{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bbfa9fa9-7275-4a00-ad8c-a156298b18e9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages/pandas/core/computation/expressions.py:21: UserWarning: Pandas requires version '2.8.0' or newer of 'numexpr' (version '2.7.3' currently installed).\n",
      "  from pandas.core.computation.check import NUMEXPR_INSTALLED\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import boto3 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e53e9553-fb5e-478f-b4fb-5b9db154a703",
   "metadata": {},
   "outputs": [],
   "source": [
    "s3 = boto3.resource('s3')\n",
    "bucket_name = 'dev-cucumbers'\n",
    "bucket = s3.Bucket(bucket_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "79cfbf19",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = 'eimpara/ARIMA'\n",
    "table_names = []\n",
    "\n",
    "for obj in bucket.objects.filter(Prefix=path):\n",
    "    table_name = obj.key.split('/')[-1]\n",
    "    if len(table_name) > 0:\n",
    "        table_names.append(table_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "77a40409",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1692958078682143.2_0.csv',\n",
       " '1692958078682143.2_1.csv',\n",
       " '1692958078682143.2_2.csv',\n",
       " '1692958078682143.2_3.csv',\n",
       " '1692958078682143.2_4.csv',\n",
       " '1692958078682143.2_5.csv',\n",
       " '1692958078682143.2_6.csv',\n",
       " '1692958078682143.2_7.csv',\n",
       " '1692958078682143.2_8.csv',\n",
       " '1692958078682143.2_9.csv',\n",
       " '1697479703766685.2_0.csv',\n",
       " '1697479703766685.2_1.csv',\n",
       " '1697479703766685.2_2.csv',\n",
       " '1697479703766685.2_3.csv',\n",
       " '1697479703766685.2_4.csv',\n",
       " '1697479703766685.2_5.csv',\n",
       " '1697479703766685.2_6.csv',\n",
       " '1697479703766685.2_7.csv',\n",
       " '1699025023892356.8_0.csv',\n",
       " '1699025023892356.8_1.csv',\n",
       " '1699025023892356.8_2.csv',\n",
       " '1699025023892356.8_3.csv',\n",
       " '1699025023892356.8_4.csv',\n",
       " '1699025023892356.8_5.csv',\n",
       " '1699025023892356.8_6.csv',\n",
       " '1699025969000250.5_0.csv',\n",
       " '1699025969000250.5_1.csv',\n",
       " '1699025969000250.5_2.csv',\n",
       " '1699025969000250.5_3.csv',\n",
       " '1699028268094845.8_0.csv',\n",
       " '1699028268094845.8_1.csv',\n",
       " '1699028268094845.8_2.csv',\n",
       " '1699028268094845.8_3.csv',\n",
       " '1699306048173382.2_0.csv',\n",
       " '1699306048173382.2_1.csv',\n",
       " '1699306048173382.2_2.csv',\n",
       " '1699306048173382.2_3.csv',\n",
       " '1699306048173382.2_4.csv',\n",
       " 'Positive_Sign_table_for_clustering_25Aug23.csv']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "429b9ff7",
   "metadata": {},
   "outputs": [],
   "source": [
    "obj = bucket.Object(f'{path}/{table_name}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "27693843",
   "metadata": {},
   "outputs": [
    {
     "ename": "NoSuchKey",
     "evalue": "An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNoSuchKey\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/boto3/resources/factory.py:580\u001b[0m, in \u001b[0;36mResourceFactory._create_action.<locals>.do_action\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    579\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdo_action\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 580\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[43maction\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    582\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mload\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m    583\u001b[0m         \u001b[38;5;66;03m# Clear cached data. It will be reloaded the next\u001b[39;00m\n\u001b[1;32m    584\u001b[0m         \u001b[38;5;66;03m# time that an attribute is accessed.\u001b[39;00m\n\u001b[1;32m    585\u001b[0m         \u001b[38;5;66;03m# TODO: Make this configurable in the future?\u001b[39;00m\n\u001b[1;32m    586\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmeta\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/boto3/resources/action.py:88\u001b[0m, in \u001b[0;36mServiceAction.__call__\u001b[0;34m(self, parent, *args, **kwargs)\u001b[0m\n\u001b[1;32m     79\u001b[0m params\u001b[38;5;241m.\u001b[39mupdate(kwargs)\n\u001b[1;32m     81\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[1;32m     82\u001b[0m     \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCalling \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m with \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     83\u001b[0m     parent\u001b[38;5;241m.\u001b[39mmeta\u001b[38;5;241m.\u001b[39mservice_name,\n\u001b[1;32m     84\u001b[0m     operation_name,\n\u001b[1;32m     85\u001b[0m     params,\n\u001b[1;32m     86\u001b[0m )\n\u001b[0;32m---> 88\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmeta\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     90\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mResponse: \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m'\u001b[39m, response)\n\u001b[1;32m     92\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response_handler(parent, params, response)\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/botocore/client.py:535\u001b[0m, in \u001b[0;36mClientCreator._create_api_method.<locals>._api_call\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    531\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m    532\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpy_operation_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m() only accepts keyword arguments.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    533\u001b[0m     )\n\u001b[1;32m    534\u001b[0m \u001b[38;5;66;03m# The \"self\" in this scope is referring to the BaseClient.\u001b[39;00m\n\u001b[0;32m--> 535\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_api_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/botocore/client.py:980\u001b[0m, in \u001b[0;36mBaseClient._make_api_call\u001b[0;34m(self, operation_name, api_params)\u001b[0m\n\u001b[1;32m    978\u001b[0m     error_code \u001b[38;5;241m=\u001b[39m parsed_response\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCode\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    979\u001b[0m     error_class \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexceptions\u001b[38;5;241m.\u001b[39mfrom_code(error_code)\n\u001b[0;32m--> 980\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m error_class(parsed_response, operation_name)\n\u001b[1;32m    981\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    982\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parsed_response\n",
      "\u001b[0;31mNoSuchKey\u001b[0m: An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist."
