cba0ee58-6280-45fe-99b3-0be09db5922b", "metadata": {}, "outputs": [ @@ -3232,7 +3232,7 @@ "4 7ccc51049a85e0df9b80662e45b6ddb8 " ] }, - "execution_count": 124, + "execution_count": 300, "metadata": {}, "output_type": "execute_result" } @@ -3244,7 +3244,7 @@ }, { "cell_type": "code", - "execution_count": 125, + "execution_count": 301, "id": "6fa82fd7-d6d3-4857-af24-ea573b1129d0", "metadata": {}, "outputs": [ @@ -3364,7 +3364,7 @@ "4 89feffd283ebdabdc3b81fb62ea4f6f0 " ] }, - "execution_count": 125, + "execution_count": 301, "metadata": {}, "output_type": "execute_result" } @@ -3408,7 +3408,7 @@ }, { "cell_type": "code", - "execution_count": 126, + "execution_count": 302, "id": "c240b811-48a6-4501-9e70-bc51d69e3ac4", "metadata": {}, "outputs": [], @@ -3424,7 +3424,7 @@ }, { "cell_type": "code", - "execution_count": 127, + "execution_count": 303, "id": "54057367-9df9-42f4-aa07-bf524bb76462", "metadata": {}, "outputs": [ @@ -3445,7 +3445,7 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": 304, "id": "63914e20-9efc-4088-877b-edab5f225d00", "metadata": {}, "outputs": [ @@ -3493,7 +3493,7 @@ }, { "cell_type": "code", - "execution_count": 129, + "execution_count": 305, "id": "590a132a-4f57-4ea3-a282-2ef913e4b753", "metadata": {}, "outputs": [], @@ -3503,7 +3503,7 @@ }, { "cell_type": "code", - "execution_count": 130, + "execution_count": 306, "id": "0fbebfb7-a827-46b1-890b-86c9def7cdbb", "metadata": {}, "outputs": [], @@ -3513,7 +3513,7 @@ }, { "cell_type": "code", - "execution_count": 131, + "execution_count": 307, "id": "b8aa5f8f-845e-4ee5-b80d-38b7061a94a2", "metadata": {}, "outputs": [], @@ -3528,7 +3528,7 @@ }, { "cell_type": "code", - "execution_count": 132, + "execution_count": 308, "id": "2c478213-09ae-44ef-8c7c-125bcb571642", "metadata": {}, "outputs": [], @@ -3546,7 +3546,7 @@ }, { "cell_type": "code", - "execution_count": 133, + "execution_count": 309, "id": "327e44b0-eb99-4022-b4ca-79548072f0f0", "metadata": {}, "outputs": [], @@ -3561,7 +3561,7 @@ }, { "cell_type": "code", - "execution_count": 134, + "execution_count": 310, "id": "10926def-267f-4e86-b2c9-72e27ff9a9df", "metadata": {}, "outputs": [], @@ -3585,7 +3585,7 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": 311, "id": "862a7658-0602-4d94-bb58-d23774c00d32", "metadata": {}, "outputs": [ @@ -3755,7 +3755,7 @@ "4 NaN f1c4689bc47dee6f60b56d74b593dd46 " ] }, - "execution_count": 135, + "execution_count": 311, "metadata": {}, "output_type": "execute_result" } @@ -3768,7 +3768,7 @@ }, { "cell_type": "code", - "execution_count": 136, + "execution_count": 312, "id": "f0db8c51-2792-4d49-9b1a-d98ce0d9ea28", "metadata": {}, "outputs": [ @@ -3921,7 +3921,7 @@ "4 8.5 False 0.0 NaN NaN " ] }, - "execution_count": 136, + "execution_count": 312, "metadata": {}, "output_type": "execute_result" } @@ -3936,7 +3936,7 @@ }, { "cell_type": "code", - "execution_count": 137, + "execution_count": 313, "id": "a383474f-7da9-422c-bb69-3f0cc0b7053f", "metadata": {}, "outputs": [ @@ -3966,7 +3966,7 @@ }, { "cell_type": "code", - "execution_count": 138, + "execution_count": 314, "id": "460749ac-aa26-4216-8667-518546f72f72", "metadata": {}, "outputs": [ @@ -4005,7 +4005,7 @@ }, { "cell_type": "code", - "execution_count": 139, + "execution_count": 315, "id": "3efce2b6-2d2f-4da9-98ed-1aae17da624c", "metadata": {}, "outputs": [], @@ -4015,7 +4015,7 @@ }, { "cell_type": "code", - "execution_count": 140, + "execution_count": 316, "id": "38aa39fd-58af-4fb8-98f2-4269dbaf35de", "metadata": {}, "outputs": [ @@ -4136,7 +4136,7 @@ "4 ff48df4b2dd5a14116bf4d280b31621e " ] }, - "execution_count": 140, + "execution_count": 316, "metadata": {}, "output_type": "execute_result" } @@ -4149,7 +4149,7 @@ }, { "cell_type": "code", - "execution_count": 141, + "execution_count": 317, "id": "99eb6d14-8b4b-4d55-8fc7-ddf2726096f4", "metadata": {}, "outputs": [ @@ -4256,7 +4256,7 @@ "4 NaN NaN " ] }, - "execution_count": 141, + "execution_count": 317, "metadata": {}, "output_type": "execute_result" } @@ -4268,7 +4268,7 @@ }, { "cell_type": "code", - "execution_count": 142, + "execution_count": 318, "id": "c5f39cc9-dff8-452c-9a3e-9f7df81a8a19", "metadata": {}, "outputs": [ @@ -4283,7 +4283,7 @@ "dtype: object" ] }, - "execution_count": 142, + "execution_count": 318, "metadata": {}, "output_type": "execute_result" } @@ -4326,7 +4326,7 @@ }, { "cell_type": "code", - "execution_count": 143, + "execution_count": 319, "id": "2d52d6da-cca5-4abd-be05-2f00fd3eca8e", "metadata": {}, "outputs": [], @@ -4336,7 +4336,7 @@ }, { "cell_type": "code", - "execution_count": 144, + "execution_count": 320, "id": "6cab507d-8b11-404d-9286-5cc205228af9", "metadata": {}, "outputs": [ @@ -4494,7 +4494,7 @@ "4 1 bfa22f5a2364a2dacfc45cca1c8d3215 " ] }, - "execution_count": 144, + "execution_count": 320, "metadata": {}, "output_type": "execute_result" } @@ -4507,7 +4507,7 @@ }, { "cell_type": "code", - "execution_count": 145, + "execution_count": 321, "id": "9fe57873-8108-44c9-b8a5-f58d3cbb6d17", "metadata": {}, "outputs": [ @@ -4658,7 +4658,7 @@ "4 jeff koons épisodes 4 False True " ] }, - "execution_count": 145, + "execution_count": 321, "metadata": {}, "output_type": "execute_result" } @@ -4670,7 +4670,7 @@ }, { "cell_type": "code", - "execution_count": 146, + "execution_count": 322, "id": "7fd9e5bd-baac-4b3b-9ffb-5a9baa18399b", "metadata": {}, "outputs": [ @@ -4690,7 +4690,7 @@ "dtype: object" ] }, - "execution_count": 146, + "execution_count": 322, "metadata": {}, "output_type": "execute_result" } @@ -4709,7 +4709,7 @@ }, { "cell_type": "code", - "execution_count": 147, + "execution_count": 323, "id": "90ab62d4-a086-4469-961c-67eefb375388", "metadata": {}, "outputs": [], @@ -4719,7 +4719,7 @@ }, { "cell_type": "code", - "execution_count": 148, + "execution_count": 324, "id": "58db1751-fd56-4c28-b49e-bc8235bb0dc8", "metadata": {}, "outputs": [ @@ -4834,7 +4834,7 @@ "4 d41d8cd98f00b204e9800998ecf8427e " ] }, - "execution_count": 148, + "execution_count": 324, "metadata": {}, "output_type": "execute_result" } @@ -4847,7 +4847,7 @@ }, { "cell_type": "code", - "execution_count": 149, + "execution_count": 325, "id": "ac93382c-0b5f-462d-8021-0dd1e7201b8c", "metadata": {}, "outputs": [ @@ -4940,7 +4940,7 @@ "4 2723 36 d41d8cd98f00b204e9800998ecf8427e NaN" ] }, - "execution_count": 149, + "execution_count": 325, "metadata": {}, "output_type": "execute_result" } @@ -4952,7 +4952,7 @@ }, { "cell_type": "code", - "execution_count": 150, + "execution_count": 326, "id": "18cbd630-3c7d-49e1-932b-9460badf3758", "metadata": {}, "outputs": [ @@ -4966,7 +4966,7 @@ "dtype: object" ] }, - "execution_count": 150, + "execution_count": 326, "metadata": {}, "output_type": "execute_result" } @@ -4985,7 +4985,7 @@ }, { "cell_type": "code", - "execution_count": 151, + "execution_count": 327, "id": "ae544dcc-f23d-4216-bb5b-597cc1b3765e", "metadata": {}, "outputs": [], @@ -4995,7 +4995,7 @@ }, { "cell_type": "code", - "execution_count": 152, + "execution_count": 328, "id": "1ac97963-9208-4329-be41-d71a5797487f", "metadata": {}, "outputs": [ @@ -5110,7 +5110,7 @@ "4 8d8818c8e140c64c743113f563cf750f " ] }, - "execution_count": 152, + "execution_count": 328, "metadata": {}, "output_type": "execute_result" } @@ -5123,7 +5123,7 @@ }, { "cell_type": "code", - "execution_count": 153, + "execution_count": 329, "id": "b4593d46-105c-47dd-aa71-babd8e63e65b", "metadata": {}, "outputs": [ @@ -5216,7 +5216,7 @@ "4 4 8d8818c8e140c64c743113f563cf750f 2017 NaN" ] }, - "execution_count": 153, + "execution_count": 329, "metadata": {}, "output_type": "execute_result" } @@ -5228,7 +5228,7 @@ }, { "cell_type": "code", - "execution_count": 154, + "execution_count": 330, "id": "5d3b096d-8e73-4514-94e5-f2dcd4d0a89c", "metadata": {}, "outputs": [ @@ -5242,7 +5242,7 @@ "dtype: object" ] }, - "execution_count": 154, + "execution_count": 330, "metadata": {}, "output_type": "execute_result" } @@ -5261,7 +5261,7 @@ }, { "cell_type": "code", - "execution_count": 155, + "execution_count": 331, "id": "d95ef015-d44c-4353-8761-771b910d21c9", "metadata": {}, "outputs": [], @@ -5271,7 +5271,7 @@ }, { "cell_type": "code", - "execution_count": 156, + "execution_count": 332, "id": "ef5fe794-8df7-4f27-8554-ecdc4074ac0b", "metadata": {}, "outputs": [ @@ -5353,7 +5353,7 @@ "1 702bd76fe3dd5dbcf118a6965a946f54 " ] }, - "execution_count": 156, + "execution_count": 332, "metadata": {}, "output_type": "execute_result" } @@ -5366,7 +5366,7 @@ }, { "cell_type": "code", - "execution_count": 157, + "execution_count": 333, "id": "e3621201-fab9-49fd-95c1-0b9d5da76e50", "metadata": {}, "outputs": [ @@ -5439,7 +5439,7 @@ "1 1 1 702bd76fe3dd5dbcf118a6965a946f54 mucem NaN" ] }, - "execution_count": 157, + "execution_count": 333, "metadata": {}, "output_type": "execute_result" } @@ -5451,7 +5451,7 @@ }, { "cell_type": "code", - "execution_count": 158, + "execution_count": 334, "id": "1b198b92-8654-4531-a0dd-8f2e01c2e6c1", "metadata": {}, "outputs": [ @@ -5466,7 +5466,7 @@ "dtype: object" ] }, - "execution_count": 158, + "execution_count": 334, "metadata": {}, "output_type": "execute_result" } @@ -5485,7 +5485,7 @@ }, { "cell_type": "code", - "execution_count": 159, + "execution_count": 335, "id": "43576244-c8cf-4ca0-b056-7aea1fbf0bc7", "metadata": {}, "outputs": [], @@ -5500,7 +5500,7 @@ }, { "cell_type": "code", - "execution_count": 160, + "execution_count": 336, "id": "0fad097e-474c-4af7-b1e1-7d8dda3f09ea", "metadata": {}, "outputs": [], @@ -5526,7 +5526,7 @@ }, { "cell_type": "code", - "execution_count": 161, + "execution_count": 337, "id": "6213b1eb-c5f8-49dd-ab69-366542380e80", "metadata": {}, "outputs": [], @@ -5563,7 +5563,7 @@ }, { "cell_type": "code", - "execution_count": 162, + "execution_count": 338, "id": "b853e020-f73d-44e8-b086-e5548ce21011", "metadata": {}, "outputs": [ @@ -5716,7 +5716,7 @@ "4 indiv entrées tp " ] }, - "execution_count": 162, + "execution_count": 338, "metadata": {}, "output_type": "execute_result" } @@ -5736,7 +5736,7 @@ }, { "cell_type": "code", - "execution_count": 163, + "execution_count": 339, "id": "6ed0ad20-8315-4112-9a85-10e5f04ef852", "metadata": {}, "outputs": [], @@ -5779,7 +5779,7 @@ }, { "cell_type": "code", - "execution_count": 164, + "execution_count": 340, "id": "98ef0636-8c45-4a23-a62a-1fbe1544f8ce", "metadata": {}, "outputs": [ @@ -5949,7 +5949,7 @@ "4 spectacle vivant mucem " ] }, - "execution_count": 164, + "execution_count": 340, "metadata": {}, "output_type": "execute_result" } @@ -5969,7 +5969,7 @@ }, { "cell_type": "code", - "execution_count": 165, + "execution_count": 341, "id": "481dddd6-80a8-4b9e-a05e-ed06fa3ed7a6", "metadata": {}, "outputs": [], @@ -5994,7 +5994,7 @@ }, { "cell_type": "code", - "execution_count": 166, + "execution_count": 342, "id": "677f4ed8-ef58-45f2-9056-ede0898c6a64", "metadata": {}, "outputs": [ @@ -6093,7 +6093,7 @@ "4 37 383 269 1" ] }, - "execution_count": 166, + "execution_count": 342, "metadata": {}, "output_type": "execute_result" } @@ -6113,7 +6113,7 @@ }, { "cell_type": "code", - "execution_count": 167, + "execution_count": 343, "id": "c52621e7-01de-48dc-b572-2974542a8be5", "metadata": {}, "outputs": [ @@ -6169,7 +6169,7 @@ "0 1 NaN 0" ] }, - "execution_count": 167, + "execution_count": 343, "metadata": {}, "output_type": "execute_result" } @@ -6181,7 +6181,7 @@ }, { "cell_type": "code", - "execution_count": 168, + "execution_count": 344, "id": "9e4f60ab-9a2c-4090-b0c4-f9a1530b2d39", "metadata": {}, "outputs": [ @@ -6265,7 +6265,7 @@ "4 1496 billet nb famille mecene 1a NaN" ] }, - "execution_count": 168, + "execution_count": 344, "metadata": {}, "output_type": "execute_result" } @@ -6277,7 +6277,7 @@ }, { "cell_type": "code", - "execution_count": 169, + "execution_count": 345, "id": "247b5c45-a18a-4cfd-86b4-d3453e157bcd", "metadata": {}, "outputs": [ @@ -6361,7 +6361,7 @@ "4 5 1 7" ] }, - "execution_count": 169, + "execution_count": 345, "metadata": {}, "output_type": "execute_result" } @@ -6373,7 +6373,7 @@ }, { "cell_type": "code", - "execution_count": 170, + "execution_count": 346, "id": "4b48f7b3-0f06-4ef6-9355-5016af82f49c", "metadata": {}, "outputs": [ @@ -6490,7 +6490,7 @@ "4 0.0 0.0 " ] }, - "execution_count": 170, + "execution_count": 346, "metadata": {}, "output_type": "execute_result" } @@ -6510,7 +6510,7 @@ }, { "cell_type": "code", - "execution_count": 171, + "execution_count": 347, "id": "b26f4e7e-134d-4e32-a615-4b0e6bb80b25", "metadata": {}, "outputs": [ @@ -6542,7 +6542,7 @@ }, { "cell_type": "code", - "execution_count": 172, + "execution_count": 348, "id": "d40b1e3b-b1f3-4915-8ebc-6bb7856da42a", "metadata": {}, "outputs": [ @@ -6684,7 +6684,7 @@ "4 indiv entrées tp 8 21 " ] }, - "execution_count": 172, + "execution_count": 348, "metadata": {}, "output_type": "execute_result" } @@ -6699,7 +6699,7 @@ }, { "cell_type": "code", - "execution_count": 173, + "execution_count": 349, "id": "78d75a08-e959-429c-847a-7d70a2804806", "metadata": {}, "outputs": [ @@ -6919,7 +6919,7 @@ "[5 rows x 22 columns]" ] }, - "execution_count": 173, + "execution_count": 349, "metadata": {}, "output_type": "execute_result" } @@ -6933,7 +6933,7 @@ }, { "cell_type": "code", - "execution_count": 174, + "execution_count": 350, "id": "4a6950e8-4818-4df2-afa9-562e0921698c", "metadata": {}, "outputs": [ @@ -6949,7 +6949,7 @@ " dtype='object')" ] }, - "execution_count": 174, + "execution_count": 350, "metadata": {}, "output_type": "execute_result" } @@ -6960,7 +6960,7 @@ }, { "cell_type": "code", - "execution_count": 175, + "execution_count": 351, "id": "b18f6428-90e0-4b1b-9b8d-bad995fb6c98", "metadata": {}, "outputs": [ @@ -6970,7 +6970,7 @@ "(94803, 22)" ] }, - "execution_count": 175, + "execution_count": 351, "metadata": {}, "output_type": "execute_result" } @@ -6989,7 +6989,7 @@ }, { "cell_type": "code", - "execution_count": 176, + "execution_count": 352, "id": "33ee07a2-d871-4436-9860-9be389bc4902", "metadata": {}, "outputs": [ @@ -7021,7 +7021,7 @@ "dtype: int64" ] }, - "execution_count": 176, + "execution_count": 352, "metadata": {}, "output_type": "execute_result" } @@ -7032,7 +7032,7 @@ }, { "cell_type": "code", - "execution_count": 177, + "execution_count": 353, "id": "557fc475-4417-4d9f-8d4e-8c49bc42367f", "metadata": {}, "outputs": [ @@ -7043,7 +7043,7 @@ " 'offre muséale groupe', 'formule adhésion'], dtype=object)" ] }, - "execution_count": 177, + "execution_count": 353, "metadata": {}, "output_type": "execute_result" } @@ -7056,7 +7056,7 @@ }, { "cell_type": "code", - "execution_count": 178, + "execution_count": 354, "id": "a9b9a23c-b0de-4685-97e5-d52dd78349f5", "metadata": {}, "outputs": [ @@ -7066,7 +7066,7 @@ "644" ] }, - "execution_count": 178, + "execution_count": 354, "metadata": {}, "output_type": "execute_result" } @@ -7079,7 +7079,7 @@ }, { "cell_type": "code", - "execution_count": 179, + "execution_count": 355, "id": "fb374c72-58ca-404d-a86b-e834a2fc4a34", "metadata": {}, "outputs": [ @@ -7099,7 +7099,7 @@ " 'groupe forfait etudiant'], dtype=object)" ] }, - "execution_count": 179, + "execution_count": 355, "metadata": {}, "output_type": "execute_result" } @@ -7111,7 +7111,7 @@ }, { "cell_type": "code", - "execution_count": 180, + "execution_count": 356, "id": "11f89771-8d50-4ef4-b34e-53e4f6b419bb", "metadata": {}, "outputs": [ @@ -7121,7 +7121,7 @@ "27" ] }, - "execution_count": 180, + "execution_count": 356, "metadata": {}, "output_type": "execute_result" } @@ -7132,7 +7132,7 @@ }, { "cell_type": "code", - "execution_count": 181, + "execution_count": 357, "id": "8add1ff2-b7e8-4381-90d8-d18d8660ed39", "metadata": {}, "outputs": [], @@ -7169,7 +7169,7 @@ }, { "cell_type": "code", - "execution_count": 182, + "execution_count": 358, "id": "1fd9dcb0-164a-4fd0-90c3-2fd9e7b44016", "metadata": {}, "outputs": [ @@ -7395,7 +7395,7 @@ "[5 rows x 40 columns]" ] }, - "execution_count": 182, + "execution_count": 358, "metadata": {}, "output_type": "execute_result" } @@ -7407,7 +7407,7 @@ }, { "cell_type": "code", - "execution_count": 183, + "execution_count": 359, "id": "e4a5f890-d5aa-40d7-a70c-8d8a254a5c9a", "metadata": {}, "outputs": [ @@ -7457,7 +7457,7 @@ "dtype: int64" ] }, - "execution_count": 183, + "execution_count": 359, "metadata": {}, "output_type": "execute_result" } @@ -7476,7 +7476,7 @@ }, { "cell_type": "code", - "execution_count": 211, + "execution_count": 360, "id": "de370d66-852e-46a1-8fb4-5c1e5756f5cd", "metadata": {}, "outputs": [], @@ -7486,7 +7486,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 361, "id": "088a1f50-cf5d-4d1a-891d-4e9df7e1c35b", "metadata": {}, "outputs": [ @@ -7513,7 +7513,7 @@ " \n", " customer_id\n", " birthdate\n", - " street_id_x\n", + " street_id\n", " is_partner\n", " gender\n", " is_email_true\n", @@ -7522,16 +7522,16 @@ " profession\n", " language\n", " ...\n", - " season_id\n", - " facility_id\n", + " first_buying_date\n", + " country\n", + " age\n", + " tenant_id\n", + " nb_campaigns\n", + " nb_campaigns_opened\n", + " time_to_open\n", " event_type_id\n", - " event_type_key_id\n", - " facility_key_id\n", - " street_id_y\n", - " amount\n", - " is_full_price\n", - " name_event_types\n", - " name_facilities\n", + " nb_tickets\n", + " avg_amount\n", " \n", " \n", " \n", @@ -7549,9 +7549,9 @@ " NaN\n", " ...\n", " NaN\n", + " fr\n", " NaN\n", - " NaN\n", - " NaN\n", + " 1311\n", " NaN\n", " NaN\n", " NaN\n", @@ -7573,9 +7573,9 @@ " NaN\n", " ...\n", " NaN\n", + " fr\n", " NaN\n", - " NaN\n", - " NaN\n", + " 1311\n", " NaN\n", " NaN\n", " NaN\n", @@ -7597,9 +7597,9 @@ " NaN\n", " ...\n", " NaN\n", + " fr\n", " NaN\n", - " NaN\n", - " NaN\n", + " 1311\n", " NaN\n", " NaN\n", " NaN\n", @@ -7621,9 +7621,9 @@ " NaN\n", " ...\n", " NaN\n", + " fr\n", " NaN\n", - " NaN\n", - " NaN\n", + " 1311\n", " NaN\n", " NaN\n", " NaN\n", @@ -7647,52 +7647,52 @@ " NaN\n", " NaN\n", " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", + " 1311\n", + " 80.0\n", + " 2.0\n", + " 0 days 19:53:02.500000\n", " NaN\n", " NaN\n", " NaN\n", " \n", " \n", "\n", - "

