{
  "id": 25212,
  "title": "Request regarding consecutive/duplicate rows",
  "url": "/competitions/bosch-production-line-performance/discussion/25212",
  "author_name": "",
  "post_date": "2016-11-08T02:32:13.390Z",
  "votes": 19,
  "comment_count": 3,
  "views": 766,
  "content": "<p>I have a request for Kaggle and Bosch. After the competition is over four days from now, would it be possible for Kaggle and/or Bosch to give an explanation of the phenomena of consecutive rows that are duplicates (or near duplicates). Was this the result of some quirk of data preparation?  Or does it represent some underlying aspect of the manufacturing process?  Was this a non-useful finding or a useful finding? Many of us have spent many hours digging into the data. I&#8217;ve enjoyed this competition, and it would personally give me a better sense of closure if Kaggle and/or Bosch could shed more light on this to the extent possible.</p>\n\n<p>Thanks,</p>\n\n<p>Steve</p>",
  "messages": [
    {
      "id": "143316",
      "postDate": "11/08/2016 02:32:13",
      "content": "<p>I have a request for Kaggle and Bosch. After the competition is over four days from now, would it be possible for Kaggle and/or Bosch to give an explanation of the phenomena of consecutive rows that are duplicates (or near duplicates). Was this the result of some quirk of data preparation?  Or does it represent some underlying aspect of the manufacturing process?  Was this a non-useful finding or a useful finding? Many of us have spent many hours digging into the data. I&#8217;ve enjoyed this competition, and it would personally give me a better sense of closure if Kaggle and/or Bosch could shed more light on this to the extent possible.</p>\n\n<p>Thanks,</p>\n\n<p>Steve</p>",
      "rawMarkdown": "I have a request for Kaggle and Bosch. After the competition is over four days from now, would it be possible for Kaggle and/or Bosch to give an explanation of the phenomena of consecutive rows that are duplicates (or near duplicates). Was this the result of some quirk of data preparation?  Or does it represent some underlying aspect of the manufacturing process?  Was this a non-useful finding or a useful finding? Many of us have spent many hours digging into the data. I’ve enjoyed this competition, and it would personally give me a better sense of closure if Kaggle and/or Bosch could shed more light on this to the extent possible.\r\n\r\nThanks,\r\n\r\nSteve",
      "votes": null
    },
    {
      "id": "144063",
      "postDate": "11/12/2016 03:00:40",
      "content": "<p>Just checking on this again. Thanks!</p>",
      "rawMarkdown": "Just checking on this again. Thanks!",
      "votes": null
    },
    {
      "id": "144143",
      "postDate": "11/12/2016 15:14:06",
      "content": "<p>Me too - I would like to know if the duplicates or near duplicated are an artifact</p>\n\n<p>I am not sure how useful it will be for fault finding - if all we are doing is finding similar process pathways at a similar time to known faults - still it was interesting dealing with relatively large data.</p>\n\n<p>Well done Steve by the way!</p>",
      "rawMarkdown": "Me too - I would like to know if the duplicates or near duplicated are an artifact\r\n\r\nI am not sure how useful it will be for fault finding - if all we are doing is finding similar process pathways at a similar time to known faults - still it was interesting dealing with relatively large data.\r\n\r\nWell done Steve by the way!",
      "votes": null
    },
    {
      "id": "144203",
      "postDate": "11/13/2016 00:37:10",
      "content": "<p>Would have been more challenging if we were to predict when the parts needed removing from the production lines :)</p>",
      "rawMarkdown": "Would have been more challenging if we were to predict when the parts needed removing from the production lines :)",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 144063,
      "author_name": "breakfastpirate",
      "author_url": "",
      "post_date": "11/12/2016 03:00:40",
      "content": "<p>Just checking on this again. Thanks!</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 144143,
      "author_name": "scirpus",
      "author_url": "",
      "post_date": "11/12/2016 15:14:06",
      "content": "<p>Me too - I would like to know if the duplicates or near duplicated are an artifact</p>\n\n<p>I am not sure how useful it will be for fault finding - if all we are doing is finding similar process pathways at a similar time to known faults - still it was interesting dealing with relatively large data.</p>\n\n<p>Well done Steve by the way!</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 144203,
      "author_name": "",
      "author_url": "",
      "post_date": "11/13/2016 00:37:10",
      "content": "<p>Would have been more challenging if we were to predict when the parts needed removing from the production lines :)</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "143316": "I have a request for Kaggle and Bosch. After the competition is over four days from now, would it be possible for Kaggle and/or Bosch to give an explanation of the phenomena of consecutive rows that are duplicates (or near duplicates). Was this the result of some quirk of data preparation?  Or does it represent some underlying aspect of the manufacturing process?  Was this a non-useful finding or a useful finding? Many of us have spent many hours digging into the data. I’ve enjoyed this competition, and it would personally give me a better sense of closure if Kaggle and/or Bosch could shed more light on this to the extent possible.\r\n\r\nThanks,\r\n\r\nSteve",
    "144063": "Just checking on this again. Thanks!",
    "144143": "Me too - I would like to know if the duplicates or near duplicated are an artifact\r\n\r\nI am not sure how useful it will be for fault finding - if all we are doing is finding similar process pathways at a similar time to known faults - still it was interesting dealing with relatively large data.\r\n\r\nWell done Steve by the way!",
    "144203": "Would have been more challenging if we were to predict when the parts needed removing from the production lines :)"
  },
  "source": "meta"
}