TEST_ML-Copy3.ipynb

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   "source": [
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "pd.set_option(\"display.max_columns\", 100)\n",
    "DATA_PATH = Path.cwd().parent / \"ML project\" \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = pd.read_csv(\n",
    "    DATA_PATH / \"train.csv\", \n",
    "    index_col=\"tripid\"\n",
    ")\n",
    "submission_file_list = ['mlp_9762_my_submission',\n",
    "                        'mlp_9766_my_submission',\n",
    "                        'mlp_kfold_9770_my_submission',\n",
    "                        'mlp_kfold_9782_my_submission',\n",
    "                       'mlp_my_submission',\n",
    "                       'mlp_kfold_state33_9822_my_submission',\n",
    "                       'my_submission_test_try',\n",
    "                       'xgboost_9732_my_submission',\n",
    "                       'xgboost_9734_my_submission',\n",
    "                       'xgboost_my_submission',\n",
    "                        'my_submission_9716',\n",
    "                        'kfold_fillna0_state2_my_submission']\n",
    "sub_df_list = []\n",
    "for i in submission_file_list:\n",
    "    fileName = \"tosubmit\\\\\"+i+\".csv\"\n",
    "    train_df = pd.read_csv(\n",
    "        DATA_PATH / fileName, \n",
    "        index_col=\"tripid\"\n",
    "    )\n",
    "    sub_df_list.append([i,train_df])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "submisionFile = pd.read_csv(\n",
    "    DATA_PATH / 'my_submission.csv', \n",
    "    index_col=\"tripid\"\n",
    ")\n",
    "for i in sub_df_list:\n",
    "    if(submisionFile.equals(i[1])):\n",
    "        print(i[0])"
   ]
  },
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    "\n"
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