In this chapter, we took an in-depth look at collecting a type of social data and using it to see whether we could identify trends in the data that can be correlated with market movements in order to gain an advantage over the general movement of the market. We did this by reproducing results from a published paper, which concludes that it is possible. We were able to reproduce very similar results and you learned a general process of analyzing data and making decisions on trading in the market.

The best part of this is that during this process, you saw that pandas provides a very robust framework for financial time-series analysis as well as for the analysis of simple social data. You learned how to work with multiple time-series that have different frequencies and how to manipulate them to be able to have frequencies that can be aligned to be able to apply decisions made in one to execution in another. This included various concepts such as frequency conversion, grouping by year...