This document outlines a project exploring the use of Python and R for business applications. It provides brief descriptions of Python and R, noting their uses in scientific computing, big data, automation, web scraping, visualization, and more. Potential business applications are mentioned but not described. The document discusses success factors such as continuing to learn the syntax of Python and R, defining requirements, and investigating applications. It proposes taking what was learned about the languages and identifying a realistic business problem and solution to develop using Python, R, or both. Next steps include meeting with a professor, exploring solutions, and coordinating with teammates to develop materials showcasing Python and R.
2. Outline
1. What is Python?
2. What is R?
3. Potential business applications
4. Success factors
5. Approach
6. Next steps
3. Python
● Scientific and mathematical computing “Panda”
● Big data
● System automation (scripting/bots)
● Web scraping
● Visualization (Modules)
● Web Applications/Flexibility
4. R
● Statistical computation and graphics
● Predictive analytics
● Integrated library tools for data analysis
● Large data sets
● Visualization
6. Success Factors
● Continue to learn syntax of Python and R
● Define necessary requirements
● Investigate various business applications
● Coordinate with teammates and come up with concrete
solutions
7. Approach
Take what we
learned from
Python and R and
identify realistic
solution
Identify business
problem/solution
Familiarize
ourselves with
Python and R syntax
to gauge
possibilities
Learn languages
Use python, R, or
both to establish
solution that can
solve real-word
problems
Deploy prototype
8. Next Steps
● Meet with Professor Schuff
● Explore possible solutions using Python and R
● Coordinate with teammates to begin development of
website & slide deck to showcase Python vs R for data
analytics
Integration into low level code
Useful when analysis tasks need to be integrated into web applications
Talk about how python is a general purpose coding language but go more into how it can be used for computing, analytics, machine learning because we are comparing it to R
https://medium.freecodecamp.org/what-can-you-do-with-python-the-3-main-applications-518db9a68a78 ←------ great source to learn more about Python and what it can do
https://www.quora.com/Whats-the-R-programming-language-used-for ←--- second answer has mutlple examples of what R is used for and what companies are currently using it (even though its quora, sources can be found)https://blog.revolutionanalytics.com/2012/04/NOAA-R-river-flooding.html ←- example of how the natuinal National Oceanic and Atmospheric Administration uses R to forecast river flooding
Business Applications for Python - Data Analysis, scripting for data, machine learning, and automation
R - Predictive analytics, transforming large sets of data so they have meaning (healthcare)
Chose project because of our interest in data analytics ←- what language is best suited for it, etc.
Data scientist - turning data into information
Predictive analytics - extracting info from data sets to determine patterns and trends