Employ advanced data structures.
You are interested in building a more sophisticated set of examples for your code repository to support the implementation of grouping, filtering, and index based techniques upon frame data structures. In the interest of supporting extended modeling in the area of financial analytics, you are interested in creating examples of advanced techniques to perform side-by-side comparisons between the stock-based examples without having to manipulate the entire data structure. In this case you will apply an advanced grouping technique in order to reference stocks between each other without having to physically reconstruct the module.
Using Python, take the Kaggle GAFA Stock prices. You will have to read in the four stocks and associated attributes into separate columns for each stock from a single data frame. Create an output file to be read in read in by R.
Using R, use the Lattice or ggplot. Create plots of the stocks side-by-side. Additionally, calculate the mean and standard deviation of each stock between Amazon, Facebook, and Apple.
Your specific deliverables are your source codes in a plain text file, including plots of each stock price (all in the same plot), and means and standard deviation of the stock.