Fast Data Mining with PyTables and pandas

by Yves Hilpisch for EuroPython 2012

In a number of industries, like financial services or utilities, it is important to analyze huge sets of data in an efficient and fast manner. Typical solutions that are based on SQL databases or follow some kind of data warehouse approach are generally quite expensive and demand for huge computing power.

Using the Python libraries PyTables and pandas brings high performance data mining to your desktop computer or even notebook. The talk illustrates how to beneficially apply these libraries in the context of financial time series and other data sets. It is also illustrated how you can implement fast calculations on data sets which do not fit into the memory of your computer.

In addition, the talk provides a number of examples for the visualization of your data mining efforts.

Video

Comments

no audio??
bahaelaila7, 06 May 2013 #
I checked and the audio works well?!
Yves, 06 May 2013 #
only left channel at the beginning, and audio doesn't really start until 1:15
David Rasch, 14 November 2013 #
Yves, I attempted the simulation. The object "m" was used in the range() function. I got an error message say range() is expecting an end param in the type INT. So I added one statement prior to the for loop m = int(m). It worked. The simulation objection S, can be printed. However, when I attempted the option pricing, the calculation of VO did not result in any error but there was no result returned. Would you suggest what is wrong with my work? I was using a ipython notebook under Enthought EPD/Canopy.
Simon Sin, 08 July 2013 #
Would like to help. Just send me or post the code/IPYNB.
Yves, 08 July 2013 #
Hello.
In Video: There are subtitles for part 2?
Spanish translation exists for the two videos?
Thank you.
jralarbelo, 13 September 2013 #