Selection Grouping And Filtering Of Data

  Competency

Utilize core programming fundamentals to achieve desired analytical outcomes. Scenario

You are interested in building examples for your code repository to support the means of implementing frame data structures. As you are interested in working on financial applications, it would make sense to examine stock prices in the context of frames and allow for the means of quick comparison between individual stocks. A good starting point is to provide examples that will support the means of comparing statistics between stocks side-by-side. Instructions

Taking the Kaggle GAFA Stock prices, you will have two distinct submissions.

For the first submission, using Python, you are to read in the four stocks and associated attributes (stock prices) into separate columns for each stock into the same data frame, thus allowing for side-by-side comparisons for the purpose of analyzing the correlation and covariance between the four stocks. This will require reading and filtering each stock (by stock name), and assigning to your fame data structure. Complete this first submission using Python.

The submission in this case will be your source code in a plain text file written to perform this activity along with the associated input and output files.

For the second submission, using R, you are to take stock prices (per day) from your favorite Internet search engine and determine the correlation and covariance between it and related stock prices ( for similar dates) between Amazon, Facebook, and Apple. For this second submission, you are to use R. Use the input file from the first submission as your input.

Your submission in this case will be your source code in a plain text file written to perform this activity along with the associated input and output files.

Data Sets

https://learning.rasmussen.edu/bbcswebdav/pid-5842498-dt-content-rid-151631794_1/xid-151631794_1

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