5 rows × 52 columns

\n", + "

5 rows × 31 columns

\n", "" ], "text/plain": [ - " customer_id birthdate street_id_x is_partner gender is_email_true \\\n", - "0 12751 NaN 2 False 1 True \n", - "1 12825 NaN 2 False 2 True \n", - "2 11261 NaN 2 False 1 True \n", - "3 13071 NaN 2 False 2 True \n", - "4 653061 NaN 10 False 2 True \n", + " customer_id birthdate street_id is_partner gender is_email_true \\\n", + "0 12751 NaN 2 False 1 True \n", + "1 12825 NaN 2 False 2 True \n", + "2 11261 NaN 2 False 1 True \n", + "3 13071 NaN 2 False 2 True \n", + "4 653061 NaN 10 False 2 True \n", "\n", - " opt_in structure_id profession language ... season_id facility_id \\\n", - "0 True NaN NaN NaN ... NaN NaN \n", - "1 True NaN NaN NaN ... NaN NaN \n", - "2 True NaN NaN NaN ... NaN NaN \n", - "3 True NaN NaN NaN ... NaN NaN \n", - "4 False NaN NaN NaN ... NaN NaN \n", + " opt_in structure_id profession language ... first_buying_date country \\\n", + "0 True NaN NaN NaN ... NaN fr \n", + "1 True NaN NaN NaN ... NaN fr \n", + "2 True NaN NaN NaN ... NaN fr \n", + "3 True NaN NaN NaN ... NaN fr \n", + "4 False NaN NaN NaN ... NaN NaN \n", "\n", - " event_type_id event_type_key_id facility_key_id street_id_y amount \\\n", - "0 NaN NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN NaN \n", - "2 NaN NaN NaN NaN NaN \n", - "3 NaN NaN NaN NaN NaN \n", - "4 NaN NaN NaN NaN NaN \n", + " age tenant_id nb_campaigns nb_campaigns_opened time_to_open \\\n", + "0 NaN 1311 NaN NaN NaN \n", + "1 NaN 1311 NaN NaN NaN \n", + "2 NaN 1311 NaN NaN NaN \n", + "3 NaN 1311 NaN NaN NaN \n", + "4 NaN 1311 80.0 2.0 0 days 19:53:02.500000 \n", "\n", - " is_full_price name_event_types name_facilities \n", - "0 NaN NaN NaN \n", - "1 NaN NaN NaN \n", - "2 NaN NaN NaN \n", - "3 NaN NaN NaN \n", - "4 NaN NaN NaN \n", + " event_type_id nb_tickets avg_amount \n", + "0 NaN NaN NaN \n", + "1 NaN NaN NaN \n", + "2 NaN NaN NaN \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", "\n", - "[5 rows x 52 columns]" + "[5 rows x 31 columns]" ] }, - "execution_count": 8, + "execution_count": 361, "metadata": {}, "output_type": "execute_result" } @@ -7704,7 +7704,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 362, "id": "bdd582af-0cf1-4e04-90ad-7165b8a36ac8", "metadata": {}, "outputs": [ @@ -7712,21 +7712,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "(206713, 52)\n", - "Index(['customer_id', 'birthdate', 'street_id_x', 'is_partner', 'gender',\n", + "(156289, 31)\n", + "Index(['customer_id', 'birthdate', 'street_id', 'is_partner', 'gender',\n", " 'is_email_true', 'opt_in', 'structure_id', 'profession', 'language',\n", " 'mcp_contact_id', 'last_buying_date', 'max_price', 'ticket_sum',\n", " 'average_price', 'fidelity', 'average_purchase_delay',\n", " 'average_price_basket', 'average_ticket_basket', 'total_price',\n", " 'purchase_count', 'first_buying_date', 'country', 'age', 'tenant_id',\n", - " 'nb_campaigns', 'nb_campaigns_opened', 'time_to_open', 'product_id',\n", - " 'nb_tickets', 'nb_suppliers', 'purchase_date_max', 'purchase_date_min',\n", - " 'time_between_purchase', 'id_products', 'representation_id',\n", - " 'pricing_formula_id', 'category_id', 'products_group_id',\n", - " 'product_pack_id', 'event_id', 'id_representation_cap', 'season_id',\n", - " 'facility_id', 'event_type_id', 'event_type_key_id', 'facility_key_id',\n", - " 'street_id_y', 'amount', 'is_full_price', 'name_event_types',\n", - " 'name_facilities'],\n", + " 'nb_campaigns', 'nb_campaigns_opened', 'time_to_open', 'event_type_id',\n", + " 'nb_tickets', 'avg_amount'],\n", " dtype='object')\n" ] } @@ -7740,7 +7734,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 363, "id": "55fa2361-ebde-4472-b8d2-521a20be766d", "metadata": {}, "outputs": [ @@ -7748,61 +7742,40 @@ "data": { "text/plain": [ "customer_id 0\n", - "birthdate 195073\n", - "street_id_x 0\n", + "birthdate 149375\n", + "street_id 0\n", "is_partner 0\n", "gender 0\n", "is_email_true 0\n", "opt_in 0\n", - "structure_id 171660\n", - "profession 199762\n", - "language 205574\n", - "mcp_contact_id 81495\n", - "last_buying_date 78450\n", - "max_price 78450\n", + "structure_id 136867\n", + "profession 150004\n", + "language 155184\n", + "mcp_contact_id 53519\n", + "last_buying_date 78445\n", + "max_price 78445\n", "ticket_sum 0\n", - "average_price 13122\n", + "average_price 13120\n", "fidelity 0\n", - "average_purchase_delay 78450\n", - "average_price_basket 78450\n", - "average_ticket_basket 78450\n", - "total_price 65328\n", + "average_purchase_delay 78445\n", + "average_price_basket 78445\n", + "average_ticket_basket 78445\n", + "total_price 65325\n", "purchase_count 0\n", - "first_buying_date 78450\n", - "country 8490\n", - "age 195073\n", + "first_buying_date 78445\n", + "country 8304\n", + "age 149375\n", "tenant_id 0\n", - "nb_campaigns 46315\n", - "nb_campaigns_opened 46315\n", - "time_to_open 100811\n", - "product_id 78355\n", - "nb_tickets 78355\n", - "nb_suppliers 78355\n", - "purchase_date_max 78355\n", - "purchase_date_min 78355\n", - "time_between_purchase 78355\n", - "id_products 78355\n", - "representation_id 78355\n", - "pricing_formula_id 78355\n", - "category_id 78355\n", - "products_group_id 78355\n", - "product_pack_id 78355\n", - "event_id 78355\n", - "id_representation_cap 78355\n", - "season_id 78355\n", - "facility_id 78355\n", + "nb_campaigns 21623\n", + "nb_campaigns_opened 21623\n", + "time_to_open 69017\n", "event_type_id 78355\n", - "event_type_key_id 78355\n", - "facility_key_id 78355\n", - "street_id_y 78355\n", - "amount 78355\n", - "is_full_price 78355\n", - "name_event_types 78355\n", - "name_facilities 78355\n", + "nb_tickets 78355\n", + "avg_amount 78355\n", "dtype: int64" ] }, - "execution_count": 10, + "execution_count": 363, "metadata": {}, "output_type": "execute_result" } @@ -7815,8 +7788,8 @@ }, { "cell_type": "code", - "execution_count": 234, - "id": "76fbd8d5-443c-43b7-976d-b0028cd90d5e", + "execution_count": 364, + "id": "2e228eb6-8cc7-4fd7-8e17-2b818095cb96", "metadata": {}, "outputs": [ { @@ -7847,13 +7820,11 @@ " nb_campaigns\n", " nb_campaigns_opened\n", " fidelity\n", - " product_id\n", " nb_tickets\n", " ticket_sum\n", " average_price\n", - " amount\n", + " avg_amount\n", " event_type_id\n", - " name_event_types\n", " \n", " \n", " \n", @@ -7867,12 +7838,10 @@ " NaN\n", " 0\n", " NaN\n", - " NaN\n", " 0\n", " 0.0\n", " NaN\n", " NaN\n", - " NaN\n", " \n", " \n", " 1\n", @@ -7884,12 +7853,10 @@ " NaN\n", " 0\n", " NaN\n", - " NaN\n", " 0\n", " 0.0\n", " NaN\n", " NaN\n", - " NaN\n", " \n", " \n", " 2\n", @@ -7901,12 +7868,10 @@ " NaN\n", " 0\n", " NaN\n", - " NaN\n", " 0\n", " 0.0\n", " NaN\n", " NaN\n", - " NaN\n", " \n", " \n", " 3\n", @@ -7918,12 +7883,10 @@ " NaN\n", " 0\n", " NaN\n", - " NaN\n", " 0\n", " 0.0\n", " NaN\n", " NaN\n", - " NaN\n", " \n", " \n", " 4\n", @@ -7935,12 +7898,10 @@ " 2.0\n", " 0\n", " NaN\n", - " NaN\n", " 0\n", " 0.0\n", " NaN\n", " NaN\n", - " NaN\n", " \n", " \n", "\n", @@ -7954,22 +7915,22 @@ "3 13071 2 False True NaN \n", "4 653061 2 False True 80.0 \n", "\n", - " nb_campaigns_opened fidelity product_id nb_tickets ticket_sum \\\n", - "0 NaN 0 NaN NaN 0 \n", - "1 NaN 0 NaN NaN 0 \n", - "2 NaN 0 NaN NaN 0 \n", - "3 NaN 0 NaN NaN 0 \n", - "4 2.0 0 NaN NaN 0 \n", + " nb_campaigns_opened fidelity nb_tickets ticket_sum average_price \\\n", + "0 NaN 0 NaN 0 0.0 \n", + "1 NaN 0 NaN 0 0.0 \n", + "2 NaN 0 NaN 0 0.0 \n", + "3 NaN 0 NaN 0 0.0 \n", + "4 2.0 0 NaN 0 0.0 \n", "\n", - " average_price amount event_type_id name_event_types \n", - "0 0.0 NaN NaN NaN \n", - "1 0.0 NaN NaN NaN \n", - "2 0.0 NaN NaN NaN \n", - "3 0.0 NaN NaN NaN \n", - "4 0.0 NaN NaN NaN " + " avg_amount event_type_id \n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN " ] }, - "execution_count": 234, + "execution_count": 364, "metadata": {}, "output_type": "execute_result" } @@ -7977,14 +7938,14 @@ "source": [ "## Investigate a subset of variables\n", "\n", - "df = customer_product[[\"customer_id\", \"gender\", \"is_partner\", \"is_email_true\",\"nb_campaigns\", \"nb_campaigns_opened\", \"fidelity\", \"product_id\",\n", - " \"nb_tickets\", \"ticket_sum\", \"average_price\", \"amount\", \"event_type_id\", \"name_event_types\"]]\n", + "df = customer_product[[\"customer_id\", \"gender\", \"is_partner\", \"is_email_true\",\"nb_campaigns\", \"nb_campaigns_opened\", \"fidelity\",\n", + " \"nb_tickets\", \"ticket_sum\", \"average_price\", \"avg_amount\", \"event_type_id\"]]\n", "df.head()" ] }, { "cell_type": "code", - "execution_count": 235, + "execution_count": 368, "id": "80120f51-f91e-4d4d-9578-1dc88cd94754", "metadata": {}, "outputs": [ @@ -7992,42 +7953,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "shape : (206713, 14)\n", + "shape : (156289, 12)\n", "Nombre de customer unique : 151866\n", - "Nombre de ligne où produit est non nul : 128358\n" + "Nombre de ligne où nb_tickets est non nul : 77934\n" ] } ], "source": [ "print(\"shape : \", df.shape)\n", "print(\"Nombre de customer unique : \", len(df[\"customer_id\"].unique()))\n", - "print(\"Nombre de ligne où produit est non nul : \", df[\"product_id\"].count())" + "print(\"Nombre de ligne où nb_tickets est non nul : \", df[\"nb_tickets\"].count())" ] }, { "cell_type": "code", - "execution_count": 236, - "id": "ae277ede-cc97-4303-a2d4-3381ccb98a5c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "78355" - ] - }, - "execution_count": 236, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "206713-128358" - ] - }, - { - "cell_type": "code", - "execution_count": 237, + "execution_count": 370, "id": "0d56bfa9-c93c-42ee-bec2-96f0598fce2c", "metadata": {}, "outputs": [ @@ -8036,8 +7976,7 @@ "output_type": "stream", "text": [ "Nombre de consommateur unique : 73511\n", - "Nombre de type d'évènement : 4\n", - "Nombre de type d'évènement (nom) : 4\n" + "Nombre de type d'évènement : 4\n" ] }, { @@ -8068,13 +8007,11 @@ " nb_campaigns\n", " nb_campaigns_opened\n", " fidelity\n", - " product_id\n", " nb_tickets\n", " ticket_sum\n", " average_price\n", - " amount\n", + " avg_amount\n", " event_type_id\n", - " name_event_types\n", " \n", " \n", " \n", @@ -8087,13 +8024,11 @@ " 2.0\n", " 2.0\n", " 0\n", - " 264371.0\n", " 2.0\n", " 0\n", - " 0.0\n", - " 11.0\n", + " 0.000000\n", + " 7.762474\n", " 4.0\n", - " spectacle vivant\n", " \n", " \n", " 195\n", @@ -8104,50 +8039,14 @@ " 133.0\n", " 19.0\n", " 0\n", - " 222125.0\n", - " 1.0\n", + " 5.0\n", " 5\n", - " 2.8\n", - " 6.0\n", + " 2.800000\n", + " 7.762474\n", " 4.0\n", - " spectacle vivant\n", - " \n", - " \n", - " 196\n", - " 7772\n", - " 0\n", - " False\n", - " True\n", - " 133.0\n", - " 19.0\n", - " 0\n", - " 222126.0\n", - " 2.0\n", - " 5\n", - " 2.8\n", - " 4.0\n", - " 4.0\n", - " spectacle vivant\n", " \n", " \n", " 197\n", - " 7772\n", - " 0\n", - " False\n", - " True\n", - " 133.0\n", - " 19.0\n", - " 0\n", - " 222571.0\n", - " 2.0\n", - " 5\n", - " 2.8\n", - " 0.0\n", - " 4.0\n", - " spectacle vivant\n", - " \n", - " \n", - " 199\n", " 280009\n", " 0\n", " False\n", @@ -8155,13 +8054,41 @@ " 116.0\n", " 32.0\n", " 1\n", - " 266306.0\n", " 1.0\n", " 1\n", - " 11.0\n", - " 11.0\n", + " 11.000000\n", + " 7.762474\n", " 4.0\n", - " spectacle vivant\n", + " \n", + " \n", + " 199\n", + " 1556\n", + " 0\n", + " False\n", + " True\n", + " 9.0\n", + " 8.0\n", + " 1\n", + " 2.0\n", + " 3\n", + " 23.333333\n", + " 6.150659\n", + " 2.0\n", + " \n", + " \n", + " 200\n", + " 1556\n", + " 0\n", + " False\n", + " True\n", + " 9.0\n", + " 8.0\n", + " 1\n", + " 1.0\n", + " 3\n", + " 23.333333\n", + " 6.439463\n", + " 6.0\n", " \n", " \n", " ...\n", @@ -8177,11 +8104,39 @@ " ...\n", " ...\n", " ...\n", - " ...\n", - " ...\n", " \n", " \n", - " 206703\n", + " 156245\n", + " 293753\n", + " 2\n", + " False\n", + " True\n", + " 94.0\n", + " 34.0\n", + " 1\n", + " 1.0\n", + " 1\n", + " 11.000000\n", + " 7.762474\n", + " 4.0\n", + " \n", + " \n", + " 156246\n", + " 293798\n", + " 2\n", + " False\n", + " True\n", + " 7.0\n", + " 0.0\n", + " 2\n", + " 2.0\n", + " 2\n", + " 12.000000\n", + " 7.762474\n", + " 4.0\n", + " \n", + " \n", + " 156281\n", " 295224\n", " 2\n", " False\n", @@ -8189,50 +8144,14 @@ " 10.0\n", " 0.0\n", " 1\n", - " 340286.0\n", - " 3.0\n", + " 98.0\n", " 98\n", - " 0.0\n", - " 0.0\n", + " 0.000000\n", + " 6.150659\n", " 2.0\n", - " offre muséale individuel\n", " \n", " \n", - " 206704\n", - " 295224\n", - " 2\n", - " False\n", - " True\n", - " 10.0\n", - " 0.0\n", - " 1\n", - " 340287.0\n", - " 62.0\n", - " 98\n", - " 0.0\n", - " 0.0\n", - " 2.0\n", - " offre muséale individuel\n", - " \n", - " \n", - " 206705\n", - " 295224\n", - " 2\n", - " False\n", - " True\n", - " 10.0\n", - " 0.0\n", - " 1\n", - " 340288.0\n", - " 33.0\n", - " 98\n", - " 0.0\n", - " 0.0\n", - " 2.0\n", - " offre muséale individuel\n", - " \n", - " \n", - " 206711\n", + " 156287\n", " 295366\n", " 2\n", " False\n", @@ -8240,16 +8159,14 @@ " 5.0\n", " 0.0\n", " 1\n", - " 216060.0\n", " 3.0\n", " 3\n", - " 11.0\n", - " 11.0\n", + " 11.000000\n", + " 7.762474\n", " 4.0\n", - " spectacle vivant\n", " \n", " \n", - " 206712\n", + " 156288\n", " 295368\n", " 2\n", " False\n", @@ -8257,63 +8174,61 @@ " 5.0\n", " 0.0\n", " 1\n", - " 264331.0\n", " 2.0\n", " 2\n", - " 11.0\n", - " 11.0\n", + " 11.000000\n", + " 7.762474\n", " 4.0\n", - " spectacle vivant\n", " \n", " \n", "\n", - "

128358 rows × 14 columns

\n", + "

77934 rows × 12 columns

\n", "" ], "text/plain": [ " customer_id gender is_partner is_email_true nb_campaigns \\\n", "162 309255 2 False True 2.0 \n", "195 7772 0 False True 133.0 \n", - "196 7772 0 False True 133.0 \n", - "197 7772 0 False True 133.0 \n", - "199 280009 0 False True 116.0 \n", + "197 280009 0 False True 116.0 \n", + "199 1556 0 False True 9.0 \n", + "200 1556 0 False True 9.0 \n", "... ... ... ... ... ... \n", - "206703 295224 2 False True 10.0 \n", - "206704 295224 2 False True 10.0 \n", - "206705 295224 2 False True 10.0 \n", - "206711 295366 2 False True 5.0 \n", - "206712 295368 2 False True 5.0 \n", + "156245 293753 2 False True 94.0 \n", + "156246 293798 2 False True 7.0 \n", + "156281 295224 2 False True 10.0 \n", + "156287 295366 2 False True 5.0 \n", + "156288 295368 2 False True 5.0 \n", "\n", - " nb_campaigns_opened fidelity product_id nb_tickets ticket_sum \\\n", - "162 2.0 0 264371.0 2.0 0 \n", - "195 19.0 0 222125.0 1.0 5 \n", - "196 19.0 0 222126.0 2.0 5 \n", - "197 19.0 0 222571.0 2.0 5 \n", - "199 32.0 1 266306.0 1.0 1 \n", - "... ... ... ... ... ... \n", - "206703 0.0 1 340286.0 3.0 98 \n", - "206704 0.0 1 340287.0 62.0 98 \n", - "206705 0.0 1 340288.0 33.0 98 \n", - "206711 0.0 1 216060.0 3.0 3 \n", - "206712 0.0 1 264331.0 2.0 2 \n", + " nb_campaigns_opened fidelity nb_tickets ticket_sum average_price \\\n", + "162 2.0 0 2.0 0 0.000000 \n", + "195 19.0 0 5.0 5 2.800000 \n", + "197 32.0 1 1.0 1 11.000000 \n", + "199 8.0 1 2.0 3 23.333333 \n", + "200 8.0 1 1.0 3 23.333333 \n", + "... ... ... ... ... ... \n", + "156245 34.0 1 1.0 1 11.000000 \n", + "156246 0.0 2 2.0 2 12.000000 \n", + "156281 0.0 1 98.0 98 0.000000 \n", + "156287 0.0 1 3.0 3 11.000000 \n", + "156288 0.0 1 2.0 2 11.000000 \n", "\n", - " average_price amount event_type_id name_event_types \n", - "162 0.0 11.0 4.0 spectacle vivant \n", - "195 2.8 6.0 4.0 spectacle vivant \n", - "196 2.8 4.0 4.0 spectacle vivant \n", - "197 2.8 0.0 4.0 spectacle vivant \n", - "199 11.0 11.0 4.0 spectacle vivant \n", - "... ... ... ... ... \n", - "206703 0.0 0.0 2.0 offre muséale individuel \n", - "206704 0.0 0.0 2.0 offre muséale individuel \n", - "206705 0.0 0.0 2.0 offre muséale individuel \n", - "206711 11.0 11.0 4.0 spectacle vivant \n", - "206712 11.0 11.0 4.0 spectacle vivant \n", + " avg_amount event_type_id \n", + "162 7.762474 4.0 \n", + "195 7.762474 4.0 \n", + "197 7.762474 4.0 \n", + "199 6.150659 2.0 \n", + "200 6.439463 6.0 \n", + "... ... ... \n", + "156245 7.762474 4.0 \n", + "156246 7.762474 4.0 \n", + "156281 6.150659 2.0 \n", + "156287 7.762474 4.0 \n", + "156288 7.762474 4.0 \n", "\n", - "[128358 rows x 14 columns]" + "[77934 rows x 12 columns]" ] }, - "execution_count": 237, + "execution_count": 370, "metadata": {}, "output_type": "execute_result" } @@ -8321,28 +8236,32 @@ "source": [ "# Filter only customer that buy tickets\n", "\n", - "df_purchase = df.dropna(subset= [\"product_id\"])\n", + "df_purchase = df.dropna(subset= [\"nb_tickets\"])\n", "print(\"Nombre de consommateur unique : \", len(df_purchase[\"customer_id\"].unique()))\n", "print(\"Nombre de type d'évènement : \", len(df_purchase[\"event_type_id\"].unique()))\n", - "print(\"Nombre de type d'évènement (nom) : \", len(df_purchase[\"name_event_types\"].unique()))\n", + "#print(\"Nombre de type d'évènement (nom) : \", len(df_purchase[\"name_event_types\"].unique()))\n", "df_purchase" ] }, { "cell_type": "code", - "execution_count": 239, + "execution_count": 371, "id": "0cc96c4e-f3f3-43d2-94b5-a11719f09607", "metadata": {}, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "ename": "KeyError", + "evalue": "'name_event_types'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[371], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m event_counts \u001b[38;5;241m=\u001b[39m \u001b[43mdf_purchase\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroupby\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mname_event_types\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcustomer_id\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mnunique()\n\u001b[1;32m 3\u001b[0m event_counts\u001b[38;5;241m.\u001b[39mplot(kind\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbar\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 4\u001b[0m plt\u001b[38;5;241m.