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{
"alias": "video/3760/introduction-to-open-and-collaborative-data-analy",
"category": "PyGotham 2015",
"copyright_text": "CC BY-SA",
"description": "Data munging is typically an involved and noisy process, but pandas --\nespecially using the notebook format -- make it easy to share and\nreproduce the process of analyzing data, from munging to analysis and\neven exploratory visualization! In this talk you'll get a glimpse of the\npandas workflow and some tips for getting the most out of its use in the\nIPython/Jupyter notebook.\n",
"duration": 2221,
"id": 3760,
"language": "eng",
"quality_notes": "",
"recorded": "2015-08-16",
"slug": "introduction-to-open-and-collaborative-data-analy",
"speakers": [
"Melissa Lewis"
],
"summary": "",
"tags": [],
"thumbnail_url": "https://archive.org/services/img/pyvideo_3760___introduction_to_open_and_collaborative_data_analys",
"title": "introduction to open and collaborative data analysis with pandas and IPython/Jupyter Notebook",
"videos": [
{
"type": "archive.org",
"url": "https://archive.org/details/pyvideo_3760___introduction_to_open_and_collaborative_data_analys"
},
{
"type": "mp4",
"url": "http://64966d3674e0a64d8f4a-47c94b14ef8e1f83d5390cdb0629c6ed.r53.cf2.rackcdn.com/pygotham-2015/3760_introduction_to_open_and_collaborative_data_analys.mp4"
},
{
"length": 0,
"type": "youtube",
"url": "http://youtu.be/0yOhWKs-sAE"
}
]
}
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