Summary
[EuroPython 2012] Y Hipisch - 5 JULY 2012 in "Track Tagliatelle"
Description
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.