\u001b[39mxlabel(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mType d\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mévènement\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m/opt/mamba/lib/python3.10/site-packages/pandas/core/frame.py:8869\u001b[0m, in \u001b[0;36mDataFrame.groupby\u001b[0;34m(self, by, axis, level, as_index, sort, group_keys, observed, dropna)\u001b[0m\n\u001b[1;32m 8866\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m by \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 8867\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou have to supply one of \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mby\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m and \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlevel\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 8869\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mDataFrameGroupBy\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 8870\u001b[0m \u001b[43m \u001b[49m\u001b[43mobj\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8871\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mby\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8872\u001b[0m \u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8873\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8874\u001b[0m \u001b[43m \u001b[49m\u001b[43mas_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mas_index\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8875\u001b[0m \u001b[43m \u001b[49m\u001b[43msort\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8876\u001b[0m \u001b[43m \u001b[49m\u001b[43mgroup_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8877\u001b[0m \u001b[43m \u001b[49m\u001b[43mobserved\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mobserved\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8878\u001b[0m \u001b[43m \u001b[49m\u001b[43mdropna\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdropna\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8879\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/mamba/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1278\u001b[0m, in \u001b[0;36mGroupBy.__init__\u001b[0;34m(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, observed, dropna)\u001b[0m\n\u001b[1;32m 1275\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdropna \u001b[38;5;241m=\u001b[39m dropna\n\u001b[1;32m 1277\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m grouper \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1278\u001b[0m grouper, exclusions, obj \u001b[38;5;241m=\u001b[39m \u001b[43mget_grouper\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1279\u001b[0m \u001b[43m \u001b[49m\u001b[43mobj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1280\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1281\u001b[0m \u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1282\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1283\u001b[0m \u001b[43m \u001b[49m\u001b[43msort\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1284\u001b[0m \u001b[43m \u001b[49m\u001b[43mobserved\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mobserved\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mno_default\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mobserved\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1285\u001b[0m \u001b[43m \u001b[49m\u001b[43mdropna\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdropna\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1286\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1288\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m observed \u001b[38;5;129;01mis\u001b[39;00m lib\u001b[38;5;241m.\u001b[39mno_default:\n\u001b[1;32m 1289\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28many\u001b[39m(ping\u001b[38;5;241m.\u001b[39m_passed_categorical \u001b[38;5;28;01mfor\u001b[39;00m ping \u001b[38;5;129;01min\u001b[39;00m grouper\u001b[38;5;241m.\u001b[39mgroupings):\n", + "File \u001b[0;32m/opt/mamba/lib/python3.10/site-packages/pandas/core/groupby/grouper.py:1009\u001b[0m, in \u001b[0;36mget_grouper\u001b[0;34m(obj, key, axis, level, sort, observed, validate, dropna)\u001b[0m\n\u001b[1;32m 1007\u001b[0m in_axis, level, gpr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m, gpr, \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1008\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1009\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(gpr)\n\u001b[1;32m 1010\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(gpr, Grouper) \u001b[38;5;129;01mand\u001b[39;00m gpr\u001b[38;5;241m.\u001b[39mkey \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1011\u001b[0m \u001b[38;5;66;03m# Add key to exclusions\u001b[39;00m\n\u001b[1;32m 1012\u001b[0m exclusions\u001b[38;5;241m.\u001b[39madd(gpr\u001b[38;5;241m.\u001b[39mkey)\n", + "\u001b[0;31mKeyError\u001b[0m: 'name_event_types'" + ] } ], "source": [ @@ -8357,21 +8276,10 @@ }, { "cell_type": "code", - "execution_count": 238, + "execution_count": null, "id": "e37ad847-7ea5-4afe-9c6d-e07a668d2a27", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "average_tickets_by_event = df_purchase.groupby('name_event_types')['nb_tickets'].mean()\n", "\n", @@ -8385,39 +8293,22 @@ }, { "cell_type": "code", - "execution_count": 241, + "execution_count": null, "id": "e02b260a-fcb7-418b-87a8-de2bb4e6eb0a", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "customer_id 0\n", - "gender 0\n", - "is_partner 0\n", - "is_email_true 0\n", - "nb_campaigns 34417\n", - "nb_campaigns_opened 34417\n", - "fidelity 0\n", - "product_id 0\n", - "nb_tickets 0\n", - "ticket_sum 0\n", - "average_price 22\n", - "amount 0\n", - "event_type_id 0\n", - "name_event_types 0\n", - "dtype: int64" - ] - }, - "execution_count": 241, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df_purchase.isna().sum()" ] }, + { + "cell_type": "markdown", + "id": "26fa888d-dd33-4990-89bd-6a9c1391098b", + "metadata": {}, + "source": [ + "## Modelisation K-means" + ] + }, { "cell_type": "code", "execution_count": 242, -- 2.34.1 From ac2e6ca81e6224390da51b9fbb5bf578e05d9591 Mon Sep 17 00:00:00 2001 From: arevelle-ensae Date: Sun, 11 Feb 2024 10:47:58 +0000 Subject: [PATCH 3/3] add stat on customer --- 0_Cleaning_and_merge.ipynb | 983 ++++++++++++++++++++++++++++----- 1_Descriptive_Statistics.ipynb | 845 +++++++++++++++++++++++++++- 2 files changed, 1688 insertions(+), 140 deletions(-) diff --git a/0_Cleaning_and_merge.ipynb b/0_Cleaning_and_merge.ipynb index 20c5a03..b61b004 100644 --- a/0_Cleaning_and_merge.ipynb +++ b/0_Cleaning_and_merge.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 80, "id": "15103481-8d74-404c-aa09-7601fe7730da", "metadata": {}, "outputs": [], @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 81, "id": "5d83bb1a-d341-446e-91f6-1c428607f6d4", "metadata": {}, "outputs": [], @@ -45,7 +45,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 82, "id": "a9b84234-d5df-4c43-a9cd-80cfe2f1e34d", "metadata": {}, "outputs": [], @@ -72,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 83, "id": "699664b9-eee4-4f8d-a207-e524526560c5", "metadata": {}, "outputs": [], @@ -83,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 84, "id": "dd6a3518-b752-4a1e-b77b-9e03e853c3ed", "metadata": {}, "outputs": [], @@ -114,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 85, "id": "d237be96-8c86-4a91-b7a1-487e87a16c3d", "metadata": {}, "outputs": [], @@ -155,7 +155,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 86, "id": "7e7b90ce-da54-4f00-bc34-64c543b0858f", "metadata": {}, "outputs": [], @@ -177,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 87, "id": "03329e32-00a5-42c8-9470-75f7b6216ccd", "metadata": {}, "outputs": [], @@ -195,7 +195,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 88, "id": "b95464b1-26bc-4aac-84b4-45da83b92251", "metadata": {}, "outputs": [], @@ -239,7 +239,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 89, "id": "3e1d2ba7-ff4f-48eb-93a8-2bb648c70396", "metadata": {}, "outputs": [], @@ -249,7 +249,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 90, "id": "4b18edfc-6450-4c6a-9e7b-ee5a5808c8c9", "metadata": {}, "outputs": [ @@ -360,7 +360,7 @@ "4 Atelier pricing_formula 2018-12-28 14:47:50+00:00 48187 " ] }, - "execution_count": 10, + "execution_count": 90, "metadata": {}, "output_type": "execute_result" } @@ -379,7 +379,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 91, "id": "baed146a-9d3a-4397-a812-3d50c9a2f038", "metadata": {}, "outputs": [], @@ -408,7 +408,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 92, "id": "5fbfd88b-b94c-489c-9201-670e96e453e7", "metadata": {}, "outputs": [], @@ -426,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 93, "id": "d883cc7b-ac43-4485-b86f-eaf595fbad85", "metadata": {}, "outputs": [], @@ -451,7 +451,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 94, "id": "c8552dd6-52c5-4431-b43d-3cd6c578fd9f", "metadata": {}, "outputs": [], @@ -461,7 +461,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 95, "id": "c24457e7-3cad-451a-a65b-7373b656bd6e", "metadata": { "scrolled": true @@ -581,7 +581,7 @@ "4 404 2021-03-27 23:00:00+00:00 " ] }, - "execution_count": 15, + "execution_count": 95, "metadata": {}, "output_type": "execute_result" } @@ -608,7 +608,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 96, "id": "30488a40-1b38-4b9a-9d3b-26a0597c5e6d", "metadata": {}, "outputs": [], @@ -619,7 +619,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 97, "id": "607eb4b4-eed9-4b50-b823-f75c116dd37c", "metadata": {}, "outputs": [], @@ -690,7 +690,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 98, "id": "350b09b9-451f-4d47-81fe-f34b892db027", "metadata": {}, "outputs": [], @@ -778,7 +778,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 99, "id": "0fccc8ef-e575-4857-a401-94a7274394df", "metadata": {}, "outputs": [ @@ -931,7 +931,7 @@ "4 indiv entrées tp " ] }, - "execution_count": 19, + "execution_count": 99, "metadata": {}, "output_type": "execute_result" } @@ -943,7 +943,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 100, "id": "779d8aaf-6668-4f66-8852-847304407ea3", "metadata": {}, "outputs": [ @@ -1113,7 +1113,7 @@ "4 spectacle vivant mucem " ] }, - "execution_count": 20, + "execution_count": 100, "metadata": {}, "output_type": "execute_result" } @@ -1125,7 +1125,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 101, "id": "7714fa32-303b-4ea7-b174-3fd0fcab5af0", "metadata": {}, "outputs": [ @@ -1224,7 +1224,7 @@ "4 37 383 269 1" ] }, - "execution_count": 21, + "execution_count": 101, "metadata": {}, "output_type": "execute_result" } @@ -1244,7 +1244,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 102, "id": "15a62ed6-35e4-4abc-aeef-a7daeec0a4ba", "metadata": {}, "outputs": [], @@ -1272,7 +1272,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 103, "id": "89dc9685-1de9-4ce3-a6c0-8d7f1931a951", "metadata": {}, "outputs": [ @@ -1511,7 +1511,7 @@ "[5 rows x 21 columns]" ] }, - "execution_count": 23, + "execution_count": 103, "metadata": {}, "output_type": "execute_result" } @@ -1523,7 +1523,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 104, "id": "98f78cd5-b694-4cc6-b033-20170aa13e8d", "metadata": {}, "outputs": [], @@ -1553,7 +1553,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 105, "id": "e2c88552-b863-47a2-be23-8d2898fb28bc", "metadata": {}, "outputs": [], @@ -1587,7 +1587,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 106, "id": "24537647-bc29-4777-9848-ac4120a4aa60", "metadata": {}, "outputs": [], @@ -1597,7 +1597,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 107, "id": "6be2a9a6-056b-4e19-8c26-a18ba3df36b3", "metadata": {}, "outputs": [ @@ -1677,7 +1677,7 @@ "4 6 20 0.0 NaT" ] }, - "execution_count": 27, + "execution_count": 107, "metadata": {}, "output_type": "execute_result" } @@ -1696,7 +1696,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 108, "id": "b913a69e-3146-4919-b5f6-a6108532bffa", "metadata": {}, "outputs": [ @@ -1707,7 +1707,7 @@ " 'offre muséale groupe'], dtype=object)" ] }, - "execution_count": 28, + "execution_count": 108, "metadata": {}, "output_type": "execute_result" } @@ -1718,7 +1718,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 109, "id": "2bda0b97-b28b-4070-a57d-aeab0e2f7dfe", "metadata": {}, "outputs": [], @@ -1729,7 +1729,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 110, "id": "043303fe-e90f-4689-a2a9-5d690555a045", "metadata": {}, "outputs": [], @@ -1775,7 +1775,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 111, "id": "5882234a-1ed5-4269-87a6-0d75613476e3", "metadata": {}, "outputs": [], @@ -1793,7 +1793,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 112, "id": "a4a2311d-8a72-4030-afd5-218004d5d2a5", "metadata": {}, "outputs": [], @@ -1809,7 +1809,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 113, "id": "a7a452a6-cd5e-4c8b-b250-8a7d26e48fad", "metadata": {}, "outputs": [ @@ -1939,7 +1939,7 @@ "5032 1049 days 18:46:12 13497.0 " ] }, - "execution_count": 33, + "execution_count": 113, "metadata": {}, "output_type": "execute_result" } @@ -1958,85 +1958,8 @@ }, { "cell_type": "code", - "execution_count": 34, - "id": "4ab1c0d2-0097-4669-b984-b6822c976740", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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event_type_idname_event_typesavg_amount
02offre muséale individuel6.150659
14spectacle vivant7.762474
25offre muséale groupe4.452618
36formule adhésion6.439463
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" + ], + "text/plain": [ + " event_type_id name_event_types avg_amount\n", + "0 2 offre muséale individuel 6.150659\n", + "1 4 spectacle vivant 7.762474\n", + "2 5 offre muséale groupe 4.452618\n", + "3 6 formule adhésion 6.439463" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "avg_amount = (df1_products_purchased_reduced.groupby([\"event_type_id\", 'name_event_types'])\n", + " .agg({\"amount\" : \"mean\"}).reset_index()\n", + " .rename(columns = {'amount' : 'avg_amount'}))\n", + "\n", + "avg_amount" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "id": "b54bd9e8-3cad-453b-8e58-bf6d047912eb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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customer_idevent_type_idnb_ticketstotal_amountnb_suppliersvente_internet_maxpurchase_date_minpurchase_date_maxtime_between_purchasenb_tickets_internetname_event_typesavg_amount
123842262686540.5712014-12-03 14:55:37+00:002023-11-04 15:12:16+00:003258 days 00:16:3951.0offre muséale individuel6.150659
144532423248965.5612013-09-23 14:45:01+00:002023-11-03 14:11:01+00:003692 days 23:26:002988.0spectacle vivant7.762474
152017501459190.0612013-06-10 10:37:58+00:002023-11-08 15:59:45+00:003803 days 05:21:479.0offre muséale groupe4.452618
162173561435871.5512017-01-01 02:20:08+00:002019-12-31 02:20:06+00:001093 days 23:59:585.0formule adhésion6.439463
221430.0102018-04-07 12:55:07+00:002020-03-08 12:06:43+00:00700 days 23:11:360.0offre muséale individuel6.150659
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customer_idbirthdatestreet_idis_partnergenderis_email_trueopt_instructure_idprofessionlanguage...nb_ticketstotal_amountnb_suppliersvente_internet_maxpurchase_date_minpurchase_date_maxtime_between_purchasenb_tickets_internetname_event_typesavg_amount
598971NaN2False2TrueFalseNaNNaNNaN...384226.02686540.57.01.02014-12-03 14:55:37+00:002023-11-04 15:12:16+00:003258 days 00:16:3951.0offre muséale individuel6.150659
599001NaN2False2TrueFalseNaNNaNNaN...217356.01435871.55.01.02017-01-01 02:20:08+00:002019-12-31 02:20:06+00:001093 days 23:59:585.0formule adhésion6.439463
598981NaN2False2TrueFalseNaNNaNNaN...453242.03248965.56.01.02013-09-23 14:45:01+00:002023-11-03 14:11:01+00:003692 days 23:26:002988.0spectacle vivant7.762474
598991NaN2False2TrueFalseNaNNaNNaN...201750.01459190.06.01.02013-06-10 10:37:58+00:002023-11-08 15:59:45+00:003803 days 05:21:479.0offre muséale groupe4.452618
1346952NaN2False1TrueTrueNaNNaNNaN...164.00.01.00.02019-03-09 13:14:21+00:002019-11-13 11:29:55+00:00248 days 22:15:340.0formule adhésion6.439463
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5 rows × 36 columns

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" + ], + "text/plain": [ + " customer_id birthdate street_id is_partner gender is_email_true \\\n", + "59897 1 NaN 2 False 2 True \n", + "59900 1 NaN 2 False 2 True \n", + "59898 1 NaN 2 False 2 True \n", + "59899 1 NaN 2 False 2 True \n", + "134695 2 NaN 2 False 1 True \n", + "\n", + " opt_in structure_id profession language ... nb_tickets \\\n", + "59897 False NaN NaN NaN ... 384226.0 \n", + "59900 False NaN NaN NaN ... 217356.0 \n", + "59898 False NaN NaN NaN ... 453242.0 \n", + "59899 False NaN NaN NaN ... 201750.0 \n", + "134695 True NaN NaN NaN ... 164.0 \n", + "\n", + " total_amount nb_suppliers vente_internet_max \\\n", + "59897 2686540.5 7.0 1.0 \n", + "59900 1435871.5 5.0 1.0 \n", + "59898 3248965.5 6.0 1.0 \n", + "59899 1459190.0 6.0 1.0 \n", + "134695 0.0 1.0 0.0 \n", + "\n", + " purchase_date_min purchase_date_max \\\n", + "59897 2014-12-03 14:55:37+00:00 2023-11-04 15:12:16+00:00 \n", + "59900 2017-01-01 02:20:08+00:00 2019-12-31 02:20:06+00:00 \n", + "59898 2013-09-23 14:45:01+00:00 2023-11-03 14:11:01+00:00 \n", + "59899 2013-06-10 10:37:58+00:00 2023-11-08 15:59:45+00:00 \n", + "134695 2019-03-09 13:14:21+00:00 2019-11-13 11:29:55+00:00 \n", + "\n", + " time_between_purchase nb_tickets_internet name_event_types \\\n", + "59897 3258 days 00:16:39 51.0 offre muséale individuel \n", + "59900 1093 days 23:59:58 5.0 formule adhésion \n", + "59898 3692 days 23:26:00 2988.0 spectacle vivant \n", + "59899 3803 days 05:21:47 9.0 offre muséale groupe \n", + "134695 248 days 22:15:34 0.0 formule adhésion \n", + "\n", + " avg_amount \n", + "59897 6.150659 \n", + "59900 6.439463 \n", + "59898 7.762474 \n", + "59899 4.452618 \n", + "134695 6.439463 \n", + "\n", + "[5 rows x 36 columns]" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "## Add customer information\n", + "df1_customer = (df1_customerplus_clean.merge(df1_tickets_kpi, how = \"left\", on='customer_id')\n", + " .sort_values(by='customer_id', ascending=True))\n", + "df1_customer.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "id": "433921de-03ad-4024-9462-ecd267db1756", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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customer_idbirthdatestreet_idis_partnergenderis_email_trueopt_instructure_idprofessionlanguage...vente_internet_maxpurchase_date_minpurchase_date_maxtime_between_purchasenb_tickets_internetname_event_typesavg_amountnb_campaignsnb_campaigns_openedtime_to_open