     ]
    }
   ],
   "source": [
    "obj.get()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8b1d4caa",
   "metadata": {},
   "outputs": [
    {
     "ename": "NoSuchKey",
     "evalue": "An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNoSuchKey\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[8], line 5\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m table_name \u001b[38;5;129;01min\u001b[39;00m table_names:\n\u001b[1;32m      4\u001b[0m     obj \u001b[38;5;241m=\u001b[39m bucket\u001b[38;5;241m.\u001b[39mObject(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtable_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 5\u001b[0m     table_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(\u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBody\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m      6\u001b[0m     merged_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mconcat([merged_df,table_data])\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/boto3/resources/factory.py:580\u001b[0m, in \u001b[0;36mResourceFactory._create_action.<locals>.do_action\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    579\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdo_action\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 580\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[43maction\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    582\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mload\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m    583\u001b[0m         \u001b[38;5;66;03m# Clear cached data. It will be reloaded the next\u001b[39;00m\n\u001b[1;32m    584\u001b[0m         \u001b[38;5;66;03m# time that an attribute is accessed.\u001b[39;00m\n\u001b[1;32m    585\u001b[0m         \u001b[38;5;66;03m# TODO: Make this configurable in the future?\u001b[39;00m\n\u001b[1;32m    586\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmeta\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/boto3/resources/action.py:88\u001b[0m, in \u001b[0;36mServiceAction.__call__\u001b[0;34m(self, parent, *args, **kwargs)\u001b[0m\n\u001b[1;32m     79\u001b[0m params\u001b[38;5;241m.\u001b[39mupdate(kwargs)\n\u001b[1;32m     81\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[1;32m     82\u001b[0m     \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCalling \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m with \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     83\u001b[0m     parent\u001b[38;5;241m.\u001b[39mmeta\u001b[38;5;241m.\u001b[39mservice_name,\n\u001b[1;32m     84\u001b[0m     operation_name,\n\u001b[1;32m     85\u001b[0m     params,\n\u001b[1;32m     86\u001b[0m )\n\u001b[0;32m---> 88\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmeta\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     90\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mResponse: \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m'\u001b[39m, response)\n\u001b[1;32m     92\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response_handler(parent, params, response)\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/botocore/client.py:535\u001b[0m, in \u001b[0;36mClientCreator._create_api_method.<locals>._api_call\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    531\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m    532\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpy_operation_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m() only accepts keyword arguments.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    533\u001b[0m     )\n\u001b[1;32m    534\u001b[0m \u001b[38;5;66;03m# The \"self\" in this scope is referring to the BaseClient.\u001b[39;00m\n\u001b[0;32m--> 535\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_api_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/python3/lib/python3.10/site-packages/botocore/client.py:980\u001b[0m, in \u001b[0;36mBaseClient._make_api_call\u001b[0;34m(self, operation_name, api_params)\u001b[0m\n\u001b[1;32m    978\u001b[0m     error_code \u001b[38;5;241m=\u001b[39m parsed_response\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCode\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    979\u001b[0m     error_class \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexceptions\u001b[38;5;241m.\u001b[39mfrom_code(error_code)\n\u001b[0;32m--> 980\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m error_class(parsed_response, operation_name)\n\u001b[1;32m    981\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    982\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parsed_response\n",
      "\u001b[0;31mNoSuchKey\u001b[0m: An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist."
     ]
    }
   ],
   "source": [
    "merged_df = pd.DataFrame() \n",
    "\n",
    "for table_name in table_names:\n",
    "    obj = bucket.Object(f'{path}/{table_name}')\n",
    "    table_data = pd.read_csv(obj.get()['Body'])\n",
    "    merged_df = pd.concat([merged_df,table_data])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "34637e13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(219, 11)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a219581d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_dataframe_s3(df):\n",
    "    s3 = boto3.client('s3')\n",
    "    bucket_name = 'dev-cucumbers'\n",
    "    filepath = \"eimpara/ARIMA/Positive_Sign_table_for_clustering_25Aug23.csv\"\n",
    "    csv_buffer = df.to_csv(index=False).encode('utf-8')\n",
    "    # Save the CSV file to S3\n",
    "    s3.put_object(Body=csv_buffer, Bucket=bucket_name, Key=filepath)\n",
    "    print(f\"Table saved to S3 bucket: {bucket_name}, with file name: {filepath}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "758c2b1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "save_dataframe_s3(merged_df)"
   ]
  }
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