Option #1: Python in a Jupyter NotebookInstall Anaconda with the latest version
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Option #1: Python in a Jupyter NotebookInstall Anaconda with the latest version of Python as directed in the installation instructions Download installation instructions. Capture screenshot 1 showing the Anaconda navigator window with your system date and time.
Create a new Jupyter notebook named MIS542. Capture screenshot 2 showing the MIS542 Jupyter notebook with your system date and time.
Perform the following tasks in Python:
Use a variable
Use three different data types
Output an equation and the results of the equation
Create a for loop
Create an if, elif, else block
Capture as many screenshots as necessary to demonstrate successful completion of all the above tasks. One screenshot can be used to demonstrate more than one task. Ensure the code is large enough in the screenshots to be readable in your Word document submission.
All code must be explained in the narrative of your paper.
Submit one Word document with your screenshots demonstrating successful completion of the above items. In addition to the screenshots, include a description of lessons you learned from this exercise.
Your paper should be 2-3 pages in length, not including the title page, and conform to the CSU Global Writing Center Links to an external site.. (No reference page is required for this assignment.)
Useful resources:
Chapters 1 and 2 in Nelson (2018) provide the foundation for what you will be learning throughout the remainder of this course. Chapters 1 and 2 in McKinney (2018) will get you started with Python. If you are new to programming or just new to Python, watching Vijayan’s (2019) course, Python Quick Start, will be tremendously helpful.
Chapters 1 & 2 in The Analytics Lifecycle Toolkit
Chapters 1 & 2 in Python for Data Analysis
Aydiner, A. S., Tatoglu, E., Bayraktar, E., Zaim, S., & Delen, D. (2019). Business analytics and firm performance: The mediating role of business process performance. Journal of Business Research, 96, 228-237.
Brown, S. (2020, September 24). How to build a data-driven company. MIT Sloan. https://mitsloan.mit.edu/ideas-made-to-matter/how-to-build-a-data-driven-company
Option #2: Python in the IPython ShellInstall Anaconda with the latest version of Python as directed in the installation instructions Download installation instructions. Capture screenshot 1 showing the Anaconda navigator window with your system date and time.
Open the IPython shell. Capture screenshot 2 showing the IPython shell with your system date and time.
Perform the following tasks in Python:
Use a variable
Use three different data types
Output an equation and the results of the equation
Create a for loop
Create an if, elif, else block
Capture as many screenshots as necessary to demonstrate successful completion of all the above tasks. One screenshot can be used to demonstrate more than one task. Ensure the code is large enough in the screenshots to be readable in your Word document submission.
All code must be explained in the narrative of your paper.
Submit one Word document with your screenshots demonstrating successful completion of the above items. In addition to the screenshots, include a description of lessons you learned from this exercise.
Your paper should be 2-3 pages in length, not including the title page, and conform to the CSU Global Writing Center Links to an external site.. (No reference page is required for this assignment.)
Useful resources:
Chapters 1 and 2 in Nelson (2018) provide the foundation for what you will be learning throughout the remainder of this course. Chapters 1 and 2 in McKinney (2018) will get you started with Python. If you are new to programming or just new to Python, watching Vijayan’s (2019) course, Python Quick Start, will be tremendously helpful.
Chapters 1 & 2 in The Analytics Lifecycle Toolkit
Chapters 1 & 2 in Python for Data Analysis
Aydiner, A. S., Tatoglu, E., Bayraktar, E., Zaim, S., & Delen, D. (2019). Business analytics and firm performance: The mediating role of business process performance. Journal of Business Research, 96, 228-237.
Brown, S. (2020, September 24). How to build a data-driven company. MIT Sloan. https://mitsloan.mit.edu/ideas-made-to-matter/how-to-build-a-data-driven-company
