{
  "id": 113759,
  "title": "Tips for R Beginners when handling large data",
  "url": "/competitions/ashrae-energy-prediction/discussion/113759",
  "author_name": "",
  "post_date": "2019-10-22T01:55:01.414725400Z",
  "votes": 1,
  "comment_count": 6,
  "views": 0,
  "content": "<p>Hey guys!</p>\n\n<p>Although I find many python tips shared by kagglers, it is kid of \"rare\" to see technical tips for R users especially these days ;(</p>\n\n<p>so here are couple of my go-to tips/functions to handle large dataset.</p>\n\n<ul>\n<li><code>gc()</code>: garbage collection function. this function shows us basic memory usage info and release unused memory!</li>\n<li><code>object_size()</code>: this outputs the size of specific object.</li>\n<li>convert numeric data into integer: this will help you reduce the size of data you are handling.</li>\n</ul>\n\n<p>Here are my basic techniques. I hope this will help R beginners like me. </p>\n\n<p>I would love to know your knowledges! so... feel free to share in this thread!!\nThanks.</p>\n\n<p>KA</p>",
  "messages": [
    {
      "id": "654532",
      "postDate": "10/22/2019 01:55:01",
      "content": "<p>Hey guys!</p>\n\n<p>Although I find many python tips shared by kagglers, it is kid of \"rare\" to see technical tips for R users especially these days ;(</p>\n\n<p>so here are couple of my go-to tips/functions to handle large dataset.</p>\n\n<ul>\n<li><code>gc()</code>: garbage collection function. this function shows us basic memory usage info and release unused memory!</li>\n<li><code>object_size()</code>: this outputs the size of specific object.</li>\n<li>convert numeric data into integer: this will help you reduce the size of data you are handling.</li>\n</ul>\n\n<p>Here are my basic techniques. I hope this will help R beginners like me. </p>\n\n<p>I would love to know your knowledges! so... feel free to share in this thread!!\nThanks.</p>\n\n<p>KA</p>",
      "rawMarkdown": "Hey guys!\n\nAlthough I find many python tips shared by kagglers, it is kid of \"rare\" to see technical tips for R users especially these days ;(\n\nso here are couple of my go-to tips/functions to handle large dataset.\n\n+ `gc()`: garbage collection function. this function shows us basic memory usage info and release unused memory!\n+ `object_size()`: this outputs the size of specific object.\n+ convert numeric data into integer: this will help you reduce the size of data you are handling.\n\nHere are my basic techniques. I hope this will help R beginners like me. \n\nI would love to know your knowledges! so... feel free to share in this thread!!\nThanks.\n\nKA",
      "votes": null
    },
    {
      "id": "654534",
      "postDate": "10/22/2019 02:12:58",
      "content": "<p>having more ram helps no matter what you are using ;)</p>",
      "rawMarkdown": "having more ram helps no matter what you are using ;)",
      "votes": null
    },
    {
      "id": "654542",
      "postDate": "10/22/2019 02:37:55",
      "content": "<p>True. True.\nBut my laptop I'm using rn is not that great. I do encounter situations such as 'R session aborted', which is a nightmare for R users haha</p>",
      "rawMarkdown": "True. True.\nBut my laptop I'm using rn is not that great. I do encounter situations such as 'R session aborted', which is a nightmare for R users haha",
      "votes": null
    },
    {
      "id": "654560",
      "postDate": "10/22/2019 02:57:31",
      "content": "<p>I'm using R too. I have 48GB of ram and it makes things a lot easier.</p>",
      "rawMarkdown": "I'm using R too. I have 48GB of ram and it makes things a lot easier.",
      "votes": null
    },
    {
      "id": "654568",
      "postDate": "10/22/2019 03:10:01",
      "content": "<p>Sounds very nice.</p>",
      "rawMarkdown": "Sounds very nice.",
      "votes": null
    },
    {
      "id": "654707",
      "postDate": "10/22/2019 07:48:15",
      "content": "<p>Free yourself from the R wrappers and convert it to python while it's still time! lol jk</p>",
      "rawMarkdown": "Free yourself from the R wrappers and convert it to python while it's still time! lol jk",
      "votes": null
    },
    {
      "id": "654713",
      "postDate": "10/22/2019 07:58:16",
      "content": "<p>haha you got the point!! :)</p>",
      "rawMarkdown": "haha you got the point!! :)",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 654534,
      "author_name": "abednadir",
      "author_url": "",
      "post_date": "10/22/2019 02:12:58",
      "content": "<p>having more ram helps no matter what you are using ;)</p>",
      "votes": null,
      "replies": [
        {
          "id": 654542,
          "author_name": "koki25ando",
          "author_url": "",
          "post_date": "10/22/2019 02:37:55",
          "content": "<p>True. True.\nBut my laptop I'm using rn is not that great. I do encounter situations such as 'R session aborted', which is a nightmare for R users haha</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 654560,
          "author_name": "abednadir",
          "author_url": "",
          "post_date": "10/22/2019 02:57:31",
          "content": "<p>I'm using R too. I have 48GB of ram and it makes things a lot easier.</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 654568,
          "author_name": "koki25ando",
          "author_url": "",
          "post_date": "10/22/2019 03:10:01",
          "content": "<p>Sounds very nice.</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 654707,
      "author_name": "dhacker",
      "author_url": "",
      "post_date": "10/22/2019 07:48:15",
      "content": "<p>Free yourself from the R wrappers and convert it to python while it's still time! lol jk</p>",
      "votes": null,
      "replies": [
        {
          "id": 654713,
          "author_name": "koki25ando",
          "author_url": "",
          "post_date": "10/22/2019 07:58:16",
          "content": "<p>haha you got the point!! :)</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "654532": "Hey guys!\n\nAlthough I find many python tips shared by kagglers, it is kid of \"rare\" to see technical tips for R users especially these days ;(\n\nso here are couple of my go-to tips/functions to handle large dataset.\n\n+ `gc()`: garbage collection function. this function shows us basic memory usage info and release unused memory!\n+ `object_size()`: this outputs the size of specific object.\n+ convert numeric data into integer: this will help you reduce the size of data you are handling.\n\nHere are my basic techniques. I hope this will help R beginners like me. \n\nI would love to know your knowledges! so... feel free to share in this thread!!\nThanks.\n\nKA",
    "654534": "having more ram helps no matter what you are using ;)",
    "654542": "True. True.\nBut my laptop I'm using rn is not that great. I do encounter situations such as 'R session aborted', which is a nightmare for R users haha",
    "654560": "I'm using R too. I have 48GB of ram and it makes things a lot easier.",
    "654568": "Sounds very nice.",
    "654707": "Free yourself from the R wrappers and convert it to python while it's still time! lol jk",
    "654713": "haha you got the point!! :)"
  },
  "source": "meta"
}