Chicago Crime Data Analysis

Presentation Guidelines

You are free to structure your presentations to your liking, but students tend to have success with the following format.

• Title Slide

  • Include the name of the Project and Group Members

• Motivation & Summary Slide

  • Define the core message or hypothesis of your project.
  • Describe the questions you asked, and why you asked them
  • Describe whether you were able to answer these questions to your satisfaction, and briefly summarize your findings

• Questions & Data

  • Elaborate on the questions you asked, describing what kinds of data you needed to answer them, and where you found it

• Data Cleanup & Exploration

  • Describe the exploration and cleanup process
  • Discuss insights you had while exploring the data that you didn't anticipate
  • Discuss any problems that arose after exploring the data, and how you resolved them
  • Present and discuss interesting figures developed during exploration, ideally with the help of Jupyter Notebook

• Data Analysis

  • Discuss the steps you took to analyze the data and answer each question you asked in your proposal
  • Present and discuss interesting figures developed during analysis, ideally with the help of Jupyter Notebook

• Discussion

  • Discuss your findings. Did you find what you expected to find? If not, why not? What inferences or general conclusions can you draw from your analysis?

• Post Mortem

  • Discuss any difficulties that arose, and how you dealt with them
  • Discuss any additional questions that came up, but which you didn't have time to answer: What would you research next, if you had two more weeks?

• Questions

  • Open-floor Q&A with the audience

  Technical Requirements

The technical requirements for Project 1 are as follows.

• Use Pandas to clean and format your data set(s)

• Create a Jupyter Notebook describing the data exploration and cleanup process

• Create a Jupyter Notebook illustrating the final data analysis

• Use Matplotlib to create a total of 6-8 visualizations of your data (ideally, at least 2 per "question" you ask of your data)

• Save PNG images of your visualizations to distribute to the class and instructional team, and for inclusion in your presentation

• Optionally, use at least one API, if you can find an API with data pertinent to your primary research questions

• Create a write-up summarizing your major findings. This should include a heading for each "question" you asked of your data, and under each heading, a short description of what you found and any relevant plots.