Data Analysis Group Presentation:

Objective: Students will work in groups to select and analyze a dataset from data.gov, applying Python-based data analysis techniques to clean, explore, and visualize the data. Each group will present their findings to the class, demonstrating their ability to extract insights and communicate results effectively.

Overview: Your group’s presentation should be approximately 10 minutes long (no more than 15 minutes), clearly explaining your dataset, analysis, and key insights. Each group member is expected to participate in the in-class presentation. Points will not be awarded to any group member who does not present. Structure your Jupyter Notebook with Markdown cells for explanations and Code cells for analysis and visualization. Ensure that all code is well-documented, with explanations of why specific methods, libraries, or visualizations were used.

 

Dataset Selection & Justification

  • What dataset did your group choose, and why?
  • What makes this dataset interesting or relevant?

Data Accessibility & Cleaning

  • How difficult was it to load the data into Python?
  • What state is the data in?
  • Did your group need to perform any significant cleaning?

Exploratory Analysis & Visualization

  • What types of analysis did your group carry out?
  • Compute summary statistics
  • Include visualizations to help explain your findings (using Matplotlib, Seaborn, Plotly, or Bokeh)

Insights & Conclusions

  • What did your group learn from the dataset?
  • What key takeaways can you share from your analysis?

Format:

  • The presentation should be approximately 10 minutes long (no more than 15 minutes), covering key aspects of your dataset and analysis.
  • Structure your Jupyter Notebook using:
    • Markdown cells for explanations and documentation.
    • Code cells for data loading, cleaning, analysis, and visualization.
  • Clearly explain your code, including the reasoning behind:
    • Dataset selection and preprocessing steps.
    • Analytical methods and calculations.
    • Choice of visualizations and their interpretations.
  • Ensure your Jupyter Notebook is well-organized, readable, and effectively communicates your findings.

Due: Please upload your Jupyter Notebook to Canvas by 1:10 PM on the day your group is scheduled to present. Every member of the group is required to submit the Jupyter Notebook file individually to Canvas. Groups 1 - 3 will present on Monday, November 30. Groups 4 - 6 will present on Wednesday, December 2. Groups 7 - 9 will present on Friday, December 4.