alexander-hendorf-data-analysis-and-map-reduce-with-mongodb-and-pymongo.json

{
  "copyright_text": "Creative Commons Attribution license (reuse allowed)",
  "description": "Alexander Hendorf - Data Analysis and Map-Reduce with mongoDB and pymongo\n[EuroPython 2015]\n[22 July 2015]\n[Bilbao, Euskadi, Spain]\n\nThe MongoDB aggregation framework provides a means to calculate\naggregated values without having to use map-reduce. While map-reduce\nis powerful, it is often more difficult than necessary for many simple\naggregation tasks, such as totaling or averaging field values.\n\nSee how to use the build-in data-aggregation-pipelines for averages,\nsummation, grouping, reshaping. See how to work with documents, sub-\ndocuments, grouping by year, month, day, etc.\n\nThis talk will give many (live) examples how to make the most of your\ndata with pymongo with a few lines of code.\n\nadded 28/07/15:\niPython notebook & sample data can be found in [this git][1]\n\n[1]: https://bitbucket.org/alanderex/ep2015-dataanalysis-with-mongodb",
  "duration": 2281,
  "language": "eng",
  "recorded": "2015-08-04",
  "related_urls": [
    "https://bitbucket.org/alanderex/ep2015-dataanalysis-with-mongodb"
  ],
  "speakers": [
    "Alexander Hendorf"
  ],
  "tags": [],
  "thumbnail_url": "https://i.ytimg.com/vi/O_pzz5X0s04/maxresdefault.jpg",
  "title": "Data Analysis and Map-Reduce with mongoDB and pymongo",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=O_pzz5X0s04"
    }
  ]
}