veyepar: pandas: Powerful data analysis tools for Python

Hi user

Admin Login:

Name: pandas: Powerful data analysis tools for Python
--client psf --show pycon_2012 --room E2 735 --force
Next: 6 The Journey to Give Every Scientist a Supercomputer

show more... Marks

Author(s):	Wes McKinney
Location	Track III (E2)
Date	mar Fri 09	Days Raw Files
Start	March 9, 2012, 5:20 p.m.	First Raw Start	March 8, 2012, 5:19 p.m.
Duration	00:40:00	Offset	1 day, 0:00:17
End	March 9, 2012, 6 p.m.	Last Raw End	March 8, 2012, 5:54 p.m.
Chapters	00:00
Total cuts_time	34 min.

http://us.pycon.org/2012/schedule/presentation/416/
raw-playlist raw-mp4-playlist encoded-files-playlist host public mp4 svg png

final audio

assets release.pdf pandas_Powerful_data_analysis_tools_for_Python.json
logs
Admin: episode episode list cut list raw files day marks day marks day image_files

State:
Locked:	clear this to unlock
Locked by:	user/process that locked.
Start:	initially scheduled time from master, adjusted to match reality
Duration:	length in hh:mm:ss
Name:	Video Title (shows in video search results)
Emails:	email(s) of the presenter(s)
Released:	has someone authorised pubication
Normalise:
Channelcopy:	m=mono, 01=copy left to right, 10=right to left, 00=ignore.
Thumbnail:	filename.png
Description:	pandas is a Python library providing fast, expressive data structures for working with structured or relational data sets. In addition to being used for general purpose data manipulation and data analysis, it has also been designed to enable Python to become a competitive statistical computing platform. In this talk, I will discuss the library's features and show a variety of topical examples. markdown
Comment:	<?xml version='1.0' encoding='UTF-8'?> <ns0:entry xmlns:ns0="http://www.w3.org/2005/Atom" xmlns:ns1="http://schemas.google.com/g/2005" xmlns:ns2="http://search.yahoo.com/mrss/" xmlns:ns3="http://gdata.youtube.com/schemas/2007" xmlns:ns4="http://purl.org/atom/app#"><ns0:category scheme="http://schemas.google.com/g/2005#kind" term="http://gdata.youtube.com/schemas/2007#video" /><ns0:category label="Education" scheme="http://gdata.youtube.com/schemas/2007/categories.cat" term="Education" /><ns0:category scheme="http://gdata.youtube.com/schemas/2007/keywords.cat" term="psf" /><ns0:category scheme="http://gdata.youtube.com/schemas/2007/keywords.cat" term="python pycon pycon2012" /><ns0:category scheme="http://gdata.youtube.com/schemas/2007/keywords.cat" term="pycon_2012" /><ns0:category scheme="http://gdata.youtube.com/schemas/2007/keywords.cat" term="WesMcKinney" /><ns0:id>http://gdata.youtube.com/feeds/api/videos/qbYYamU42Sw</ns0:id><ns0:author><ns0:name>NextDayVideo</ns0:name><ns0:uri>https://gdata.youtube.com/feeds/api/users/NextDayVideo</ns0:uri></ns0:author><ns0:content type="text">Wes McKinney pandas is a Python library providing fast, expressive data structures for working with structured or relational data sets. In addition to being used for general purpose data manipulation and data analysis, it has also been designed to en</ns0:content><ns0:updated>2012-03-13T03:10:04.000Z</ns0:updated><ns0:published>2012-03-13T03:10:04.000Z</ns0:published><ns1:comments><ns1:feedLink countHint="0" href="https://gdata.youtube.com/feeds/api/videos/qbYYamU42Sw/comments?client=ndv" rel="http://gdata.youtube.com/schemas/2007#comments" /></ns1:comments><ns2:group><ns2:keywords>psf, python pycon pycon2012, pycon_2012, WesMcKinney</ns2:keywords><ns2:description type="plain">Wes McKinney pandas is a Python library providing fast, expressive data structures for working with structured or relational data sets. In addition to being used for general purpose data manipulation and data analysis, it has also been designed to en</ns2:description><ns2:title type="plain">pandas: Powerful data analysis tools for Python</ns2:title><ns3:duration seconds="0" /><ns2:content duration="0" expression="full" isDefault="true" medium="video" type="application/x-shockwave-flash" url="https://www.youtube.com/v/qbYYamU42Sw?version=3&f=user_uploads&c=ndv&d=Aarb2r5skm2_yNTuKEinXdAO88HsQjpE1a8d1GxQnGDm&app=youtube_gdata" ns3:format="5" /><ns2:thumbnail height="360" time="00:00:00" url="http://i.ytimg.com/vi/qbYYamU42Sw/0.jpg" width="480" /><ns2:thumbnail height="90" time="00:00:00" url="http://i.ytimg.com/vi/qbYYamU42Sw/1.jpg" width="120" /><ns2:thumbnail height="90" time="00:00:00" url="http://i.ytimg.com/vi/qbYYamU42Sw/2.jpg" width="120" /><ns2:thumbnail height="90" time="00:00:00" url="http://i.ytimg.com/vi/qbYYamU42Sw/3.jpg" width="120" /><ns2:category label="Education" scheme="http://gdata.youtube.com/schemas/2007/categories.cat">Education</ns2:category><ns2:category scheme="http://gdata.youtube.com/schemas/2007/developertags.cat">psf</ns2:category><ns2:category scheme="http://gdata.youtube.com/schemas/2007/developertags.cat">python pycon pycon2012</ns2:category><ns2:category scheme="http://gdata.youtube.com/schemas/2007/developertags.cat">pycon_2012</ns2:category><ns2:category scheme="http://gdata.youtube.com/schemas/2007/developertags.cat">WesMcKinney</ns2:category><ns2:player url="https://www.youtube.com/watch?v=qbYYamU42Sw&feature=youtube_gdata_player" /></ns2:group><ns0:title type="text">pandas: Powerful data analysis tools for Python</ns0:title><ns4:control><ns4:draft>yes</ns4:draft><ns3:state name="processing" /></ns4:control><ns0:link href="https://www.youtube.com/watch?v=qbYYamU42Sw&feature=youtube_gdata" rel="alternate" type="text/html" /><ns0:link href="https://gdata.youtube.com/feeds/api/videos/qbYYamU42Sw/responses?client=ndv" rel="http://gdata.youtube.com/schemas/2007#video.responses" type="application/atom+xml" /><ns0:link href="https://gdata.youtube.com/feeds/api/videos/qbYYamU42Sw/ratings?client=ndv" rel="http://gdata.youtube.com/schemas/2007#video.ratings" type="application/atom+xml" /><ns0:link href="https://gdata.youtube.com/feeds/api/videos/qbYYamU42Sw/complaints?client=ndv" rel="http://gdata.youtube.com/schemas/2007#video.complaints" type="application/atom+xml" /><ns0:link href="https://gdata.youtube.com/feeds/api/videos/qbYYamU42Sw/related?client=ndv" rel="http://gdata.youtube.com/schemas/2007#video.related" type="application/atom+xml" /><ns0:link href="https://gdata.youtube.com/feeds/api/users/nextdayvideo/uploads/qbYYamU42Sw?client=ndv" rel="self" type="application/atom+xml" /><ns0:link href="https://gdata.youtube.com/feeds/api/users/nextdayvideo/uploads/qbYYamU42Sw?client=ndv" rel="edit" type="application/atom+xml" /></ns0:entry> production notes

