The tutorial covers standard Python and Open Source tools (pandas, matplotlib, seaborn, R/ggplot, etc.) and recent innovations (TsTables, bcolz, blaze, plot.ly) for financial time series analysis and visualization. In addition, approaches are illustrated for high performance I/O of high frequency financial data. It briefly sheds light on the visualization of real-time/streaming financial data.
Slides available here: https://github.com/yhilpisch/pydlon15