{
  "id": 343267,
  "title": "The difference between .apply(func) and .func()",
  "url": "/competitions/amex-default-prediction/discussion/343267",
  "author_name": "",
  "post_date": "2022-08-10T15:32:34.939575900Z",
  "votes": 3,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Hello,<br>\nI saw a lot of people avoid using .apply(function) for the data. Instead, they use .func() instantly (e.g. .mean() instead of .apply(pd.Series.mean))<br>\nJust want to know if there is a problem with the apply function as that I'm using it in my pipeline? </p>\n<p>Regards</p>",
  "messages": [
    {
      "id": "1893168",
      "postDate": "08/10/2022 15:32:34",
      "content": "<p>Hello,<br>\nI saw a lot of people avoid using .apply(function) for the data. Instead, they use .func() instantly (e.g. .mean() instead of .apply(pd.Series.mean))<br>\nJust want to know if there is a problem with the apply function as that I'm using it in my pipeline? </p>\n<p>Regards</p>",
      "rawMarkdown": "Hello,\nI saw a lot of people avoid using .apply(function) for the data. Instead, they use .func() instantly (e.g. .mean() instead of .apply(pd.Series.mean))\nJust want to know if there is a problem with the apply function as that I'm using it in my pipeline? \n\nRegards",
      "votes": null
    },
    {
      "id": "1893500",
      "postDate": "08/10/2022 21:41:52",
      "content": "<p>Apply often slows down the implementation process, considering the large size of the data, it is advised to avoid apply and rather use faster options that vectorize the process. </p>",
      "rawMarkdown": "Apply often slows down the implementation process, considering the large size of the data, it is advised to avoid apply and rather use faster options that vectorize the process.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1893500,
      "author_name": "ravi20076",
      "author_url": "",
      "post_date": "08/10/2022 21:41:52",
      "content": "<p>Apply often slows down the implementation process, considering the large size of the data, it is advised to avoid apply and rather use faster options that vectorize the process. </p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1893168": "Hello,\nI saw a lot of people avoid using .apply(function) for the data. Instead, they use .func() instantly (e.g. .mean() instead of .apply(pd.Series.mean))\nJust want to know if there is a problem with the apply function as that I'm using it in my pipeline? \n\nRegards",
    "1893500": "Apply often slows down the implementation process, considering the large size of the data, it is advised to avoid apply and rather use faster options that vectorize the process."
  },
  "source": "meta"
}