01NaN2False2TrueFalseNaNNaNNaN...1.02014-12-03 14:55:37+00:002023-11-04 15:12:16+00:003258 days 00:16:3951.0offre muséale individuel6.150659NaNNaNNaT
11NaN2False2TrueFalseNaNNaNNaN...1.02017-01-01 02:20:08+00:002019-12-31 02:20:06+00:001093 days 23:59:585.0formule adhésion6.439463NaNNaNNaT
21NaN2False2TrueFalseNaNNaNNaN...1.02013-09-23 14:45:01+00:002023-11-03 14:11:01+00:003692 days 23:26:002988.0spectacle vivant7.762474NaNNaNNaT
31NaN2False2TrueFalseNaNNaNNaN...1.02013-06-10 10:37:58+00:002023-11-08 15:59:45+00:003803 days 05:21:479.0offre muséale groupe4.452618NaNNaNNaT
42NaN2False1TrueTrueNaNNaNNaN...0.02019-03-09 13:14:21+00:002019-11-13 11:29:55+00:00248 days 22:15:340.0formule adhésion6.4394634.00.0NaT
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5 rows × 39 columns

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" + ], + "text/plain": [ + " customer_id birthdate street_id is_partner gender is_email_true \\\n", + "0 1 NaN 2 False 2 True \n", + "1 1 NaN 2 False 2 True \n", + "2 1 NaN 2 False 2 True \n", + "3 1 NaN 2 False 2 True \n", + "4 2 NaN 2 False 1 True \n", + "\n", + " opt_in structure_id profession language ... vente_internet_max \\\n", + "0 False NaN NaN NaN ... 1.0 \n", + "1 False NaN NaN NaN ... 1.0 \n", + "2 False NaN NaN NaN ... 1.0 \n", + "3 False NaN NaN NaN ... 1.0 \n", + "4 True NaN NaN NaN ... 0.0 \n", + "\n", + " purchase_date_min purchase_date_max time_between_purchase \\\n", + "0 2014-12-03 14:55:37+00:00 2023-11-04 15:12:16+00:00 3258 days 00:16:39 \n", + "1 2017-01-01 02:20:08+00:00 2019-12-31 02:20:06+00:00 1093 days 23:59:58 \n", + "2 2013-09-23 14:45:01+00:00 2023-11-03 14:11:01+00:00 3692 days 23:26:00 \n", + "3 2013-06-10 10:37:58+00:00 2023-11-08 15:59:45+00:00 3803 days 05:21:47 \n", + "4 2019-03-09 13:14:21+00:00 2019-11-13 11:29:55+00:00 248 days 22:15:34 \n", + "\n", + " nb_tickets_internet name_event_types avg_amount nb_campaigns \\\n", + "0 51.0 offre muséale individuel 6.150659 NaN \n", + "1 5.0 formule adhésion 6.439463 NaN \n", + "2 2988.0 spectacle vivant 7.762474 NaN \n", + "3 9.0 offre muséale groupe 4.452618 NaN \n", + "4 0.0 formule adhésion 6.439463 4.0 \n", + "\n", + " nb_campaigns_opened time_to_open \n", + "0 NaN NaT \n", + "1 NaN NaT \n", + "2 NaN NaT \n", + "3 NaN NaT \n", + "4 0.0 NaT \n", + "\n", + "[5 rows x 39 columns]" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Add campaigns information\n", + "\n", + "df1_customer = df1_customer.merge(df1_campaigns_kpi, how='left', on='customer_id')\n", + "df1_customer.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "id": "25e54131-6835-4e94-86d3-1a78520ed7bc", + "metadata": {}, + "outputs": [], + "source": [ + "## Exportation\n", + "\n", + "# Exportation vers 'projet-bdc2324-team1'\n", + "BUCKET_OUT = \"projet-bdc2324-team1\"\n", + "FILE_KEY_OUT_S3 = \"0_Temp/Company 1 - customer_event.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_customer.to_csv(file_out, index = False)" + ] + }, + { + "cell_type": "markdown", + "id": "edae177c-1247-454d-b3d1-08fea37001f7", + "metadata": {}, + "source": [ + "## End of Alexis' work" ] }, { @@ -2343,8 +3052,8 @@ ], "source": [ "# Fusion avec KPI campaigns liés au customer\n", - "df1_customer = pd.merge(df1_customerplus_clean, df1_campaigns_kpi, on = 'customer_id', how = 'left')\n", - "df1_customer.head()" + "#df1_customer = pd.merge(df1_customerplus_clean, df1_campaigns_kpi, on = 'customer_id', how = 'left')\n", + "#df1_customer.head()" ] }, { @@ -2580,7 +3289,7 @@ "metadata": {}, "outputs": [], "source": [ - "# df1_customer_product.to_csv(\"customer_product.csv\", index = False)" + "df1_customer_product.to_csv(\"customer_product.csv\", index = False)" ] }, { diff --git a/1_Descriptive_Statistics.ipynb b/1_Descriptive_Statistics.ipynb index 113fd77..19b7854 100644 --- a/1_Descriptive_Statistics.ipynb +++ b/1_Descriptive_Statistics.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 49, "id": "abfaf341-7b35-4407-9133-d21336c04027", "metadata": {}, "outputs": [], @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 50, "id": "7fb72fa3-7940-496f-ac78-c2837f65eefa", "metadata": {}, "outputs": [], @@ -510,10 +510,849 @@ "tickets_kpi_filtered = tickets_kpi[tickets_kpi['customer_id'] != 1]" ] }, + { + "cell_type": "markdown", + "id": "b8a90eaa-c383-4f73-9fd6-6fbbe8eeefb8", + "metadata": {}, + "source": [ + "# 2 - Comportement d'achat bis (Alexis)" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "dc45c1cd-2a78-48a6-aa2b-6a501254b6f2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(141017, 39)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_526/626921812.py:7: DtypeWarning: Columns (6) have mixed types. Specify dtype option on import or set low_memory=False.\n", + " customer = pd.read_csv(file_in, sep=\",\")\n" + ] + }, + { + "data": { + "text/html": [ + "
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customer_idbirthdatestreet_idis_partnergenderis_email_trueopt_instructure_idprofessionlanguage...vente_internet_maxpurchase_date_minpurchase_date_maxtime_between_purchasenb_tickets_internetname_event_typesavg_amountnb_campaignsnb_campaigns_openedtime_to_open
01NaN2False2TrueFalseNaNNaNNaN...1.02014-12-03 14:55:37+00:002023-11-04 15:12:16+00:003258 days 00:16:3951.0offre muséale individuel6.150659NaNNaNNaN
11NaN2False2TrueFalseNaNNaNNaN...1.02017-01-01 02:20:08+00:002019-12-31 02:20:06+00:001093 days 23:59:585.0formule adhésion6.439463NaNNaNNaN
21NaN2False2TrueFalseNaNNaNNaN...1.02013-09-23 14:45:01+00:002023-11-03 14:11:01+00:003692 days 23:26:002988.0spectacle vivant7.762474NaNNaNNaN
31NaN2False2TrueFalseNaNNaNNaN...1.02013-06-10 10:37:58+00:002023-11-08 15:59:45+00:003803 days 05:21:479.0offre muséale groupe4.452618NaNNaNNaN
42NaN2False1TrueTrueNaNNaNNaN...0.02019-03-09 13:14:21+00:002019-11-13 11:29:55+00:00248 days 22:15:340.0formule adhésion6.4394634.00.0NaN
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5 rows × 39 columns

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" + ], + "text/plain": [ + " customer_id birthdate street_id is_partner gender is_email_true opt_in \\\n", + "0 1 NaN 2 False 2 True False \n", + "1 1 NaN 2 False 2 True False \n", + "2 1 NaN 2 False 2 True False \n", + "3 1 NaN 2 False 2 True False \n", + "4 2 NaN 2 False 1 True True \n", + "\n", + " structure_id profession language ... vente_internet_max \\\n", + "0 NaN NaN NaN ... 1.0 \n", + "1 NaN NaN NaN ... 1.0 \n", + "2 NaN NaN NaN ... 1.0 \n", + "3 NaN NaN NaN ... 1.0 \n", + "4 NaN NaN NaN ... 0.0 \n", + "\n", + " purchase_date_min purchase_date_max \\\n", + "0 2014-12-03 14:55:37+00:00 2023-11-04 15:12:16+00:00 \n", + "1 2017-01-01 02:20:08+00:00 2019-12-31 02:20:06+00:00 \n", + "2 2013-09-23 14:45:01+00:00 2023-11-03 14:11:01+00:00 \n", + "3 2013-06-10 10:37:58+00:00 2023-11-08 15:59:45+00:00 \n", + "4 2019-03-09 13:14:21+00:00 2019-11-13 11:29:55+00:00 \n", + "\n", + " time_between_purchase nb_tickets_internet name_event_types \\\n", + "0 3258 days 00:16:39 51.0 offre muséale individuel \n", + "1 1093 days 23:59:58 5.0 formule adhésion \n", + "2 3692 days 23:26:00 2988.0 spectacle vivant \n", + "3 3803 days 05:21:47 9.0 offre muséale groupe \n", + "4 248 days 22:15:34 0.0 formule adhésion \n", + "\n", + " avg_amount nb_campaigns nb_campaigns_opened time_to_open \n", + "0 6.150659 NaN NaN NaN \n", + "1 6.439463 NaN NaN NaN \n", + "2 7.762474 NaN NaN NaN \n", + "3 4.452618 NaN NaN NaN \n", + "4 6.439463 4.0 0.0 NaN \n", + "\n", + "[5 rows x 39 columns]" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Chargement des données temporaires\n", + "BUCKET = \"projet-bdc2324-team1\"\n", + "FILE_KEY_S3 = \"0_Temp/Company 1 - customer_event.csv\"\n", + "FILE_PATH_S3 = BUCKET + \"/\" + FILE_KEY_S3\n", + "\n", + "with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n", + " customer = pd.read_csv(file_in, sep=\",\")\n", + "\n", + "print(customer.shape)\n", + "customer.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "89fcb455-efb4-4ad4-ab88-efd6c8a76287", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['customer_id', 'birthdate', 'street_id', 'is_partner', 'gender',\n", + " 'is_email_true', 'opt_in', 'structure_id', 'profession', 'language',\n", + " 'mcp_contact_id', 'last_buying_date', 'max_price', 'ticket_sum',\n", + " 'average_price', 'fidelity', 'average_purchase_delay',\n", + " 'average_price_basket', 'average_ticket_basket', 'total_price',\n", + " 'purchase_count', 'first_buying_date', 'country', 'age', 'tenant_id',\n", + " 'event_type_id', 'nb_tickets', 'total_amount', 'nb_suppliers',\n", + " 'vente_internet_max', 'purchase_date_min', 'purchase_date_max',\n", + " 'time_between_purchase', 'nb_tickets_internet', 'name_event_types',\n", + " 'avg_amount', 'nb_campaigns', 'nb_campaigns_opened', 'time_to_open'],\n", + " dtype='object')" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "id": "d7b2356a-d5fc-4547-b3ff-fded0e304fb6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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customer_idaverage_priceaverage_purchase_delayaverage_price_basketaverage_ticket_basketpurchase_counttotal_pricenb_campaignsnb_campaigns_opened
