{
  "id": 404810,
  "title": "Submission Scoring Error",
  "url": "/competitions/benetech-making-graphs-accessible/discussion/404810",
  "author_name": "",
  "post_date": "2023-04-25T02:21:52.589334600Z",
  "votes": 1,
  "comment_count": 2,
  "views": 0,
  "content": "<p>I can't make a submission in this competition<br>\nI made a simple test submission(with stubs instead of real data),<br>\nchecked the output file format many times. <br>\nIt looks like some kind of error unrelated to the output file format.<br>\nEvery time I get the error \"Submission Scoring Error\". <br>\nNeed help</p>\n<pre><code> pandas  pd\n os\n csv\n ():\n    img_folder =   \n    col0=[]\n    col1=[]\n    col2=[]\n    flist = (os.listdir(img_folder))\n     index, imgname  (flist):\n         index%==: (index, , imgname)\n        fnam = os.path.splitext(imgname)[]\n        col0.append(fnam+)\n        col1.append()\n        col2.append()\n        col0.append(fnam+)\n        col1.append()\n        col2.append()\n    csv_fullname = os.getcwd()+ \n    submission = pd.DataFrame({: col0, : col1, : col2})        \n    submission.to_csv(csv_fullname, sep=, index=)  \n    ()\n\ntestSubmit()\n</code></pre>\n<p>Here is the output file</p>",
  "messages": [
    {
      "id": "2234206",
      "postDate": "04/25/2023 02:21:52",
      "content": "<p>I can't make a submission in this competition<br>\nI made a simple test submission(with stubs instead of real data),<br>\nchecked the output file format many times. <br>\nIt looks like some kind of error unrelated to the output file format.<br>\nEvery time I get the error \"Submission Scoring Error\". <br>\nNeed help</p>\n<pre><code> pandas  pd\n os\n csv\n ():\n    img_folder =   \n    col0=[]\n    col1=[]\n    col2=[]\n    flist = (os.listdir(img_folder))\n     index, imgname  (flist):\n         index%==: (index, , imgname)\n        fnam = os.path.splitext(imgname)[]\n        col0.append(fnam+)\n        col1.append()\n        col2.append()\n        col0.append(fnam+)\n        col1.append()\n        col2.append()\n    csv_fullname = os.getcwd()+ \n    submission = pd.DataFrame({: col0, : col1, : col2})        \n    submission.to_csv(csv_fullname, sep=, index=)  \n    ()\n\ntestSubmit()\n</code></pre>\n<p>Here is the output file</p>",
      "rawMarkdown": "I can't make a submission in this competition\nI made a simple test submission(with stubs instead of real data),\nchecked the output file format many times. \nIt looks like some kind of error unrelated to the output file format.\nEvery time I get the error \"Submission Scoring Error\". \nNeed help\n\n```python\nimport pandas as pd\nimport os\nimport csv\ndef testSubmit():\n    img_folder = \"/kaggle/input/benetech-making-graphs-accessible/train/images\"  \n    col0=[]\n    col1=[]\n    col2=[]\n    flist = sorted(os.listdir(img_folder))\n    for index, imgname in enumerate(flist):\n        if index%1000==0: print(index, \" \", imgname)\n        fnam = os.path.splitext(imgname)[0]\n        col0.append(fnam+\"_x\")\n        col1.append('0.0;1.0')\n        col2.append('vertical_bar')\n        col0.append(fnam+\"_y\")\n        col1.append('0.0;1.0')\n        col2.append('vertical_bar')\n    csv_fullname = os.getcwd()+'/submission.csv' \n    submission = pd.DataFrame({'id': col0, 'data_series': col1, 'chart_type': col2})        \n    submission.to_csv(csv_fullname, sep=',', index=False)  \n    print(\"Done\")\n\ntestSubmit()\n```\n\n\nHere is the output file",
      "votes": null
    },
    {
      "id": "2234237",
      "postDate": "04/25/2023 03:39:44",
      "content": "<p>You should be using the test set for submission.  It looks like you are using the train set in your definition of <code>img_folder</code>.</p>",
      "rawMarkdown": "You should be using the test set for submission.  It looks like you are using the train set in your definition of `img_folder`.",
      "votes": null
    },
    {
      "id": "2234245",
      "postDate": "04/25/2023 03:53:48",
      "content": "<p>Thank you, it worked</p>",
      "rawMarkdown": "Thank you, it worked",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2234237,
      "author_name": "pabyrnes",
      "author_url": "",
      "post_date": "04/25/2023 03:39:44",
      "content": "<p>You should be using the test set for submission.  It looks like you are using the train set in your definition of <code>img_folder</code>.</p>",
      "votes": null,
      "replies": [
        {
          "id": 2234245,
          "author_name": "anuarsenk",
          "author_url": "",
          "post_date": "04/25/2023 03:53:48",
          "content": "<p>Thank you, it worked</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2234206": "I can't make a submission in this competition\nI made a simple test submission(with stubs instead of real data),\nchecked the output file format many times. \nIt looks like some kind of error unrelated to the output file format.\nEvery time I get the error \"Submission Scoring Error\". \nNeed help\n\n```python\nimport pandas as pd\nimport os\nimport csv\ndef testSubmit():\n    img_folder = \"/kaggle/input/benetech-making-graphs-accessible/train/images\"  \n    col0=[]\n    col1=[]\n    col2=[]\n    flist = sorted(os.listdir(img_folder))\n    for index, imgname in enumerate(flist):\n        if index%1000==0: print(index, \" \", imgname)\n        fnam = os.path.splitext(imgname)[0]\n        col0.append(fnam+\"_x\")\n        col1.append('0.0;1.0')\n        col2.append('vertical_bar')\n        col0.append(fnam+\"_y\")\n        col1.append('0.0;1.0')\n        col2.append('vertical_bar')\n    csv_fullname = os.getcwd()+'/submission.csv' \n    submission = pd.DataFrame({'id': col0, 'data_series': col1, 'chart_type': col2})        \n    submission.to_csv(csv_fullname, sep=',', index=False)  \n    print(\"Done\")\n\ntestSubmit()\n```\n\n\nHere is the output file",
    "2234237": "You should be using the test set for submission.  It looks like you are using the train set in your definition of `img_folder`.",
    "2234245": "Thank you, it worked"
  },
  "source": "meta"
}