BUAN 346/446 Python Applications for Business
Project Instruction
· Purpose
This is an end-term project that you can choose to complete either yourself or with a teammate. The project comprises final presentation slides, a recording of you presenting the slides, a Colab file, and if you’re working with a teammate, a peer evaluation form. You and your teammate will record your presentation during the final week.
The objectives of the assignment are to assess your ability to:
● apply basic Python skills covered in class to analyze a new dataset;
● perform. independent research to fill in gaps in the analysis to answer a realistic real-life business question.
● Data:
Option 1: You can use the PLUTO (Primary Land Use Tax Lot Output) database, which lists every building in New York The data base is accessed via NYC Open Data Portal, and additional details about the data are found here: data dictionary. While there may be 96 columns in the dataset. You are not expected to use all variables in your analysis. It suffices to choose a total of 15-20 variables and to perform. a thorough analysis using just those variables.
Option 2: It is also okay to use some of the datasets posted by Kaggle, but you need to have original ideas if you are going to use the Kaggle dataset. Your dataset needs to have at least 1000 observations and 15-20 variables, without repeated measure. It is advised to not use survey data.
· Final Project Presentations
Presentations should be rehearsed, and if you are working with a teammate, each of you should speak for about half the presentation. The presentation should be 12-15 mins long. The slide deck should consist of 8-15 slides that follows this outline:
1. Title, Name(s): The first slide should have a title of your project, the names of you and your teammate, the course number, and the date.
2. Introduction and background:
· Provide relevant background information related to your analysis.
3. Purpose and Objectives of the Report:
· Clearly describe the research questions you intend to answer through your analysis.
· If you choose to work with data from Kaggle, also summarize what has been done with this dataset on Kaggle. Explain how your work differs from others' work.
· For each research question, provide an overview of the approach you took to explore and analyze the data, such as plots or important descriptive statistics.
4. Data: When starting your analysis, it is important to provide a description of the available data and specify the columns you will be utilizing. While there may be 96 columns in the dataset, it is not necessary to use all of them for your analysis:
· Begin by describing the available data and the specific columns you are utilizing for your analysis.
· Display statistical summaries and explain the variables that you choose and how they relate to the research questions you proposed.
· Discuss any preprocessing, cleansing, or transformation techniques applied to the data, such as converting numerical data to categorical using if-else functions. Also discuss your choice of meaningful variable names to properly label your data.
5. Analysis Results: Provide an overview of the approach you took to explore and analyze the data. This is where you tell the story of how you got to your main findings. Figures and tables that are presented without accompanying description/discussion will receive at most half credit. To earn full credit, you must describe what each table/figure is showing and discuss any key takeaways. In other words, it is not sufficient to simply display Python output. You must also provide thoughtful discussion of the output.
· You will perform. at least 4 types of analysis. The analyses should be presented using plots (with carefully labelled axes, titles, and legends) and important descriptive statistics.
· Present your main findings and the results obtained.
6. Discussion & Conclusion:
· Summarize the findings derived from your analysis.
· Discuss any limitations in your analysis. For example, did you produce any tables or plots that you thought would reveal interesting trends but didn't?
7. References:
· You must include a link to your data in the references of your report.
· Make sure to keep track of all bibliographic information as you do your research. Any resources used should be appropriately cited in-text and/or in a references section.
You can structure the report differently, but these major elements and the listed required content should be incorporated into your report.