017.030122-67.79096913.7515301.956087641472.08821221.50.00.0
420.0000000.0000000.0000001.000000307.00.04.00.0
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" + ], + "text/plain": [ + " customer_id average_price average_purchase_delay average_price_basket \\\n", + "0 1 7.030122 -67.790969 13.751530 \n", + "4 2 0.000000 0.000000 0.000000 \n", + "6 3 18.333333 30.666667 36.666667 \n", + "7 4 10.250000 5.000000 20.500000 \n", + "9 5 9.500000 0.000000 19.000000 \n", + "\n", + " average_ticket_basket purchase_count total_price nb_campaigns \\\n", + "0 1.956087 641472.0 8821221.5 0.0 \n", + "4 1.000000 307.0 0.0 4.0 \n", + "6 2.000000 3.0 110.0 222.0 \n", + "7 2.000000 2.0 41.0 7.0 \n", + "9 2.000000 1.0 19.0 4.0 \n", + "\n", + " nb_campaigns_opened \n", + "0 0.0 \n", + "4 0.0 \n", + "6 124.0 \n", + "7 7.0 \n", + "9 0.0 " + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "achat = ['customer_id', 'average_price', 'average_purchase_delay', 'average_price_basket',\n", + " 'average_ticket_basket', 'purchase_count', 'total_price', 'nb_campaigns',\n", + " 'nb_campaigns_opened']\n", + "\n", + "customer_achat = customer[achat].drop_duplicates(subset = ['customer_id'])\n", + "customer_achat['nb_campaigns'] = customer_achat['nb_campaigns'].fillna(0)\n", + "customer_achat['nb_campaigns_opened'] = customer_achat['nb_campaigns_opened'].fillna(0)\n", + "customer_achat = customer_achat.fillna(0)\n", + "customer_achat.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "5559748f-1745-4651-a9f6-94702c7ee66f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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average_priceaverage_purchase_delayaverage_price_basketaverage_ticket_basketpurchase_counttotal_pricenb_campaignsnb_campaigns_opened
count136732.000000136732.000000136732.000000136732.000000136732.000000136732.000000136732.000000136732.000000
mean5.036239-158.65155810.7981081.6791390.64684916.67020945.1893498.673193
std7.9701842616.84415848.7900527.1172655.464266327.46417372.99632624.226327
min0.000000-44862.0000000.0000000.0000000.0000000.0000000.0000000.000000
25%0.0000000.0000000.0000000.0000000.0000000.0000002.0000000.000000
50%0.0000000.0000000.0000000.0000000.0000000.0000006.0000001.000000
75%11.0000000.00000018.0000002.0000001.00000019.00000038.0000004.000000
max290.0000001914.0000009900.000000900.0000001508.00000064350.000000439.000000434.000000
\n", + "
" + ], + "text/plain": [ + " average_price average_purchase_delay average_price_basket \\\n", + "count 136732.000000 136732.000000 136732.000000 \n", + "mean 5.036239 -158.651558 10.798108 \n", + "std 7.970184 2616.844158 48.790052 \n", + "min 0.000000 -44862.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 \n", + "50% 0.000000 0.000000 0.000000 \n", + "75% 11.000000 0.000000 18.000000 \n", + "max 290.000000 1914.000000 9900.000000 \n", + "\n", + " average_ticket_basket purchase_count total_price nb_campaigns \\\n", + "count 136732.000000 136732.000000 136732.000000 136732.000000 \n", + "mean 1.679139 0.646849 16.670209 45.189349 \n", + "std 7.117265 5.464266 327.464173 72.996326 \n", + "min 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 2.000000 \n", + "50% 0.000000 0.000000 0.000000 6.000000 \n", + "75% 2.000000 1.000000 19.000000 38.000000 \n", + "max 900.000000 1508.000000 64350.000000 439.000000 \n", + "\n", + " nb_campaigns_opened \n", + "count 136732.000000 \n", + "mean 8.673193 \n", + "std 24.226327 \n", + "min 0.000000 \n", + "25% 0.000000 \n", + "50% 1.000000 \n", + "75% 4.000000 \n", + "max 434.000000 " + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer_wto_outlier = customer_achat[customer_achat['customer_id']!=1]\n", + "\n", + "customer_wto_outlier[['average_price', 'average_purchase_delay', 'average_price_basket',\n", + " 'average_ticket_basket', 'purchase_count', 'total_price', 'nb_campaigns', 'nb_campaigns_opened']].describe()" + ] + }, + { + "cell_type": "markdown", + "id": "b49c9e93-f324-42ee-a262-34ffb44a2261", + "metadata": {}, + "source": [ + "# 3 - Event" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "4971e35d-a762-4e18-9443-fd9571bd3f1e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Nombre de consommateurs uniques par type d'évènement\n", + "\n", + "event_counts = customer.groupby('name_event_types')['customer_id'].nunique()\n", + "\n", + "event_counts.plot(kind='bar')\n", + "plt.xlabel(\"Type d'évènement\")\n", + "plt.ylabel('Nombre de consommateurs uniques')\n", + "plt.title(\"Nombre de consommateurs uniques par type d'évènement\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bc65a711-d172-4839-b487-3047280fc3a6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Nombre Total de tickets achetés par Type d'évènements\n", + "\n", + "total_tickets_by_event = customer.groupby('name_event_types')['nb_tickets'].sum()\n", + "\n", + "total_tickets_by_event.plot(kind='bar', figsize=(8, 5))\n", + "plt.xlabel(\"Type d'évènements\")\n", + "plt.ylabel('Nombre Total de tickets achetés')\n", + "plt.title(\"Nombre Total de tickets achetés par Type d'évènements\")\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "c95cc35c-abfc-47c7-9b8a-ac69bfd60dd8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Nombre de Canaux de Ventes Moyen utilisé par les Consommateurs par type d'évènement\n", + "\n", + "avg_supp_event = customer.groupby('name_event_types')['nb_suppliers'].mean()\n", + "avg_supp_event.plot(kind='bar')\n", + "plt.xlabel(\"Type d'évènement\")\n", + "plt.ylabel('Nombre de Canaux de Ventes Moyen')\n", + "plt.title(\"Nombre de Canaux de Ventes Moyen utilisé par les Consommateurs par type d'évènement\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "49d5fd2d-9bc1-43ac-9270-1efd73759854", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Nombre Total de tickets achetés sur Internet par Type d'évènements\n", + "\n", + "nb_tickets_internet = customer.groupby('name_event_types')['nb_tickets_internet'].sum()\n", + "nb_tickets_internet.plot(kind='bar', figsize=(8, 5))\n", + "plt.xlabel(\"Type d'évènements\")\n", + "plt.ylabel('Nombre Total de tickets achetés sur Internet')\n", + "plt.title(\"Nombre Total de tickets achetés sur Internet par Type d'évènements\")\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "31e4e6f1-efc4-410d-b1d3-bb49950ef58e", + "id": "dc071992-cf4d-4b9f-9c3b-3f0e98e20eff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "4f9561a9-6a94-434e-b8e7-9b708f5b5529", + "metadata": {}, + "source": [ + "# 3 - Caractéristiques Démographiques (peu exploitable)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "e50e2583-4b8f-478e-87ac-591dde200af8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['customer_id', 'birthdate', 'street_id', 'is_partner', 'gender',\n", + " 'is_email_true', 'opt_in', 'structure_id', 'profession', 'language',\n", + " 'mcp_contact_id', 'last_buying_date', 'max_price', 'ticket_sum',\n", + " 'average_price', 'fidelity', 'average_purchase_delay',\n", + " 'average_price_basket', 'average_ticket_basket', 'total_price',\n", + " 'purchase_count', 'first_buying_date', 'country', 'age', 'tenant_id',\n", + " 'event_type_id', 'nb_tickets', 'total_amount', 'nb_suppliers',\n", + " 'vente_internet_max', 'purchase_date_min', 'purchase_date_max',\n", + " 'time_between_purchase', 'nb_tickets_internet', 'name_event_types',\n", + " 'avg_amount'],\n", + " dtype='object')" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "c724a315-9fe8-4874-be8f-a8115b17b5e2", + "metadata": {}, + "outputs": [], + "source": [ + "def percent_of_na(df, column):\n", + " na_percentage = df[column].isna().mean() * 100\n", + " non_na_percentage = 100 - na_percentage\n", + " \n", + " labels = ['Valeurs Manquantes', 'Non-Valeurs Manquantes']\n", + " sizes = [na_percentage, non_na_percentage]\n", + " colors = ['#ff9999','#66b3ff']\n", + " explode = (0.1, 0)\n", + "\n", + " plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', startangle=140)\n", + " plt.axis('equal') \n", + " plt.title('Pourcentage de Valeurs Manquantes : {}'.format(column))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "58af5dcb-673e-4f4d-ad5c-f66ce1e8a22c", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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