{
  "id": 70724,
  "title": "Quick Flatten out Datasets using Pandas and Pyspark",
  "url": "/competitions/ga-customer-revenue-prediction/discussion/70724",
  "author_name": "Khanna",
  "post_date": "2018-11-06T19:53:54.706000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Friends, please look up this NB : <code>https://www.kaggle.com/khanna/quick-pandas-pyspark-flatten-out-datajsons</code> for quickly fighting out flattening those JSON data / attribs in training / test sets. All steps on setting / working with pyspark in there!</p>",
  "messages": [
    {
      "id": 416521,
      "postDate": "2018-11-06T19:53:54.707Z",
      "content": "<p>Friends, please look up this NB : <code>https://www.kaggle.com/khanna/quick-pandas-pyspark-flatten-out-datajsons</code> for quickly fighting out flattening those JSON data / attribs in training / test sets. All steps on setting / working with pyspark in there!</p>",
      "rawMarkdown": "Friends, please look up this NB : `https://www.kaggle.com/khanna/quick-pandas-pyspark-flatten-out-datajsons` for quickly fighting out flattening those JSON data / attribs in training / test sets. All steps on setting / working with pyspark in there!",
      "votes": 1
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "416521": "Friends, please look up this NB : `https://www.kaggle.com/khanna/quick-pandas-pyspark-flatten-out-datajsons` for quickly fighting out flattening those JSON data / attribs in training / test sets. All steps on setting / working with pyspark in there!"
  }
}