2012-03-08/17:19:43.dv Apply: 17:19:43 - 17:54:19 ( 00:34:36 ) S: 17:19:43 - E: 17:54:19 D: 00:34:36 show more...

vlc ~/Videos/veyepar/psf/pycon_2012/dv/E2/2012-03-08/17:19:43.dv :start-time=00.0 --audio-desync=0

	Raw File	Cut List
	March 8, 2012, 5:19 p.m.		seconds: 0.0 Wall: 17:19:43
Duration	00:34:36
	March 8, 2012, 5:54 p.m.		seconds: 0.0 Wall: 17:19:43
Comments:
mp4 mp4.m3u	dv.m3u	Split: Sequence:: delete

audio viz

2012-03-08/17:54:20.dv Apply: 17:54:20 - 17:54:49 ( 00:00:29 ) S: 17:54:20 - E: 17:54:49 D: 00:00:29 show more...

vlc ~/Videos/veyepar/psf/pycon_2012/dv/E2/2012-03-08/17:54:20.dv :start-time=00.0 --audio-desync=0

	Raw File	Cut List
	March 8, 2012, 5:54 p.m.		seconds: 0.0 Wall: 17:54:20
Duration	00:00:29
	March 8, 2012, 5:54 p.m.		seconds: 0.0 Wall: 17:54:20
Comments:
mp4 mp4.m3u	dv.m3u	Split: Sequence:: delete

audio viz

Rf filename:	root is .../show/dv/location/, example: 2013-03-13/13:13:30.dv
Sequence:
get this:	check and save to add this

2012-03-08/17:19:43.dv
audio viz

audio viz

2012-03-08/17:54:20.dv
audio viz

audio viz

Veyepar Video Eyeball Processor and Review