From be0bcda0baf410bbd4dcb7230719e6f0dedfcd8d Mon Sep 17 00:00:00 2001
From: ajoubrel-ensae <antoine.joubrel@ensae.fr>
Date: Wed, 27 Mar 2024 18:55:11 +0000
Subject: [PATCH] =?UTF-8?q?Compl=C3=A9tion=20brouillon?=
MIME-Version: 1.0
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Content-Transfer-Encoding: 8bit

---
 Exploration_billet_AJ.ipynb | 37 +++++++++++++++++++++++++++++--------
 1 file changed, 29 insertions(+), 8 deletions(-)

diff --git a/Exploration_billet_AJ.ipynb b/Exploration_billet_AJ.ipynb
index 886aaae..93995f5 100644
--- a/Exploration_billet_AJ.ipynb
+++ b/Exploration_billet_AJ.ipynb
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 22,
    "id": "b1a5b9d3",
    "metadata": {},
    "outputs": [],
@@ -20,7 +20,9 @@
     "import os\n",
     "import s3fs\n",
     "import re\n",
-    "import warnings"
+    "import warnings\n",
+    "import io\n",
+    "import matplotlib.pyplot as plt\n"
    ]
   },
   {
@@ -97,6 +99,24 @@
     "        df.to_csv(file_out, index = False)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "108fc5ef-c56a-4f03-a867-943d9d6492fd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def save_file_s3(File_name, type_of_activity):\n",
+    "    image_buffer = io.BytesIO()\n",
+    "    plt.savefig(image_buffer, format='png')\n",
+    "    image_buffer.seek(0)\n",
+    "    FILE_PATH = f\"projet-bdc2324-team1/stat_desc/{type_of_activity}/\"\n",
+    "    FILE_PATH_OUT_S3 = FILE_PATH + File_name + type_of_activity + '.png'\n",
+    "    with fs.open(FILE_PATH_OUT_S3, 'wb') as s3_file:\n",
+    "        s3_file.write(image_buffer.read())\n",
+    "    plt.close()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "ccf597b0-b459-4ea5-baf0-5ba8c90915e4",
@@ -599,7 +619,7 @@
     "            'sport': ['5', '6', '7', '8', '9'],\n",
     "            'musique' : ['10', '11', '12', '13', '14']}\n",
     "\n",
-    "nb_compagnie = companies['sport']\n",
+    "nb_compagnie = companies['mu']\n",
     "\n",
     "def load_files(nb_compagnie):\n",
     "    targets = pd.DataFrame()\n",
@@ -632,13 +652,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 27,
    "id": "3c911274-0ebd-49af-9487-26524ba20e74",
    "metadata": {},
    "outputs": [],
    "source": [
     "\n",
-    "def target_description(targets):\n",
+    "def target_description(targets, type_of_activity):\n",
     "\n",
     "    describe_target = targets.groupby('number_company').agg(\n",
     "        prop_target_jeune=('target_jeune', lambda x: (x.sum() / x.count())*100),\n",
@@ -665,12 +685,13 @@
     "    # Adding a legend\n",
     "    plot.legend([\"Youth\", \"School\", \"Enterprise\", \"Family\", \"Optin\", \"Optout\", \"Newsletter\", \"Subscriber\"], title=\"Target Category\")\n",
     "\n",
+    "    # save_file_s3(\"target_category_proportion_\", type_of_activity)\n",
     "    return plot"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 28,
    "id": "af62ecef-9120-4107-af3e-512588a96800",
    "metadata": {},
    "outputs": [
@@ -680,7 +701,7 @@
        "<Axes: title={'center': 'Distribution of Targets by Category'}, xlabel='Company Number', ylabel='Target Proportion'>"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -696,7 +717,7 @@
     }
    ],
    "source": [
-    "target_description(targets)"
+    "target_description(targets, 'sport')"
    ]
   },
   {