Synthesize the application of software used in data science environments.
Sprockets Corporation designs high-end, specialty machine parts for a variety of industries. You have been hired by Sprockets to assist them with their data analysis needs. Sprockets Corporation has asked you to help them with data analytics in support of their Customer Relationship Management (CRM). They are in the process of preparing an existing data file for migration into a new application, which requires some immediate reformatting in order to support a test. There is also a need to perform quick statistics on the exact same data for a product planning department. You have decided to use Python for the purpose of reformatting data and R for generating a brief summary on key points related to the data.
John Sprocket, CEO of Sprockets Corporation, has asked you for a white paper including the following elements:
The python code for the data reformatting job and the converted file
The R code and a screenshot image showing how to generate the related statistics
For the data file reformatting, start with a csv formatted data file of sales data, and to read in the file (.csv) and write it out as a tab delimited file in order to have it processed by another system. Switching the first two columns in order to support the new format will also be necessary.
For the quick statistics, John asks you for some specifics:
Generate the mean and standard deviation of the quantity ordered, price of each and sales for the sales_sample_file.csv using the R programming language.
Generate a histogram for the quantity ordered, price of each, and sale. Present as a screenshot placed in the deliverable.
For source code examples and data sets: https://learning.rasmussen.edu/bbcswebdav/pid-5855335-dt-content-rid-151629588_1/xid-151629588_1
For a specific tutorial on Python string replacement: http://proquest.safaribooksonline.com.ezproxy.rasmussen.edu/book/programming/python/9781784390341/using-string-and-bytes-values/ch02lvl2sec30_html?uicode=rasmussen
For additional information on using graphs in R: http://proquest.safaribooksonline.com.ezproxy.rasmussen.edu/book/statistics/9781118497579/chapter-1-variation/c01_sec1_0005_xhtml?uicode=rasmussen
For additional information on using built-in functions in R: http://proquest.safaribooksonline.com.ezproxy.rasmussen.edu/book/programming/r/9781617291388/part-1dot-getting-started/kindle_split_014_html?uicode=rasmussen
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