'Himrod' web sites
Welcome to occ.
www.occrwa.org 2012-04-20
himrod Vivienne Lee Jenkins Chelley Kitzmiller Louella Nelson Lynda Nusser June Potter Pat Teal Sandy Watt Linda Wisdom PAST PRESIDENTS 1981. Chelley Kitzmiller ndash; Founding President 1982. Penny Richards 1983. Jenny Spindle 1984. Louella Nelson 1985. Maralys Wills Ann Johnson 1986. Rita Rainville Frankie Merkt 1987. Jill Marie Landis Gini Wilson 1988. Gini Wilson Louzana Kaku 1989. Sue Phillips Stephanie Westphal 1990. Sharon
www.occrwa.org 2012-04-20
himrod Vivienne Lee Jenkins Chelley Kitzmiller Louella Nelson Lynda Nusser June Potter Pat Teal Sandy Watt Linda Wisdom PAST PRESIDENTS 1981. Chelley Kitzmiller ndash; Founding President 1982. Penny Richards 1983. Jenny Spindle 1984. Louella Nelson 1985. Maralys Wills Ann Johnson 1986. Rita Rainville Frankie Merkt 1987. Jill Marie Landis Gini Wilson 1988. Gini Wilson Louzana Kaku 1989. Sue Phillips Stephanie Westphal 1990. Sharon
Pydata nyc 2012. conference schedule
nyc2012.pydata.org 2012-11-26
himrod and Steve Kannan 9 30 a.m. 9 45 a.m. 10 00 a.m. Introduction to NumPy. Stefan van der Walt and Travis Oliphant GIS in Python Using Shapely. Zain Memon 10 15 a.m. 10 30 a.m. 10 45 a.m. Pandas. Wes McKinney Generators Coroutines for Stream Data Processing. V.James Powell 11 00 a.m. 11 15 a.m. 11 30 a.m. Matplotlib Tutorial. Jake VanderPlas Blaze. Stephen Diehl 11 45 a.m. 12 00 p.m. 12 15 p.m. Lunch included with registration
nyc2012.pydata.org 2012-11-26
himrod and Steve Kannan 9 30 a.m. 9 45 a.m. 10 00 a.m. Introduction to NumPy. Stefan van der Walt and Travis Oliphant GIS in Python Using Shapely. Zain Memon 10 15 a.m. 10 30 a.m. 10 45 a.m. Pandas. Wes McKinney Generators Coroutines for Stream Data Processing. V.James Powell 11 00 a.m. 11 15 a.m. 11 30 a.m. Matplotlib Tutorial. Jake VanderPlas Blaze. Stephen Diehl 11 45 a.m. 12 00 p.m. 12 15 p.m. Lunch included with registration
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Python data analysis library mdash; pandas python data analysis library
himrod Director of Optimization Analytics AppNexus 8220;pandas is the perfect tool for bridging the gap between rapid iterations of ad.hoc analysis and production quality code. If you want one tool to be used across a multi.disciplined organization of engineers, mathematicians and analysts, look no further. 8221; Olivier Pomel CEO Datadog 8220;We use pandas to process time series data on our production servers. The simplicity and
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Pydata nyc 2012. talk abstracts
himrod and Steve Kannan At AppNexus, we ve experienced explosive growth over the last three years. Our data pipeline, horizontally scaled in Hadoop and Hbase, now processes more than 15 terabytes every day. This has meant the rapid scaling and iteration of our optimization tools used for big data exploration and aggregations. Unlike other more complicated programming languages, Python versatility allows us to use it both for
MORE
ⓘ
Python data analysis library mdash; pandas python data analysis library
himrod Director of Optimization Analytics AppNexus 8220;pandas is the perfect tool for bridging the gap between rapid iterations of ad.hoc analysis and production quality code. If you want one tool to be used across a multi.disciplined organization of engineers, mathematicians and analysts, look no further. 8221; Olivier Pomel CEO Datadog 8220;We use pandas to process time series data on our production servers. The simplicity and
MORE
ⓘ
Pydata nyc 2012. talk abstracts
himrod and Steve Kannan At AppNexus, we ve experienced explosive growth over the last three years. Our data pipeline, horizontally scaled in Hadoop and Hbase, now processes more than 15 terabytes every day. This has meant the rapid scaling and iteration of our optimization tools used for big data exploration and aggregations. Unlike other more complicated programming languages, Python versatility allows us to use it both for
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