Techniques for Advanced Data Aggregation

Utilize advanced programming fundamentals.
You are interested in expanding your code base even further to leverage merging and combining data in both the Python and R programming languages. Here you have a need to support the characterization of a portfolio that may include a number of all four stocks, all purchased in similar proportions to the overall proportion. Here you are interested in supporting the need-to-average the four stocks for each day of historical data.
You will have two distinct submissions with one leveraging the Python programming language, and the second leveraging the R programming language.
For your first submission, using Python, you will take the Kaggle GAFA Stock prices and create categories from your four stock statistics in order to identify number of shares that can be purchased with 10,000.00 each trading day (2500.00 to spend on each stock).
This will rely on the combined four prices of the four stocks-per-day using advanced grouping functions in both the R and Python programming language. Assuming a portfolio containing equal number of shares in all four stocks (Google, amazon, Apple, and Facebook) you will generate the number of shares purchased.
Your output will be your source code in a plain text file performing this first activity in Python. You are to turn in the source code as well as associated output from the data set.
Using the R programming language for your second submission, you will take the stock prices, using your output file from the first submission, and generate a distribution plot of the stock prices. Your output will include both your source code in a plain text file as well as the output.

Data Sets

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